Performance exploration of various C/C++ compilers for AMD EPYC processors in numerical modeling of solidification

Halbiniak, Kamil; Wyrzykowski, Roman; Szustak, Łukasz; Kulawik, Adam; Meyer, Norbert; Gepner, Paweł

doi:10.1016/j.advengsoft.2021.103078

Cited by 7 publications

(2 citation statements)

References 19 publications

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“…The achieved results show that V100 GPU accelerates the simulation about 3.4 times against two Intel processors. Also, our work 25 presents the performance of the studied application on the platform with two AMD EPYC Rome 7742 CPUs (Zen 2 architecture with 64 cores per CPU). The execution times achieved in this work show that using V100 and A100 GPUs permits speeding the computations up to 1.53 and 3.25 times against two AMD processors.…”

Section: Performance Evaluation For Nvidia‐based Platformsmentioning

confidence: 99%

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Single‐ and multi‐GPU computing on NVIDIA‐ and AMD‐based server platforms for solidification modeling application

Halbiniak,

Meyer,

Rojek

2023

Concurrency and Computation

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SummaryThis work explores the performance of single‐ and multi‐GPU computing on state‐of‐the‐art NVIDIA‐ and AMD‐based server‐class hardware using various programming interfaces to accelerate a real‐world scientific application for solidification modeling based on the phase‐field method. The main computations of this memory‐bound application correspond to 20 stencils computed across grid nodes. We investigate the application's scalability for two basic schemes of organizing computation: without and with hiding data transfers behind computation, combined with using either peer‐to‐peer inter‐GPU data transfers through NVIDIA NVLink and AMD Infinity interconnects or communication over the PCIe and main memory. Among the studied programming interfaces is CUDA, HIP, and OpenMP Accelerator Model. While the first two are designed to write the codes for a specific hardware platform, OpenMP enables code portability between NVIDIA and AMD GPUs. The resulting performance is experimentally assessed on computing platforms containing NVIDIA V100 (up to 8 GPUs) and A100 (one GPU), as well as AMD MI210 (one device) and MI250 (up to 8 logical GPUs).

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Section: Performance Evaluation For Nvidia‐based Platformsmentioning

confidence: 99%

“…Following our previous works, [22][23][24][25] the real-life scientific application used as a testbed in our study is the numerical modeling of alloy solidification. The model is based on the phase-field method 26 with the generalized finite difference method (FDM) and explicit scheme of calculations.…”

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confidence: 99%