Performance optimization and modeling of blocked sparse kernels

被引:20
作者
Buttari, Alfredo [1 ]
Eijkhout, Victor
Langou, Julien
Filippone, Salvatore
机构
[1] Univ Tennessee, Innovat Comp Lab, Knoxville, TN 37996 USA
[2] Univ Texas, Texas Adv Comp Lab, Austin, TX 78712 USA
[3] Univ Colorado, Dept Math Sci, Denver, CO 80202 USA
[4] Univ Colorado, Hlth Sci Ctr, Denver, CO USA
[5] Univ Roma Tor Vergata, Rome, Italy
关键词
optimization; sparse; matrix-vector product; blocking; self-adaptivity;
D O I
10.1177/1094342007083801
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
We present a method for automatically selecting optimal implementations of sparse matrix-vector operations. Our software "AcCELS" (Accelerated Compress-storage Elements for Linear Solvers) involves a setup phase that probes machine characteristics, and a run-time phase where stored characteristics are combined with a measure of the actual sparse matrix to find the optimal kernel implementation. We present a performance model that is shown to be accurate over a large range of matrices.
引用
收藏
页码:467 / 484
页数:18
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