@inproceedings{RazzaqBerrendorfHacketal.2016,
author = {Javed Razzaq and Rudolf Berrendorf and Soenke Hack and Max Weierstall and Florian Manuss},
title = {Fixed and Variable Sized Block Techniques for Sparse Matrix Vector Multiplication with General Matrix Structures},
series = {Cheptsov, Alharbi (Eds.): ADVCOMP 2016, The Tenth International Conference on Advanced Engineering Computing and Applications in Sciences. Venice, Italy, October 9-13, 2016},
publisher = {ThinkMind},
isbn = {978-1-61208-506-7},
pages = {84 -- 90},
year = {2016},
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.},
language = {en}
}