Several implementations of matrix multiplication (MMUL) in Fortran and VAX assembly language are discussed. On a VAX-11/780 computer, the most efficient MMUL is achieved through vector-scalarmultiply-and-add (VSMA) operations, rather than by means of dot products. We also discuss optimal MMUL algori
Fast sparse matrix multiplication
β Scribed by S.C. Park; J.P. Draayer; S.-Q. Zheng
- Book ID
- 103048026
- Publisher
- Elsevier Science
- Year
- 1992
- Tongue
- English
- Weight
- 834 KB
- Volume
- 70
- Category
- Article
- ISSN
- 0010-4655
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β¦ Synopsis
A new space-efficient representation for sparse matrices is introduced and a fast sparse matrix multiplication algorithm based on the new representation is presented. The scheme is very efficient when the nonzero elements of a sparse matrix are partially or fully adjacent to one another as in band or triangular matrices. The space complexity of the new representation is better than that of existing algorithms when the number of sets of adjacent nonzero elements, called segments, is less than two thirds of the total number of nonzero elements. The time complexity of the associated sparse matrix multiplication algorithm is also better or even much better than that of existing schemes depending on the number of segments in the factor matrices.
π SIMILAR VOLUMES
A simple algorithm for multiplication of sparse matrices is proposed. This algorithm can be easily incorporate into existing matrix multiplication routines. Behavior of the given algorithm on scalar and vector processors is discussed.