DocumentCode :
3312076
Title :
Parallelizing a highly vectorized multigrid code with zebra relaxation
Author :
Lioen, Walter M.
Author_Institution :
CWI, Amsterdam, Netherlands
fYear :
1992
fDate :
16-20 Nov 1992
Firstpage :
180
Lastpage :
189
Abstract :
After a brief introduction to multigrid methods, the author discusses some of the algorithmic choices in MGZEB, a parallelized highly vectorized multigrid code for the solution of linear systems resulting from the seven-point discretization of general linear second-order elliptic partial differential equations in two dimensions. He describes the minimization of the scalar operation count, the vector tuning on a vector-register machine, and the parallelization of the already existing highly vectorized MGZEB code. At present the same algorithm would be used with the same scalar operation count on a scalar uniprocessor. The overall parallel vector-performance using autotasking on a Cray Y-MP4/464 is discussed
Keywords :
elliptic equations; matrix algebra; parallel algorithms; partial differential equations; relaxation theory; Cray Y-MP4/464; MGZEB; algorithmic choices; autotasking; general linear second-order elliptic partial differential equations; linear systems; minimization; multigrid methods; parallel vector-performance; scalar operation count; seven-point discretization; vector tuning; vector-register machine; vectorized multigrid code; zebra relaxation; Boundary conditions; Code standards; Documentation; Equations; Linear systems; Multigrid methods; Performance gain; Piecewise linear techniques; Smoothing methods; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Supercomputing '92., Proceedings
Conference_Location :
Minneapolis, MN
Print_ISBN :
0-8186-2630-5
Type :
conf
DOI :
10.1109/SUPERC.1992.236695
Filename :
236695
Link To Document :
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