Thursday Nov 19, 2015

SPECvirt_2013: SPARC T7-2 World Record Performance for Two- and Four-Chip Systems

Oracle's SPARC T7-2 server delivered a world record SPECvirt_sc2013 result for systems with two to four chips.

  • The SPARC T7-2 server produced a result of 3198 @ 179 VMs SPECvirt_sc2013.

  • The two-chip SPARC T7-2 server beat the best four-chip x86 Intel E7-8890 v3 server (HP ProLiant DL580 Gen9), demonstrating that the SPARC M7 processor is 2.1 times faster than the Intel Xeon Processor E7-8890 v3 (chip-to-chip comparison).

  • The two-chip SPARC T7-2 server beat the best two-chip x86 Intel E5-2699 v3 server results by nearly 2 times (Huawei FusionServer RH2288H V3, HP ProLiant DL360 Gen9).

  • The two-chip SPARC T7-2 server delivered nearly 2.2 times the performance of the four-chip IBM Power System S824 server solution which used 3.5 GHz POWER8 six core chips.

  • The SPARC T7-2 server running Oracle Solaris 11.3 operating system, utilizes embedded virtualization products as the Oracle Solaris 11 zones, which in turn provide a low overhead, flexible, scalable and manageable virtualization environment.

  • The SPARC T7-2 server result used Oracle VM Server for SPARC 3.3 and Oracle Solaris Zones providing a flexible, scalable and manageable virtualization environment.

Performance Landscape

Complete benchmark results are at the SPEC website, SPECvirt_sc2013 Results. The following table highlights the leading two-, and four-chip results for the benchmark, bigger is better.

SPECvirt_sc2013
Leading Two to Four-Chip Results
System
Processor
Chips Result @ VMs Virtualization Software
SPARC T7-2
SPARC M7 (4.13 GHz, 32core)
2 3198 @ 179 Oracle VM Server for SPARC 3.3
Oracle Solaris Zones
HP ProLiant DL580 Gen9
Intel E7-8890 v3 (2.5 GHz, 18core)
4 3020 @ 168 Red Hat Enterprise Linux 7.1 KVM
Lenovo System x3850 X6
Intel E7-8890 v3 (2.5 GHz, 18core)
4 2655 @ 147 Red Hat Enterprise Linux 6.6 KVM
Huawei FusionServer RH2288H V3
Intel E5-2699 v3 (2.3 GHz, 18core)
2 1616 @ 95 Huawei FusionSphere V1R5C10
HP ProLiant DL360 Gen9
Intel E5-2699 v3 (2.3 GHz, 18core)
2 1614 @ 95 Red Hat Enterprise Linux 7.1 KVM
IBM Power S824
POWER8 (3.5 GHz, 6core)
4 1370 @ 79 PowerVM Enterprise Edition 2.2.3

Configuration Summary

System Under Test Highlights:

Hardware:
1 x SPARC T7-2 server, with
2 x 4.13 GHz SPARC M7
1 TB memory
2 Sun Dual Port 10GBase-T Adapter
2 Sun Storage Dual 16 Gb Fibre Channel PCIe Universal HBA

Software:
Oracle Solaris 11.3
Oracle VM Server for SPARC 3.3 (LDom)
Oracle Solaris Zones
Oracle iPlanet Web Server 7.0.20
Oracle PHP 5.3.29
Dovecot v2.2.18
Oracle WebLogic Server Standard Edition Release 10.3.6
Oracle Database 12c Enterprise Edition (12.1.0.2.0)
Java HotSpot(TM) 64-Bit Server VM on Solaris, version 1.7.0_85-b15

Storage:
3 x Oracle Server X5-2L, with
2 x Intel Xeon Processor E5-2630 v3 8-core 2.4 GHz
32 GB memory
4 x Oracle Flash Accelerator F160 PCIe Card
Oracle Solaris 11.3

1 x Oracle Server X5-2L, with
2 x Intel Xeon Processor E5-2630 v3 8-core 2.4 GHz
32 GB memory
4 x Oracle Flash Accelerator F160 PCIe Card
4x 400 GB SSDs
Oracle Solaris 11.3

Benchmark Description

SPECvirt_sc2013 is SPEC's updated benchmark addressing performance evaluation of datacenter servers used in virtualized server consolidation. SPECvirt_sc2013 measures the end-to-end performance of all system components including the hardware, virtualization platform, and the virtualized guest operating system and application software. It utilizes several SPEC workloads representing applications that are common targets of virtualization and server consolidation. The workloads were made to match a typical server consolidation scenario of CPU resource requirements, memory, disk I/O, and network utilization for each workload. These workloads are modified versions of SPECweb2005, SPECjAppServer2004, SPECmail2008, and SPEC CPU2006. The client-side SPECvirt_sc2013 harness controls the workloads. Scaling is achieved by running additional sets of virtual machines, called "tiles", until overall throughput reaches a peak.

Key Points and Best Practices

  • The SPARC T7-2 server running the Oracle Solaris 11.3, utilizes embedded virtualization products as the Oracle VM Server for SPARC and Oracle Solaris Zones, which provide a low overhead, flexible, scalable and manageable virtualization environment.

  • In order to provide a high level of data integrity and availability, all the benchmark data sets are stored on mirrored (RAID1) storage

  • Using Oracle VM Server for SPARC to bind the SPARC M7 processor with its local memory optimized the memory use in this virtual environment.

  • This improved result used a fractional tile to fully saturate the system.

See Also

Disclosure Statement

SPEC and the benchmark name SPECvirt_sc are registered trademarks of the Standard Performance Evaluation Corporation. Results from www.spec.org as of 11/19/2015. SPARC T7-2, SPECvirt_sc2013 3198@179 VMs; HP ProLiant DL580 Gen9, SPECvirt_sc2013 3020@168 VMs; Lenovo x3850 X6; SPECvirt_sc2013 2655@147 VMs; Huawei FusionServer RH2288H V3, SPECvirt_sc2013 1616@95 VMs; HP ProLiant DL360 Gen9, SPECvirt_sc2013 1614@95 VMs; IBM Power S824, SPECvirt_sc2013 1370@79 VMs.

Monday Oct 26, 2015

SPECvirt_sc2013: SPARC T7-2 World Record for 2 and 4 Chip Systems

Oracle has had a new result accepted by SPEC as of November 19, 2015. This new result may be found here.

Oracle's SPARC T7-2 server delivered a world record SPECvirt_sc2013 result for systems with two to four chips.

  • The SPARC T7-2 server produced a result of 3026 @ 168 VMs SPECvirt_sc2013.

  • The two-chip SPARC T7-2 server beat the best two-chip x86 Intel E5-2699 v3 server results by nearly 1.9 times (Huawei FusionServer RH2288H V3, HP ProLiant DL360 Gen9).

  • The two-chip SPARC T7-2 server delivered nearly 2.2 times the performance of the four-chip IBM Power System S824 server solution which used 3.5 GHz POWER8 six core chips.

  • The SPARC T7-2 server running Oracle Solaris 11.3 operating system, utilizes embedded virtualization products as the Oracle Solaris 11 zones, which in turn provide a low overhead, flexible, scalable and manageable virtualization environment.

  • The SPARC T7-2 server result used Oracle VM Server for SPARC 3.3 and Oracle Solaris Zones providing a flexible, scalable and manageable virtualization environment.

Performance Landscape

Complete benchmark results are at the SPEC website, SPECvirt_sc2013 Results. The following table highlights the leading two-, and four-chip results for the benchmark, bigger is better.

SPECvirt_sc2013
Leading Two to Four-Chip Results
System
Processor
Chips Result @ VMs Virtualization Software
SPARC T7-2
SPARC M7 (4.13 GHz, 32core)
2 3026 @ 168 Oracle VM Server for SPARC 3.3
Oracle Solaris Zones
HP DL580 Gen9
Intel E7-8890 v3 (2.5 GHz, 18core)
4 3020 @ 168 Red Hat Enterprise Linux 7.1 KVM
Lenovo System x3850 X6
Intel E7-8890 v3 (2.5 GHz, 18core)
4 2655 @ 147 Red Hat Enterprise Linux 6.6 KVM
Huawei FusionServer RH2288H V3
Intel E5-2699 v3 (2.3 GHz, 18core)
2 1616 @ 95 Huawei FusionSphere V1R5C10
HP DL360 Gen9
Intel E5-2699 v3 (2.3 GHz, 18core)
2 1614 @ 95 Red Hat Enterprise Linux 7.1 KVM
IBM Power S824
POWER8 (3.5 GHz, 6core)
4 1370 @ 79 PowerVM Enterprise Edition 2.2.3

Configuration Summary

System Under Test Highlights:

Hardware:
1 x SPARC T7-2 server, with
2 x 4.13 GHz SPARC M7
1 TB memory
2 Sun Dual Port 10GBase-T Adapter
2 Sun Storage Dual 16 Gb Fibre Channel PCIe Universal HBA

Software:
Oracle Solaris 11.3
Oracle VM Server for SPARC 3.3 (LDom)
Oracle Solaris Zones
Oracle iPlanet Web Server 7.0.20
Oracle PHP 5.3.29
Dovecot v2.2.18
Oracle WebLogic Server Standard Edition Release 10.3.6
Oracle Database 12c Enterprise Edition (12.1.0.2.0)
Java HotSpot(TM) 64-Bit Server VM on Solaris, version 1.7.0_85-b15

Storage:
3 x Oracle Server X5-2L, with
2 x Intel Xeon Processor E5-2630 v3 8-core 2.4 GHz
32 GB memory
4 x Oracle Flash Accelerator F160 PCIe Card
Oracle Solaris 11.3

1 x Oracle Server X5-2L, with
2 x Intel Xeon Processor E5-2630 v3 8-core 2.4 GHz
32 GB memory
4 x Oracle Flash Accelerator F160 PCIe Card
4x 400 GB SSDs
Oracle Solaris 11.3

Benchmark Description

SPECvirt_sc2013 is SPEC's updated benchmark addressing performance evaluation of datacenter servers used in virtualized server consolidation. SPECvirt_sc2013 measures the end-to-end performance of all system components including the hardware, virtualization platform, and the virtualized guest operating system and application software. It utilizes several SPEC workloads representing applications that are common targets of virtualization and server consolidation. The workloads were made to match a typical server consolidation scenario of CPU resource requirements, memory, disk I/O, and network utilization for each workload. These workloads are modified versions of SPECweb2005, SPECjAppServer2004, SPECmail2008, and SPEC CPU2006. The client-side SPECvirt_sc2013 harness controls the workloads. Scaling is achieved by running additional sets of virtual machines, called "tiles", until overall throughput reaches a peak.

Key Points and Best Practices

  • The SPARC T7-2 server running the Oracle Solaris 11.3, utilizes embedded virtualization products as the Oracle VM Server for SPARC and Oracle Solaris Zones, which provide a low overhead, flexible, scalable and manageable virtualization environment.

  • In order to provide a high level of data integrity and availability, all the benchmark data sets are stored on mirrored (RAID1) storage

  • Using Oracle VM Server for SPARC to bind the SPARC M7 processor with its local memory optimized system memory use in this virtual environment.

See Also

Disclosure Statement

SPEC and the benchmark name SPECvirt_sc are registered trademarks of the Standard Performance Evaluation Corporation. Results from www.spec.org as of 10/25/2015. SPARC T7-2, SPECvirt_sc2013 3026@168 VMs; HP DL580 Gen9, SPECvirt_sc2013 3020@168 VMs; Lenovo x3850 X6; SPECvirt_sc2013 2655@147 VMs; Huawei FusionServer RH2288H V3, SPECvirt_sc2013 1616@95 VMs; HP ProLiant DL360 Gen9, SPECvirt_sc2013 1614@95 VMs; IBM Power S824, SPECvirt_sc2013 1370@79 VMs.

Oracle Internet Directory: SPARC T7-2 World Record

Oracle's SPARC T7-2 server running Oracle Internet Directory (OID, Oracle's LDAP Directory Server) on Oracle Solaris 11 on a virtualized processor configuration achieved a record result on the Oracle Internet Directory benchmark.

  • The SPARC T7-2 server, virtualized to use a single processor, achieved world record performance running Oracle Internet Directory benchmark with 50M users.

  • The SPARC T7-2 server and Oracle Internet Directory using Oracle Database 12c running on Oracle Solaris 11 achieved record result of 1.18M LDAP searches/sec with an average latency of 0.85 msec with 1000 clients.

  • The SPARC T7 server demonstrated 25% better throughput and 23% better latency for LDAP search/sec over similarly configured SPARC T5 server benchmark environment.

  • Oracle Internet Directory achieved near linear scalability on the virtualized single processor domain on the SPARC T7-2 server with 79K LDAP searches/sec with 2 cores to 1.18M LDAP searches/sec with 32 cores.

  • Oracle Internet Directory and the virtualized single processor domain on the SPARC T7-2 server achieved up to 22,408 LDAP modify/sec with an average latency of 2.23 msec for 50 clients.

Performance Landscape

A virtualized single SPARC M7 processor in a SPARC T7-2 server was used for the test results presented below. The SPARC T7-2 server and SPARC T5-2 server results were run as part of this benchmark effort. The remaining results were part of a previous benchmark effort.

Oracle Internet Directory Tests
System chips/
cores
Search Modify Add
ops/sec lat (msec) ops/sec lat (msec) ops/sec lat (msec)
SPARC T7-2 1/32 1,177,947 0.85 22,400 2.2 1,436 11.1
SPARC T5-2 2/32 944,624 1.05 16,700 2.9 1,000 15.95
SPARC T4-4 4/32 682,000 1.46 12,000 4.0 835 19.0

Scaling runs were also made on the virtualized single processor domain on the SPARC T7-2 server.

Scaling of Search Tests – SPARC T7-2, One Processor
Cores Clients ops/sec Latency (msec)
32 1000 1,177,947 0.85
24 1000 863,343 1.15
16 500 615,563 0.81
8 500 280,029 1.78
4 100 156,114 0.64
2 100 79,300 1.26

Configuration Summary

System Under Test:

SPARC T7-2
2 x SPARC M7 processors, 4.13 GHz
512 GB memory
6 x 600 GB internal disks
1 x Sun Storage ZS3-2 (used for database and log files)
Flash storage (used for redo logs)
Oracle Solaris 11.3
Oracle Internet Directory 11g Release 1 PS7 (11.1.1.7.0)
Oracle Database 12c Enterprise Edition 12.1.0.2 (64-bit)

Benchmark Description

Oracle Internet Directory (OID) is Oracle's LDAPv3 Directory Server. The throughput for five key operations are measured — Search, Compare, Modify, Mix and Add.

LDAP Search Operations Test

This test scenario involved concurrent clients binding once to OID and then performing repeated LDAP Search operations. The salient characteristics of this test scenario is as follows:

  • SLAMD SearchRate job was used.
  • BaseDN of the search is root of the DIT, the scope is SUBTREE, the search filter is of the form UID=, DN and UID are the required attribute.
  • Each LDAP search operation matches a single entry.
  • The total number concurrent clients was 1000 and were distributed amongst two client nodes.
  • Each client binds to OID once and performs repeated LDAP Search operations, each search operation resulting in the lookup of a unique entry in such a way that no client looks up the same entry twice and no two clients lookup the same entry and all entries are searched randomly.
  • In one run of the test, random entries from the 50 Million entries are looked up in as many LDAP Search operations.
  • Test job was run for 60 minutes.

LDAP Compare Operations Test

This test scenario involved concurrent clients binding once to OID and then performing repeated LDAP Compare operations on userpassword attribute. The salient characteristics of this test scenario is as follows:

  • SLAMD CompareRate job was used.
  • Each LDAP compare operation matches user password of user.
  • The total number concurrent clients was 1000 and were distributed amongst two client nodes.
  • Each client binds to OID once and performs repeated LDAP compare operations.
  • In one run of the test, random entries from the 50 Million entries are compared in as many LDAP compare operations.
  • Test job was run for 60 minutes.

LDAP Modify Operations Test

This test scenario consisted of concurrent clients binding once to OID and then performing repeated LDAP Modify operations. The salient characteristics of this test scenario is as follows:

  • SLAMD LDAP modrate job was used.
  • A total of 50 concurrent LDAP clients were used.
  • Each client updates a unique entry each time and a total of 50 Million entries are updated.
  • Test job was run for 60 minutes.
  • Value length was set to 11.
  • Attribute that is being modified is not indexed.

LDAP Mixed Load Test

The test scenario involved both the LDAP search and LDAP modify clients enumerated above.

  • The ratio involved 60% LDAP search clients, 30% LDAP bind and 10% LDAP modify clients.
  • A total of 1000 concurrent LDAP clients were used and were distributed on 2 client nodes.
  • Test job was run for 60 minutes.

LDAP Add Load Test

The test scenario involved concurrent clients adding new entries as follows.

  • Slamd standard add rate job is used.
  • A total of 500,000 entries were added.
  • A total of 16 concurrent LDAP clients were used.
  • Slamd add's inetorgperson objectclass entry with 21 attributes (includes operational attributes).

See Also

Disclosure Statement

Copyright 2015, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 25 October 2015.

PeopleSoft Human Capital Management 9.1 FP2: SPARC M7-8 World Record

This result demonstrates how Oracle's SPARC M7-8 server using Oracle VM Server for SPARC (LDoms) provides mission critical enterprise virtualization.

  • The virtualized two-chip, 1 TB LDom of the SPARC M7-8 server set a world record two-chip PeopleSoft Human Capital Management (HCM) 9.1 FP2 benchmark result, supporting 35,000 HR Self-Service online users with response times under one second, while simultaneously running the Payroll batch workload.

  • The virtualized two-chip LDom of the SPARC M7-8 server demonstrated 4 times better Search and 6 times better Save average response times running nearly double the number of online users along with payroll batch, compared to the ten-chip x86 solution from Cisco.

  • Using only a single chip in the virtualized two-chip LDom on the SPARC M7-8 server, the batch-only run demonstrated 1.8 times better throughput (payments/hour) compared to a four-chip Cisco UCSB460 M4 server.

  • Using only a single chip in the virtualized two-chip LDom on the SPARC M7-8 server, the batch-only run demonstrated 2.3 times better throughput (payments/hour) compared to a nine-chip IBM zEnterprise z196 server (EC 2817-709, 9-way, 8943 MIPS).

  • This record result demonstrates that a two SPARC M7 processor LDom (in SPARC M7-8), can run the same number of online users as a dynamic domain (PDom) of eight SPARC M6 processors (in SPARC M6-32), with better online response times, batch elapsed times and batch throughput (payments/hour).

  • The SPARC M7-8 server provides enterprise applications high availability and security, where each application is executed on its own environment independent of the others.

Performance Landscape

The first table presents the combined results, running both the PeopleSoft HR Self-Service Online and Payroll Batch tests concurrently.

PeopleSoft HR Self-Service Online And Payroll Batch Using Oracle Database 11g
System
Processors
Chips
Used
Users Search/Save Batch Elapsed
Time
Batch Pay/Hr
SPARC M7-8
SPARC M7
LDom1 2 35,000 0.67 sec/0.42 sec 22.71 min 1,322,272
LDom2 2 35,000 0.85 sec/0.50 sec 22.96 min 1,307,875
SPARC M6-32
SPARC M6
8 35,000 1.80 sec/1.12 sec 29.2 min 1,029,440
Cisco 1 x B460 M4, 3 x B200 M3
Intel E7-4890 v2, Intel E5-2697 v2
10 18,000 2.70 sec/2.60 sec 21.70 min 1,383,816

The following results are running only the Peoplesoft HR Self-Service Online test.

PeopleSoft HR Self-Service Online Using Oracle Database 11g
System
Processors
Chips
Used
Users Search/Save
Avg Response Times
SPARC M7-8
SPARC M7
LDom1 2 40,000 0.55 sec/0.33 sec
LDom2 2 40,000 0.56 sec/0.32 sec
SPARC M6-32
SPARC M6
8 40,000 2.73 sec/1.33 sec
Cisco 1 x B460 M4, 3 x B200 M3
Intel E7-4890 v2, Intel E5-2697 v2
10 20,000 0.35 sec/0.17 sec

The following results are running only the Peoplesoft Payroll Batch test. For the SPARC M7-8 server results, only one of the processors was used per LDom. This was accomplished using processor sets to further restrict the test to a single SPARC M7 processor.

PeopleSoft Payroll Batch Using Oracle Database 11g
System
Processors
Chips
Used
Batch Elapsed
Time
Batch Pay/Hr
SPARC M7-8
SPARC M7
LDom1 1 13.06 min 2,299,296
LDom2 1 12.85 min 2,336,872
SPARC M6-32
SPARC M6
2 18.27 min 1,643,612
Cisco UCS B460 M4
Intel E7-4890 v2
4 23.02 min 1,304,655
IBM z196
zEnterprise (5.2 GHz, 8943 MIPS)
9 30.50 min 984,551

Configuration Summary

System Under Test:

SPARC M7-8 server with
8 x SPARC M7 processor (4.13 GHz)
4 TB memory
Virtualized as two Oracle VM Server for SPARC (LDom) each with
2 x SPARC M7 processor (4.13 GHz)
1 TB memory

Storage Configuration:

2 x Oracle ZFS Storage ZS3-2 appliance (DB Data) each with
40 x 300 GB 10K RPM SAS-2 HDD,
8 x Write Flash Accelerator SSD and
2 x Read Flash Accelerator SSD 1.6TB SAS
2 x Oracle Server X5-2L (DB redo logs & App object cache) each with
2 x Intel Xeon Processor E5-2630 v3
32 GB memory
4 x 1.6 TB NVMe SSD

Software Configuration:

Oracle Solaris 11.3
Oracle Database 11g Release 2 (11.2.0.3.0)
PeopleSoft Human Capital Management 9.1 FP2
PeopleSoft PeopleTools 8.52.03
Oracle Java SE 6u32
Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 043
Oracle WebLogic Server 11g (10.3.5)

Benchmark Description

The PeopleSoft Human Capital Management benchmark simulates thousands of online employees, managers and Human Resource administrators executing transactions typical of a Human Resources Self Service application for the Enterprise. Typical transactions are: viewing paychecks, promoting and hiring employees, updating employee profiles, etc. The database tier uses a database instance of about 500 GB in size, containing information for 500,480 employees. The application tier for this test includes web and application server instances, specifically Oracle WebLogic Server 11g, PeopleSoft Human Capital Management 9.1 FP2 and Oracle Java SE 6u32.

Key Points and Best Practices

In the HR online along with Payroll batch run, each LDom had one Oracle Solaris Zone of 7 cores containing the Web tier, two Oracle Solaris Zones of 16 cores each containing the Application tier and one Oracle Solaris Zone of 23 cores containing the Database tier. Two cores were dedicated to network and disk interrupt handling. In the HR online only run, each LDom had one Oracle Solaris Zone of 12 cores containing the Web tier, two Oracle Solaris Zones of 18 cores each containing the Application tier and one Oracle Solaris Zone of 14 cores containing the Database tier. 2 cores were dedicated to network and disk interrupt handling. In the Payroll batch only run, each LDom had one Oracle Solaris Zone of 31 cores containing the Database tier. 1 core was dedicated to disk interrupt handling.

All database data files, recovery files and Oracle Clusterware files for the PeopleSoft test were created with the Oracle Automatic Storage Management (Oracle ASM) volume manager for the added benefit of the ease of management provided by Oracle ASM integrated storage management solution.

In the application tier on each LDom, 5 PeopleSoft application domains with 350 application servers (70 per domain) were hosted in two separate Oracle Solaris Zones for a total of 10 domains with 700 application server processes.

All PeopleSoft Application processes and the 32 Web Server JVM instances were executed in the Oracle Solaris FX scheduler class.

See Also

Disclosure Statement

Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 10/25/2015.

Oracle E-Business Suite Applications R12.1.3 (OLTP X-Large): SPARC M7-8 World Record

Oracle's SPARC M7-8 server, using a four-chip Oracle VM Server for SPARC (LDom) virtualized server, produced a world record 20,000 users running the Oracle E-Business OLTP X-Large benchmark. The benchmark runs five Oracle E-Business online workloads concurrently: Customer Service, iProcurement, Order Management, Human Resources Self-Service, and Financials.

  • The virtualized four-chip LDom on the SPARC M7-8 was able to handle more users than the previous best result which used eight processors of Oracle's SPARC M6-32 server.

  • The SPARC M7-8 server using Oracle VM Server for SPARC provides enterprise applications high availability, where each application is executed on its own environment, insulated and independent of the others.

