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Adaptive sparse matrix representation for efficient matrix–vector multiplication
, Article Journal of Supercomputing ; November , 2015 , Pages 1-21 ; 09208542 (ISSN) ; Khunjush, F ; Sarbazi Azad, H ; Sharif University of Technology
Springer New York LLC
2015
Abstract
A wide range of applications in engineering and scientific computing are based on the sparse matrix computation. There exist a variety of data representations to keep the non-zero elements in sparse matrices, and each representation favors some matrices while not working well for some others. The existing studies tend to process all types of applications, e.g., the most popular application which is matrix–vector multiplication, with different sparse matrix structures using a fixed representation. While Graphics Processing Units (GPUs) have evolved into a very attractive platform for general purpose computations, most of the existing works on sparse matrix–vector multiplication (SpMV, for...
Adaptive sparse matrix representation for efficient matrix–vector multiplication
, Article Journal of Supercomputing ; Volume 72, Issue 9 , Volume 72, Issue 9 , 2016 , Pages 3366-3386 ; 09208542 (ISSN) ; Khunjush, F ; Sarbazi Azad, H ; Sharif University of Technology
Springer New York LLC
Abstract
A wide range of applications in engineering and scientific computing are based on the sparse matrix computation. There exist a variety of data representations to keep the non-zero elements in sparse matrices, and each representation favors some matrices while not working well for some others. The existing studies tend to process all types of applications, e.g., the most popular application which is matrix–vector multiplication, with different sparse matrix structures using a fixed representation. While Graphics Processing Units (GPUs) have evolved into a very attractive platform for general purpose computations, most of the existing works on sparse matrix–vector multiplication (SpMV, for...