Low-Order Finite Element Solver with Small Matrix-Matrix Multiplication Accelerated by AI-Specific Hardware for Crustal Deformation Computation

Low-Order Finite Element Solver with Small Matrix-Matrix Multiplication Accelerated by AI-Specific Hardware for Crustal Deformation Computation
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具有小矩阵-矩阵乘法的低阶有限元求解器,由 AI 专用硬件加速,用于地壳变形计算

DOI:
10.1145/3394277.3401860
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发表时间:
2020
期刊:
Proceedings of the Platform for Advanced Scientific Computing Conference
影响因子:
--
通讯作者:
Ueda Naonori
Ueda Naonori
中科院分区:
--
文献类型:
--
作者:
Yamaguchi Takuma;Fujita Kohei;Ichimura Tsuyoshi;Naruse Akira;Wells Jack C.;Zimmer Christopher J.;Straatsma Tjerk P.;Hori Muneo;Maddegedara Lalith;Ueda Naonori

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本研究通过在Volta GPU上应用Tensor Core (ai专用硬件),提出了一种用于地壳变形计算的快速低阶有限元求解器。张量核心能够以半精度快速计算大矩阵-矩阵乘法。我们重新设计了最先进的求解器算法,以便可以使用低精度的数据类型,并且即使在使用小矩阵时也可以降低内存访问成本。利用Summit的36个计算节点,求解了模拟地壳和地幔的130亿个自由度双层问题。在矩阵-向量内核中,我们在单精度格式下获得了比标准内核快4.1倍的加速。我们提出的求解器增加了整个求解器的FLOP计数;然而,由于Tensor Core提供了高效的性能,我们将求解时间缩短了1.7倍。
This study proposes a fast low-order finite element solver for crustal deformation computations by applying Tensor Core, AI-specific hardware on a Volta GPU. Tensor Core can compute large matrix-matrix multiplications rapidly in half precision. We redesign a state-of-the-art solver algorithm so that lower-precision data types can be used and memory access costs can be reduced even when we use small matrices. With the proposed solver, we solved 13 billion degrees-of-freedom two-layered problems that mimicked the Earth's crust and mantle using 36 compute nodes of Summit. In the matrix-vector kernel, we obtained a 4.1-fold speedup over a standard kernel in a single-precision format. Our proposed solver increased the FLOP count of the entire solver; however, we reduced the time-to-solution by 1.7-fold since the Tensor Core provided a high effective performance.
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