Structure-based Optimizations for Sparse Matrix-Vector Multiply

Structure-based Optimizations for Sparse Matrix-Vector Multiply

This dissertation introduces two novel techniques, OSF and PBR, to improve the performance of Sparse Matrix-vector Multiply (SMVM) kernels, which dominate the runtime of iterative solvers for systems of linear equations. SMVM computations that use sparse formats typically achieve only a small fracti...

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Bibliographic Details
Main Author: Belgin, Mehmet
Other Authors: Computer Science
Format: Others
Published: Virginia Tech 2014
Subjects:
Code Generators
Vectorization
Sparse
SpMV
SMVM
Matrix Vector Multiply
PBR
OSF
thread pool
parallel SpMV
Online Access:http://hdl.handle.net/10919/30260
http://scholar.lib.vt.edu/theses/available/etd-12242010-124006/

Internet

http://hdl.handle.net/10919/30260
http://scholar.lib.vt.edu/theses/available/etd-12242010-124006/

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