Performance Landscape

Oracle E-Business (3-tier) OLTP X-Large Benchmark
System Chips Total Online Users Weighted Average
Response Time (sec)
90th Percentile
Response Time (s)
SPARC M7-8 4 20,000 0.70 1.13
SPARC M6-32 8 18,500 0.61 1.16

Break down of the total number of users by component.

Users per Component
Component SPARC M7-8 SPARC M6-32
Total Online Users 20,000 users 18,500 users
HR Self-Service
Order-to-Cash
iProcurement
Customer Service
Financial
5000 users
2500 users
2700 users
7000 users
2800 users
4000 users
2300 users
2400 users
7000 users
2800 users

Configuration Summary

System Under Test:

SPARC M7-8 server
8 x SPARC M7 processors (4.13 GHz)
4 TB memory
2 x 600 GB SAS-2 HDD
using a Logical Domain with
4 x SPARC M7 processors (4.13 GHz)
2 TB memory
2 x Sun Storage Dual 16Gb Fibre Channel PCIe Universal HBA
2 x Sun Dual Port 10GBase-T Adapter
Oracle Solaris 11.3
Oracle E-Business Suite 12.1.3
Oracle Database 11g Release 2

Storage Configuration:

4 x Oracle ZFS Storage ZS3-2 appliances each with
2 x Read Flash Accelerator SSD
1 x Storage Drive Enclosure DE2-24P containing:
20 x 900 GB 10K RPM SAS-2 HDD
4 x Write Flash Accelerator SSD
1 x Sun Storage Dual 8Gb FC PCIe HBA
Used for Database files, Zones OS, EBS Mid-Tier Apps software stack
and db-tier Oracle Server
2 x Sun Server X4-2L server with
2 x Intel Xeon Processor E5-2650 v2
128 GB memory
1 x Sun Storage 6Gb SAS PCIe RAID HBA
4 x 400 GB SSD
14 x 600 GB HDD
Used for Redo log files, db backup storage.

Benchmark Description

The Oracle E-Business OLTP X-Large benchmark simulates thousands of online users executing transactions typical of an internal Enterprise Resource Processing, simultaneously executing five application modules: Customer Service, Human Resources Self Service, iProcurement, Order Management and Financial.

Each database tier uses a database instance of about 600 GB in size, supporting thousands of application users, accessing hundreds of objects (tables, indexes, SQL stored procedures, etc.).

Key Points and Best Practices

This test demonstrates virtualization technologies running concurrently various Oracle multi-tier business critical applications and databases on four SPARC M7 processors contained in a single SPARC M7-8 server supporting thousands of users executing a high volume of complex transactions with constrained (<1 sec) weighted average response time.

The Oracle E-Business LDom is further configured using Oracle Solaris Zones.

This result of 20,000 users was achieved by load balancing the Oracle E-Business Suite Applications 12.1.3 five online workloads across two Oracle Solaris processor sets and redirecting all network interrupts to a dedicated third processor set.

Each applications processor set (set-1 and set-2) was running concurrently two Oracle E-Business Suite Application servers and two database servers instances, each within its own Oracle Solaris Zone (4 x Zones per set).

Each application server network interface (to a client) was configured to map with the locality group associated to the CPUs processing the related workload, to guarantee memory locality of network structures and application servers hardware resources.

All external storage was connected with at least two paths to the host multipath-capable fibre channel controller ports and Oracle Solaris I/O multipathing feature was enabled.

See Also

Disclosure Statement

Oracle E-Business Suite R12 extra-large multiple-online module benchmark, SPARC M7-8, SPARC M7, 4.13 GHz, 4 chips, 128 cores, 1024 threads, 2 TB memory, 20,000 online users, average response time 0.70 sec, 90th percentile response time 1.13 sec, Oracle Solaris 11.3, Oracle Solaris Zones, Oracle VM Server for SPARC, Oracle E-Business Suite 12.1.3, Oracle Database 11g Release 2, Results as of 10/25/2015.

Wednesday Mar 05, 2014

SPARC T5-2 Delivers World Record 2-Socket SPECvirt_sc2010 Benchmark

Oracle's SPARC T5-2 server delivered a world record two-chip SPECvirt_sc2010 result of 4270 @ 264 VMs, establishing performance superiority in virtualized environments of the SPARC T5 processors with Oracle Solaris 11, which includes as standard virtualization products Oracle VM for SPARC and Oracle Solaris Zones.

  • The SPARC T5-2 server has 2.3x better performance than an HP BL620c G7 blade server (with two Westmere EX processors) which used VMware ESX 4.1 U1 virtualization software (best SPECvirt_sc2010 result on two-chip servers using VMware software).

  • The SPARC T5-2 server has 1.6x better performance than an IBM Flex System x240 server (with two Sandy Bridge processors) which used Kernel-based Virtual Machines (KVM).

  • This is the first SPECvirt_sc2010 result using Oracle production level software: Oracle Solaris 11.1, Oracle WebLogic Server 10.3.6, Oracle Database 11g Enterprise Edition, Oracle iPlanet Web Server 7 and Oracle Java Development Kit 7 (JDK). The only exception for the Dovecot mail server.

Performance Landscape

Complete benchmark results are at the SPEC website, SPECvirt_sc2010 Results. The following table highlights the leading two-chip results for the benchmark, bigger is better.

SPECvirt_sc2010
Leading Two-Chip Results
System Processor Result @ VMs Virtualization Software
SPARC T5-2 2 x SPARC T5, 3.6 GHz 4270 @ 264 Oracle VM Server for SPARC 3.0
Oracle Solaris Zones
IBM Flex System x240 2 x Intel E5-2690, 2.9 GHz 2741 @ 168 Red Hat Enterprise Linux 6.4 KVM
HP Proliant BL6200c G7 2 x Intel E7-2870, 2.4 GHz 1878 @ 120 VMware ESX 4.1 U1

Configuration Summary

System Under Test Highlights:

1 x SPARC T5-2 server, with
2 x 3.6 GHz SPARC T5 processors
1 TB memory
Oracle Solaris 11.1
Oracle VM Server for SPARC 3.0
Oracle iPlanet Web Server 7.0.15
Oracle PHP 5.3.14
Dovecot 2.1.17
Oracle WebLogic Server 11g (10.3.6)
Oracle Database 11g (11.2.0.3)
Java HotSpot(TM) 64-Bit Server VM on Solaris, version 1.7.0_51

Benchmark Description

The SPECvirt_sc2010 benchmark is SPEC's first benchmark addressing performance of virtualized systems. It measures the end-to-end performance of all system components that make up a virtualized environment.

The benchmark utilizes several previous SPEC benchmarks which represent common tasks which are commonly used in virtualized environments. The workloads included are derived from SPECweb2005, SPECjAppServer2004 and SPECmail2008. Scaling of the benchmark is achieved by running additional sets of virtual machines until overall throughput reaches a peak. The benchmark includes a quality of service criteria that must be met for a successful run.

Key Points and Best Practices

  • The SPARC T5 server running the Oracle Solaris 11.1, utilizes embedded virtualization products as the Oracle VM for SPARC and Oracle Solaris Zones, which provide a low overhead, flexible, scalable and manageable virtualization environment.

  • In order to provide a high level of data integrity and availability, all the benchmark data sets are stored on mirrored (RAID1) storage.

See Also

Disclosure Statement

SPEC and the benchmark name SPECvirt_sc are registered trademarks of the Standard Performance Evaluation Corporation. Results from www.spec.org as of 3/5/2014. SPARC T5-2, SPECvirt_sc2010 4270 @ 264 VMs; IBM Flex System x240, SPECvirt_sc2010 2741 @ 168 VMs; HP Proliant BL620c G7, SPECvirt_sc2010 1878 @ 120 VMs.

Friday Feb 14, 2014

SPARC M6-32 Delivers Oracle E-Business and PeopleSoft World Record Benchmarks, Linear Data Warehouse Scaling in a Virtualized Configuration

This result demonstrates how the combination of Oracle virtualization technologies for SPARC and Oracle's SPARC M6-32 server allow the deployment and concurrent high performance execution of multiple Oracle applications and databases sized for the Enterprise.

  • In an 8-chip Dynamic Domain (also known as PDom), the SPARC M6-32 server set a World Record E-Business 12.1.3 X-Large world record with 14,660 online users running five simultaneous E-Business modules.

  • In a second 8-chip Dynamic Domain, the SPARC M6-32 server set a World Record PeopleSoft HCM 9.1 HR Self-Service online supporting 35,000 users while simultaneously running a batch workload in 29.17 minutes. This was done with a database of 600,480 employees. Two other separate tests were run, one supporting 40,000 online users only and another a batch-only workload that was run in 18.27 min.

  • In a third Dynamic Domain with 16-chips on the SPARC M6-32 server, a data warehouse test was run that showed near-linear scaling.

  • On the SPARC M6-32 server, several critical applications instances were virtualized: an Oracle E-Business application and database, an Oracle's PeopleSoft application and database, and a Decision Support database instance using Oracle Database 12c.

  • In this Enterprise Virtualization benchmark a SPARC M6-32 server utilized all levels of Oracle Virtualization features available for SPARC servers. The 32-chip SPARC M6 based server was divided in three separate Dynamic Domains (also known as PDoms), available only on the SPARC Enterprise M-Series systems, which are completely electrically isolated and independent hardware partitions. Each PDom was subsequently split into multiple hypervisor-based Oracle VM for SPARC partitions (also known as LDoms), each one running its own Oracle Solaris kernel and managing its own CPUs and I/O resources. The hardware resources allocated to each Oracle VM for SPARC partition were then organized in various Oracle Solaris Zones, to further refine application tier isolation and resources management. The three PDoms were dedicated to the enterprise applications as follows:

    • Oracle E-Business PDom: Oracle E-Business 12.1.3 Suite World Record Extra-Large benchmark, exercising five Online Modules: Customer Service, Human Resources Self Service, iProcurement, Order Management and Financial, with 14,660 users and an average user response time under 2 seconds.

    • PeopleSoft PDom: PeopleSoft Human Capital Management (HCM) 9.1 FP2 World Record Benchmark, using PeopleTools 8.52 and an Oracle Database 11g Release 2, with 35,000 users, at an average user Search Time of 1.46 seconds and Save Time of 0.93 seconds. An online run with 40,000 users, had an average user Search Time of 2.17 seconds and Save Time of 1.39 seconds, and a Payroll batch run completed in 29.17 minutes elapsed time for more than 500,000 employees.

    • Decision Support PDom: An Oracle Database 12c instance executing a Decision Support workload on about 30 billion rows of data and achieving linear scalability, i.e. on the 16 chips comprising the PDom, the workload ran 16x faster than on a single chip. Specifically, the 16-chip PDom processed about 320M rows/sec whereas a single chip could process about 20M rows/sec.

  • The SPARC M6-32 server is ideally suited for large-memory utilization. In this virtualized environment, three critical applications made use of 16 TB of physical memory. Each of the Oracle VM Server for SPARC environments utilized from 4 to 8 TB of memory, more than the limits of other virtualization solutions.

  • SPARC M6-32 Server Virtualization Layout Highlights

    • The Oracle E-Business application instances were run in a dedicated Dynamic Domain consisting of 8 SPARC M6 processors and 4 TB of memory. The PDom was split into four symmetric Oracle VM Server for SPARC (LDoms) environments of 2 chips and 1 TB of memory each, two dedicated to the Application Server tier and the other two to the Database Server tier. Each Logical Domain was subsequently divided into two Oracle Solaris Zones, for a total of eight, one for each E-Business Application server and one for each Oracle Database 11g instance.

    • The PeopleSoft application was run in a dedicated Dynamic Domain (PDom) consisting of 8 SPARC M6 processors and 4 TB of memory. The PDom was split into two Oracle VM Server for SPARC (LDoms) environments one of 6 chips and 3 TB of memory, reserved for the Web and Application Server tiers, and a second one of 2 chips and 1 TB of memory, reserved for the Database tier. Two PeopleSoft Application Servers, a Web Server instance, and a single Oracle Database 11g instance were each executed in their respective and exclusive Oracle Solaris Zone.

    • The Oracle Database 12c Decision Support workload was run in a Dynamic Domain consisting of 16 SPARC M6 processors and 8 TB of memory.

  • All the Oracle Applications and Database instances were running at high level of performance and concurrently in a virtualized environment. Running three Enterprise level application environments on a single SPARC M6-32 server offers centralized administration, simplified physical layout, high availability and security features (as each PDom and LDom runs its own Oracle Solaris operating system copy physically and logically isolated from the other environments), enabling the coexistence of multiple versions Oracle Solaris and application software on a single physical server.

  • Dynamic Domains and Oracle VM Server for SPARC guests were configured with independent direct I/O domains, allowing for fast and isolated I/O paths, providing secure and high performance I/O access.

Performance Landscape

Oracle E-Business Test using Oracle Database 11g
SPARC M6-32 PDom, 8 SPARC M6 Processors, 4 TB Memory
Total Online Users Weighted Average
Response Time (sec)
90th Percentile
Response Time (s)
14,660 0.81 0.88
Multiple Online Modules X-Large Configuration (HR Self-Service, Order Management, iProcurement, Customer Service, Financial)

PeopleSoft HR Self-Service Online Plus Payroll Batch using Oracle Database 11g
SPARC M6-32 PDom, 8 SPARC M6 Processors, 4 TB Memory
HR Self-Service Payroll Batch
Elapsed (min)
Online Users Average User
Search / Save
Time (sec)
Transactions
per Second
35,000 1.46 / 0.93 116 29.17

HR Self-Service Only Payroll Batch Only
Elapsed (min)
40,000 2.17 / 1.39 132 18.27

Oracle Database 12c Decision Support Query Test
SPARC M6-32 PDom, 16 SPARC M6 Processors, 8 TB Memory
Parallelism
Chips Used
Rows Processing Rate
(rows/s)
Scaling Normalized to 1 Chip
16 319,981,734 15.9
8 162,545,303 8.1
4 80,943,271 4.0
2 40,458,329 2.0
1 20,086,829 1.0

Configuration Summary

System Under Test:

SPARC M6-32 server with
32 x SPARC M6 processors (3.6 GHz)
16 TB memory

Storage Configuration:

6 x Sun Storage 2540-M2 each with
8 x Expansion Trays (each tray equipped with 12 x 300 GB SAS drives)
7 x Sun Server X3-2L each with
2 x Intel Xeon E5-2609 2.4 GHz Processors
16 GB Memory
4 x Sun Flash Accelerator F40 PCIe 400 GB cards
Oracle Solaris 11.1 (COMSTAR)
1 x Sun Server X3-2L with
2 x Intel Xeon E5-2609 2.4 GHz Processors
16 GB Memory
12 x 3 TB SAS disks
Oracle Solaris 11.1 (COMSTAR)

Software Configuration:

Oracle Solaris 11.1 (11.1.10.5.0), Oracle E-Business
Oracle Solaris 11.1 (11.1.10.5.0), PeopleSoft
Oracle Solaris 11.1 (11.1.9.5.0), Decision Support
Oracle Database 11g Release 2, Oracle E-Business and PeopleSoft
Oracle Database 12c Release 1, Decision Support
Oracle E-Business Suite 12.1.3
PeopleSoft Human Capital Management 9.1 FP2
PeopleSoft PeopleTools 8.52.03
Oracle Java SE 6u32
Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 043
Oracle WebLogic Server 11g (10.3.4)

Oracle Dynamic Domains (PDoms) resources:


Oracle E-Business PeopleSoft Oracle DSS
Processors 8 8 16
Memory 4 TB 4 TB 8 TB
Oracle Solaris 11.1 (11.1.10.5.0) 11.1 (11.1.10.5.0) 11.1 (11.1.9.5.0)
Oracle Database 11g 11g 12c
Oracle VM for SPARC /
Oracle Solaris Zones
4 LDom / 8 Zones 2 LDom / 4 Zones None
Storage 7 x Sun Server X3-2L 1 x Sun Server X3-2L
(12 x 3 TB SAS )
2 x Sun Storage 2540-M2 / 2501 pairs
4 x Sun Storage 2540-M2/2501 pairs

Benchmark Description

This benchmark consists of three different applications running concurrently. It shows that large, enterprise workloads can be run on a single system and without performance impact between application environments.

The three workloads are:

  • Oracle E-Business Suite Online

    • This test simulates thousands of online users executing transactions typical of an internal Enterprise Resource Processing, including 5 application modules: Customer Service, Human Resources Self Service, Procurement, Order Management and Financial.

    • Each database tier uses a database instance of about 600 GB in size, and supporting thousands of application users, accessing hundreds of objects (tables, indexes, SQL stored procedures, etc.).

    • The application tier includes multiple web and application server instances, specifically Apache Web Server, Oracle Application Server 10g and Oracle Java SE 6u32.

  • PeopleSoft Human Capital Management

    • This test simulates thousands of online employees, managers and Human Resource administrators executing transactions typical of a Human Resources Self Service application for the Enterprise. Typical transactions are: viewing paychecks, promoting and hiring employees, updating employee profiles, etc.

    • The database tier uses a database instance of about 500 GB in size, containing information for 500,480 employees.

    • The application tier for this test includes web and application server instances, specifically Oracle WebLogic Server 11g, PeopleSoft Human Capital Management 9.1 and Oracle Java SE 6u32.

  • Decision Support Workload using the Oracle Database.

    • The query processes 30 billion rows stored in the Oracle Database, making heavy use of Oracle parallel query processing features. It performs multiple aggregations and summaries by reading and processing all the rows of the database.

Key Points and Best Practices

Oracle E-Business Environment

The Oracle E-Business Suite setup consisted 4 Oracle E-Business environments running 5 online Oracle E-Business modules simultaneously.

The Oracle E-Business environments were deployed on 4 Oracle VM for SPARC, respectively 2 for the Application tier and 2 for the Database tier. Each LDom included 2 SPARC M6 processor chips. The Application LDom was further split into 2 Oracle Solaris Zones, each one containing one Oracle E-Business Application instance. Similarly, on the Database tier, each LDom was further divided into 2 Oracle Solaris Zones, each containing an Oracle Database instance. Applications on the same LDom shared a 10 GbE network link to connect to the Database tier LDom. Each Application in a Zone was connected to its own dedicated Database Zone. The communication between the two Zones was implemented via Oracle Solaris 11 virtual network, which provides high performance, low latency transfers at memory speed using large frames (9000 bytes vs typical 1500 bytes frames).

The Oracle E-Business setup made use of the Oracle Database Shared Server feature in order to limit memory utilization, as well as the number of database Server processes. The Oracle Database configuration and optimization was substantially out-of-the-box, except for proper sizing the Oracle Database memory areas (System Global Area and Program Global Area).

In the Oracle E-Business Application LDom handling Customer Service and HR Self Service modules, 28 Forms servers and 8 OC4J application servers were hosted in the two separate Oracle Solaris Zones, for a total of 56 forms servers and 16 applications servers.

All the Oracle Database server processes and the listener processes were executed in the Oracle Solaris FX scheduler class.

PeopleSoft Environment

The PeopleSoft Application Oracle VM for SPARC had one Oracle Solaris Zone of 12 cores containing the web tier and two Oracle Solaris Zones of 57 cores total containing the Application tier. The Database tier was contained in an Oracle VM for SPARC consisting of one Oracle Solaris Zone of 24 cores. One core, in the Application Oracle VM, was dedicated to network and disk interrupt handling.

All database data files, recovery files and Oracle Clusterware files for the PeopleSoft test were created with the Oracle Automatic Storage Management (Oracle ASM) volume manager for the added benefit of the ease of management provided by Oracle ASM integrated storage management solution.

In the application tier, 5 PeopleSoft domains with 350 application servers (70 per each domain) were hosted in the two separate Oracle Solaris Zones for a total of 10 domains with 700 application server processes.

All PeopleSoft Application processes and Web Server JVM instances were executed in the Oracle Solaris FX scheduler class.

Oracle Decision Support Environment

The decision support workload showed how the combination of a large memory (8 TB) and a large number of processors (16 chips comprising 1536 virtual CPUs) together with Oracle parallel query facility can linearly increase the performance of certain decision support queries as the number of CPUs increase.

The large memory was used to cache the entire 30 billion row Oracle table in memory. There are a number of ways to accomplish this. The method deployed in this test was to allocate sufficient memory for Oracle's "keep cache" and direct the table to the "keep cache."

To demonstrate scalability, it was necessary to ensure that the number of Oracle parallel servers was always equal to the number of available virtual CPUs. This was accomplished by the combination of providing a degree of parallelism hint to the query and setting both parallel_max_servers and parallel_min_servers to the number of virtual CPUs.

The number of virtual CPUs for each stage of the scalability test was adjusted using the psradm command available in Oracle Solaris.

See Also

Disclosure Statement

Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. PeopleSoft results as of 02/14/2014. Other results as of 09/22/2013.

Oracle E-Business Suite R12 extra-large multiple-online module benchmark, SPARC M6-32, SPARC M6, 3.6 GHz, 8 chips, 96 cores, 768 threads, 4 TB memory, 14,660 online users, average response time 0.81 sec, 90th percentile response time 0.88 sec, Oracle Solaris 11.1, Oracle Solaris Zones, Oracle VM for SPARC, Oracle E-Business Suite 12.1.3, Oracle Database 11g Release 2, Results as of 9/22/2013.

Thursday Sep 26, 2013

SPARC M6-32 Delivers Oracle E-Business and PeopleSoft World Record Benchmarks, Linear Data Warehouse Scaling in a Virtualized Configuration

This result has been superceded.  Please see the latest result.

 This result demonstrates how the combination of Oracle virtualization technologies for SPARC and Oracle's SPARC M6-32 server allow the deployment and concurrent high performance execution of multiple Oracle applications and databases sized for the Enterprise.

  • In an 8-chip Dynamic Domain (also known as PDom), the SPARC M6-32 server set a World Record E-Business 12.1.3 X-Large world record with 14,660 online users running five simultaneous E-Business modules.

  • In a second 8-chip Dynamic Domain, the SPARC M6-32 server set a World Record PeopleSoft HCM 9.1 HR Self-Service online supporting 34,000 users while simultaneously running a batch workload in 29.7 minutes. This was done with a database of 600,480 employees. In a separate test running a batch-only workload was run in 21.2 min.

  • In a third Dynamic Domain with 16-chips on the SPARC M6-32 server, a data warehouse test was run that showed near-linear scaling.

  • On the SPARC M6-32 server, several critical applications instances were virtualized: an Oracle E-Business application and database, an Oracle's PeopleSoft application and database, and a Decision Support database instance using Oracle Database 12c.

  • In this Enterprise Virtualization benchmark a SPARC M6-32 server utilized all levels of Oracle Virtualization features available for SPARC servers. The 32-chip SPARC M6 based server was divided in three separate Dynamic Domains (also known as PDoms), available only on the SPARC Enterprise M-Series systems, which are completely electrically isolated and independent hardware partitions. Each PDom was subsequently split into multiple hypervisor-based Oracle VM for SPARC partitions (also known as LDoms), each one running its own Oracle Solaris kernel and managing its own CPUs and I/O resources. The hardware resources allocated to each Oracle VM for SPARC partition were then organized in various Oracle Solaris Zones, to further refine application tier isolation and resources management. The three PDoms were dedicated to the enterprise applications as follows:

    • Oracle E-Business PDom: Oracle E-Business 12.1.3 Suite World Record Extra-Large benchmark, exercising five Online Modules: Customer Service, Human Resources Self Service, iProcurement, Order Management and Financial, with 14,660 users and an average user response time under 2 seconds.

    • PeopleSoft PDom: PeopleSoft Human Capital Management (HCM) 9.1 FP2 World Record Benchmark, using PeopleTools 8.52 and an Oracle Database 11g Release 2, with 34,000 users, at an average user Search Time of 1.11 seconds and Save Time of 0.77 seconds, and a Payroll batch run completed in 29.7 minutes elapsed time for more than 500,000 employees.

    • Decision Support PDom: An Oracle Database 12c instance executing a Decision Support workload on about 30 billion rows of data and achieving linear scalability, i.e. on the 16 chips comprising the PDom, the workload ran 16x faster than on a single chip. Specifically, the 16-chip PDom processed about 320M rows/sec whereas a single chip could process about 20M rows/sec.

  • The SPARC M6-32 server is ideally suited for large-memory utilization. In this virtualized environment, three critical applications made use of 16 TB of physical memory. Each of the Oracle VM Server for SPARC environments utilized from 4 to 8 TB of memory, more than the limits of other virtualization solutions.

