Skip to main content
Open Access Publications from the University of California

UC Davis

UC Davis Previously Published Works bannerUC Davis

Fast Sparse Matrix and Sparse Vector Multiplication Algorithm on the GPU


We implement a promising algorithm for sparse-matrix sparse-vector multiplication (SpMSpV) on the GPU. An efficient k-way merge lies at the heart of finding a fast parallel SpMSpV algorithm. We examine the scalability of three approaches—no sorting, merge sorting, and radix sorting—in solving this problem. For breadth-first search(BFS), we achieve a 1.26x speedup over state-of-the-art sparse-matrix dense-vector (SpMV) implementations. The algorithm seems generalizeable for single-source shortest path (SSSP) and sparse-matrix sparse-matrix multiplication, and other core graph primitives such as maximal independent set and bipartite matching.

Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.

Main Content
For improved accessibility of PDF content, download the file to your device.
Current View