Home // ADVCOMP 2016, The Tenth International Conference on Advanced Engineering Computing and Applications in Sciences // View article
Authors:
Javed Razzaq
Rudolf Berrendorf
Soenke Hack
Max Weierstall
Florian Manuss
Keywords: Sparse Matrix Vector Multiplication; Blocking; Vector Intrinsics
Abstract:
In this paper, several blocking techniques are applied to matrices that do not have a strong blocked structure. The aim is to efficiently use vectorization with current CPUs, even for matrices without an explicit block structure on nonzero elements. Different approaches are known to find fixed or variable sized blocks of nonzero elements in a matrix. We present a new matrix format for 2D rectangular blocks of variable size, allowing fill-ins per block of explicit zero values up to a user definable threshold. We give a heuristic to detect such 2D blocks in a sparse matrix. The performance of a Sparse Matrix Vector Multiplication for chosen block formats is measured and compared. Results show that the benefit of blocking formats depend – as to be expected – on the structure of the matrix and that variable sized block formats can have advantages over fixed size formats.
Pages: 84 to 90
Copyright: Copyright (c) IARIA, 2016
Publication date: October 9, 2016
Published in: conference
ISSN: 2308-4499
ISBN: 978-1-61208-506-7
Location: Venice, Italy
Dates: from October 9, 2016 to October 13, 2016