Name
Abstract | ||
|---|---|---|
In this paper we revisit the performance issues of the widely used sparse matrix-vector multiplication 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 on the details of performance, we conduct a suite of experiments on a rich set of matrices for three different commodity hardware platforms. Based on our experiments we extractuseful conclusions that can serve as guidelines for the subsequent optimization process of the kernel. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/PDP.2008.41 | PDP |
Keywords | Field | DocType |
sparse matrix,sparse matrices | Kernel (linear algebra),Suite,Sparse matrix-vector multiplication,Computer science,Matrix (mathematics),Sparse approximation,Parallel computing,Theoretical computer science,Multiplication,Commodity hardware,Sparse matrix,Distributed computing | Conference |
ISSN | Citations | PageRank |
1066-6192 | 32 | 2.04 |
References | Authors | |
14 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Georgios Goumas | 1 | 268 | 22.03 |
| Kornilios Kourtis | 2 | 340 | 29.44 |
| Nikos Anastopoulos | 3 | 103 | 9.07 |
| Vasileios Karakasis | 4 | 138 | 10.24 |
| N. Koziris | 5 | 1015 | 107.53 |