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ConvStencil: Transform Stencil Computation to Matrix Multiplication on Tensor Cores

Yuetao Chen, Kun Li, Yuhao Wang, Donglin Bai, Lei Wang, Lingxiao Ma, Liang Yuan, Yunquan Zhang, Ting Cao, Mao Yang

2024Year
25Citations
9Top-tier citations

Abstract

Tensor Core Unit (TCU) is increasingly integrated into modern high-performance processors to enhance matrix multiplication performance. However, constrained to its overspecification, its potential for improving other critical scientific operations like stencil computations remains untapped.

This paper presents ConvStencil 1 , a novel stencil computing system designed to efficiently transform stencil computation to matrix multiplication on Tensor Cores. We first develop a performance model for ConvStencil to guide algorithm design and optimization on TCUs. Based on this model, we propose three techniques: (1) Memory-efficient Layout Transformation using the stencil2row method; (2) * Work done during an internship at Microsoft Research.

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