Title
Performance evaluation of the sparse matrix-vector multiplication on modern architectures
Abstract
In this paper, we revisit the performance issues of the widely used sparse matrix-vector multiplication (SpMxV) kernel on modern microarchitectures. Previous scientific work reports a number of different factors that may significantly reduce performance. However, the interaction of these factors with the underlying architectural characteristics is not clearly understood, a fact that may lead to misguided, and thus unsuccessful attempts for optimization. In order to gain an insight into the details of SpMxV performance, we conduct a suite of experiments on a rich set of matrices for three different commodity hardware platforms. In addition, we investigate the parallel version of the kernel and report on the corresponding performance results and their relation to each architecture's specific multithreaded configuration. Based on our experiments, we extract useful conclusions that can serve as guidelines for the optimization process of both single and multithreaded versions of the kernel.
Year
DOI
Venue
2009
10.1007/s11227-008-0251-8
The Journal of Supercomputing
Keywords
Field
DocType
Sparse matrix-vector multiplication,Multicore architectures,Scientific applications,Performance evaluation
Kernel (linear algebra),Computer science,Sparse matrix-vector multiplication,Parallel computing,Multiplication,Vector processor,Matrix multiplication,Multi-core processor,Sparse matrix,Microarchitecture
Journal
Volume
Issue
ISSN
50
1
0920-8542
Citations 
PageRank 
References 
42
2.54
21
Authors
5
Name
Order
Citations
PageRank
Georgios Goumas126822.03
Kornilios Kourtis234029.44
Nikos Anastopoulos31039.07
Vasileios Karakasis413810.24
N. Koziris51015107.53