  • SPARC M6-32 Server Virtualization Layout Highlights

    • The Oracle E-Business application instances were run in a dedicated Dynamic Domain consisting of 8 SPARC M6 processors and 4 TB of memory. The PDom was split into four symmetric Oracle VM Server for SPARC (LDoms) environments of 2 chips and 1 TB of memory each, two dedicated to the Application Server tier and the other two to the Database Server tier. Each Logical Domain was subsequently divided into two Oracle Solaris Zones, for a total of eight, one for each E-Business Application server and one for each Oracle Database 11g instance.

    • The PeopleSoft application was run in a dedicated Dynamic Domain (PDom) consisting of 8 SPARC M6 processors and 4 TB of memory. The PDom was split into two Oracle VM Server for SPARC (LDoms) environments one of 6 chips and 3 TB of memory, reserved for the Web and Application Server tiers, and a second one of 2 chips and 1 TB of memory, reserved for the Database tier. Two PeopleSoft Application Servers, a Web Server instance, and a single Oracle Database 11g instance were each executed in their respective and exclusive Oracle Solaris Zone.

    • The Oracle Database 12c Decision Support workload was run in a Dynamic Domain consisting of 16 SPARC M6 processors and 8 TB of memory.

  • All the Oracle Applications and Database instances were running at high level of performance and concurrently in a virtualized environment. Running three Enterprise level application environments on a single SPARC M6-32 server offers centralized administration, simplified physical layout, high availability and security features (as each PDom and LDom runs its own Oracle Solaris operating system copy physically and logically isolated from the other environments), enabling the coexistence of multiple versions Oracle Solaris and application software on a single physical server.

  • Dynamic Domains and Oracle VM Server for SPARC guests were configured with independent direct I/O domains, allowing for fast and isolated I/O paths, providing secure and high performance I/O access.

Performance Landscape

Oracle E-Business Test using Oracle Database 11g
SPARC M6-32 PDom, 8 SPARC M6 Processors, 4 TB Memory
Total Online Users Weighted Average
Response Time (sec)
90th Percentile
Response Time (s)
14,660 0.81 0.88
Multiple Online Modules X-Large Configuration (HR Self-Service, Order Management, iProcurement, Customer Service, Financial)

PeopleSoft HR Self-Service Online Plus Payroll Batch using Oracle Database 11g
SPARC M6-32 PDom, 8 SPARC M6 Processors, 4 TB Memory
HR Self-Service Payroll Batch
Elapsed (min)
Online Users Average User
Search / Save
Time (sec)
Transactions
per Second
34,000 1.11 / 0.77 113 29.7

Payroll Batch Only
Elapsed (min)
21.17

Oracle Database 12c Decision Support Query Test
SPARC M6-32 PDom, 16 SPARC M6 Processors, 8 TB Memory
Parallelism
Chips Used
Rows Processing Rate
(rows/s)
Scaling Normalized to 1 Chip
16 319,981,734 15.9
8 162,545,303 8.1
4 80,943,271 4.0
2 40,458,329 2.0
1 20,086,829 1.0

Configuration Summary

System Under Test:

SPARC M6-32 server with
32 x SPARC M6 processors (3.6 GHz)
16 TB memory

Storage Configuration:

6 x Sun Storage 2540-M2 each with
8 x Expansion Trays (each tray equipped with 12 x 300 GB SAS drives)
7 x Sun Server X3-2L each with
2 x Intel Xeon E5-2609 2.4 GHz Processors
16 GB Memory
4 x Sun Flash Accelerator F40 PCIe 400 GB cards
Oracle Solaris 11.1 (COMSTAR)
1 x Sun Server X3-2L with
2 x Intel Xeon E5-2609 2.4 GHz Processors
16 GB Memory
12 x 3 TB SAS disks
Oracle Solaris 11.1 (COMSTAR)

Software Configuration:

Oracle Solaris 11.1 (11.1.10.5.0), Oracle E-Business
Oracle Solaris 11.1 (11.1.10.5.0), PeopleSoft
Oracle Solaris 11.1 (11.1.9.5.0), Decision Support
Oracle Database 11g Release 2, Oracle E-Business and PeopleSoft
Oracle Database 12c Release 1, Decision Support
Oracle E-Business Suite 12.1.3
PeopleSoft Human Capital Management 9.1 FP2
PeopleSoft PeopleTools 8.52.03
Oracle Java SE 6u32
Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 043
Oracle WebLogic Server 11g (10.3.4)

Oracle Dynamic Domains (PDoms) resources:


Oracle E-Business PeopleSoft Oracle DSS
Processors 8 8 16
Memory 4 TB 4 TB 8 TB
Oracle Solaris 11.1 (11.1.10.5.0) 11.1 (11.1.10.5.0) 11.1 (11.1.9.5.0)
Oracle Database 11g 11g 12c
Oracle VM for SPARC /
Oracle Solaris Zones
4 LDom / 8 Zones 2 LDom / 4 Zones None
Storage 7 x Sun Server X3-2L 1 x Sun Server X3-2L
(12 x 3 TB SAS )
2 x Sun Storage 2540-M2 / 2501 pairs
4 x Sun Storage 2540-M2/2501 pairs

Benchmark Description

This benchmark consists of three different applications running concurrently. It shows that large, enterprise workloads can be run on a single system and without performance impact between application environments.

The three workloads are:

  • Oracle E-Business Suite Online

    • This test simulates thousands of online users executing transactions typical of an internal Enterprise Resource Processing, including 5 application modules: Customer Service, Human Resources Self Service, Procurement, Order Management and Financial.

    • Each database tier uses a database instance of about 600 GB in size, and supporting thousands of application users, accessing hundreds of objects (tables, indexes, SQL stored procedures, etc.).

    • The application tier includes multiple web and application server instances, specifically Apache Web Server, Oracle Application Server 10g and Oracle Java SE 6u32.

  • PeopleSoft Human Capital Management

    • This test simulates thousands of online employees, managers and Human Resource administrators executing transactions typical of a Human Resources Self Service application for the Enterprise. Typical transactions are: viewing paychecks, promoting and hiring employees, updating employee profiles, etc.

    • The database tier uses a database instance of about 500 GB in size, containing information for 500,480 employees.

    • The application tier for this test includes web and application server instances, specifically Oracle WebLogic Server 11g, PeopleSoft Human Capital Management 9.1 and Oracle Java SE 6u32.

  • Decision Support Workload using the Oracle Database.

    • The query processes 30 billion rows stored in the Oracle Database, making heavy use of Oracle parallel query processing features. It performs multiple aggregations and summaries by reading and processing all the rows of the database.

Key Points and Best Practices

Oracle E-Business Environment

The Oracle E-Business Suite setup consisted 4 Oracle E-Business environments running 5 online Oracle E-Business modules simultaneously. The Oracle E-Business environments were deployed on 4 Oracle VM for SPARC, respectively 2 for the Application tier and 2 for the Database tier. Each LDom included 2 SPARC M6 processor chips. The Application LDom was further split into 2 Oracle Solaris Zones, each one containing one Oracle E-Business Application instance. Similarly, on the Database tier, each LDom was further divided into 2 Oracle Solaris Zones, each containing an Oracle Database instance. Applications on the same LDom shared a 10 GbE network link to connect to the Database tier LDom. Each Application in a Zone was connected to its own dedicated Database Zone. The communication between the two Zones was implemented via Oracle Solaris 11 virtual network, which provides high performance, low latency transfers at memory speed using large frames (9000 bytes vs typical 1500 bytes frames).

The Oracle E-Business setup made use of the Oracle Database Shared Server feature in order to limit memory utilization, as well as the number of database Server processes. The Oracle Database configuration and optimization was substantially out-of-the-box, except for proper sizing the Oracle Database memory areas (System Global Area and Program Global Area).

In the Oracle E-Business Application LDom handling Customer Service and HR Self Service modules, 28 Forms servers and 8 OC4J application servers were hosted in the two separate Oracle Solaris Zones, for a total of 56 forms servers and 16 applications servers.

All the Oracle Database server processes and the listener processes were executed in the Oracle Solaris FX scheduler class.

PeopleSoft Environment

The PeopleSoft Application Oracle VM for SPARC had one Oracle Solaris Zone of 12 cores containing the web tier and two Oracle Solaris Zones of 28 cores each containing the Application tier. The Database tier was contained in an Oracle VM for SPARC consisting of one Oracle Solaris Zone of 24 cores. One and a half cores, in the Application Oracle VM, were dedicated to network and disk interrupt handling.

All database data files, recovery files and Oracle Clusterware files for the PeopleSoft test were created with the Oracle Automatic Storage Management (Oracle ASM) volume manager for the added benefit of the ease of management provided by Oracle ASM integrated storage management solution.

In the application tier, 5 PeopleSoft domains with 350 application servers (70 per each domain) were hosted in the two separate Oracle Solaris Zones for a total of 10 domains with 700 application server processes.

All PeopleSoft Application processes and Web Server JVM instances were executed in the Oracle Solaris FX scheduler class.

Oracle Decision Support Environment

The decision support workload showed how the combination of a large memory (8 TB) and a large number of processors (16 chips comprising 1536 virtual CPUs) together with Oracle parallel query facility can linearly increase the performance of certain decision support queries as the number of CPUs increase.

The large memory was used to cache the entire 30 billion row Oracle table in memory. There are a number of ways to accomplish this. The method deployed in this test was to allocate sufficient memory for Oracle's "keep cache" and direct the table to the "keep cache."

To demonstrate scalability, it was necessary to ensure that the number of Oracle parallel servers was always equal to the number of available virtual CPUs. This was accomplished by the combination of providing a degree of parallelism hint to the query and setting both parallel_max_servers and parallel_min_servers to the number of virtual CPUs.

The number of virtual CPUs for each stage of the scalability test was adjusted using the psradm command available in Oracle Solaris.

See Also

Disclosure Statement

Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 09/22/2013.

Oracle E-Business Suite R12 extra-large multiple-online module benchmark, SPARC M6-32, SPARC M6, 3.6 GHz, 8 chips, 96 cores, 768 threads, 4 TB memory, 14,660 online users, average response time 0.81 sec, 90th percentile response time 0.88 sec, Oracle Solaris 11.1, Oracle Solaris Zones, Oracle VM for SPARC, Oracle E-Business Suite 12.1.3, Oracle Database 11g Release 2, Results as of 9/20/2013.

Wednesday Sep 25, 2013

SPARC T5-8 Delivers World Record Oracle OLAP Perf Version 3 Benchmark Result on Oracle Database 12c

Oracle's SPARC T5-8 server delivered world record query performance for systems running Oracle Database 12c for the Oracle OLAP Perf Version 3 benchmark.

  • The query throughput on the SPARC T5-8 server is 1.7x higher than that of an 8-chip Intel Xeon E7-8870 server. Both systems had sub-second average response times.

  • The SPARC T5-8 server with the Oracle Database demonstrated the ability to support at least 700 concurrent users querying OLAP cubes (with no think time), processing 2.33 million analytic queries per hour with an average response time of less than 1 second per query. This performance was enabled by keeping the entire cube in-memory utilizing the 4 TB of memory on the SPARC T5-8 server.

  • Assuming a 60 second think time between query requests, the SPARC T5-8 server can support approximately 39,450 concurrent users with the same sub-second response time.

  • The workload uses a set of realistic Business Intelligence (BI) queries that run against an OLAP cube based on a 4 billion row fact table of sales data. The 4 billion rows are partitioned by month spanning 10 years.

  • The combination of the Oracle Database 12cwith the Oracle OLAP option running on a SPARC T5-8 server supports live data updates occurring concurrently with minimally impacted user query executions.

Performance Landscape

Oracle OLAP Perf Version 3 Benchmark
Oracle cube base on 4 billion fact table rows
10 years of data partitioned by month
System Queries/
hour
Users Average Response
Time (sec)
0 sec think time 60 sec think time
SPARC T5-8 2,329,000 700 39,450 <1 sec
8-chip Intel Xeon E7-8870 1,354,000 120 22,675 <1 sec

Configuration Summary

SPARC T5-8:

1 x SPARC T5-8 server with
8 x SPARC T5 processors, 3.6 GHz
4 TB memory
Data Storage and Redo Storage
Flash Storage
Oracle Solaris 11.1 (11.1.8.2.0)
Oracle Database 12c Release 1 (12.1.0.1) with Oracle OLAP option

Sun Server X2-8:

1 x Sun Server X2-8 with
8 x Intel Xeon E7-8870 processors, 2.4 GHz
1 TB memory
Data Storage and Redo Storage
Flash Storage
Oracle Solaris 10 10/12
Oracle Database 12c Release 1 (12.1.0.1) with Oracle OLAP option

Benchmark Description

The Oracle OLAP Perf Version 3 benchmark is a workload designed to demonstrate and stress the ability of the OLAP Option to deliver fast query, near real-time updates and rich calculations using a multi-dimensional model in the context of the Oracle data warehousing.

The bulk of the benchmark entails running a number of concurrent users, each issuing typical multidimensional queries against an Oracle cube. The cube has four dimensions: time, product, customer, and channel. Each query user issues approximately 150 different queries. One query chain may ask for total sales in a particular region (e.g South America) for a particular time period (e.g. Q4 of 2010) followed by additional queries which drill down into sales for individual countries (e.g. Chile, Peru, etc.) with further queries drilling down into individual stores, etc. Another query chain may ask for yearly comparisons of total sales for some product category (e.g. major household appliances) and then issue further queries drilling down into particular products (e.g. refrigerators, stoves. etc.), particular regions, particular customers, etc.

While the core of every OLAP Perf benchmark is real world query performance, the benchmark itself offers numerous execution options such as varying data set sizes, number of users, numbers of queries for any given user and cube update frequency. Version 3 of the benchmark is executed with a much larger number of query streams than previous versions and used a cube designed for near real-time updates. The results produced by version 3 of the benchmark are not directly comparable to results produced by previous versions of the benchmark.

The near real-time update capability is implemented along the following lines. A large Oracle cube, H, is built from a 4 billion row star schema, containing data up until the end of last business day. A second small cube, D, is then created which will contain all of today's new data coming in from outside the world. It will be updated every L minutes with the data coming in within the last L minutes. A third cube, R, joins cubes H and D for reporting purposes much like a view might join data from two tables. Calculations are installed into cube R. The use of a reporting cube which draws data from different storage cubes is a common practice.

Query users are never locked out of query operations while new data is added to the update cube. The point of the demonstration is to show that an Oracle OLAP system can be designed which results in data being no more than L minutes out of date, where L may be as low as just a few minutes. This is what is meant by near real-time analytics.

Key Points and Best Practices

  • Building and querying cubes with the Oracle OLAP option requires a large temporary tablespace. Normally temporary tablespaces would reside on disk storage. However, because the SPARC T5-8 server used in this benchmark had 4 TB of main memory, it was possible to use main memory for the OLAP temporary tablespace. This was accomplished by using a temporary, memory-based file system (TMPFS) for the temporary tablespace datafiles.

  • Since typical business intelligence users are often likely to issue similar queries, either with the same or different constants in the where clauses, setting the init.ora parameter "cursor_sharing" to "force" provides for additional query throughput and a larger number of potential users.

  • Assuming the normal Oracle Database initialization parameters (e.g. SGA, PGA, processes etc.) are appropriately set, out of the box performance for the Oracle OLAP workload should be close to what is reported here. Additional performance resulted from using memory for the OLAP temporary tablespace setting "cursor_sharing" to force.

  • Oracle OLAP Cube update performance was optimized by running update processes in the FX class with a priority greater than 0.

  • The maximum lag time between updates to the source fact table and data availability to query users (what was referred to as L in the benchmark description) was less than 3 minutes for the benchmark environment on the SPARC T5-8 server.

See Also

Disclosure Statement

Copyright 2013, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 09/22/2013.

Tuesday Mar 26, 2013

SPARC T5-8 Produces TPC-C Benchmark Single-System World Record Performance

Oracle's SPARC T5-8 server equipped with eight 3.6 GHz SPARC T5 processors obtained a result of 8,552,523 tpmC on the TPC-C benchmark. This result is a world record for single servers. Oracle demonstrated this world record database performance running Oracle Database 11g Release 2 Enterprise Edition with Partitioning.

  • The SPARC T5-8 server delivered a single system TPC-C world record of 8,552,523 tpmC with a price performance of $0.55/tpmC using Oracle Database 11g Release 2. This configuration is available 09/25/13.

  • The SPARC T5-8 server has 2.8x times better performance than the 4-processor IBM x3850 X5 system equipped with Intel Xeon processors.

  • The SPARC T5-8 server delivers 1.7x the performance compared to the next best eight processor result.

  • The SPARC T5-8 server delivers 2.4x the performance per chip compared to the IBM Power 780 3-node cluster result.

  • The SPARC T5-8 server delivers 1.8x the performance per chip compared to the IBM Power 780 non-clustered result.

  • The SPARC T5-8 server delivers 1.4x the performance per chip compared to the IBM Flex x240 Xeon result.

  • The SPARC T5-8 server delivers 1.7x the performance per chip compared to the Sun Server X2-8 system equipped with Intel Xeon processors.

  • The SPARC T5-8 server demonstrated over 3.1 Million 4KB IOP/sec with 76% idle, in a separate IO intensive workload, demonstrating its ability process a large IO workload with lots of processing headroom.

  • This result showed Oracle's integrated hardware and software stacks provide industry leading performance.

  • The Oracle solution utilized Oracle Solaris 11.1 with Oracle Database 11g Enterprise Edition with Partitioning and demonstrates stability and performance with this highly secure operating environment to produce the world record TPC-C benchmark performance.

Performance Landscape

Select TPC-C results (sorted by tpmC, bigger is better)

System p/c/t tpmC Price
/tpmC
Avail Database Memory
Size
IBM Power 780 Cluster 24/192/768 10,366,254 1.38 USD 10/13/2010 IBM DB2 9.7 6 TB
SPARC T5-8 8/128/1024 8,552,523 0.55 USD 9/25/2013 Oracle 11g R2 4 TB
IBM Power 595 32/64/128 6,085,166 2.81 USD 12/10/2008 IBM DB2 9.5 4 TB
Sun Server X2-8 8/80/160 5,055,888 0.89 USD 7/10/2012 Oracle 11g R2 4 TB
IBM x3850 X5 4/40/80 3,014,684 0.59 USD 7/11/2011 IBM DB2 9.7 3 TB
IBM Flex x240 2/16/32 1,503,544 0.53 USD 8/16/2012 IBM DB2 9.7 768 GB
IBM Power 780 2/8/32 1,200,011 0.69 USD 10/13/2010 IBM DB2 9.5 512 GB

p/c/t - processors, cores, threads
Avail - availability date

Oracle and IBM TPC-C Response times

System tpmC Response Time (sec)
New Order 90th%
Response Time (sec)
New Order Average
IBM Power 780 Cluster 10,366,254 2.100 1.137
SPARC T5-8 8,552,523 0.410 0.234
IBM Power 595 6,085,166 1.690 1.220
IBM Power 780 1,200,011 0.694 0.403

Oracle uses Response Time New Order Average and Response Time New Order 90th% for comparison between Oracle and IBM.

Graphs of Oracle's and IBM's Response Time New Order Average and Response Time New Order 90th% can be found in the full disclosure reports on TPC's website TPC-C Official Result Page.

Configuration Summary and Results

Hardware Configuration:

Server
SPARC T5-8
8 x 3.6 GHz SPARC T5
4 TB memory
2 x 600 GB 10K RPM SAS2 internal disks
12 x 8 Gbs FC HBA

Data Storage
54 x Sun Server X3-2L systems configured as COMSTAR heads, each with
2 x 2.4 GHz Intel Xeon E5-2609 processors
16 GB memory
4 x Sun Flash Accelerator F40 PCIe Cards (400 GB each)
12 x 3 TB 7.2K RPM 3.5" SAS disks
2 x 600 GB 10K RPM SAS2 disks
2 x Brocade 6510 switches

Redo Storage
2 x Sun Server X3-2L systems configured as COMSTAR heads, each with
2 x 2.4 GHz Intel Xeon E5-2609 processors
16 GB memory
12 x 3 TB 7.2K RPM 3.5" SAS disks
2 x 600 GB 10K RPM SAS2 disks

Clients
16 x Sun Server X3-2 servers, each with
2 x 2.9 GHz Intel Xeon E5-2690 processors
64 GB memory
2 x 600 GB 10K RPM SAS2 disks

Software Configuration:

Oracle Solaris 11.1 SRU 4.5 (for SPARC T5-8)
Oracle Solaris 11.1 (for COMSTAR systems)
Oracle Database 11g Release 2 Enterprise Edition with Partitioning
Oracle iPlanet Web Server 7.0 U5
Oracle Tuxedo CFS-R

Results:

System: SPARC T5-8
tpmC: 8,552,523
Price/tpmC: 0.55 USD
Available: 9/25/2013
Database: Oracle Database 11g
Cluster: no
Response Time New Order Average: 0.234 seconds

Benchmark Description

TPC-C is an OLTP system benchmark. It simulates a complete environment where a population of terminal operators executes transactions against a database. The benchmark is centered around the principal activities (transactions) of an order-entry environment. These transactions include entering and delivering orders, recording payments, checking the status of orders, and monitoring the level of stock at the warehouses.

Key Points and Best Practices

  • Oracle Database 11g Release 2 Enterprise Edition with Partitioning scales easily to this high level of performance.

  • COMSTAR (Common Multiprotocol SCSI Target) is the software framework that enables an Oracle Solaris host to serve as a SCSI Target platform. COMSTAR uses a modular approach to break the huge task of handling all the different pieces in a SCSI target subsystem into independent functional modules which are glued together by the SCSI Target Mode Framework (STMF). The modules implementing functionality at SCSI level (disk, tape, medium changer etc.) are not required to know about the underlying transport. And the modules implementing the transport protocol (FC, iSCSI, etc.) are not aware of the SCSI-level functionality of the packets they are transporting. The framework hides the details of allocation providing execution context and cleanup of SCSI commands and associated resources and simplifies the task of writing the SCSI or transport modules.

  • Oracle iPlanet Web Server middleware is used for the client tier of the benchmark. Each web server instance supports more than a quarter-million users while satisfying the response time requirement from the TPC-C benchmark.

See Also

Disclosure Statement

TPC Benchmark C, tpmC, and TPC-C are trademarks of the Transaction Processing Performance Council (TPC). SPARC T5-8 (8/128/1024) with Oracle Database 11g Release 2 Enterprise Edition with Partitioning, 8,552,523 tpmC, $0.55 USD/tpmC, available 9/25/2013. IBM Power 780 Cluster (24/192/768) with DB2 ESE 9.7, 10,366,254 tpmC, $1.38 USD/tpmC, available 10/13/2010. IBM x3850 X5 (4/40/80) with DB2 ESE 9.7, 3,014,684 tpmC, $0.59 USD/tpmC, available 7/11/2011. IBM x3850 X5 (4/32/64) with DB2 ESE 9.7, 2,308,099 tpmC, $0.60 USD/tpmC, available 5/20/2011. IBM Flex x240 (2/16/32) with DB2 ESE 9.7, 1,503,544 tpmC, $0.53 USD/tpmC, available 8/16/2012. IBM Power 780 (2/8/32) with IBM DB2 9.5, 1,200,011 tpmC, $0.69 USD/tpmC, available 10/13/2010. Source: http://www.tpc.org/tpcc, results as of 3/26/2013.

SPARC T5-2 Achieves JD Edwards EnterpriseOne Benchmark World Records

Oracle produced World Record batch throughput for single system results on Oracle's JD Edwards EnterpriseOne Day-in-the-Life benchmark using Oracle's SPARC T5-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2. There are two workloads tested: online plus batch workload and batch-only workload.

Online plus batch workload:

  • The SPARC T5-2 server delivered a result of 12,000 online users at 180 msec average response time while concurrently executing a mix of JD Edwards EnterpriseOne long and short batch processes at 198.5 UBEs/min (Universal Batch Engines per minute).

  • The SPARC T5-2 server online plus batch throughput is 2.7x higher than the IBM Power 770 server, both running 12,000 online users.

  • The SPARC T5-2 server online plus batch throughput is 6x higher per chip than the IBM Power 770 server. The SPARC T5-2 server has 2 chips and the IBM Power 770 has 4 chips, both ran 12,000 online users.

  • The SPARC T5-2 server online plus batch throughput is 3x higher per core than the IBM Power 770 server. Both servers have 32 cores and ran 12,000 online users.

Batch-only workload:

  • The SPARC T5-2 server delivered throughput of 880 UBEs/min while executing the batch-only workload (Long and Short batch processes).

  • The SPARC T5-2 server batch-only throughput is 2.7x faster per chip than the IBM Power 770 server. The SPARC T5-2 server has 2 chips and the IBM Power 770 has 4 chips.

  • The SPARC T5-2 server batch-only throughput is 1.4x higher per core than the IBM Power 770 server. Both servers have 32 cores.

