MMStencil: Optimizing High-order Stencils on Multicore CPU using Matrix Unit Article Swipe

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Yinuo Wang , Mao Tian-qi , Lin Gan , Wubing Wan , Zeyu Song , Jiayu Fu , Ling He , Wenqiang Wang , Zhiya Yin , Wei Xue , Guangwen Yang ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2507.11067

Matrix-accelerated stencil computation is a hot research topic, yet its application to three-dimensional (3D) high-order stencils and HPC remains underexplored. With the emergence of matrix units on multicore CPUs, we analyze matrix-based acceleration strategies and tailor an optimal approach for 3D high-order stencils. We introduce algorithmic optimizations based on SIMD and matrix units to address strided memory accesses, alignment conflicts, and redundant accesses. We propose memory optimizations to boost on-package memory efficiency, and a novel multi-thread parallelism paradigm to overcome data-sharing challenges caused by the absence of shared data caches. MMStencil sustains consistently high hardware utilization across diverse stencil shapes and dimensions. Our DMA-based inter-NUMA communication further mitigates NUMA effects and MPI limitations in hybrid parallelism. Combining all the innovations, MMStencil outperforms state-of-the-art libraries on Nvidia A100 GPGPU by up to 2.1x. Moreover, the performance improvements translate directly to real-world HPC applications and enable RTM applications to yield 1.8x speedup versus a highly optimized industrial Nvidia A100 GPGPU version.

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2507.11067
PDF: https://arxiv.org/pdf/2507.11067
OA Status: green
OpenAlex ID: https://openalex.org/W4414944741

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OpenAlex ID: https://openalex.org/W4414944741

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DOI: https://doi.org/10.48550/arxiv.2507.11067

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Title: MMStencil: Optimizing High-order Stencils on Multicore CPU using Matrix Unit

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Type: preprint

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Language: en

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Publication year: 2025

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Publication date: 2025-07-15

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Authors: Yinuo Wang, Mao Tian-qi, Lin Gan, Wubing Wan, Zeyu Song, Jiayu Fu, Ling He, Wenqiang Wang, Zhiya Yin, Wei Xue, Guangwen Yang

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Landing page: https://arxiv.org/abs/2507.11067

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PDF URL: https://arxiv.org/pdf/2507.11067

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OA status: green

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Cited by: 0

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