DocumentCode :
124075
Title :
An efficient sparse conjugate gradient solver using a Beneš permutation network
Author :
Chow, Gary C. T. ; Grigoras, Paul ; Burovskiy, Pavel ; Luk, Wayne
Author_Institution :
Dept. of Comput., Imperial Coll. London, London, UK
fYear :
2014
fDate :
2-4 Sept. 2014
Firstpage :
1
Lastpage :
7
Abstract :
The conjugate gradient (CG) is one of the most widely used iterative methods for solving systems of linear equations. However, parallelizing CG for large sparse systems is difficult due to the inherent irregularity in memory access pattern. We propose a novel processor architecture for the sparse conjugate gradient method. The architecture consists of multiple processing elements and memory banks, and is able to compute efficiently both sparse matrix-vector multiplication, and other dense vector operations. A Beneš permutation network with an optimised control scheme is introduced to reduce memory bank conflicts without expensive logic. We describe a heuristics for offline scheduling, the effect of which is captured in a parametric model for estimating the performance of designs generated from our approach.
Keywords :
conjugate gradient methods; integrated memory circuits; iterative methods; sparse matrices; Benes permutation network; efficient sparse conjugate gradient solver; iterative methods; large sparse systems; linear equations; optimised control scheme; processor architecture; sparse conjugate gradient method; sparse matrix-vector multiplication; Adders; Indexes; Memory management; Resource management; Sparse matrices; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Field Programmable Logic and Applications (FPL), 2014 24th International Conference on
Conference_Location :
Munich
Type :
conf
DOI :
10.1109/FPL.2014.6927464
Filename :
6927464
Link To Document :
بازگشت