  • The SPARC T5-2 server batch-only throughput is 61% faster than the Cisco multiple system solution.

  • The SPARC T5-2 server batch-only throughput is 5x faster per chip than the Cisco UCS B200/B250 M2 servers. The SPARC T5-2 server has 2 chips and the Cisco 3 server solution has 6 chips.

  • The SPARC T5-2 server batch-only throughput is 18x higher per core than the Cisco UCS B200/B250 M2 servers. The SPARC T5-2 server has 32 cores while the Cisco solution utilized 36 cores.

Both workloads:

  • The SPARC T5-2 server offers a 5.4x cost savings for the application server when compared to the IBM Power 770 application server.

  • The SPARC T5-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2 utilized a maximum 65% of the available CPU power, leaving headroom for additional processing.

  • The database server in a shared-server configuration allows for optimized CPU resource utilization and significant memory savings on the SPARC T5-2 server without sacrificing performance.

Performance Landscape

JD Edwards EnterpriseOne Day in the Life (DIL) Benchmark
Consolidated Online with Batch Workload
System Rack
Units (U)
Batch
Rate
(UBEs/min)
Online
Users
Users/
U
UBEs/
Core
UBEs/
Chip
Version
SPARC T5-2 (2 x SPARC T5, 3.6 GHz) 3 198.5 12000 4000 6.2 99 9.0.2
IBM Power 770 (4 x POWER7, 3.3 GHz) 8 65 12000 1500 2.0 16 9.0.2

Batch Rate (UBEs/min) — Batch transaction rate in UBEs per minute.

JD Edwards EnterpriseOne Batch Only Benchmark
System Rack
Units (U)
Batch
Rate
(UBEs/min)
UBEs/
U
UBEs/
Core
UBEs/
Chip
Version
SPARC T5-2 (2 x SPARC T5, 3.6 GHz) 3 880 267 25 440 9.0.2
IBM Power 770 (4 x POWER7, 3.3 GHz) 8 643 81 20 161 9.0.2
2 x Cisco B200 M2 (2 x X5690, 3.46 GHz)
1 x Cisco B250 M2 (2 x X5680, 3.33 GHz)
3 546 182 15 91 9.0.2

Configuration Summary

Hardware Configuration:

1 x SPARC T5-2 server with
2 x SPARC T5 processors, 3.6 GHz
512 GB memory
4 x 300 GB 10K RPM SAS internal disk
2 x 300 GB internal SSD
4 x Sun Flash Accelerator F40 PCIe Card (4 x 93 GB)

Software Configuration:

Oracle Solaris 10 1/13
Oracle Solaris Containers
JD Edwards EnterpriseOne 9.0.2
JD Edwards EnterpriseOne Tools (8.98.4.2)
Oracle WebLogic Server 11g (10.3.4)
Oracle HTTP Server 11g
Oracle Database 11g Release 2 (11.2.0.3)

Benchmark Description

JD Edwards EnterpriseOne is an integrated applications suite of Enterprise Resource Planning (ERP) software. Oracle offers 70 JD Edwards EnterpriseOne application modules to support a diverse set of business operations.

Oracle's Day in the Life (DIL) kit is a suite of scripts that exercises most common transactions of JD Edwards EnterpriseOne applications, including business processes such as payroll, sales order, purchase order, work order, and manufacturing processes, such as ship confirmation. These are labeled by industry acronyms such as SCM, CRM, HCM, SRM and FMS. The kit's scripts execute transactions typical of a mid-sized manufacturing company.

  • The workload consists of online transactions and the UBE – Universal Business Engine workload of 61 short and 4 long UBEs.

  • LoadRunner runs the DIL workload, collects the user’s transactions response times and reports the key metric of Combined Weighted Average Transaction Response time.

  • The UBE processes workload runs from the JD Enterprise Application server.

    • Oracle's UBE processes come as three flavors:
      • Short UBEs < 1 minute engage in Business Report and Summary Analysis,
      • Mid UBEs > 1 minute create a large report of Account, Balance, and Full Address,
      • Long UBEs > 2 minutes simulate Payroll, Sales Order, night only jobs.
    • The UBE workload generates large numbers of PDF files reports and log files.
    • The UBE Queues are categorized as the QBATCHD, a single threaded queue for large and medium UBEs, and the QPROCESS queue for short UBEs run concurrently.

Oracle's UBE process performance metric is Number of Maximum Concurrent UBE processes at transaction rate, UBEs/minute.

Key Points and Best Practices

Four Oracle Solaris processors sets were used with Oracle Solaris Containers assigned to the processor sets as follows:

  • one JD Edwards EnterpriseOne Application server, two Oracle WebLogic Servers 11g Release 1 each coupled with an Oracle Web Tier HTTP server instances (online workload), each in an Oracle Solaris Container (three total),

  • one JD Edwards EnterpriseOne Application server (for batch only workload) in an Oracle Solaris Container,

  • Oracle Database 11g Release 2.0.3 database in an Oracle Solaris Container,

  • the Oracle database log writer.

Other items of note:

  • Each Oracle WebLogic vertical cluster, with twelve managed instances, was configured in a dedicated webserver container in order to load balance users' requests and to provide the infrastructure to support high number of users with ease of deployment and high availability.

  • The database redo logs were configured on the raw disk partitions.

  • The mixed batch workload of 44 short UBEs and 8 long UBEs was executed concurrently with the 12,000 online application users, producing a sustained rate of 198.5 UBE/min.

See Also

Disclosure Statement

Copyright 2013, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 03/26/2013

SPARC T5-2 (SPARC T5-2 Server base package, 2xSPARC T5 16-core processors, 32x16GB-1066 DIMMS, 4x600GB 10K RPM 2.5. SAS-2 HDD,2x300GB SSDs, 4x Sun Flash Accelerator F40 PCIe Cards, 2x Power Cables) List Price $98,190. IBM Power 770 (IBM Power 770:9917 Model MMC, 2x3.3GHz 16-core, 32x one processor activation, 2xCEC Enclosure with IBM Bezel, I/O Backplane and System Midplane,2x Service Processor, 16x 0/64GB DDR3 Memory (4x16GB) DIMMS-1066MHz Power7 CoD Memory, 24x Activation of 1 GB DDR3 Power7 Memory, 10x Activation of 100GB DDR3 Power7 Memory, 2x Disk/Media Backplane. 2x 300GB SAS 15K RPM 2.5. HDD (AIX/Linux only), 1x SATA slimline DVD-RAM drive, 4x AC Power Supply 1925W) List Price $532,143. Source: ibm.com, collected 03/18/2013.

SPARC T5 Systems Produce Oracle TimesTen Benchmark World Record

The Oracle TimesTen In-Memory Database is optimized to run on Oracle's SPARC T5 processor platforms running Oracle Solaris 11. In this series of tests, systems with the new SPARC T5 processor were significantly faster than systems based on other processors. Two tests were run to explore TimesTen performance: a Mobile Call Processing test (based on customer workload) and Oracle's TimesTen Performance Throughput Benchmark (TPTBM). TimesTen version 11.2.2.4 was used for all tests.

  • On the TimesTen Performance Throughput Benchmark (TPTBM), SPARC T5-8 server produced a world record 59.9 million read transactions per second.

  • On the Mobile Call Processing test, the SPARC T5 processor achieves 2.4 times more throughput than the Intel Xeon E7-4870 processor. The two-chip SPARC T5-2 server is 22% faster than an x86 server with four Intel E7-4870 2.4 GHz processors.

  • On the TimesTen Performance Throughput Benchmark (TPTBM) read-only workload, the SPARC T5 processor achieves 2.2 times higher throughput than the Intel Xeon E7-4870 processor. On the same workload, the two-chip SPARC T5-2 server produces 10% more throughput than an x86 server with four Intel E7-4870 processors and has almost twice the performance of a 2-chip Intel E5-2680 system.

  • With the TPTBM read-only workload, the SPARC T5-8 server delivers 3.8x more throughput than a SPARC T5-2 Server, showing excellent scalability.

  • The SPARC T5 processor delivers over twice the performace of the previous generation SPARC T4 processor and over 4x the performace of the SPARC T3 processor, all in the same amount of space.

  • The SPARC T5-2 server delivers 2.4x the performace of the SPARC T4-2 server in the same 3U space. This is better performance than that of the SPARC T4-4 server which occupies 5U.

Performance Landscape

Mobile Call Processing Test Performance

Processor Tps
SPARC T5, 3.6 GHz 367,600
Intel Xeon E7-4870, 2.4 GHz 302,000
SPARC T4, 2.85 GHz 230,500

All systems measured using Oracle Solaris 11 and Oracle TimesTen In-Memory Database 11.2.2.4.1

TimesTen Performance Throughput Benchmark (TPTBM) Read-Only

System Processor Chips Tps Tps/
Chip
SPARC T5-8 SPARC T5, 3.6 GHz 8 59.9M 7.5M
SPARC T5-2 SPARC T5, 3.6 GHz 2 15.9M 7.9M
x86 Intel Xeon E7-4870, 2.4 GHz 4 14.5M 3.6M
SPARC T4-4 SPARC T4, 3.0 GHz 4 14.2M 3.6M
x86* Intel Xeon E5-2680, 2.7 GHz 2 8.5M 4.3
SPARC T4-2 SPARC T4, 2.85 GHz 2 6.5M 3.3M
SPARC T3-4 SPARC T3, 1.65 GHz 4 7.9M 1.9M
T5440 SPARC T2+, 1.4 GHz 4 3.1M 0.8M

All systems measured using Oracle Solaris 11 and Oracle TimesTen In-Memory Database 11.2.2.4.1

*Intel E5-2680 using Oracle Linux and Oracle TimesTen In-Memory Database 11.2.2.4.1

TimesTen Performance Throughput Benchmark (TPTBM) Update-Only

Processor Tps
SPARC T5, 3.6 GHz 1,031.7K
Intel Xeon E7-4870, 2.4 GHz 988.1K
Intel Xeon E5-2680, 2.7 GHz * 944.3K
SPARC T4, 3.0 GHz 678.0K

All systems measured using Oracle Solaris 11 and Oracle TimesTen In-Memory Database 11.2.2.4.1

*Intel E5-2680 using Oracle Linux and Oracle TimesTen In-Memory Database 11.2.2.4.1

Configuration Summary

Hardware Configurations:

SPARC T5-8 server
8 x SPARC T5 processors, 3.6 GHz
2 TB memory
1 x 8 Gbs FC Qlogic HBA
1 x 6 Gbs SAS HBA
2 x 300 GB internal disks
Oracle Solaris 11
TimesTen 11.2.2.4.1
1 x Sun Fire X4275 server configured as COMSTAR redo head (log)

SPARC T5-2 server
2 x SPARC T5 processors, 3.6 GHz
512 GB memory
1 x 8 Gbs FC Qlogic HBA
1 x 6 Gbs SAS HBA
2 x 300 GB internal disks
Oracle Solaris 11
TimesTen 11.2.2.4.1
1 x Sun Fire X4275 server configured as COMSTAR redo head (log)

SPARC T4-4 server
4 x SPARC T4 processors, 3.0 GHz
1 TB memory
1 x 8 Gbs FC Qlogic HBA
1 x 6 Gbs SAS HBA
6 x 300 GB internal disks
Oracle Solaris 11
TimesTen 11.2.2.4.1
Sun Storage F5100 Flash Array (80 x 24 GB flash modules)
1 x Sun Fire X4275 server configured as COMSTAR redo head (log)

SPARC T4-2 server
2 x SPARC T4 processors, 2.85 GHz
256 GB memory
1 x 8 Gbs FC Qlogic HBA
1 x 6 Gbs SAS HBA
4 x 300 GB internal disks
Oracle Solaris 11
TimesTen 11.2.2.4.1
Sun Storage F5100 Flash Array (40 x 24 GB flash modules)
1 x Sun Fire X4275 server configured as COMSTAR head

SPARC T3-4 server
4 x SPARC T3 processors, 1.6 GHz
512 GB memory
1 x 8 Gbs FC Qlogic HBA
8 x 146 GB internal disks
Oracle Solaris 11
TimesTen 11.2.2.4.1
1 x Sun Fire X4275 server configured as COMSTAR head

Intel Server x86_64
2 x Intel Xeon E5-2680 processors, 2.7 GHz
256 GB memory
4 x SSD SAS disks (log)
1 x 600 GB internal disks
Oracle Linux
TimesTen 11.2.2.4.1

Sun Server X2-4
4 x Intel Xeon E7-4870 processors, 2.4 GHz
512 GB memory
1 x 8 Gbs FC Qlogic HBA
6 x 146 GB internal disks
Oracle Solaris 11
TimesTen 11.2.2.4.1
1 x Sun Fire X4275 server configured as COMSTAR redo head (log)

Benchmark Descriptions

TimesTen Performance Throughput BenchMark (TPTBM) is shipped with TimesTen and measures the total throughput of the system. The benchmark workloads can be reads, inserts, updates, and delete operations, or a mix of them as required.

Mobile Call Processing is a customer-based workload for processing calls made by mobile phone subscribers. The workload has a mixture of read-only, update, and insert-only transactions. The peak throughput performance is measured from multiple concurrent processes executing the transactions until a peak performance is reached via saturation of the available resources.

Key Points and Best Practices

The Mobile Call Processing test utilized Oracle Solaris processor sets in all environments for optimum performance. This features isolates running processes from other processes in the system. Combined with parameters to limit memory pages to the lgroup within the processor set and isolating the processor set to a single processor within the system.

See Also

Disclosure Statement

Copyright 2013, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 26 March 2013.

SPARC T5-8 Delivers Oracle OLAP World Record Performance

Oracle's SPARC T5-8 server delivered world record query performance with near real-time analytic capability using the Oracle OLAP Perf Version 3 workload running Oracle Database 11g Release 2 on Oracle Solaris 11.

  • The maximum query throughput on the SPARC T5-8 server is 1.6x higher than that of the 8-chip Intel Xeon E7-8870 server. Both systems had sub-second response time.

  • The SPARC T5-8 server with the Oracle Database demonstrated the ability to support at least 600 concurrent users querying OLAP cubes (with no think time), processing 2.93 million analytic queries per hour with an average response time of 0.66 seconds per query. This performance was enabled by keeping the entire cube in-memory utilizing the 4 TB of memory on the SPARC T5-8 server.

  • Assuming a 60 second think time between query requests, the SPARC T5-8 server can support approximately 49,450 concurrent users with the same 0.66 sec response time.

  • The SPARC T5-8 server delivered 4.3x times the maximum query throughput of a SPARC T4-4 server.

  • The workload uses a set of realistic BI queries that run against an OLAP cube based on a 4 billion row fact table of sales data. The 4 billion rows are partitioned by month spanning 10 years.

  • The combination of the Oracle Database with the Oracle OLAP option running on a SPARC T5-8 server supports live data updates occurring concurrently with minimally impacted user query executions.

Performance Landscape

Oracle OLAP Perf Version 3 Benchmark
Oracle cube base on 4 billion fact table rows
10 years of data partitioned by month
System Queries/
hour
Users* Average Response
Time (sec)
0 sec think time 60 sec think time
SPARC T5-8 2,934,000 600 49,450 0.66
8-chip Intel Xeon E7-8870 1,823,000 120 30,500 0.19
SPARC T4-4 686,500 150 11,580 0.71

Configuration Summary and Results

SPARC T5-8 Hardware Configuration:

1 x SPARC T5-8 server with
8 x SPARC T5 processors, 3.6 GHz
4 TB memory
Data Storage and Redo Storage
1 x Sun Storage F5100 Flash Array (with 80 FMODs)
Oracle Solaris 11.1
Oracle Database 11g Release 2 (11.2.0.3) with Oracle OLAP option

Sun Server X2-8 Hardware Configuration:

1 x Sun Server X2-8 with
8 x Intel Xeon E7-8870 processors, 2.4 GHz
512 GB memory
Data Storage and Redo Storage
3 x StorageTek 2540/2501 array pairs
Oracle Solaris 10 10/12
Oracle Database 11g Release 2 (11.2.0.2) with Oracle OLAP option

SPARC T4-4 Hardware Configuration:

1 x SPARC T4-4 server with
4 x SPARC T4 processors, 3.0 GHz
1 TB memory
Data Storage
1 x Sun Fire X4275 (using COMSTAR)
2 x Sun Storage F5100 Flash Array (each with 80 FMODs)
Redo Storage
1 x Sun Fire X4275 (using COMSTAR with 8 HDD)
Oracle Solaris 11 11/11
Oracle Database 11g Release 2 (11.2.0.3) with Oracle OLAP option

Benchmark Description

The Oracle OLAP Perf Version 3 benchmark is a workload designed to demonstrate and stress the ability of the OLAP Option to deliver fast query, near real-time updates and rich calculations using a multi-dimensional model in the context of the Oracle data warehousing.

The bulk of the benchmark entails running a number of concurrent users, each issuing typical multidimensional queries against an Oracle cube. The cube has four dimensions: time, product, customer, and channel. Each query user issues approximately 150 different queries. One query chain may ask for total sales in a particular region (e.g South America) for a particular time period (e.g. Q4 of 2010) followed by additional queries which drill down into sales for individual countries (e.g. Chile, Peru, etc.) with further queries drilling down into individual stores, etc. Another query chain may ask for yearly comparisons of total sales for some product category (e.g. major household appliances) and then issue further queries drilling down into particular products (e.g. refrigerators, stoves. etc.), particular regions, particular customers, etc.

While the core of every OLAP Perf benchmark is real world query performance, the benchmark itself offers numerous execution options such as varying data set sizes, number of users, numbers of queries for any given user and cube update frequency. Version 3 of the benchmark is executed with a much larger number of query streams than previous versions and used a cube designed for near real-time updates. The results produced by version 3 of the benchmark are not directly comparable to results produced by previous versions of the benchmark.

The near real-time update capability is implemented along the following lines. A large Oracle cube, H, is built from a 4 billion row star schema, containing data up until the end of last business day. A second small cube, D, is then created which will contain all of today's new data coming in from outside the world. It will be updated every L minutes with the data coming in within the last L minutes. A third cube, R, joins cubes H and D for reporting purposes much like a view might join data from two tables. Calculations are installed into cube R. The use of a reporting cube which draws data from different storage cubes is a common practice.

Query users are never locked out of query operations while new data is added to the update cube. The point of the demonstration is to show that an Oracle OLAP system can be designed which results in data being no more than L minutes out of date, where L may be as low as just a few minutes. This is what is meant by near real-time analytics.

Key Points and Best Practices

  • Update performance of the D cube was optimized by running update processes in the FX class with a priority greater than 0. The maximum lag time between updates to the source fact table and data availability to query users (what was referred to as L in the benchmark description) was less than 3 minutes for the benchmark environment on the SPARC T5-8 server.

  • Building and querying cubes with the Oracle OLAP option requires a large temporary tablespace. Normally temporary tablespaces would reside on disk storage. However, because the SPARC T5-8 server used in this benchmark had 4 TB of main memory, it was possible to use main memory for the OLAP temporary tablespace. This was done by using files in /tmp for the temporary tablespace datafiles.

  • Since typical BI users are often likely to issue similar queries, either with the same, or different, constants in the where clauses, setting the init.ora parameter "cursor_sharing" to "force" provides for additional query throughput and a larger number of potential users.

  • Assuming the normal Oracle initialization parameters (e.g. SGA, PGA, processes etc.) are appropriately set, out of the box performance for the OLAP Perf workload should be close to what is reported here. Additional performance resulted from (a)using memory for the OLAP temporary tablespace (b)setting "cursor_sharing" to force.

  • For a given number of query users with zero think time, the main measured metrics are the average query response time and the query throughput. A derived metric is the maximum number of users the system can support, with the same response time, assuming some non-zero think time. The calculation of this maximum is from the well-known "response-time law"

      N = (rt + tt) * tp

    where rt is the average response time, tt is the think time and tp is the measured throughput.

    Setting tt to 60 seconds, rt to 0.66 seconds and tp to 815 queries/sec (2,934,000 queries/hour), the above formula shows that the SPARC T5-8 server will support 49,450 concurrent users with a think time of 60 seconds and an average response time of 0.66 seconds.

    For more information about the "response-time law" see chapter 3 from the book "Quantitative System Performance" cited below.

See Also

Disclosure Statement

Copyright 2013, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 03/26/2013.

SPARC T5-2 Obtains Oracle Internet Directory Benchmark World Record Performance

Oracle's SPARC T5-2 server running Oracle Internet Directory (OID, Oracle's LDAP Directory Server) on Oracle Solaris 11 achieved a record result for LDAP searches/second with 1000 clients.

  • The SPARC T5-2 server running Oracle Internet Directory on Oracle Solaris 11 achieved a result of 944,624 LDAP searches/sec with an average latency of 1.05 ms with 1000 clients.

  • The SPARC T5-2 server running Oracle Internet Directory demonstrated 2.7x better throughput and 39% better latency improvement over similarly configured OID and SPARC T4 benchmark environment.

  • The SPARC T5-2 server running Oracle Internet Directory demonstrates 39% better throughput and latency for LDAP searches on core-to-core comparison over an x86 system configured with two Intel Xeon X5675 processors.

  • Oracle Internet Directory achieved near linear scaling on the SPARC T5-2 server with 68,399 LDAP searches/sec with 2 cores to 944,624 LDAP searches/sec with 32 cores.

  • Oracle Internet Directory and the SPARC T5-2 server achieved up to 12,453 LDAP modifys/sec with an average latency of 3.9 msec for 50 clients.

Performance Landscape

Oracle Internet Directory Tests
System c/c/th Search Modify Add
ops/sec lat (msec) ops/sec lat (msec) ops/sec lat (msec)
SPARC T5-2 2/32/256 944,624 1.05 12,453 3.9 888 17.9
SPARC T4-4 4/32/256 682,000 1.46 12,000 4.0 835 19.0

In order to compare the SPARC T5-2 to a 12-core x86 system, only 1 processor and 12 cores was used in the SPARC T5-2.

Oracle Internet Directory Tests – Comparing Against x86
System c/c/th Search Compare Authentication
ops/sec lat (msec) ops/sec lat (msec) ops/sec lat (msec)
SPARC T5-2 1/12/96 417,000 1.19 274,185 1.82 149,623 3.30
x86 2 x Intel X5675 2/12/24 299,000 1.66 202,433 2.46 119,198 4.19

Scaling runs were also made on the SPARC T5-2 server.

Scaling of Search Tests – SPARC T5-2
Cores Clients ops/sec Latency (msec)
32 1000 944,624 1.05
24 1000 823,741 1.21
16 500 560,709 0.88
8 500 270,601 1.84
4 100 145,879 0.68
2 100 68,399 1.46

Configuration Summary

System Under Test:

SPARC T5-2
2 x SPARC T5 processors, 3.6 GHz
512 GB memory
4 x 300 GB internal disks
Flash Storage (used for database and log files)
1 x Sun Storage 2540-M2 (used for redo logs)
Oracle Solaris 11.1
Oracle Internet Directory 11g Release 1 PS6 (11.1.1.7.0)
Oracle Database 11g Enterprise Edition 11.2.0.3 (64-bit)

Benchmark Description

Oracle Internet Directory (OID) is Oracle's LDAPv3 Directory Server. The throughput for five key operations are measured — Search, Compare, Modify, Mix and Add.

LDAP Search Operations Test

This test scenario involved concurrent clients binding once to OID and then performing repeated LDAP Search operations. The salient characteristics of this test scenario is as follows:

  • SLAMD SearchRate job was used.
  • BaseDN of the search is root of the DIT, the scope is SUBTREE, the search filter is of the form UID=, DN and UID are the required attribute.
  • Each LDAP search operation matches a single entry.
  • The total number concurrent clients was 1000 and were distributed amongst two client nodes.
  • Each client binds to OID once and performs repeated LDAP Search operations, each search operation resulting in the lookup of a unique entry in such a way that no client looks up the same entry twice and no two clients lookup the same entry and all entries are searched randomly.
  • In one run of the test, random entries from the 50 Million entries are looked up in as many LDAP Search operations.
  • Test job was run for 60 minutes.

LDAP Compare Operations Test

This test scenario involved concurrent clients binding once to OID and then performing repeated LDAP Compare operations on userpassword attribute. The salient characteristics of this test scenario is as follows:

  • SLAMD CompareRate job was used.
  • Each LDAP compare operation matches user password of user.
  • The total number concurrent clients was 1000 and were distributed amongst two client nodes.
  • Each client binds to OID once and performs repeated LDAP compare operations.
  • In one run of the test, random entries from the 50 Million entries are compared in as many LDAP compare operations.
  • Test job was run for 60 minutes.

