A novel graph transformation strategy for optimizing SpTRSV on CPUs.

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Název: A novel graph transformation strategy for optimizing SpTRSV on CPUs.
Autoři: Yılmaz, Buse
Zdroj: Concurrency & Computation: Practice & Experience; Nov2023, Vol. 35 Issue 24, p1-18, 18p
Témata: SPARSE matrices, SPARSE graphs, PARALLEL programming
Abstrakt: Summary: Sparse triangular solve (SpTRSV) is an extensively studied computational kernel. An important obstacle in parallel SpTRSV implementations is that in some parts of a sparse matrix the computation is serial. By transforming the dependency graph, it is possible to increase the parallelism of the parts that lack it. In this work, we present a novel graph transformation strategy to increase the parallelism degree of a sparse matrix and compare it to our previous strategy. It is seen that our transformation strategy can provide a speedup as high as 1.42x$$ 1.42x $$. [ABSTRACT FROM AUTHOR]
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Databáze: Complementary Index
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Abstrakt:Summary: Sparse triangular solve (SpTRSV) is an extensively studied computational kernel. An important obstacle in parallel SpTRSV implementations is that in some parts of a sparse matrix the computation is serial. By transforming the dependency graph, it is possible to increase the parallelism of the parts that lack it. In this work, we present a novel graph transformation strategy to increase the parallelism degree of a sparse matrix and compare it to our previous strategy. It is seen that our transformation strategy can provide a speedup as high as 1.42x$$ 1.42x $$. [ABSTRACT FROM AUTHOR]
ISSN:15320626
DOI:10.1002/cpe.7761