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Octane Rendering Benchmarks of NVIDIA A100 and V100 GPU shapes on Oracle Cloud

Karthi Subramaniam
Master Principal Cloud Architect

Oracle Cloud Infrastructure (OCI) offers different GPU shapes for different types of workloads. Choosing the right shapes for the right workloads saves direct infrastructure-related costs and the indirect labor productivity and time-to-market costs in 3D modeling and rendering. Performing standard benchmark tests are a great way to understand the performance differences between GPUs and server configurations. Before we look into benchmark comparison of GPUs, review the quick start guide to set up GPU workstations in Oracle Cloud.

One of the popular benchmarking tools for rendering using GPU is OctaneBench. It allows you to benchmark your GPU using OctaneRender. It tests the same version, the same scenes, and settings across the GPUs to ensure a fair comparison. You can find publicly published results of various GPUs on OctaneBench’s site.

Benchmarking OCI with OctaneBench

We compare the following OCI GPU shapes rendering different 3D models as part of OctaneBench benchmarking:

  • A VM shape with four of V100 GPUs running Windows 2016 Server running OctaneBench Version 4.0

  • A bare metal shape with eight of A100 GPUs running Ubuntu 20 LTS running OctaneBench Version 2020.1.5

We use four different models in this OctaneBench Benchmark in both GPU types. The following graphics show some sample models and their rendered versions:

A screenshot of unrendered models in OctaneBench.

A screenshot of rendered models in OctaneBench.

Some models involve complex lighting and composition, including the following example:

A screenshot of a rendered model with complex lighting.

OctaneBench produced the following results on the V100 GPU shape:

A screenshot of the results of the V100 test.

OctaneBench produced the following results on A100:

The following screenshot shows the output of “nvidia-smi” CLI while OctaneBench is running. All GPUs are running closer to 100%.

A screenshot of the output of the NVIDIA smi CLI.

The following charts show more detailed comparisons.

  A100 V100
Scene Kernel Ms/s GTX980 Ms/s Ratio Score Ms/s GTX980 Ms/s Ratio Score
Interior (by Julia Lynen) Info channels 2406.575448 51.52 46.711 116.7787 866.835291 51.52 16.825 42.063048
Interior (by Julia Lynen) Direct lighting 786.999573 17.8 44.213 442.134592 301.828121 17.8 16.957 169.56636
Interior (by Julia Lynen) Path tracing 370.090978 8.54 43.336 541.702251 135.803053 8.54 15.902 198.774961
Idea (by Julio Cayetaño) Info channels 2185.555242 85.99 25.416 63.540971 992.86314 85.99 11.546 28.865657
Idea (by Julio Cayetaño) Direct lighting 770.396538 21.05 36.598 365.984104 285.22701 21.05 13.55 135.499767
Idea (by Julio Cayetaño) Path tracing 688.094549 19.38 35.505 443.817434 256.221166 19.38 13.221 165.26133
ATV (by Jürgen Aleksejev) Info channels 1623.244713 31.39 51.712 129.280401 575.44937 31.39 18.332 45.830628
ATV (by Jürgen Aleksejev) Direct lighting 630.777566 15.21 41.471 414.712404 218.859478 15.21 14.389 143.891833
ATV (by Jürgen Aleksejev) Path tracing 542.004713 12.92 41.951 524.385365 184.506869 12.92 14.281 178.508968
Box (by Enrico Cerica) Info channels 2394.771736 65.75 36.422 91.05596 1006.106289 65.75 15.302 38.254992
Box (by Enrico Cerica) Direct lighting 532.508886 13.84 38.476 384.760756 192.387149 13.84 13.901 139.008056
Box (by Enrico Cerica) ]Path tracing 521.309758 13.45 38.759 484.488623 197.256713 13.45 14.666 183.324083
  A100 (8 GPUs) V100 (4 GPUs)
Total score 4002.641560 1468.849682

The scores shown in the previous image are for the whole servers with two different counts of GPUs. To compare the single GPU performance, divide the overall server-level score by the number of GPUs.

This graph shows the single GPU score for A100 GPU, 500.25, and V100 GPU, 367. It aligns with the other published results on the OctaneBench website.

A bar graph comparing the single GPU OctaneBench scores of A100 and V100.

Learn more

You can find all the GPU shapes available at Oracle Cloud GPU Offerings.

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