LDAP Modify Operations Test

This test scenario consisted of concurrent clients binding once to OID and then performing repeated LDAP Modify operations. The salient characteristics of this test scenario is as follows:

  • SLAMD LDAP modrate job was used.
  • A total of 50 concurrent LDAP clients were used.
  • Each client updates a unique entry each time and a total of 50 Million entries are updated.
  • Test job was run for 60 minutes.
  • Value length was set to 11.
  • Attribute that is being modified is not indexed.

LDAP Mixed Load Test

The test scenario involved both the LDAP search and LDAP modify clients enumerated above.

  • The ratio involved 60% LDAP search clients, 30% LDAP bind and 10% LDAP modify clients.
  • A total of 1000 concurrent LDAP clients were used and were distributed on 2 client nodes.
  • Test job was run for 60 minutes.

LDAP Add Load Test

The test scenario involved concurrent clients adding new entries as follows.

  • Slamd standard add rate job is used.
  • A total of 500,000 entries were added.
  • A total of 16 concurrent LDAP clients were used.
  • Slamd add's inetorgperson objectclass entry with 21 attributes (includes operational attributes).

See Also

Disclosure Statement

Copyright 2013, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 26 March 2013.

Thursday Nov 08, 2012

SPARC T4-4 Delivers World Record Performance on Oracle OLAP Perf Version 2 Benchmark

Oracle's SPARC T4-4 server delivered world record performance with subsecond response time on the Oracle OLAP Perf Version 2 benchmark using Oracle Database 11g Release 2 running on Oracle Solaris 11.

  • The SPARC T4-4 server achieved throughput of 430,000 cube-queries/hour with an average response time of 0.85 seconds and the median response time of 0.43 seconds. This was achieved by using only 60% of the available CPU resources leaving plenty of headroom for future growth.

Performance Landscape

Oracle OLAP Perf Version 2 Benchmark
4 Billion Fact Table Rows
System Queries/
hour
Users* Response Time (sec)
Average Median
SPARC T4-4 430,000 7,300 0.85 0.43

* Users - the supported number of users with a given think time of 60 seconds

Configuration Summary and Results

Hardware Configuration:

SPARC T4-4 server with
4 x SPARC T4 processors, 3.0 GHz
1 TB memory
Data Storage
1 x Sun Fire X4275 (using COMSTAR)
2 x Sun Storage F5100 Flash Array (each with 80 FMODs)
Redo Storage
1 x Sun Fire X4275 (using COMSTAR with 8 HDD)

Software Configuration:

Oracle Solaris 11 11/11
Oracle Database 11g Release 2 (11.2.0.3) with Oracle OLAP option

Benchmark Description

The Oracle OLAP Perf Version 2 benchmark is a workload designed to demonstrate and stress the Oracle OLAP product's core features of fast query, fast update, and rich calculations on a multi-dimensional model to support enhanced Data Warehousing.

The bulk of the benchmark entails running a number of concurrent users, each issuing typical multidimensional queries against an Oracle OLAP cube. The cube has four dimensions: time, product, customer, and channel. Each query user issues approximately 150 different queries. One query chain may ask for total sales in a particular region (e.g South America) for a particular time period (e.g. Q4 of 2010) followed by additional queries which drill down into sales for individual countries (e.g. Chile, Peru, etc.) with further queries drilling down into individual stores, etc. Another query chain may ask for yearly comparisons of total sales for some product category (e.g. major household appliances) and then issue further queries drilling down into particular products (e.g. refrigerators, stoves. etc.), particular regions, particular customers, etc.

Results from version 2 of the benchmark are not comparable with version 1. The primary difference is the type of queries along with the query mix.

Key Points and Best Practices

  • Since typical BI users are often likely to issue similar queries, with different constants in the where clauses, setting the init.ora prameter "cursor_sharing" to "force" will provide for additional query throughput and a larger number of potential users. Except for this setting, together with making full use of available memory, out of the box performance for the OLAP Perf workload should provide results similar to what is reported here.

  • For a given number of query users with zero think time, the main measured metrics are the average query response time, the median query response time, and the query throughput. A derived metric is the maximum number of users the system can support achieving the measured response time assuming some non-zero think time. The calculation of the maximum number of users follows from the well-known response-time law

      N = (rt + tt) * tp

    where rt is the average response time, tt is the think time and tp is the measured throughput.

    Setting tt to 60 seconds, rt to 0.85 seconds and tp to 119.44 queries/sec (430,000 queries/hour), the above formula shows that the T4-4 server will support 7,300 concurrent users with a think time of 60 seconds and an average response time of 0.85 seconds.

    For more information see chapter 3 from the book "Quantitative System Performance" cited below.

See Also

Disclosure Statement

Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 11/2/2012.

Improved Performance on PeopleSoft Combined Benchmark using SPARC T4-4

Oracle's SPARC T4-4 server running Oracle's PeopleSoft HCM 9.1 combined online and batch benchmark achieved a world record 18,000 concurrent users experiencing subsecond response time while executing a PeopleSoft Payroll batch job of 500,000 employees in 32.4 minutes.

  • This result was obtained with a SPARC T4-4 server running Oracle Database 11g Release 2, a SPARC T4-4 server running PeopleSoft HCM 9.1 application server and a SPARC T4-2 server running Oracle WebLogic Server in the web tier.

  • The SPARC T4-4 server running the application tier used Oracle Solaris Zones which provide a flexible, scalable and manageable virtualization environment.

  • The average CPU utilization on the SPARC T4-2 server in the web tier was 17%, on the SPARC T4-4 server in the application tier it was 59%, and on the SPARC T4-4 server in the database tier was 47% (online and batch) leaving significant headroom for additional processing across the three tiers.

  • The SPARC T4-4 server used for the database tier hosted Oracle Database 11g Release 2 using Oracle Automatic Storage Management (ASM) for database files management with I/O performance equivalent to raw devices.

Performance Landscape

Results are presented for the PeopleSoft HRMS Self-Service and Payroll combined benchmark. The new result with 128 streams shows significant improvement in the payroll batch processing time with little impact on the self-service component response time.

PeopleSoft HRMS Self-Service and Payroll Benchmark
Systems Users Ave Response
Search (sec)
Ave Response
Save (sec)
Batch
Time (min)
Streams
SPARC T4-2 (web)
SPARC T4-4 (app)
SPARC T4-4 (db)
18,000 0.988 0.539 32.4 128
SPARC T4-2 (web)
SPARC T4-4 (app)
SPARC T4-4 (db)
18,000 0.944 0.503 43.3 64

The following results are for the PeopleSoft HRMS Self-Service benchmark that was previous run. The results are not directly comparable with the combined results because they do not include the payroll component.

PeopleSoft HRMS Self-Service 9.1 Benchmark
Systems Users Ave Response
Search (sec)
Ave Response
Save (sec)
Batch
Time (min)
Streams
SPARC T4-2 (web)
SPARC T4-4 (app)
2x SPARC T4-2 (db)
18,000 1.048 0.742 N/A N/A

The following results are for the PeopleSoft Payroll benchmark that was previous run. The results are not directly comparable with the combined results because they do not include the self-service component.

PeopleSoft Payroll (N.A.) 9.1 - 500K Employees (7 Million SQL PayCalc, Unicode)
Systems Users Ave Response
Search (sec)
Ave Response
Save (sec)
Batch
Time (min)
Streams
SPARC T4-4 (db)
N/A N/A N/A 30.84 96

Configuration Summary

Application Configuration:

1 x SPARC T4-4 server with
4 x SPARC T4 processors, 3.0 GHz
512 GB memory
Oracle Solaris 11 11/11
PeopleTools 8.52
PeopleSoft HCM 9.1
Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031
Java Platform, Standard Edition Development Kit 6 Update 32

Database Configuration:

1 x SPARC T4-4 server with
4 x SPARC T4 processors, 3.0 GHz
256 GB memory
Oracle Solaris 11 11/11
Oracle Database 11g Release 2
PeopleTools 8.52
Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031
Micro Focus Server Express (COBOL v 5.1.00)

Web Tier Configuration:

1 x SPARC T4-2 server with
2 x SPARC T4 processors, 2.85 GHz
256 GB memory
Oracle Solaris 11 11/11
PeopleTools 8.52
Oracle WebLogic Server 10.3.4
Java Platform, Standard Edition Development Kit 6 Update 32

Storage Configuration:

1 x Sun Server X2-4 as a COMSTAR head for data
4 x Intel Xeon X7550, 2.0 GHz
128 GB memory
1 x Sun Storage F5100 Flash Array (80 flash modules)
1 x Sun Storage F5100 Flash Array (40 flash modules)

1 x Sun Fire X4275 as a COMSTAR head for redo logs
12 x 2 TB SAS disks with Niwot Raid controller

Benchmark Description

This benchmark combines PeopleSoft HCM 9.1 HR Self Service online and PeopleSoft Payroll batch workloads to run on a unified database deployed on Oracle Database 11g Release 2.

The PeopleSoft HRSS benchmark kit is a Oracle standard benchmark kit run by all platform vendors to measure the performance. It's an OLTP benchmark where DB SQLs are moderately complex. The results are certified by Oracle and a white paper is published.

PeopleSoft HR SS defines a business transaction as a series of HTML pages that guide a user through a particular scenario. Users are defined as corporate Employees, Managers and HR administrators. The benchmark consist of 14 scenarios which emulate users performing typical HCM transactions such as viewing paycheck, promoting and hiring employees, updating employee profile and other typical HCM application transactions.

All these transactions are well-defined in the PeopleSoft HR Self-Service 9.1 benchmark kit. This benchmark metric is the weighted average response search/save time for all the transactions.

The PeopleSoft 9.1 Payroll (North America) benchmark demonstrates system performance for a range of processing volumes in a specific configuration. This workload represents large batch runs typical of a ERP environment during a mass update. The benchmark measures five application business process run times for a database representing large organization. They are Paysheet Creation, Payroll Calculation, Payroll Confirmation, Print Advice forms, and Create Direct Deposit File. The benchmark metric is the cumulative elapsed time taken to complete the Paysheet Creation, Payroll Calculation and Payroll Confirmation business application processes.

The benchmark metrics are taken for each respective benchmark while running simultaneously on the same database back-end. Specifically, the payroll batch processes are started when the online workload reaches steady state (the maximum number of online users) and overlap with online transactions for the duration of the steady state.

Key Points and Best Practices

  • Two PeopleSoft Domain sets with 200 application servers each on a SPARC T4-4 server were hosted in 2 separate Oracle Solaris Zones to demonstrate consolidation of multiple application servers, ease of administration and performance tuning.

  • Each Oracle Solaris Zone was bound to a separate processor set, each containing 15 cores (total 120 threads). The default set (1 core from first and third processor socket, total 16 threads) was used for network and disk interrupt handling. This was done to improve performance by reducing memory access latency by using the physical memory closest to the processors and offload I/O interrupt handling to default set threads, freeing up cpu resources for Application Servers threads and balancing application workload across 240 threads.

  • A total of 128 PeopleSoft streams server processes where used on the database node to complete payroll batch job of 500,000 employees in 32.4 minutes.

See Also

Disclosure Statement

Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 8 November 2012.

Tuesday Oct 02, 2012

SPARC T4-4 Delivers World Record First Result on PeopleSoft Combined Benchmark

Oracle's SPARC T4-4 servers running Oracle's PeopleSoft HCM 9.1 combined online and batch benchmark achieved World Record 18,000 concurrent users while executing a PeopleSoft Payroll batch job of 500,000 employees in 43.32 minutes and maintaining online users response time at < 2 seconds.

  • This world record is the first to run online and batch workloads concurrently.

  • This result was obtained with a SPARC T4-4 server running Oracle Database 11g Release 2, a SPARC T4-4 server running PeopleSoft HCM 9.1 application server and a SPARC T4-2 server running Oracle WebLogic Server in the web tier.

  • The SPARC T4-4 server running the application tier used Oracle Solaris Zones which provide a flexible, scalable and manageable virtualization environment.

  • The average CPU utilization on the SPARC T4-2 server in the web tier was 17%, on the SPARC T4-4 server in the application tier it was 59%, and on the SPARC T4-4 server in the database tier was 35% (online and batch) leaving significant headroom for additional processing across the three tiers.

  • The SPARC T4-4 server used for the database tier hosted Oracle Database 11g Release 2 using Oracle Automatic Storage Management (ASM) for database files management with I/O performance equivalent to raw devices.

  • This is the first three tier mixed workload (online and batch) PeopleSoft benchmark also processing PeopleSoft payroll batch workload.

Performance Landscape

PeopleSoft HR Self-Service and Payroll Benchmark
Systems Users Ave Response
Search (sec)
Ave Response
Save (sec)
Batch
Time (min)
Streams
SPARC T4-2 (web)
SPARC T4-4 (app)
SPARC T4-4 (db)
18,000 0.944 0.503 43.32 64

Configuration Summary

Application Configuration:

1 x SPARC T4-4 server with
4 x SPARC T4 processors, 3.0 GHz
512 GB memory
1 x 600 GB SAS internal disks
4 x 300 GB SAS internal disks
1 x 100 GB and 2 x 300 GB internal SSDs
2 x 10 Gbe HBA
Oracle Solaris 11 11/11
PeopleTools 8.52
PeopleSoft HCM 9.1
Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031
Java Platform, Standard Edition Development Kit 6 Update 32

Database Configuration:

1 x SPARC T4-4 server with
4 x SPARC T4 processors, 3.0 GHz
256 GB memory
1 x 600 GB SAS internal disks
2 x 300 GB SAS internal disks
Oracle Solaris 11 11/11
Oracle Database 11g Release 2
PeopleTools 8.52
Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031

Web Tier Configuration:

1 x SPARC T4-2 server with
2 x SPARC T4 processors, 2.85 GHz
256 GB memory
2 x 300 GB SAS internal disks
1 x 300 GB internal SSD
1 x 100 GB internal SSD
Oracle Solaris 11 11/11
PeopleTools 8.52
Oracle WebLogic Server 10.3.4
Java Platform, Standard Edition Development Kit 6 Update 32

Storage Configuration:

1 x Sun Server X2-4 as a COMSTAR head for data
4 x Intel Xeon X7550, 2.0 GHz
128 GB memory
1 x Sun Storage F5100 Flash Array (80 flash modules)
1 x Sun Storage F5100 Flash Array (40 flash modules)

1 x Sun Fire X4275 as a COMSTAR head for redo logs
12 x 2 TB SAS disks with Niwot Raid controller

Benchmark Description

This benchmark combines PeopleSoft HCM 9.1 HR Self Service online and PeopleSoft Payroll batch workloads to run on a unified database deployed on Oracle Database 11g Release 2.

The PeopleSoft HRSS benchmark kit is a Oracle standard benchmark kit run by all platform vendors to measure the performance. It's an OLTP benchmark where DB SQLs are moderately complex. The results are certified by Oracle and a white paper is published.

PeopleSoft HR SS defines a business transaction as a series of HTML pages that guide a user through a particular scenario. Users are defined as corporate Employees, Managers and HR administrators. The benchmark consist of 14 scenarios which emulate users performing typical HCM transactions such as viewing paycheck, promoting and hiring employees, updating employee profile and other typical HCM application transactions.

All these transactions are well-defined in the PeopleSoft HR Self-Service 9.1 benchmark kit. This benchmark metric is the weighted average response search/save time for all the transactions.

The PeopleSoft 9.1 Payroll (North America) benchmark demonstrates system performance for a range of processing volumes in a specific configuration. This workload represents large batch runs typical of a ERP environment during a mass update. The benchmark measures five application business process run times for a database representing large organization. They are Paysheet Creation, Payroll Calculation, Payroll Confirmation, Print Advice forms, and Create Direct Deposit File. The benchmark metric is the cumulative elapsed time taken to complete the Paysheet Creation, Payroll Calculation and Payroll Confirmation business application processes.

The benchmark metrics are taken for each respective benchmark while running simultaneously on the same database back-end. Specifically, the payroll batch processes are started when the online workload reaches steady state (the maximum number of online users) and overlap with online transactions for the duration of the steady state.

Key Points and Best Practices

  • Two Oracle PeopleSoft Domain sets with 200 application servers each on a SPARC T4-4 server were hosted in 2 separate Oracle Solaris Zones to demonstrate consolidation of multiple application servers, ease of administration and performance tuning.

  • Each Oracle Solaris Zone was bound to a separate processor set, each containing 15 cores (total 120 threads). The default set (1 core from first and third processor socket, total 16 threads) was used for network and disk interrupt handling. This was done to improve performance by reducing memory access latency by using the physical memory closest to the processors and offload I/O interrupt handling to default set threads, freeing up cpu resources for Application Servers threads and balancing application workload across 240 threads.

See Also

Disclosure Statement

Oracle's PeopleSoft HR and Payroll combined benchmark, www.oracle.com/us/solutions/benchmark/apps-benchmark/peoplesoft-167486.html, results 09/30/2012.

Monday Oct 01, 2012

World Record Batch Rate on Oracle JD Edwards Consolidated Workload with SPARC T4-2

Oracle produced a World Record batch throughput for single system results on Oracle's JD Edwards EnterpriseOne Day-in-the-Life benchmark using Oracle's SPARC T4-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2. The workload includes both online and batch workload.

  • The SPARC T4-2 server delivered a result of 8,000 online users while concurrently executing a mix of JD Edwards EnterpriseOne Long and Short batch processes at 95.5 UBEs/min (Universal Batch Engines per minute).

  • In order to obtain this record benchmark result, the JD Edwards EnterpriseOne, Oracle WebLogic and Oracle Database 11g Release 2 servers were executed each in separate Oracle Solaris Containers which enabled optimal system resources distribution and performance together with scalable and manageable virtualization.

  • One SPARC T4-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2 utilized only 55% of the available CPU power.

  • The Oracle DB server in a Shared Server configuration allows for optimized CPU resource utilization and significant memory savings on the SPARC T4-2 server without sacrificing performance.

  • This configuration with SPARC T4-2 server has achieved 33% more Users/core, 47% more UBEs/min and 78% more Users/rack unit than the IBM Power 770 server.

  • The SPARC T4-2 server with 2 processors ran the JD Edwards "Day-in-the-Life" benchmark and supported 8,000 concurrent online users while concurrently executing mixed batch workloads at 95.5 UBEs per minute. The IBM Power 770 server with twice as many processors supported only 12,000 concurrent online users while concurrently executing mixed batch workloads at only 65 UBEs per minute.

  • This benchmark demonstrates more than 2x cost savings by consolidating the complete solution in a single SPARC T4-2 server compared to earlier published results of 10,000 users and 67 UBEs per minute on two SPARC T4-2 and SPARC T4-1.

  • The Oracle DB server used mirrored (RAID 1) volumes for the database providing high availability for the data without impacting performance.

Performance Landscape

JD Edwards EnterpriseOne Day in the Life (DIL) Benchmark
Consolidated Online with Batch Workload

System Rack
Units
(U)
Batch
Rate
(UBEs/m)
Online
Users
Users
/ U
Users
/ Core
Version
SPARC T4-2 (2 x SPARC T4, 2.85 GHz) 3 95.5 8,000 2,667 500 9.0.2
IBM Power 770 (4 x POWER7, 3.3 GHz, 32 cores) 8 65 12,000 1,500 375 9.0.2

Batch Rate (UBEs/m) — Batch transaction rate in UBEs per minute

Configuration Summary

Hardware Configuration:

1 x SPARC T4-2 server with
2 x SPARC T4 processors, 2.85 GHz
256 GB memory
4 x 300 GB 10K RPM SAS internal disk
2 x 300 GB internal SSD
2 x Sun Storage F5100 Flash Arrays

Software Configuration:

Oracle Solaris 10
Oracle Solaris Containers
JD Edwards EnterpriseOne 9.0.2
JD Edwards EnterpriseOne Tools (8.98.4.2)
Oracle WebLogic Server 11g (10.3.4)
Oracle HTTP Server 11g
Oracle Database 11g Release 2 (11.2.0.1)

Benchmark Description

JD Edwards EnterpriseOne is an integrated applications suite of Enterprise Resource Planning (ERP) software. Oracle offers 70 JD Edwards EnterpriseOne application modules to support a diverse set of business operations.

Oracle's Day in the Life (DIL) kit is a suite of scripts that exercises most common transactions of JD Edwards EnterpriseOne applications, including business processes such as payroll, sales order, purchase order, work order, and manufacturing processes, such as ship confirmation. These are labeled by industry acronyms such as SCM, CRM, HCM, SRM and FMS. The kit's scripts execute transactions typical of a mid-sized manufacturing company.

  • The workload consists of online transactions and the UBE – Universal Business Engine workload of 61 short and 4 long UBEs.

  • LoadRunner runs the DIL workload, collects the user’s transactions response times and reports the key metric of Combined Weighted Average Transaction Response time.

  • The UBE processes workload runs from the JD Enterprise Application server.

    • Oracle's UBE processes come as three flavors:

      • Short UBEs < 1 minute engage in Business Report and Summary Analysis,

      • Mid UBEs > 1 minute create a large report of Account, Balance, and Full Address,

      • Long UBEs > 2 minutes simulate Payroll, Sales Order, night only jobs.

    • The UBE workload generates large numbers of PDF files reports and log files.

    • The UBE Queues are categorized as the QBATCHD, a single threaded queue for large and medium UBEs, and the QPROCESS queue for short UBEs run concurrently.

Oracle's UBE process performance metric is Number of Maximum Concurrent UBE processes at transaction rate, UBEs/minute.

Key Points and Best Practices

Two JD Edwards EnterpriseOne Application Servers, two Oracle WebLogic Servers 11g Release 1 coupled with two Oracle Web Tier HTTP server instances and one Oracle Database 11g Release 2 database on a single SPARC T4-2 server were hosted in separate Oracle Solaris Containers bound to four processor sets to demonstrate consolidation of multiple applications, web servers and the database with best resource utilizations.

  • Interrupt fencing was configured on all Oracle Solaris Containers to channel the interrupts to processors other than the processor sets used for the JD Edwards Application server, Oracle WebLogic servers and the database server.

  • A Oracle WebLogic vertical cluster was configured on each WebServer Container with twelve managed instances each to load balance users' requests and to provide the infrastructure that enables scaling to high number of users with ease of deployment and high availability.

  • The database log writer was run in the real time RT class and bound to a processor set.

  • The database redo logs were configured on the raw disk partitions.

  • The Oracle Solaris Container running the Enterprise Application server completed 61 Short UBEs, 4 Long UBEs concurrently as the mixed size batch workload.

  • The mixed size UBEs ran concurrently from the Enterprise Application server with the 8,000 online users driven by the LoadRunner.

See Also

Disclosure Statement

Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 09/30/2012.

Oracle TimesTen In-Memory Database Performance on SPARC T4-2

The Oracle TimesTen In-Memory Database is optimized to run on Oracle's SPARC T4 processor platforms running Oracle Solaris 11 providing unsurpassed scalability, performance, upgradability, protection of investment and return on investment. The following demonstrate the value of combining Oracle TimesTen In-Memory Database with SPARC T4 servers and Oracle Solaris 11:

On a Mobile Call Processing test, the 2-socket SPARC T4-2 server outperforms:

  • Oracle's SPARC Enterprise M4000 server (4 x 2.66 GHz SPARC64 VII+) by 34%.

  • Oracle's SPARC T3-4 (4 x 1.65 GHz SPARC T3) by 2.7x, or 5.4x per processor.

Utilizing the TimesTen Performance Throughput Benchmark (TPTBM), the SPARC T4-2 server protects investments with:

  • 2.1x the overall performance of a 4-socket SPARC Enterprise M4000 server in read-only mode and 1.5x the performance in update-only testing. This is 4.2x more performance per processor than the SPARC64 VII+ 2.66 GHz based system.

  • 10x more performance per processor than the SPARC T2+ 1.4 GHz server.

  • 1.6x better performance per processor than the SPARC T3 1.65 GHz based server.

In replication testing, the two socket SPARC T4-2 server is over 3x faster than the performance of a four socket SPARC Enterprise T5440 server in both asynchronous replication environment and the highly available 2-Safe replication. This testing emphasizes parallel replication between systems.

