基于寄存器的稀疏一般矩阵-矩阵乘法在gpu上的实现

Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming Pub Date : 2018-02-10 DOI:10.1145/3178487.3178529

Junhong Liu, Xinchao He, Weifeng Liu, Guangming Tan

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引用次数: 13

摘要

一般稀疏矩阵-矩阵乘法(SpGEMM)是许多应用程序中必不可少的组成部分。在我们的工作中，与现有的实现相比，我们充分利用GPU寄存器和共享内存来实现高效和负载均衡的SpGEMM。

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General sparse matrix-matrix multiplication (SpGEMM) is an essential building block in a number of applications. In our work, we fully utilize GPU registers and shared memory to implement an efficient and load balanced SpGEMM in comparison with the existing implementations.

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Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming

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