TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Razzaq, Javed
A1  - Berrendorf, Rudolf
A1  - Hack, Soenke
A1  - Weierstall, Max
A1  - Manuss, Florian
T1  - Fixed and Variable Sized Block Techniques for Sparse Matrix Vector Multiplication with General Matrix Structures
T2  - Cheptsov, Alharbi (Eds.): ADVCOMP 2016, The Tenth International Conference on Advanced Engineering Computing and Applications in Sciences. Venice, Italy, October 9-13, 2016
N2  - 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.
KW  - Sparse Matrix Vector Multiplication
KW  - Blocking
KW  - Vector Intrinsics
UR  - https://www.thinkmind.org/index.php?view=article&articleid=advcomp_2016_4_30_20073
SN  - 978-1-61208-506-7
SB  - 978-1-61208-506-7
SP  - 84
EP  - 90
PB  - ThinkMind
ER  -