Performance Landscape

Mobile Call Processing Test Performance

System Processor Sockets/Cores Tps Tps/
Socket
SPARC T4-2 SPARC T4, 2.85 GHz 2 16 218,400 109,200
M4000 SPARC64 VII+, 2.66 GHz 4 16 162,900 40,725
SPARC T3-4 SPARC T3, 1.65 GHz 4 64 80,400 20,100

TimesTen Performance Throughput Benchmark (TPTBM) Read-Only

System Processor Sockets/Cores Tps Tps/
Socket
SPARC T4-2 SPARC T4, 2.85 GHz 2 16 6.5M 3.3M
SPARC T3-4 SPARC T3, 1.65 GHz 4 64 7.9M 2.0M
M4000 SPARC64 VII+, 2.66 GHz 4 16 3.1M 0.8M
T5440 SPARC T2+, 1.4 GHz 4 32 3.1M 0.8M

TimesTen Performance Throughput Benchmark (TPTBM) Update-Only

System Processor Sockets/Cores Tps Tps/
Socket
SPARC T4-2 SPARC T4, 2.85 GHz 2 16 547,800 273,900
M4000 SPARC64 VII+, 2.66 GHz 4 16 363,800 90,950
SPARC T3-4 SPARC T3, 1.65 GHz 4 64 240,250 60,125

TimesTen Replication Tests

System Processor Sockets/Cores Asynchronous 2-Safe
SPARC T4-2 SPARC T4, 2.85 GHz 2 16 38,024 13,701
SPARC T5440 SPARC T2+, 1.4 GHz 4 32 11,621 4,615

Configuration Summary

Hardware Configurations:

SPARC T4-2 server
2 x SPARC T4 processors, 2.85 GHz
256 GB memory
1 x 8 Gbs FC Qlogic HBA
1 x 6 Gbs SAS HBA
4 x 300 GB internal disks
Sun Storage F5100 Flash Array (40 x 24 GB flash modules)
1 x Sun Fire X4275 server configured as COMSTAR head

SPARC T3-4 server
4 x SPARC T3 processors, 1.6 GHz
512 GB memory
1 x 8 Gbs FC Qlogic HBA
8 x 146 GB internal disks
1 x Sun Fire X4275 server configured as COMSTAR head

SPARC Enterprise M4000 server
4 x SPARC64 VII+ processors, 2.66 GHz
128 GB memory
1 x 8 Gbs FC Qlogic HBA
1 x 6 Gbs SAS HBA
2 x 146 GB internal disks
Sun Storage F5100 Flash Array (40 x 24 GB flash modules)
1 x Sun Fire X4275 server configured as COMSTAR head

Software Configuration:

Oracle Solaris 11 11/11
Oracle TimesTen 11.2.2.4

Benchmark Descriptions

TimesTen Performance Throughput BenchMark (TPTBM) is shipped with TimesTen and measures the total throughput of the system. The workload can test read-only, update-only, delete and insert operations as required.

Mobile Call Processing is a customer-based workload for processing calls made by mobile phone subscribers. The workload has a mixture of read-only, update, and insert-only transactions. The peak throughput performance is measured from multiple concurrent processes executing the transactions until a peak performance is reached via saturation of the available resources.

Parallel Replication tests using both asynchronous and 2-Safe replication methods. For asynchronous replication, transactions are processed in batches to maximize the throughput capabilities of the replication server and network. In 2-Safe replication, also known as no data-loss or high availability, transactions are replicated between servers immediately emphasizing low latency. For both environments, performance is measured in the number of parallel replication servers and the maximum transactions-per-second for all concurrent processes.

See Also

Disclosure Statement

Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 1 October 2012.

Thursday Mar 29, 2012

Sun Server X2-8 (formerly Sun Fire X4800 M2) Delivers World Record TPC-C for x86 Systems

Oracle's Sun Server X2-8 (formerly Sun Fire X4800 M2 server) equipped with eight 2.4 GHz Intel Xeon Processor E7-8870 chips obtained a result of 5,055,888 tpmC on the TPC-C benchmark. This result is a world record for x86 servers. Oracle demonstrated this world record database performance running Oracle Database 11g Release 2 Enterprise Edition with Partitioning.

  • The Sun Server X2-8 delivered a new x86 TPC-C world record of 5,055,888 tpmC with a price performance of $0.89/tpmC using Oracle Database 11g Release 2. This configuration is available 7/10/12.

  • The Sun Server X2-8 delivers 3.0x times better performance than the next 8-processor result, an IBM System p 570 equipped with POWER6 processors.

  • The Sun Server X2-8 has 3.1x times better price/performance than the 8-processor 4.7GHz POWER6 IBM System p 570.

  • The Sun Server X2-8 has 1.6x times better performance than the 4-processor IBM x3850 X5 system equipped with Intel Xeon processors.

  • This is the first TPC-C result on any system using eight Intel Xeon Processor E7-8800 Series chips.

  • The Sun Server X2-8 is the first x86 system to get over 5 million tpmC.

  • The Oracle solution utilized Oracle Linux operating system and Oracle Database 11g Enterprise Edition Release 2 with Partitioning to produce the x86 world record TPC-C benchmark performance.

Performance Landscape

Select TPC-C results (sorted by tpmC, bigger is better)

System p/c/t tpmC Price
/tpmC
Avail Database Memory
Size
Sun Server X2-8 8/80/160 5,055,888 0.89 USD 7/10/2012 Oracle 11g R2 4 TB
IBM x3850 X5 4/40/80 3,014,684 0.59 USD 7/11/2011 DB2 ESE 9.7 3 TB
IBM x3850 X5 4/32/64 2,308,099 0.60 USD 5/20/2011 DB2 ESE 9.7 1.5 TB
IBM System p 570 8/16/32 1,616,162 3.54 USD 11/21/2007 DB2 9.0 2 TB

p/c/t - processors, cores, threads
Avail - availability date

Oracle and IBM TPC-C Response times

System tpmC Response Time (sec)
New Order 90th%
Response Time (sec)
New Order Average

Sun Server X2-8 5,055,888 0.210 0.166
IBM x3850 X5 3,014,684 0.500 0.272
Ratios - Oracle Better 1.6x 1.4x 1.3x

Oracle uses average new order response time for comparison between Oracle and IBM.

Graphs of Oracle's and IBM's response times for New-Order can be found in the full disclosure reports on TPC's website TPC-C Official Result Page.

Configuration Summary and Results

Hardware Configuration:

Server
Sun Server X2-8
8 x 2.4 GHz Intel Xeon Processor E7-8870
4 TB memory
8 x 300 GB 10K RPM SAS internal disks
8 x Dual port 8 Gbs FC HBA

Data Storage
10 x Sun Fire X4270 M2 servers configured as COMSTAR heads, each with
1 x 3.06 GHz Intel Xeon X5675 processor
8 GB memory
10 x 2 TB 7.2K RPM 3.5" SAS disks
2 x Sun Storage F5100 Flash Array storage (1.92 TB each)
1 x Brocade 5300 switches

Redo Storage
2 x Sun Fire X4270 M2 servers configured as COMSTAR heads, each with
1 x 3.06 GHz Intel Xeon X5675 processor
8 GB memory
11 x 2 TB 7.2K RPM 3.5" SAS disks

Clients
8 x Sun Fire X4170 M2 servers, each with
2 x 3.06 GHz Intel Xeon X5675 processors
48 GB memory
2 x 300 GB 10K RPM SAS disks

Software Configuration:

Oracle Linux (Sun Fire 4800 M2)
Oracle Solaris 11 Express (COMSTAR for Sun Fire X4270 M2)
Oracle Solaris 10 9/10 (Sun Fire X4170 M2)
Oracle Database 11g Release 2 Enterprise Edition with Partitioning
Oracle iPlanet Web Server 7.0 U5
Tuxedo CFS-R Tier 1

Results:

System: Sun Server X2-8
tpmC: 5,055,888
Price/tpmC: 0.89 USD
Available: 7/10/2012
Database: Oracle Database 11g
Cluster: no
New Order Average Response: 0.166 seconds

Benchmark Description

TPC-C is an OLTP system benchmark. It simulates a complete environment where a population of terminal operators executes transactions against a database. The benchmark is centered around the principal activities (transactions) of an order-entry environment. These transactions include entering and delivering orders, recording payments, checking the status of orders, and monitoring the level of stock at the warehouses.

Key Points and Best Practices

  • Oracle Database 11g Release 2 Enterprise Edition with Partitioning scales easily to this high level of performance.

  • COMSTAR (Common Multiprotocol SCSI Target) is the software framework that enables an Oracle Solaris host to serve as a SCSI Target platform. COMSTAR uses a modular approach to break the huge task of handling all the different pieces in a SCSI target subsystem into independent functional modules which are glued together by the SCSI Target Mode Framework (STMF). The modules implementing functionality at SCSI level (disk, tape, medium changer etc.) are not required to know about the underlying transport. And the modules implementing the transport protocol (FC, iSCSI, etc.) are not aware of the SCSI-level functionality of the packets they are transporting. The framework hides the details of allocation providing execution context and cleanup of SCSI commands and associated resources and simplifies the task of writing the SCSI or transport modules.

  • Oracle iPlanet Web Server middleware is used for the client tier of the benchmark. Each web server instance supports more than a quarter-million users while satisfying the response time requirement from the TPC-C benchmark.

See Also

Disclosure Statement

TPC Benchmark C, tpmC, and TPC-C are trademarks of the Transaction Processing Performance Council (TPC). Sun Server X2-8 (8/80/160) with Oracle Database 11g Release 2 Enterprise Edition with Partitioning, 5,055,888 tpmC, $0.89 USD/tpmC, available 7/10/2012. IBM x3850 X5 (4/40/80) with DB2 ESE 9.7, 3,014,684 tpmC, $0.59 USD/tpmC, available 7/11/2011. IBM x3850 X5 (4/32/64) with DB2 ESE 9.7, 2,308,099 tpmC, $0.60 USD/tpmC, available 5/20/2011. IBM System p 570 (8/16/32) with DB2 9.0, 1,616,162 tpmC, $3.54 USD/tpmC, available 11/21/2007. Source: http://www.tpc.org/tpcc, results as of 7/15/2011.

Monday Oct 03, 2011

SPARC T4-4 Produces World Record Oracle OLAP Capacity

Oracle's SPARC T4-4 server delivered world record capacity on the Oracle OLAP Perf workload.

  • The SPARC T4-4 server was able to operate on a cube with a 3 billion row fact table of sales data containing 4 dimensions which represents as many as 70 quintillion aggregate rows (70 followed by 18 zeros).

  • The SPARC T4-4 server supported 3,500 cube-queries/minute against the Oracle OLAP cube with an average response time of 1.5 seconds and the median response time of 0.15 seconds.

Performance Landscape

Oracle OLAP Perf Benchmark
System Fact Table
Num of Rows
Cube-Queries/
minute
Median Response
seconds
Average Response
seconds
SPARC T4-4 3 Billion 3,500 0.15 1.5

Configuration Summary and Results

Hardware Configuration:

SPARC T4-4 server with
4 x SPARC T4 processors, 3.0 GHz
1 TB main memory
2 x Sun Storage F5100 Flash Array

Software Configuration:

Oracle Solaris 10 8/11
Oracle Database 11g Enterprise Edition with Oracle OLAP option

Benchmark Description

OLAP Perf is a workload designed to demonstrate and stress the Oracle OLAP product's core functionalities of fast query, fast update, and rich calculations on a dimensional model to support Enhanced Data Warehousing. The workload uses a set of realistic business intelligence (BI) queries that run against an OLAP cube.

Key Points and Best Practices

  • The SPARC T4-4 server is estimated to support 2,400 interactive users with this fast response time assuming only 5 seconds between query requests.

See Also

Disclosure Statement

Copyright 2011, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 10/3/2011.

Wednesday Sep 28, 2011

SPARC T4 Servers Set World Record on PeopleSoft HRMS 9.1

Oracle's SPARC T4-4 servers running Oracle's PeopleSoft HRMS Self-Service 9.1 benchmark and Oracle Database 11g Release 2 achieved World Record performance on Oracle Solaris 10.

  • Using two SPARC T4-4 servers to run the application and database tiers and one SPARC T4-2 server to run the webserver tier, Oracle demonstrated world record performance of 15,000 concurrent users running the PeopleSoft HRMS Self-Service 9.1 benchmark.

  • The combination of the SPARC T4 servers running the PeopleSoft HRMS 9.1 benchmark supports 3.8x more online users with faster response time compared to the best published result from IBM on the previous PeopleSoft HRMS 8.9 benchmark.

  • The average CPU utilization on the SPARC T4-4 server in the application tier handling 15,000 users was less than 50%, leaving significant room for application growth.

  • The SPARC T4-4 server on the application tier used Oracle Solaris Containers which provide a flexible, scalable and manageable virtualization environment.

Performance Landscape

PeopleSoft HRMS Self-Service 9.1 Benchmark
Systems Processors Users Ave Response -
Search (sec)
Ave Response -
Save (sec)
SPARC T4-2 (web)
SPARC T4-4 (app)
SPARC T4-4 (db)
2 x SPARC T4, 2.85 GHz
4 x SPARC T4, 3.0 GHz
4 x SPARC T4, 3.0 GHz
15,000 1.01 0.63
PeopleSoft HRMS Self-Service 8.9 Benchmark
IBM Power 570 (web/app)
IBM Power 570 (db)
12 x POWER5, 1.9 GHz
4 x POWER5, 1.9 GHz
4,000 1.74 1.25
IBM p690 (web)
IBM p690 (app)
IBM p690 (db)
4 x POWER4, 1.9 GHz
12 x POWER4, 1.9 GHz
6 x 4392 MPIS/Gen1
4,000 1.35 1.01

The main differences between version 9.1 and version 8.9 of the benchmark are:

  • the database expanded from 100K employees and 20K managers to 500K employees and 100K managers,
  • the manager data was expanded,
  • a new transaction, "Employee Add Profile," was added, the percent of users executing it is less then 2%, and the transaction has a heavier footprint,
  • version 9.1 has a different benchmark metric (Average Response search/save time for x number of users) versus single user search/save time,
  • newer versions of the PeopleSoft application and PeopleTools software are used.

Configuration Summary

Application Server:

1 x SPARC T4-4 server
4 x SPARC T4 processors 3.0 GHz
512 GB main memory
5 x 300 GB SAS internal disks,
2 x 100 GB internal SSDs
1 x 300 GB internal SSD
Oracle Solaris 10 8/11
PeopleSoft PeopleTools 8.51.02
PeopleSoft HCM 9.1
Oracle Tuxedo, Version 10.3.0.0, 64-bit, Patch Level 031
Java HotSpot(TM) 64-Bit Server VM on Solaris, version 1.6.0_20

Web Server:

1 x SPARC T4-2 server
2 x SPARC T4 processors 2.85 GHz
256 GB main memory
1 x 300 GB SAS internal disks
1 x 300 GB internal SSD
Oracle Solaris 10 8/11
PeopleSoft PeopleTools 8.51.02
Oracle WebLogic Server 11g (10.3.3)
Java HotSpot(TM) 64-Bit Server VM on Solaris, version 1.6.0_20

Database Server:

1 x SPARC T4-4 server
4 x SPARC T4 processors 3.0 GHz
256 GB main memory
3 x 300 GB SAS internal disks
1 x Sun Storage F5100 Flash Array (80 flash modules)
Oracle Solaris 10 8/11
Oracle Database 11g Release 2

Benchmark Description

The purpose of the PeopleSoft HRMS Self-Service 9.1 benchmark is to measure comparative online performance of the selected processes in PeopleSoft Enterprise HCM 9.1 with Oracle Database 11g. The benchmark kit is an Oracle standard benchmark kit run by all platform vendors to measure the performance. It's an OLTP benchmark with no dependency on remote COBOL calls, there is no batch workload, and DB SQLs are moderately complex. The results are certified by Oracle and a white paper is published.

PeopleSoft defines a business transaction as a series of HTML pages that guide a user through a particular scenario. Users are defined as corporate Employees, Managers and HR administrators. The benchmark consists of 14 scenarios which emulate users performing typical HCM transactions such as viewing paychecks, promoting and hiring employees, updating employee profiles and other typical HCM application transactions.

All these transactions are well-defined in the PeopleSoft HR Self-Service 9.1 benchmark kit. The benchmark metric is the Average Response Time for search and save for 15,000 users..

Key Points and Best Practices

  • The application tier was configured with two PeopleSoft application server instances on the SPARC T4-4 server hosted in two separate Oracle Solaris Containers to demonstrate consolidation of multiple application, ease of administration, and load balancing.

  • Each PeopleSoft Application Server instance running in an Oracle Solaris Container was configured to run 5 application server Domains with 30 application server instances to be able to effectively handle the 15,000 users workload with zero application server queuing and minimal use of resources.

  • The web tier was configured with 20 WebLogic instances and with 4 GB JVM heap size to load balance transactions across 10 PeopleSoft Domains. That enables equitable distribution of transactions and scaling to high number of users.

  • Internal SSDs were configured in the application tier to host PeopleSoft Application Servers object CACHE file systems and in the web tier for WebLogic servers' logging providing near zero millisecond service time and faster server response time.

See Also

Disclosure Statement

Oracle's PeopleSoft HRMS 9.1 benchmark, www.oracle.com/us/solutions/benchmark/apps-benchmark/peoplesoft-167486.html, results 9/26/2011.

Tuesday Sep 27, 2011

SPARC T4-2 Servers Set World Record on JD Edwards EnterpriseOne Day in the Life Benchmark with Batch, Outperforms IBM POWER7

Using Oracle's SPARC T4-2 server for the application tier and a SPARC T4-1 server for the database tier, a world record result was produced running the Oracle's JD Edwards EnterpriseOne application Day in the Life (DIL) benchmark concurrently with a batch workload.

  • The SPARC T4-2 server running online and batch with JD Edwards EnterpriseOne 9.0.2 is 1.7x faster and has better response time than the IBM Power 750 system which only ran the online component of JD Edwards EnterpriseOne 9.0 Day in the Life test.

  • The combination of SPARC T4 servers delivered a Day in the Life benchmark result of 10,000 online users with 0.35 seconds of average transaction response time running concurrently with 112 Universal Batch Engine (UBE) processes at 67 UBEs/minute.

  • This is the first JD Edwards EnterpriseOne benchmark for 10,000 users and payroll batch on a SPARC T4-2 server for the application tier and the database tier with Oracle Database 11g Release 2. All servers ran with the Oracle Solaris 10 operating system.

  • The single-thread performance of the SPARC T4 processor produced sub-second response for the online components and provided dramatic performance for the batch jobs.

  • The SPARC T4 servers, JD Edwards EnterpriseOne 9.0.2, and Oracle WebLogic Server 11g Release 1 support 17% more users per JAS (Java Application Server) than the SPARC T3-1 server for this benchmark.

  • The SPARC T4-2 server provided a 6.7x better batch processing rate than the previous SPARC T3-1 server record result and had 2.5x faster response time.

  • The SPARC T4-2 server used Oracle Solaris Containers, which provide flexible, scalable and manageable virtualization.

  • JD Edwards EnterpriseOne uses Oracle Fusion Middleware WebLogic Server 11g R1 and Oracle Fusion Middleware Cluster Web Tier Utilities 11g HTTP server.

  • The combination of the SPARC T4-2 server and Oracle JD Edwards EnterpriseOne in the application tier with a SPARC T4-1 server in the database tier measured low CPU utilization providing headroom for growth.

Performance Landscape

JD Edwards EnterpriseOne Day in the Life Benchmark
Online with Batch Workload

System Online
Users
Resp
Time (sec)
Batch
Concur
(# of UBEs)
Batch
Rate
(UBEs/m)
Version
2xSPARC T4-2 (app+web)
SPARC T4-1 (db)
10000 0.35 112 67 9.0.2
SPARC T3-1 (app+web)
SPARC Enterprise M3000 (db)
5000 0.88 19 10 9.0.1

Resp Time (sec) — Response time of online jobs reported in seconds
Batch Concur (# of UBEs) — Batch concurrency presented in the number of UBEs
Batch Rate (UBEs/m) — Batch transaction rate in UBEs per minute

Edwards EnterpriseOne Day in the Life Benchmark
Online Workload Only

System Online
Users
Response
Time (sec)
Version
SPARC T3-1, 1 x SPARC T3 (1.65 GHz), Solaris 10 (app)
M3000, 1 x SPARC64 VII (2.75 GHz), Solaris 10 (db)
5000 0.52 9.0.1
IBM Power 750, POWER7 (3.55 GHz) (app+db) 4000 0.61 9.0

IBM result from http://www-03.ibm.com/systems/i/advantages/oracle/, IBM used WebSphere

Configuration Summary

Application Tier Configuration:

1 x SPARC T4-2 server with
2 x 2.85 GHz SPARC T4 processors
128 GB main memory
6 x 300 GB 10K RPM SAS internal HDD
Oracle Solaris 10 9/10
JD Edwards EnterpriseOne 9.0.2 with Tools 8.98.3.3

Web Tier Configuration:

1 x SPARC T4-2 server with
2 x 2.85 GHz SPARC T4 processors
256 GB main memory
2 x 300 GB SSD
4 x 300 GB 10K RPM SAS internal HDD
Oracle Solaris 10 9/10
Oracle WebLogic Server 11g Release 1

Database Tier Configuration:

1 x SPARC T4-1 server with
1 x 2.85 GHz SPARC T4 processor
128 GB main memory
6 x 300 GB 10K RPM SAS internal HDD
2 x Sun Storage F5100 Flash Array
Oracle Solaris 10 9/10
Oracle Database 11g Release 2

Benchmark Description

JD Edwards EnterpriseOne is an integrated applications suite of Enterprise Resource Planning (ERP) software. Oracle offers 70 JD Edwards EnterpriseOne application modules to support a diverse set of business operations.

Oracle's Day in the Life (DIL) kit is a suite of scripts that exercises most common transactions of JD Edwards EnterpriseOne applications, including business processes such as payroll, sales order, purchase order, work order, and manufacturing processes, such as ship confirmation. These are labeled by industry acronyms such as SCM, CRM, HCM, SRM and FMS. The kit's scripts execute transactions typical of a mid-sized manufacturing company.

  • The workload consists of online transactions and the UBE – Universal Business Engine workload of 42 short, 8 medium and 4 long UBEs.

  • LoadRunner runs the DIL workload, collects the user’s transactions response times and reports the key metric of Combined Weighted Average Transaction Response time.

  • The UBE processes workload runs from the JD Enterprise Application server.

    • Oracle's UBE processes come as three flavors:
      • Short UBEs < 1 minute engage in Business Report and Summary Analysis,
      • Mid UBEs > 1 minute create a large report of Account, Balance, and Full Address,
      • Long UBEs > 2 minutes simulate Payroll, Sales Order, night only jobs.
    • The UBE workload generates large numbers of PDF files reports and log files.
    • The UBE Queues are categorized as the QBATCHD, a single threaded queue for large and medium UBEs, and the QPROCESS queue for short UBEs run concurrently.

Oracle’s UBE process performance metric is Number of Maximum Concurrent UBE processes at transaction rate, UBEs/minute.

Key Points and Best Practices

One JD Edwards EnterpriseOne Application Server and two Oracle WebLogic Servers 11g R1 coupled with two Oracle Fusion Middleware 11g Web Tier HTTP Server instances on the SPARC T4-2 servers were hosted in three separate Oracle Solaris Containers to demonstrate consolidation of multiple application and web servers.

  • Interrupt fencing was configured on all Oracle Solaris Containers to channel the interrupts to processors other than the processor sets used for the JD Edwards Application server and WebLogic servers.

  • Processor 0 was left alone for clock interrupts.

  • The applications were executed in the FX scheduling class to improve performance by reducing the frequency of context switches.

  • A WebLogic vertical cluster was configured on each WebServer Container with twelve managed instances each to load balance users' requests and to provide the infrastructure that enables scaling to high number of users with ease of deployment and high availability.

  • The database server was run in an Oracle Solaris Container hosted on the SPARC T4-2 server.

  • The database log writer was run in the real time RT class and bound to a processor set.

  • The database redo logs were configured on the raw disk partitions.

  • The private network between the SPARC T4-2 servers was configured with a 10 GbE interface.

  • The Oracle Solaris Container on the Enterprise Application server ran 42 Short UBEs, 8 Medium UBEs and 4 Long UBEs concurrently as the mixed size batch workload.

  • The mixed size UBEs ran concurrently from the application server with the 10000 online users driven by the LoadRunner.

See Also

Disclosure Statement

Copyright 2011, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 9/26/2011.

Monday Sep 19, 2011

Halliburton ProMAX® Seismic Processing on Sun Blade X6270 M2 with Sun ZFS Storage 7320

Halliburton/Landmark's ProMAX® 3D Pre-Stack Kirchhoff Time Migration's (PSTM) single workflow scalability and multiple workflow throughput using various scheduling methods are evaluated on a cluster of Oracle's Sun Blade X6270 M2 server modules attached to Oracle's Sun ZFS Storage 7320 appliance.

