July 2011
Intermediate to advanced
648 pages
13h 2m
English
book
OpenCL Programming Guide
by Aaftab Munshi, Benedict R. Gaster, Timothy G. Mattson, James Fung, Dan Ginsburg
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Chapter 22. Sparse Matrix-Vector Multiplication
By Gordon Fossum
This chapter describes an optimized implementation of the Sparse Matrix-Vector Multiplication (SpMV) algorithm using OpenCL.
Sparse matrices, for the purposes of this chapter, are defined as large two-dimensional matrices in which the vast majority of the elements of the matrix are equal to zero. They may be largely diagonal, or not. They may be symmetric, or not (perhaps not even square). They may be singular (containing entire rows with no non-zero elements), or not. They are used to characterize and solve problems in a wide variety of domains.
The sample uses a new portable tiled and packetized sparse matrix data format, which has both a single-precision and a double-precision ...
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