GPU Clusters in 10 Minutes

Earlier this week Clay Magouyrk sent me a pointer to some very interesting work: A Couple More Nails in the Coffin of the Private Compute Cluster: Benchmarks for the Brand New Cluster GPU Instance on Amazon EC2.

This detailed article has detailed benchmark results from runs on the new Cluster GPU Instance type and leads in with:

During the past few years it has been no secret that EC2 has been best cloud provider for massive scale, but loosely connected scientific computing environments. Thankfully, many workflows we have encountered have performed well within the EC2 boundaries. Specifically, those that take advantage of pleasantly parallel, high-throughput computing workflows. Still, the AWS approach to virtualization and available hardware has made it difficult to run workloads which required high bandwidth or low latency communication within a collection of distinct worker nodes. Many of the AWS machines used CPU technology that, while respectable, was not up to par with the current generation of chip architectures. The result? Certain use cases simply were not a good fit for EC2 and were easily beaten by in-house clusters in benchmarking that we conducted within the course of our research. All of that changed when Amazon released their Cluster Compute offering.

The author goes on to run the Saleable Heterogeneous cOmputing BenChmarking Suite and compare EC2 with Native performance and conclude:

With this new AWS offering, the line between internal hardware and virtualized, cloud-based hardware for high performance computing using GPUs has indeed been blurred.

Finally a run with a Cycle Computing customer workload:

Based on the positive results of our SHOC benchmarking, we approached a Fortune 500 Life Science and a Finance/Insurance clients who develop and use their own GPU-accelerated software, to run their applications on the GPU-enabled Cluster Compute nodes. For both applications, the applications perform a large number of Monte Carlo simulations for given set of initial data, all pleasantly parallel. The results, similar to the SHOC result, were that the EC2 GPU-enabled Cluster Compute nodes performed as well as, or better than, the in-house hardware maintained by our clients.

Even if you only have a second, give the results a scan: http://blog.cyclecomputing.com/2010/11/a-couple-more-nails-in-the-coffin-of-the-private-compute-cluster-gpu-on-cloud.html.

–jrh

James Hamilton

e: jrh@mvdirona.com

w: http://www.mvdirona.com

b: http://blog.mvdirona.com / http://perspectives.mvdirona.com

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