Two resource scheduling methods, compact and distributed, are compared while increasing the system load with additional concurrent ProMAX® workflows.

  • Multiple concurrent 24-process ProMAX® PSTM workflow throughput is constant; 10 workflows on 10 nodes finish as fast as 1 workflow on one compute node. Additionally, processing twice the data volume yields similar traces/second throughput performance.

  • A single ProMAX® PSTM workflow has good scaling from 1 to 10 nodes of a Sun Blade X6270 M2 cluster scaling 4.5X. ProMAX® scales to 4.7X on 10 nodes with one input data set and 6.3X with two consecutive input data sets (i.e. twice the data).

  • A single ProMAX® PSTM workflow has near linear scaling of 11x on a Sun Blade X6270 M2 server module when running from 1 to 12 processes.

  • The 12-thread ProMAX® workflow throughput using the distributed scheduling method is equivalent or slightly faster than the compact scheme for 1 to 6 concurrent workflows.

Performance Landscape

Multiple 24-Process Workflow Throughput Scaling

This test measures the system throughput scalability as concurrent 24-process workflows are added, one workflow per node. The per workflow throughput and the system scalability are reported.

Aggregate system throughput scales linearly. Ten concurrent workflows finish in the same time as does one workflow on a single compute node.

Halliburton ProMAX® Pre-Stack Time Migration - Multiple Workflow Scaling


Single Workflow Scaling

This test measures single workflow scalability across a 10-node cluster. Utilizing a single data set, performance exhibits near linear scaling of 11x at 12 processes, and per-node scaling of 4x at 6 nodes; performance flattens quickly reaching a peak of 60x at 240 processors and per-node scaling of 4.7x with 10 nodes.

Running with two consecutive input data sets in the workflow, scaling is considerably improved with peak scaling ~35% higher than obtained using a single data set. Doubling the data set size minimizes time spent in workflow initialization, data input and output.

Halliburton ProMAX® Pre-Stack Time Migration - Single Workflow Scaling

This next test measures single workflow scalability across a 10-node cluster (as above) but limiting scheduling to a maximum of 12-process per node; effectively restricting a maximum of one process per physical core. The speedup relative to a single process, and single node are reported.

Utilizing a single data set, performance exhibits near linear scaling of 37x at 48 processes, and per-node scaling of 4.3x at 6 nodes. Performance of 55x at 120 processors and per-node scaling of 5x with 10 nodes is reached and scalability is trending higher more strongly compared to the the case of two processes running per physical core above. For equivalent total process counts, multi-node runs using only a single process per physical core appear to run between 28-64% more efficiently (96 and 24 processes respectively). With a full compliment of 10 nodes (120 processes) the peak performance is only 9.5% lower than with 2 processes per vcpu (240 processes).

Running with two consecutive input data sets in the workflow, scaling is considerably improved with peak scaling ~35% higher than obtained using a single data set.

Halliburton ProMAX® Pre-Stack Time Migration - Single Workflow Scaling

Multiple 12-Process Workflow Throughput Scaling, Compact vs. Distributed Scheduling

The fourth test compares compact and distributed scheduling of 1, 2, 4, and 6 concurrent 12-processor workflows.

All things being equal, the system bi-section bandwidth should improve with distributed scheduling of a fixed-size workflow; as more nodes are used for a workflow, more memory and system cache is employed and any node memory bandwidth bottlenecks can be offset by distributing communication across the network (provided the network and inter-node communication stack do not become a bottleneck). When physical cores are not over-subscribed, compact and distributed scheduling performance is within 3% suggesting that there may be little memory contention for this workflow on the benchmarked system configuration.

With compact scheduling of two concurrent 12-processor workflows, the physical cores become over-subscribed and performance degrades 36% per workflow. With four concurrent workflows, physical cores are oversubscribed 4x and performance is seen to degrade 66% per workflow. With six concurrent workflows over-subscribed compact scheduling performance degrades 77% per workflow. As multiple 12-processor workflows become more and more distributed, the performance approaches the non over-subscribed case.

Halliburton ProMAX® Pre-Stack Time Migration - Multiple Workflow Scaling

141616 traces x 624 samples


Test Notes

All tests were performed with one input data set (70808 traces x 624 samples) and two consecutive input data sets (2 * (70808 traces x 624 samples)) in the workflow. All results reported are the average of at least 3 runs and performance is based on reported total wall-clock time by the application.

All tests were run with NFS attached Sun ZFS Storage 7320 appliance and then with NFS attached legacy Sun Fire X4500 server. The StorageTek Workload Analysis Tool (SWAT) was invoked to measure the I/O characteristics of the NFS attached storage used on separate runs of all workflows.

Configuration Summary

Hardware Configuration:

10 x Sun Blade X6270 M2 server modules, each with
2 x 3.33 GHz Intel Xeon X5680 processors
48 GB DDR3-1333 memory
4 x 146 GB, Internal 10000 RPM SAS-2 HDD
10 GbE
Hyper-Threading enabled

Sun ZFS Storage 7320 Appliance
1 x Storage Controller
2 x 2.4 GHz Intel Xeon 5620 processors
48 GB memory (12 x 4 GB DDR3-1333)
2 TB Read Cache (4 x 512 GB Read Flash Accelerator)
10 GbE
1 x Disk Shelf
20.0 TB RAID-Z (20 x 1 TB SAS-2, 7200 RPM HDD)
4 x Write Flash Accelerators

Sun Fire X4500
2 x 2.8 GHz AMD 290 processors
16 GB DDR1-400 memory
34.5 TB RAID-Z (46 x 750 GB SATA-II, 7200 RPM HDD)
10 GbE

Software Configuration:

Oracle Linux 5.5
Parallel Virtual Machine 3.3.11 (bundled with ProMAX)
Intel 11.1.038 Compilers
Libraries: pthreads 2.4, Java 1.6.0_01, BLAS, Stanford Exploration Project Libraries

Benchmark Description

The ProMAX® family of seismic data processing tools is the most widely used Oil and Gas Industry seismic processing application. ProMAX® is used for multiple applications, from field processing and quality control, to interpretive project-oriented reprocessing at oil companies and production processing at service companies. ProMAX® is integrated with Halliburton's OpenWorks® Geoscience Oracle Database to index prestack seismic data and populate the database with processed seismic.

This benchmark evaluates single workflow scalability and multiple workflow throughput of the ProMAX® 3D Prestack Kirchhoff Time Migration (PSTM) while processing the Halliburton benchmark data set containing 70,808 traces with 8 msec sample interval and trace length of 4992 msec. Benchmarks were performed with both one and two consecutive input data sets.

Each workflow consisted of:

  • reading the previously constructed MPEG encoded processing parameter file
  • reading the compressed seismic data traces from disk
  • performing the PSTM imaging
  • writing the result to disk

Workflows using two input data sets were constructed by simply adding a second identical seismic data read task immediately after the first in the processing parameter file. This effectively doubled the data volume read, processed, and written.

This version of ProMAX® currently only uses Parallel Virtual Machine (PVM) as the parallel processing paradigm. The PVM software only used TCP networking and has no internal facility for assigning memory affinity and processor binding. Every compute node is running a PVM daemon.

The ProMAX® processing parameters used for this benchmark:

Minimum output inline = 65
Maximum output inline = 85
Inline output sampling interval = 1
Minimum output xline = 1
Maximum output xline = 200 (fold)
Xline output sampling interval = 1
Antialias inline spacing = 15
Antialias xline spacing = 15
Stretch Mute Aperature Limit with Maximum Stretch = 15
Image Gather Type = Full Offset Image Traces
No Block Moveout
Number of Alias Bands = 10
3D Amplitude Phase Correction
No compression
Maximum Number of Cache Blocks = 500000

Primary PSTM business metrics are typically time-to-solution and accuracy of the subsurface imaging solution.

Key Points and Best Practices

  • Multiple job system throughput scales perfectly; ten concurrent workflows on 10 nodes each completes in the same time and has the same throughput as a single workflow running on one node.
  • Best single workflow scaling is 6.6x using 10 nodes.

    When tasked with processing several similar workflows, while individual time-to-solution will be longer, the most efficient way to run is to fully distribute them one workflow per node (or even across two nodes) and run these concurrently, rather than to use all nodes for each workflow and running consecutively. For example, while the best-case configuration used here will run 6.6 times faster using all ten nodes compared to a single node, ten such 10-node jobs running consecutively will overall take over 50% longer to complete than ten jobs one per node running concurrently.

  • Throughput was seen to scale better with larger workflows. While throughput with both large and small workflows are similar with only one node, the larger dataset exhibits 11% and 35% more throughput with four and 10 nodes respectively.

  • 200 processes appears to be a scalability asymptote with these workflows on the systems used.
  • Hyperthreading marginally helps throughput. For the largest model run on 10 nodes, 240 processes delivers 11% more performance than with 120 processes.

  • The workflows do not exhibit significant I/O bandwidth demands. Even with 10 concurrent 24-process jobs, the measured aggregate system I/O did not exceed 100 MB/s.

  • 10 GbE was the only network used and, though shared for all interprocess communication and network attached storage, it appears to have sufficient bandwidth for all test cases run.

See Also

Disclosure Statement

The following are trademarks or registered trademarks of Halliburton/Landmark Graphics: ProMAX®, GeoProbe®, OpenWorks®. Results as of 9/1/2011.

Thursday Sep 15, 2011

Sun Fire X4800 M2 Servers (now known as Sun Server X2-8) Produce World Record on SAP SD-Parallel Benchmark

Oracle delivered an SAP enhancement package 4 for SAP ERP 6.0 (Unicode) Sales and Distribution - Parallel (SD Parallel) Benchmark world record result using eight of Oracle's Sun Fire X4800 M2 servers (now known as Sun Server X2-8), Oracle Solaris 10 and Oracle Database 11g Real Application Clusters (RAC) software that achieved 180,000 users as of 10/03/2011.

  • The eight Sun Fire X4800 M2 servers delivered a world record result of 180,000 users on the SAP SD Parallel Benchmark.

  • The eight Sun Fire X4800 M2 server SD Parallel result of 180,000 users delivered 43% more performance compared to the IBM Power 795 server SD two-tier result of 126,063 users.

Performance Landscape

Selected SAP Sales and Distribution (SD) benchmark results are presented in decreasing order of performance. All benchmarks were using SAP enhancement package 4 for SAP ERP 6.0 (Unicode).

System OS
Database
Users SAPS Type Cert #
Eight Sun Fire X4800 M2
8 x Intel Xeon E7-8870 @2.4 GHz
512 GB
Oracle Solaris 10
Oracle 11g RAC
180,000 1,016,380 Parallel 2011037
Six Sun Fire X4800 M2
8 x Intel Xeon E7-8870 @2.4 GHz
512 GB
Oracle Solaris 10
Oracle 11g RAC
137,904 765,470 Parallel 2011038
IBM Power 795
32 x POWER7 @4.0 GHz
4096 GB
AIX 7.1
DB2 9.7
126,063 688,630 Two-Tier 2010046
Four Sun Fire X4800 M2
8 x Intel Xeon E7-8870 @2.4 GHz
512 GB
Oracle Solaris 10
Oracle 11g RAC
94,736 546,050 Parallel 2011039
Two Sun Fire X4800 M2
8 x Intel Xeon E7-8870 @2.4 GHz
512 GB
Oracle Solaris 10
Oracle 11g RAC
49,860 274,080 Parallel 2011040
Four Sun Fire X4470
4 x Intel Xeon X7560 @2.26 GHz
256 GB
Solaris 10
Oracle 11g RAC
40,000 221,020 Parallel 2010039

Complete benchmark results and descriptions can be found at the SAP standard applications benchmark website.
For SD benchmark results website: Two-Tier or Three-Tier. For SD Parallel benchmark results website: SD Parallel.

Configuration and Results Summary

Hardware Configuration:

8 x Sun Fire X4800 M2 servers, each with
8 x Intel Xeon E7-8870 @ 2.4 GHz (8 processors, 80 cores, 160 threads)
512 GB memory

Software Configuration:

SAP enhancement package 4 for SAP ERP 6.0
Oracle Database 11g Real Application Clusters (RAC)
Oracle Solaris 10

Results Summary:

Number of SAP SD benchmark users:
180,000
Average dialog response time:
0.63 seconds
Throughput:

Fully processed order line items per hour:
20,327,670

Dialog steps/hour:
60,983,000

SAPS:
1,016,380
Average database request time (dialog/update):
0.010 sec / 0.055 sec
SAP Certification:
2011037

Benchmark Description

The SAP Standard Application Sales and Distribution - Parallel (SD Parallel) Benchmark is a two-tier ERP business test that is indicative of full business workloads of complete order processing and invoice processing and demonstrates the ability to run both the application and database software on a single system. The SAP Standard Application SD Benchmark represents the critical tasks performed in real-world ERP business environments.

The SD Parallel Benchmark consists of the same transactions and user interaction steps as the two-tier and three-tier SD Benchmark. This means that the SD Parallel Benchmark runs the same business processes as the SD Benchmark. The difference between the benchmarks is the technical data distribution. Additionally, the benchmark requires equal distribution of the benchmark users across all database nodes for the used benchmark clients (round-robin method). Following this rule, all database nodes work on data of all clients. This avoids unrealistic configurations such as having only one client per database node.

The SAP Benchmark Council agreed to give the parallel benchmark a different name so that the difference can be easily recognized by any interested parties - customers, prospects, and analysts. The naming convention is SD Parallel for Sales & Distribution - Parallel.

SAP is one of the premier world-wide ERP application providers, and maintains a suite of benchmark tests to demonstrate the performance of competitive systems on the various SAP products.

See Also

Disclosure Statement

SAP enhancement package 4 for SAP ERP 6.0 (Unicode) Sales and Distribution Benchmark, results as of 10/03/2011.

SD Parallel, 8 x Sun Fire X4800 M2 (each 8 processors, 80 cores, 160 threads) 180,000 SAP SD Users, Oracle Solaris 10, Oracle 11g Real Application Clusters (RAC), Certification Number 2011037.
SD Parallel, 6 x Sun Fire X4800 M2 (each 8 processors, 80 cores, 160 threads) 137,904 SAP SD Users, Oracle Solaris 10, Oracle 11g Real Application Clusters (RAC), Certification Number 2011038.
SD Parallel, 4 x Sun Fire X4470 (each 4 processors, 32 cores, 64 threads) 40,000 SAP SD Users, Oracle Solaris 10, Oracle 11g Real Application Clusters (RAC), Certification Number 2010039.
SD Two-Tier, IBM Power 795 (32 processors, 256 cores, 1024 threads) 126,063 SAP SD Users, AIX 7.1, DB2 9.7, Certification Number 2010046.

SAP, R/3 are registered trademarks of SAP AG in Germany and other countries. More information may be found at www.sap.com/benchmark.

Friday Jul 01, 2011

SPARC T3-1 Record Results Running JD Edwards EnterpriseOne Day in the Life Benchmark with Added Batch Component

Using Oracle's SPARC T3-1 server for the application tier and Oracle's SPARC Enterprise M3000 server for the database tier, a world record result was produced running the Oracle's JD Edwards EnterpriseOne applications Day in the Life benchmark run concurrently with a batch workload.

  • The SPARC T3-1 server based result has 25% better performance than the IBM Power 750 POWER7 server even though the IBM result did not include running a batch component.

  • The SPARC T3-1 server based result has 25% better space/performance than the IBM Power 750 POWER7 server as measured by the online component.

  • The SPARC T3-1 server based result is 5x faster than the x86-based IBM x3650 M2 server system when executing the online component of the JD Edwards EnterpriseOne 9.0.1 Day in the Life benchmark. The IBM result did not include a batch component.

  • The SPARC T3-1 server based result has 2.5x better space/performance than the x86-based IBM x3650 M2 server as measured by the online component.

  • The combination of SPARC T3-1 and SPARC Enterprise M3000 servers delivered a Day in the Life benchmark result of 5000 online users with 0.875 seconds of average transaction response time running concurrently with 19 Universal Batch Engine (UBE) processes at 10 UBEs/minute. The solution exercises various JD Edwards EnterpriseOne applications while running Oracle WebLogic Server 11g Release 1 and Oracle Web Tier Utilities 11g HTTP server in Oracle Solaris Containers, together with the Oracle Database 11g Release 2.

  • The SPARC T3-1 server showed that it could handle the additional workload of batch processing while maintaining the same number of online users for the JD Edwards EnterpriseOne Day in the Life benchmark. This was accomplished with minimal loss in response time.

  • JD Edwards EnterpriseOne 9.0.1 takes advantage of the large number of compute threads available in the SPARC T3-1 server at the application tier and achieves excellent response times.

  • The SPARC T3-1 server consolidates the application/web tier of the JD Edwards EnterpriseOne 9.0.1 application using Oracle Solaris Containers. Containers provide flexibility, easier maintenance and better CPU utilization of the server leaving processing capacity for additional growth.

  • A number of Oracle advanced technology and features were used to obtain this result: Oracle Solaris 10, Oracle Solaris Containers, Oracle Java Hotspot Server VM, Oracle WebLogic Server 11g Release 1, Oracle Web Tier Utilities 11g, Oracle Database 11g Release 2, the SPARC T3 and SPARC64 VII+ based servers.

  • This is the first published result running both online and batch workload concurrently on the JD Enterprise Application server. No published results are available from IBM running the online component together with a batch workload.

  • The 9.0.1 version of the benchmark saw some minor performance improvements relative to 9.0. When comparing between 9.0.1 and 9.0 results, the reader should take this into account when the difference between results is small.

Performance Landscape

JD Edwards EnterpriseOne Day in the Life Benchmark
Online with Batch Workload

This is the first publication on the Day in the Life benchmark run concurrently with batch jobs. The batch workload was provided by Oracle's Universal Batch Engine.

System Rack
Units
Online
Users
Resp
Time (sec)
Batch
Concur
(# of UBEs)
Batch
Rate
(UBEs/m)
Version
SPARC T3-1, 1xSPARC T3 (1.65 GHz), Solaris 10
M3000, 1xSPARC64 VII+ (2.86 GHz), Solaris 10
4 5000 0.88 19 10 9.0.1

Resp Time (sec) — Response time of online jobs reported in seconds
Batch Concur (# of UBEs) — Batch concurrency presented in the number of UBEs
Batch Rate (UBEs/m) — Batch transaction rate in UBEs/minute.

JD Edwards EnterpriseOne Day in the Life Benchmark
Online Workload Only

These results are for the Day in the Life benchmark. They are run without any batch workload.

System Rack
Units
Online
Users
Response
Time (sec)
Version
SPARC T3-1, 1xSPARC T3 (1.65 GHz), Solaris 10
M3000, 1xSPARC64 VII (2.75 GHz), Solaris 10
4 5000 0.52 9.0.1
IBM Power 750, 1xPOWER7 (3.55 GHz), IBM i7.1 4 4000 0.61 9.0
IBM x3650M2, 2xIntel X5570 (2.93 GHz), OVM 2 1000 0.29 9.0

IBM result from http://www-03.ibm.com/systems/i/advantages/oracle/, IBM used WebSphere

Configuration Summary

Hardware Configuration:

1 x SPARC T3-1 server
1 x 1.65 GHz SPARC T3
128 GB memory
16 x 300 GB 10000 RPM SAS
1 x Sun Flash Accelerator F20 PCIe Card, 96 GB
1 x 10 GbE NIC
1 x SPARC Enterprise M3000 server
1 x 2.86 SPARC64 VII+
64 GB memory
1 x 10 GbE NIC
2 x StorageTek 2540 + 2501

Software Configuration:

JD Edwards EnterpriseOne 9.0.1 with Tools 8.98.3.3
Oracle Database 11g Release 2
Oracle 11g WebLogic server 11g Release 1 version 10.3.2
Oracle Web Tier Utilities 11g
Oracle Solaris 10 9/10
Mercury LoadRunner 9.10 with Oracle Day in the Life kit for JD Edwards EnterpriseOne 9.0.1
Oracle’s Universal Batch Engine - Short UBEs and Long UBEs

Benchmark Description

JD Edwards EnterpriseOne is an integrated applications suite of Enterprise Resource Planning (ERP) software. Oracle offers 70 JD Edwards EnterpriseOne application modules to support a diverse set of business operations.

Oracle's Day in the Life (DIL) kit is a suite of scripts that exercises most common transactions of JD Edwards EnterpriseOne applications, including business processes such as payroll, sales order, purchase order, work order, and other manufacturing processes, such as ship confirmation. These are labeled by industry acronyms such as SCM, CRM, HCM, SRM and FMS. The kit's scripts execute transactions typical of a mid-sized manufacturing company.

  • The workload consists of online transactions and the UBE workload of 15 short and 4 long UBEs.

  • LoadRunner runs the DIL workload, collects the user’s transactions response times and reports the key metric of Combined Weighted Average Transaction Response time.

  • The UBE processes workload runs from the JD Enterprise Application server.

    • Oracle's UBE processes come as three flavors:

      • Short UBEs < 1 minute engage in Business Report and Summary Analysis,
      • Mid UBEs > 1 minute create a large report of Account, Balance, and Full Address,
      • Long UBEs > 2 minutes simulate Payroll, Sales Order, night only jobs.
    • The UBE workload generates large numbers of PDF files reports and log files.

    • The UBE Queues are categorized as the QBATCHD, a single threaded queue for large UBEs, and the QPROCESS queue for short UBEs run concurrently.

  • One of the Oracle Solaris Containers ran 4 Long UBEs, while another Container ran 15 short UBEs concurrently.

  • The mixed size UBEs ran concurrently from the SPARC T3-1 server with the 5000 online users driven by the LoadRunner.

  • Oracle’s UBE process performance metric is Number of Maximum Concurrent UBE processes at transaction rate, UBEs/minute.

Key Points and Best Practices

Two JD Edwards EnterpriseOne Application Servers and two Oracle Fusion Middleware WebLogic Servers 11g R1 coupled with two Oracle Fusion Middleware 11g Web Tier HTTP Server instances on the SPARC T3-1 server were hosted in four separate Oracle Solaris Containers to demonstrate consolidation of multiple application and web servers.

See Also

Disclosure Statement

Copyright 2011, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 6/27/2011.

Wednesday Mar 23, 2011

SPARC T3-1B Doubles Performance on Oracle Fusion Middleware WebLogic Avitek Medical Records Sample Application

The Oracle WebLogic Server 11g software was used to demonstrate the performance of the Avitek Medical Records sample application. A configuration using SPARC T3-1B and SPARC Enterprise M5000 servers from Oracle was used and showed excellent scaling of different configurations as well as doubling previous generation SPARC blade performance.

  • A SPARC T3-1B server, running a typical real-world J2EE application on Oracle WebLogic Server 11g, together with a SPARC Enterprise M5000 server running the Oracle database, had 2.1x times the transactional throughput over the previous generation UltraSPARC T2 processor based Sun Blade T6320 server module.

  • The SPARC T3-1B server shows linear scaling as the number of cores in the SPARC T3 processor used in the SPARC T3-1B system module are doubled.

  • The Avitek Medical Records application instances were deployed in Oracle Solaris zones on the SPARC T3-1B server, allowing for flexible, scalable and lightweight architecture of the application tier.

Performance Landscape

Performance for the application tier is presented. Results are the maximum transactions per second (TPS).

Server Processor Memory Maximum TPS
SPARC T3-1B 1 x SPARC T3, 1.65 GHz, 16 cores 128 GB 28,156
SPARC T3-1B 1 x SPARC T3, 1.65 GHz, 8 cores 128 GB 14,030
Sun Blade T6320 1 x UltraSPARC T2, 1.4 GHz, 8 cores 64 GB 13,386

The same SPARC Enterprise M5000 server from Oracle was used in each case as the database server. Internal disk storage was used.

Configuration Summary

Hardware Configuration:

1 x SPARC T3-1B
1 x 1.65 GHz SPARC T3
128 GB memory

1 x Sun Blade T6320
1 x 1.4Ghz GHz SPARC T2
64 GB memory

1 x SPARC Enterprise M5000
8 x 2.53 SPARC64 VII
128 GB memory

Software Configuration:

Avitek Medical Records
Oracle Database 10g Release 2
Oracle WebLogic Server 11g R1 version 10.3.3 (Oracle Fusion Middleware)
Oracle Solaris 10 9/10
HP Mercury LoadRunner 9.5

Benchmark Description

Avitek Medical Records (or MedRec) is an Oracle WebLogic Server 11g sample application suite that demonstrates all aspects of the J2EE platform. MedRec showcases the use of each J2EE component, and illustrates best practice design patterns for component interaction and client development. Oracle WebLogic server 11g is a key component of Oracle Fusion Middleware 11g.

