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A comparative investigation of device-specific mechanisms for exploiting HPC accelerators
Tarakji A., Börger L., Leupers R.  GPGPU 2015 (Proceedings of the 8th Workshop on General Purpose Processing Using GPUs, San Francisco, CA, Feb 7, 2015)1-12,2015.Type:Proceedings
Date Reviewed: 04/10/15

The performance of different high-performance computing (HPC) accelerator/coprocessor devices is evaluated and compared in this well-written paper. It analyzes the behavior of Xeon Phi, NVIDIA K20c, and AMD FirePro S9000 using an open computing language (OpenCL) framework. In order to have a fine-grain evaluation, the authors propose and develop FeatureBench, a benchmark test suite. The comparison considers only a single accelerator configuration, however.

Even though I agree with the authors on the fact that OpenCL is a portable framework and probably the best fit for this evaluation, it does not offer the productivity feature for hybrid message passing interface (MPI+X) models in HPC systems such as CUDA-aware MPI and OpenACC-aware MPI. I wish this aspect had been addressed in the discussion and comparison. Also, it is not clear how the comparison between hardware-accelerated and non-hardware-accelerated transcendental operations is performed. Is it through different benchmarks/application programming interface (API) calls or compiler options? Finally, what about the memory bandwidth and behavior? An analysis and comparison of the memory bandwidth and cache effects would have been a welcome contribution.

Reviewer:  Khaled Hamidouche Review #: CR143333 (1507-0582)

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