Fast sparse matrix multiplication on GPU
Lukáš Polok, Viorela Ila, Pavel Smrž · IEEE International Conference on High Performance Computing, Data, and Analytics · 2015
Sparse matrix multiplication is an important algorithm in a wide variety of problems, including graph algorithms, simulations and linear solving to name a few. Yet, there are but a few works related to acceleration of sparse matrix multiplication on a GPU. We present a fast, novel algorithm for sparse matrix multiplication, outperforming the previous algorithm on GPU up to 3x and CPU up to 30x. The principal improvements include more efficient load balancing strategy, and a faster sorting algorithm. The main contribution is design and implementation of efficient sparse matrix multiplication algorithm and extending it to sparse block matrices, which is to our best knowledge the first implementation of this kind.