The MedRec application provides a framework for patients, doctors, and administrators to manage patient data using a variety of different clients. Patient data includes:

  • Patient profile information: A patient's name, address, social security number, and log-in information.

  • Patient medical records: Details about a patient's visit with a physician, such as the patient's vital signs and symptoms as well as the physician's diagnosis and prescriptions.

MedRec comprises of two main Java EE applications supporting different user scenarios:

medrecEar – Patients log in to the web application (patientWebApp) to register their profile or edit. Patients can also view medical records or their prior visits. Administrators use the web application (adminWebApp) to approve or deny new patient profile requests. medrecEar also provides all of the controller and business logic used by the MedRec application suite, as well as the Web Service used by different clients.

physicianEar – Physicians and nurses login to the web application (physicianWebApp) to search and access patient profiles, create and review medical records, and prescribe medicine to patients. The physician application is designed to communicate using the Web Service provided in the medrecEar.

The medrecEAR and physicianEar application are deployed to Oracle WebLogic Server 11g instance called MedRecServer. The physicianEAR application communicates with the controller components of medrecEAR using Web Services.

The workload injected into the MedRec applications measures the average transactions per second for the following sequence:

  1. A client opens page http://{host}:7011/Start.jsp (MedRec)
  2. Patient completes Registration process
  3. Administrator login, approves the patient profile, and logout
  4. Physician connect to the on-line system and logs in
  5. Physician performs search for a patient and looks up patient's visit information
  6. Physician logs out
  7. Patient logs in and reviews the profile
  8. Patient makes changes to the profile and updates the information
  9. Patient logs out

Each of the above steps constitutes a single transaction.

Key Points and Best Practices

Please see the Oracle documentation on the Oracle Technical Network for tuning your Oracle WebLogic Server 11g deployment.

See Also

Disclosure Statement

Copyright 2011, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 3/22/2011.

Thursday Feb 17, 2011

SPARC T3-1 takes JD Edwards "Day In the Life" benchmark lead, beats IBM Power7 by 25%

Oracle's SPARC T3-1 server, running the application, together with Oracle's SPARC Enterprise M3000 server running the database, have achieved a record result of 5000 users, with 0.523 seconds of average transaction response time, for the online component of the "Day in the Life" JD Edwards EnterpriseOne benchmark.

  • The "Day in the Life" benchmark tests the Oracle JD Edwards EnterpriseOne applications, running Oracle Fusion Middleware WebLogic Server 11g R1, Oracle Fusion Middleware Web Tier Utilities 11g HTTP server and JD Edwards EnterpriseOne 9.0.1 in Oracle Solaris Containers, together with the Oracle Database 11g Release 2.

  • The SPARC T3-1 server is 25% faster and has better response time than the IBM P750 POWER7 system, when executing the JD Edwards EnterpriseOne 9.0.1 Day in the Life test, online component.

  • The SPARC T3-1 server had 25% better space/performance than the IBM P750 POWER7 server.

  • The SPARC T3-1 server is 5x faster than the x86-based IBM x3650 M2 server system, when executing the JD Edwards EnterpriseOne 9.0.1 Day in the Life test, online component.

  • The SPARC T3-1 server had 2.5x better space/performance than the x86-based IBM x3650 M2 server.

  • The SPARC T3-1 server consolidated the application/web tier of the JD Edwards EnterpriseOne 9.0.1 application using Oracle Solaris Containers. Containers provide flexibility, easier maintenance and better CPU utilization of the server leaving processing capacity for additional growth.

  • The SPARC Enterprise M3000 server provides enterprise class RAS features for customers deploying the Oracle 11g Release 2 database software.

  • To obtain this leading result, a number of Oracle advanced technology and features were used: Oracle Solaris 10, Oracle Solaris Containers, Oracle Java Hotspot Server VM, Oracle Fusion Middleware WebLogic Server 11g R1, Oracle Fusion Middleware Web Tier Utilities 11g, Oracle Database 11g Release 2, the SPARC T3 and the SPARC64 VII based servers.

Performance Landscape

JD Edwards EnterpriseOne DIL Online Component Performance Chart

System Memory OS #user JD Edwards
Version
Rack
Units
Response
Time
(sec)
SPARC T3-1, 1x1.65 GHz SPARC T3 128 Solaris 10 5000 9.0.1 2U 0.523
\*IBM Power 750, 1x3.55 GHz POWER7 120 IBM i7.1 4000 9.0 4U 0.61
IBM Power 570, 4x4.2 GHz POWER6 128 IBM i6.1 2400 8.12 4U 1.129
IBM x3650M2, 2x2.93 GHz X5570 64 OVM 1000 9.0 2U 0.29

\* from http://www-03.ibm.com/systems/i/advantages/oracle/, IBM used Websphere

Configuration Summary

Hardware Configuration:

1 x SPARC T3-1 server
1 x 1.65 GHz SPARC T3
128 GB memory
16 x 300 GB 10000 RPM SAS
1 x 1 GbE NIC
1 x SPARC Enterprise M3000
1 x 2.75 SPARC 64 VII
64 GB memory
1 x 1 GbE NIC
2 x StorageTek 2540/2501

Software Configuration:

JD Edwards EnterpriseOne 9.0.1 with Tools 8.98.3.3
Oracle Database 11g Release 2
Oracle Fusion Middleware 11g WebLogic server 11g R1 version 10.3.2
Oracle Fusion Middleware Web Tier Utilities 11g
Oracle Solaris 10 9/10
Mercury LoadRunner 9.10 with Oracle DIL kit for JD Edwards EnterpriseOne 9.0 update 1

Benchmark Description

Oracle's JD Edwards EnterpriseOne is an integrated applications suite of Enterprise Resource Planning software.

  • Oracle offers 70 JD Edwards EnterpriseOne application modules to support a diverse set of business operations.
  • Oracle 's Day-In-Life (DIL) kit is a suite of scripts that exercises most common transactions of J.D. Edwards EnterpriseOne applications including business processes such as payroll, sales order, purchase order, work order, and other manufacturing processes, such as ship confirmation. These are labeled by industry acronyms such as SCM, CRM, HCM, SRM and FMS.
  • Oracle's DIL kit's scripts execute transactions typical of a mid-sized manufacturing company.
  • The workload consists of online transactions. It does not include the batch processing job components.
  • LoadRunner is used to run the workload and collect the users' transactions response times against increasing numbers of users from 500 to 5000.
  • Key metric used to evaluate performance is the transaction response time which is reported by LoadRunner.

Key Points and Best Practices

Two JD Edwards EnterpriseOne and two Oracle Fusion Middleware WebLogic Servers 11g R1 coupled with two Fusion Middleware 11g Web Tier HTTP Servers instances on the SPARC T3-1 server were hosted in four separate Oracle Solaris Containers to demonstrate consolidation of multiple application and web servers.

  • Each Oracle Solaris container was bound to a separate processor set with 40 virtual processors allocated to each EnterpriseOne Server, 16 virtual processors allocated to each WebServer container and 16 to the default set. This was done to improve performance by using the physical memory closest to the processors, thereby, reducing memory access latency and reducing processor cross calls. The default processor set was used for network and disk interrupt handling.

  • The applications were executed in the FX scheduling class to improve performance by reducing the frequency of context switches.

  • A WebLogic Vertical cluster was configured on each WebServer container with seven managed instances each to load balance users' requests and to provide the infrastructure that enables scaling to high number of users with ease of deployment and high availability.

  • The database server was run in an Oracle Solaris Container hosted on the Oracle's SPARC Enterprise M3000 server.

See Also

Disclosure Statement

Copyright 2011, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 2/16/2011.

Wednesday Dec 08, 2010

Sun Blade X6275 M2 Cluster with Sun Storage 7410 Performance Running Seismic Processing Reverse Time Migration

This Oil & Gas benchmark highlights both the computational performance improvements of the Sun Blade X6275 M2 server module over the previous genernation server and the linear scalability achievable for the total application throughput using a Sun Storage 7410 system to deliver almost 2 GB/sec I/O effective write performance.

Oracle's Sun Storage 7410 system attached via 10 Gigabit Ethernet to a cluster of Oracle's Sun Blade X6275 M2 server modules was used to demonstrate the performance of a 3D VTI Reverse Time Migration application, a heavily used geophysical imaging and modeling application for Oil & Gas Exploration. The total application throughput scaling and computational kernel performance improvements are presented for imaging two production sized grids using 800 input samples.

  • The Sun Blade X6275 M2 server module showed up to a 40% performance improvement over the previous generation server module with super-linear scalability to 16 nodes for the 9-Point Stencil used in this Reverse Time Migration computational kernel.

  • The balanced combination of Oracle's Sun Storage 7410 system over 10 GbE to the Sun Blade X6275 M2 server module cluster showed linear scalability for the total application throughput, including the I/O and MPI communication, to produce a final 3-D seismic depth imaged cube for interpretation.

  • The final image write time from the Sun Blade X6275 M2 server module nodes to Oracle's Sun Storage 7410 system achieved 10GbE line speed of 1.25 GBytes/second or better write performance. The effects of I/O buffer caching on the Sun Blade X6275 M2 server module nodes and 34 GByte write optimized cache on the Sun Storage 7410 system gave up to 1.8 GBytes/second effective write performance.

Performance Landscape

Server Generational Performance Improvements

Performance improvements for the Reverse Time Migration computational kernel using a Sun Blade X6275 M2 cluster are compared to the previous generation Sun Blade X6275 cluster. Hyper-threading was enabled for both configurations allowing 24 OpenMP threads for the Sun Blade X6275 M2 server module nodes and 16 for the Sun Blade X6275 server module nodes.

Sun Blade X6275 M2 Performance Improvements
Number Nodes Grid Size - 1243 x 1151 x 1231 Grid Size - 2486 x 1151 x1231
X6275 Kernel Time (sec) X6275 M2 Kernel Time (sec) X6275 M2 Speedup X6275 Kernel Time (sec) X6275 M2 Kernel Time (sec) X6275 M2 Speedup
16 306 242 1.3 728 576 1.3
14 355 271 1.3 814 679 1.2
12 435 346 1.3 945 797 1.2
10 541 390 1.4 1156 890 1.3
8 726 555 1.3 1511 1193 1.3

Application Scaling

Performance and scaling results of the total application, including I/O, for the reverse time migration demonstration application are presented. Results were obtained using a Sun Blade X6275 M2 server cluster with a Sun Storage 7410 system for the file server. The servers were running with hyperthreading enabled, allowing for 24 OpenMP threads per server node.

Application Scaling Across Multiple Nodes
Number Nodes Grid Size - 1243 x 1151 x 1231 Grid Size - 2486 x 1151 x1231
Total Time (sec) Kernel Time (sec) Total Speedup Kernel Speedup Total Time (sec) Kernel Time (sec) Total Speedup Kernel Speedup
16 501 242 2.1\* 2.3\* 1060 576 2.0 2.1\*
14 583 271 1.8 2.0 1219 679 1.7 1.8
12 681 346 1.6 1.6 1420 797 1.5 1.5
10 807 390 1.3 1.4 1688 890 1.2 1.3
8 1058 555 1.0 1.0 2085 1193 1.0 1.0

\* Super-linear scaling due to the compute kernel fitting better into available cache for larger node counts

Image File Effective Write Performance

The performance for writing the final 3D image from a Sun Blade X6275 M2 server cluster over 10 Gigabit Ethernet to a Sun Storage 7410 system are presented. Each server allocated one core per node for MPI I/O thus allowing 22 OpenMP compute threads per node with hyperthreading enabled. Captured performance analytics from the Sun Storage 7410 system indicate effective use of its 34 Gigabyte write optimized cache.

Image File Effective Write Performance
Number Nodes Grid Size - 1243 x 1151 x 1231 Grid Size - 2486 x 1151 x1231
Write Time (sec) Write Performance (GB/sec) Write Time (sec) Write Performance (GB/sec)
16 4.8 1.5 10.2 1.4
14 5.0 1.4 10.2 1.4
12 4.0 1.8 11.3 1.3
10 4.3 1.6 9.1 1.6
8 4.6 1.5 9.7 1.5

Note: Performance results better than 1.3GB/sec related to I/O buffer caching on server nodes.

Configuration Summary

Hardware Configuration:

8 x 2 node Sun Blade X6275 M2 server nodes, each node with
2 x 2.93 GHz Intel Xeon X5670 processors
48 GB memory (12 x 4 GB at 1333 MHz)
1 x QDR InfiniBand Host Channel Adapter

Sun Datacenter InfiniBand Switch IB-36
Sun Network 10 GbE Switch 72p

Sun Storage 7410 system connected via 10 Gigabit Ethernet
4 x 17 GB STEC ZeusIOPs SSD mirrored - 34 GB
40 x 750 GB 7500 RPM Seagate SATA disks mirrored - 14.4 TB
No L2ARC Readzilla Cache

Software Configuration:

Oracle Enterprise Linux Server release 5.5
Oracle Message Passing Toolkit 8.2.1c (for MPI)
Oracle Solaris Studio 12.2 C++, Fortran, OpenMP

Benchmark Description

This Vertical Transverse Isotropy (VTI) Anisotropic Reverse Time Depth Migration (RTM) application measures the total time it takes to image 800 samples of various production size grids and write the final image to disk for the next work flow step involving 3-D seismic volume interpretation. In doing so, it reports the compute, interprocessor communication, and I/O performance of the individual functions that comprise the total solution. Unlike most references for the Reverse Time Migration, that focus solely on the performance of the 3D stencil compute kernel, this demonstration code additionally reports the total throughput involved in processing large data sets with a full 3D Anisotropic RTM application. It provides valuable insight into configuration and sizing for specific seismic processing requirements. The performance effects of new processors, interconnects, I/O subsystems, and software technologies can be evaluated while solving a real Exploration business problem.

This benchmark study uses the "in-core" implementation of this demonstration code where each node reads in only the trace, velocity, and conditioning data to be processed by that node plus a 4 element array pad (based on spatial order 8) shared with it's neighbors to the left and right during the initialization phase. It maintains previous, current, and next wavefield state information for each of the source, receiver, and anisotropic wavefields in memory. The second two grid dimensions used in this benchmark are specifically chosen to be prime numbers to exaggerate the effects of data alignment. Algorithm adaptions for processing higher orders in space and alternative "out-of-core" solutions using SSDs for wave state checkpointing are implemented in this demonstration application to better understand the effects of problem size scaling. Care is taken to handle absorption boundary conditioning and a variety of imaging conditions, appropriately.

RTM Application Structure:

Read Processing Parameter File, Determine Domain Decomposition, and Initialize Data Structures, and Allocate Memory.

Read Velocity, Epsilon, and Delta Data Based on Domain Decomposition and create source, receiver, & anisotropic previous, current, and next wave states.

First Loop over Time Steps

Compute 3D Stencil for Source Wavefield (a,s) - 8th order in space, 2nd order in time
Propagate over Time to Create s(t,z,y,x) & a(t,z,y,x)
Inject Estimated Source Wavelet
Apply Absorption Boundary Conditioning (a)
Update Wavefield States and Pointers
Write Snapshot of Wavefield (out-of-core) or Push Wavefield onto Stack (in-core)
Communicate Boundary Information

Second Loop over Time Steps
Compute 3D Stencil for Receiver Wavefield (a,r) - 8th order in space, 2nd order in time
Propagate over Time to Create r(t,z,y,x) & a(t,z,y,x)
Read Receiver Trace and Inject Receiver Wavelet
Apply Absorption Boundary Conditioning (a)
Update Wavefield States and Pointers
Communicate Boundary Information
Read in Source Wavefield Snapshot (out-of-core) or Pop Off of Stack (in-core)
Cross-correlate Source and Receiver Wavefields
Update image using image conditioning parameters

Write 3D Depth Image i(z,x,y) = Sum over time steps s(t,z,x,y) \* r(t,z,x,y) or other imaging conditions.

Key Points and Best Practices

This demonstration application represents a full Reverse Time Migration solution. Many references to the RTM application tend to focus on the compute kernel and ignore the complexity that the input, communication, and output bring to the task.

Image File MPI Write Performance Tuning

Changing the Image File Write from MPI non-blocking to MPI blocking and setting Oracle Message Passing Toolkit MPI environment variables revealed an 18x improvement in write performance to the Sun Storage 7410 system going from:

    86.8 to 4.8 seconds for the 1243 x 1151 x 1231 grid size
    183.1 to 10.2 seconds for the 2486 x 1151 x 1231 grid size

The Swat Sun Storage 7410 analytics data capture indicated an initial write performance of about 100 MB/sec with the MPI non-blocking implementation. After modifying to MPI blocking writes, Swat showed between 1.3 and 1.8 GB/sec with up to 13000 write ops/sec to write the final output image. The Swat results are consistent with the actual measured performance and provide valuable insight into the Reverse Time Migration application I/O performance.

The reason for this vast improvement has to do with whether the MPI file mode is sequential or not (MPI_MODE_SEQUENTIAL, O_SYNC, O_DSYNC). The MPI non-blocking routines, MPI_File_iwrite_at and MPI_wait, typically used for overlapping I/O and computation, do not support sequential file access mode. Therefore, the application could not take full performance advantages of the Sun Storage 7410 system write optimized cache. In contrast, the MPI blocking routine, MPI_File_write_at, defaults to MPI sequential mode and the performance advantages of the write optimized cache are realized. Since writing the final image is at the end of RTM execution, there is no need to overlap the I/O with computation.

Additional MPI parameters used:

    setenv SUNW_MP_PROCBIND true
    setenv MPI_SPIN 1
    setenv MPI_PROC_BIND 1

Adjusting the Level of Multithreading for Performance

The level of multithreading (8, 10, 12, 22, or 24) for various components of the RTM should be adjustable based on the type of computation taking place. Best to use OpenMP num_threads clause to adjust the level of multi-threading for each particular work task. Use numactl to specify how the threads are allocated to cores in accordance to the OpenMP parallelism level.

See Also

Disclosure Statement

Copyright 2010, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 12/07/2010.

Sun Blade X6275 M2 Delivers Best Fluent (MCAE Application) Performance on Tested Configurations

This Manufacturing Engineering benchmark highlights the performance advantage the Sun Blade X6275 M2 server module offers over IBM, Cray, and SGI solutions as shown by the ANSYS FLUENT fluid dynamics application.

A cluster of eight of Oracle's Sun Blade X6275 M2 server modules delivered outstanding performance running the FLUENT 12 benchmark test suite.

  • The Sun Blade X6275 M2 server module cluster delivered the best results in all 36 of the test configurations run, outperforming the best posted results by as much as 42%.
  • The Sun Blade X6275 M2 server module demonstrated up to 76% performance improvement over the previous generation Sun Blade X6275 server module.

Performance Landscape

In the following tables, results are "Ratings" (bigger is better).
Rating = No. of sequential runs of test case possible in 1 day: 86,400/(Total Elapsed Run Time in Seconds)

The following table compares results on the basis of core count, irrespective of processor generation. This means that in some cases, i.e., for the 32-core and 64-core configurations, systems with the Intel Xeon X5670 six-core processors did not utilize quite all of the cores available for the specified processor count.


FLUENT 12 Benchmark Test Suite

Competitive Comparisons

System
Processors Cores Benchmark Test Case Ratings
eddy
417k
turbo
500k
aircraft
2m
sedan
4m
truck
14m
truck_poly
14m

Sun Blade X6275 M2 16 96 9340.5 39272.7 8307.7 8533.3 903.8 786.9
Best Posted 24 96

7562.4
797.0 712.9
Best Posted 16 96 7337.6 33553.4 6533.1 5989.6 739.1 683.5

Sun Blade X6275 M2 11 64 6306.6 27212.6 5592.2 5158.2 568.8 518.9
Best Posted 16 64 5556.3 26381.7 5494.4 4902.1 566.6 518.6

Sun Blade X6275 M2 8 48 4620.3 19093.9 4080.3 3251.2 376.0 359.4
Best Posted 8 48 4494.1 18989.0 3990.8 3185.3 372.7 354.5

Sun Blade X6275 M2 6 32 4061.1 15091.7 3275.8 3013.1 299.5 267.8
Best Posted 8 32 3404.9 14832.6 3211.9 2630.1 286.7 266.7

Sun Blade X6275 M2 4 24 2751.6 10441.1 2161.4 1907.3 188.2 182.5
Best Posted 6 24 1458.2 9626.7 1820.9 1747.2 185.1 180.8
Best Posted 4 24 2565.7 10164.7 2109.9 1608.2 187.1 180.8

Sun Blade X6275 M2 2 12 1429.9 5358.1 1097.5 813.2 95.9 95.9
Best Posted 2 12 1338.0 5308.8 1073.3 808.6 92.9 94.4



The following table compares results on the basis of processor count showing inter-generational processor performance improvement.


FLUENT 12 Benchmark Test Suite

Intergenerational Comparisons

System
Processors Cores Benchmark Test Case Ratings
eddy
417k
turbo
500k
aircraft
2m
sedan
4m
truck
14m
truck_poly
14m

Sun Blade X6275 M2 16 96 9340.5 39272.7 8307.7 8533.3 903.8 786.9
Sun Blade X6275 16 64 5308.8 26790.7 5574.2 5074.9 547.2 525.2
X6275 M2 : X6275 16
1.76 1.47 1.49 1.68 1.65 1.50

Sun Blade X6275 M2 8 48 4620.3 19093.9 4080.3 3251.2 376.0 359.4
Sun Blade X6275 8 32 3066.5 13768.9 3066.5 2602.4 289.0 270.3
X6275 M2 : X6275 8
1.51 1.39 1.33 1.25 1.30 1.33

Sun Blade X6275 M2 4 24 2751.6 10441.1 2161.4 1907.3 188.2 182.5
Sun Blade X6275 4 16 1714.3 7545.9 1519.1 1345.8 144.4 141.8
X6275 M2 : X6275 4
1.61 1.38 1.42 1.42 1.30 1.29

Sun Blade X6275 M2 2 12 1429.9 5358.1 1097.5 813.2 95.9 95.9
Sun Blade X6275 2 8 931.8 4061.1 827.2 681.5 73.0 73.8
X6275 M2 : X6275 2
1.53 1.32 1.33 1.19 1.31 1.30

Configuration Summary

Hardware Configuration:

8 x Sun Blade X6275 M2 server modules, each with
4 Intel Xeon X5670 2.93 GHz processors, turbo enabled
96 GB memory 1333 MHz
2 x 24 GB SATA-based Sun Flash Modules
2 x QDR InfiniBand Host Channel Adapter
Sun Datacenter InfiniBand Switch IB-36

Software Configuration:

Oracle Enterprise Linux Enterprise Server 5.5
ANSYS FLUENT V12.1.2
ANSYS FLUENT Benchmark Test Suite

Benchmark Description

The following description is from the ANSYS FLUENT website:

The FLUENT benchmarks suite comprises of a set of test cases covering a large range of mesh sizes, physical models and solvers representing typical industry usage. The cases range in size from a few 100 thousand cells to more than 100 million cells. Both the segregated and coupled implicit solvers are included, as well as hexahedral, mixed and polyhedral cell cases. This broad coverage is expected to demonstrate the breadth of FLUENT performance on a variety of hardware platforms and test cases.

The performance of a CFD code will depend on several factors, including size and topology of the mesh, physical models, numerics and parallelization, compilers and optimization, in addition to performance characteristics of the hardware where the simulation is performed. The principal objective of this benchmark suite is to provide comprehensive and fair comparative information of the performance of FLUENT on available hardware platforms.

About the ANSYS FLUENT 12 Benchmark Test Suite

    CFD models tend to be very large where grid refinement is required to capture with accuracy conditions in the boundary layer region adjacent to the body over which flow is occurring. Fine grids are required to also determine accurate turbulence conditions. As such these models can run for many hours or even days as well using a large number of processors.

Key Points and Best Practices

  • ANSYS FLUENT has not yet been certified by the vendor on Oracle Enterprise Linux (OEL). However, the ANSYS FLUENT benchmark tests have been run successfully on Oracle hardware running OEL as is (i.e. with NO changes or modifications).
  • The performance improvement of the Sun Blade X6275 M2 server module over the previous generation Sun Blade X6275 server module was due to two main factors: the increased core count per processor (6 vs. 4), and the more optimal, iterative dataset partitioning scheme used for the Sun Blade X6275 M2 server module.

See Also

Disclosure Statement

All information on the FLUENT website (http://www.fluent.com) is Copyrighted 1995-2010 by ANSYS Inc. Results as of December 06, 2010.
About

BestPerf is the source of Oracle performance expertise. In this blog, Oracle's Strategic Applications Engineering group explores Oracle's performance results and shares best practices learned from working on Enterprise-wide Applications.

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