Evaluating the Performance of the hipSYCL Toolchain for HPC Kernels on NVIDIA V100 GPUs
| Autor: | Brian Homerding, John R. Tramm |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
020209 energy Suite Symmetric multiprocessor system 02 engineering and technology Parallel computing Software_PROGRAMMINGTECHNIQUES Supercomputer 01 natural sciences Toolchain 010305 fluids & plasmas Domain (software engineering) Software portability CUDA 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Programming paradigm |
| Zdroj: | IWOCL |
| Popis: | Future HPC leadership computing systems for the United States Department of Energy will utilize GPUs for acceleration of scientific codes. These systems will utilize GPUs from various vendors which places a large focus on the performance portability of the programming models used by scientific application developers. In the HPC domain, SYCL is an open C++ standard for heterogeneous computing that is gaining support. This is fueling a growing interest in understanding the performance of SYCL toolchains for the various GPU vendors.In this paper, we compare the performance of benchmarks and mini-apps having both SYCL and native CUDA implementations on an NVIDIA Volta GPU. We utilize the RAJA Performance Suite to evaluate the performance of the hipSYCL toolchain, followed by a more detailed investigation of the performance of two HPC mini-apps. We find that the kernel performance from the SYCL kernels compiled directly to CUDA perform at a competitive level with their CUDA counterparts when comparing the straightforward implementations. |
| Databáze: | OpenAIRE |
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