Challenges and Advances in Parallel Sparse Matrix-Matrix Multiplication

Abstract

We identify the challenges that are special to parallel sparse matrix-matrix multiplication (PSpGEMM). We show that sparse algorithms are not as scalable as their dense counterparts, because in general, there are not enough non-trivial arithmetic operations to hide the communication costs as well as the sparsity overheads. We analyze the scalability of 1D and 2D algorithms for PSpGEMM. While the 1D algorithm is a variant of existing implementations, 2D algorithms presented are completely novel. Most of these algorithms are based on the previous research on parallel dense matrix multiplication. We also provide results from preliminary experiments with 2D algorithms.