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“Heterochromic” Computer and Finding the Optimal System Configuration for Medical Device Engineering

Designing a computing system configuration for optimal performance of a given task is always challenging, especially if the acquisition budget is fixed. It is difficult, if not impossible, to analytically resolve all of the following questions:

  • How well does the application scale across multiple cores?
  • What is the efficiency and scalability of the application with accelerators (GPGPUs or coprocessors)?
  • Should measures be taken to prevent I/O bottlenecks?
  • Is it more efficient to scale up a single task or partition the system for multiple tasks?
  • What combination of CPU models, accelerator count, and per-core software licenses gives the best return on investment?

Rigorous benchmarking is the most reliable method of ensuring the “best bang for buck”, however, it requires access to the computing systems of interest. Colfax takes pride in being able to offer interested customers opportunities for deducing the optimal configuration for specific tasks.

Recently we received a request from Peter Newman, Systems Engineer at Carestream Health, for evaluating the performance of the software tool ANSYS Mechanical on Colfax’s computing solutions. His goal was to find the optimum number of computing accelerators (if any) and software licenses that he needed to purchase in order to achieve the best performance of specific calculations in ANSYS.

In order to allow Mr. Newman to seamlessly benchmark a variety of system configurations, we provided him access to a unique machine built by Colfax, based on an Intel Xeon E5 CPU, and supporting four Nvidia Tesla K40 GPGPUs and four Intel Xeon Phi 7120P coprocessors. Normally, this system is built either with eight GPGPUs as CXT9000, or outfitted with eight Xeon Phi coprocessors as CXP9000. However, the “heterochromic” (i.e., featuring both Nvidia’s and Intel’s accelerators) configuration that we produced for this project allowed the customer to benchmark the ANSYS software on both the Nividia Tesla and Intel Xeon Phi platforms with minimal logistic effort. Indeed, the software had to be installed only once, and the benchmark scripts and data collection scripts could all be retained in one place.

The methodology of the study was developed by Peter Newman, who also executed the benchmarks, collected and analyzed the data, and summarized findings in a comprehensive report. Mr. Jason Zbick of SimuTech Group, an ANSYS distributor, participated in the study and provided support for ANSYS Mechanical installation and configuration. Colfax’s involvement included custom system configuration, maintenance of secure remote access to the system and assistance with automated result collection.

The result of the testing, pertinent to the current state of the software and the specific models used in Carestream, allowed Mr. Newman to empirically find the best way to spend the funds allocated for improvement of his computing infrastructure. His feedback was,
“This study greatly changed my plan for what to purchase with the budget I had to work with… Having all the hardware at once made the testing very efficient. That was the best part. ”

The customer has generously shared with us the report on his thorough research. The report can be downloaded below.

Report:  Carestream_HPC_Study-December2013.pdf (4 MB)