High-performance computing (HPC) refers to the practice of combining computing power to deliver much higher horsepower than traditional computers and servers. In the world of auto racing, finding even the smallest competitive advantage is the difference between winning and losing, which is why teams are using HPC workloads like Monte Carlo simulations to get ahead of the competition. Instead of tediously going through each possible scenario, race strategists use probability distribution, a set of values reflecting the relative odds of any given event taking place. They then use this set of values at random and combine the result with random values taken from all the other probability distributions. After repeating this millions of times, the result is a realistic simulation of the race and the strategy giving the best odds of winning.

With Oracle Cloud Infrastructure (OCI)’s leading price-performance, low-latency network, broad range of the latest and greatest Compute shapes, and much more, OCI is the best place to get simulation results faster than ever to help you win. Compared to Amazon Web Services (AWS), OCI delivers more than three times better price-performance for compute while being 44% less expensive.

Don’t believe me? Maybe this Formula 1 team can change your mind by showing you how they modernized their motor sport race strategy with OCI.

Store data for Monte Carlo simulations on Autonomous Database Dedicated

Not only does OCI have the compute and networking to support these simulations, but it has an entire ecosystem to help elevate and expand it. For these Monte Carlo simulations to be as successful as they are, they need a database that can read and write data at high rates to keep up with the millions of data points generated at a single race. Here, Autonomous Database Dedicated comes in. Autonomous Database Dedicated is a private database cloud in the public cloud, a fully automated database built on Exadata Cloud Infrastructure, and a foundation of machine learning that delivers the highest performance, availability, and security for all workloads regardless of complexity, scale, or criticality.

With Autonomous Database Dedicated, you get an entire Exadata Cloud Infrastructure to yourself, 100% of those resources dedicated to your workloads, so you have no noisy neighbors to compete with. Plus, Exadata provides some of the highest IOPS across the industry so you know that Autonomous Database Dedicated can handle all the data in these simulations at the speed you want. Not only does it have a high throughput, but it can also support petabytes of data, so you don’t have to worry about running out of storage. So, no matter what size you start with, with online server expansion and support for the largest workloads, Exadata Cloud Infrastructure helps you maximize business agility and operational flexibility as workload requirements grow. Now, with the latest generation of Exadata platform, X9M, the world’s fastest cloud database platform is faster than ever.

Unlike other cloud providers that provide different databases for different workloads, you only need a single database because Autonomous Database Dedicated is a converged database that does everything for you. Autonomous Database’s converged engine supports diverse data types, simplifying application development and deployment from modeling and coding to extract, transform, load (ETL), database optimization, and data analysis.

You get everything: High IOPS, large storage capacity, converged database, all on top of the amazing benefits of Autonomous Database. So, say goodbye to administrative headache and hello to the stuff you want to do. Focus on your Monte Carlo simulations and leave all the plumbing to Oracle.

Get started with your Monte Carlo simulation

Now that we’ve talked about the reasons to run Monte Carlo simulations on OCI, let’s see what that looks like with a reference architecture, workflow steps, and further resources:

A graphic depicting the architecture for the example Monte Carlo simulation.

The workflow uses the following steps:

  1. Detect data that needs processing from Autonomous Database Dedicated or Object Storage. Autonomous Database Dedicated natively integrates with Object Storage so you can enable access data like it’s in a table in Autonomous Database Dedicated (External table) or partitioned table with hot partitions in Autonomous Database Dedicated and older partitions on Object Storage (Hybrid partitioned table). Learn more about this process in Oracle Autonomous Database on Dedicated Exadata Infrastructure.

  2. Initial data processing and Monte Carlo job submission

  3. Each experiment runs in a separate container.

  4. The aggregation of the results are pushed into post-processing,

  5. The results are pushed back to data storage.

  6. You can get further insight into your data by using Oracle Analytics Cloud (OAC).

Industries beyond motorsport use Monte Carlo simulations, such as financial services, where the market is always changing and you need to be ready for any outcome. This example of how to run it on OCI with containers uses financial services as its context but can easily transfer to any industry. Regardless of what you’re using Monte Carlo simulations for, OCI is the right choice for you.

Get started today

What are you waiting for? See first-hand how to run Monte Carlo Simulations on OCI. Get your 30-day free trial to access to a wide range of Oracle Cloud Infrastructure services, including the latest and greatest hardware from Ampere, Intel, AMD, and NVIDIA, and Autonomous Database Dedicated for all your database needs.