期刊
INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS
卷 33, 期 4, 页码 735-757出版社
SAGE PUBLICATIONS LTD
DOI: 10.1177/1094342018816368
关键词
Finite element method; elliptic problem; hexahedral elements; matrix-vector product; GPU tensor operations; NVIDIA Tesla P100
类别
资金
- Exascale Computing Project, US Department of Energy organization (Office of Science) [17-SC-20-SC]
- Exascale Computing Project, US Department of Energy organization (National Nuclear Security Administration) [17-SC-20-SC]
This article is devoted to graphics processing unit (GPU) kernel optimization and performance analysis of three tensor-product operations arising in finite element methods. We provide a mathematical background to these operations and implementation details. Achieving close to peak performance for these operators requires extensive optimization because of the operators' properties: low arithmetic intensity, tiered structure, and the need to store intermediate results during the kernel execution. We give a guided overview of optimization strategies and we present a performance model that allows us to compare the efficacy of these optimizations against an empirically calibrated roofline.
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