SPARSE MATRIX MULTIPLICATION ON VECTOR COMPUTERS

作     者：JOCELYNE ERHEL 

作者机构：IRISA – INRIA Campus Universitaire de Beaulieu F-35042 RENNES Cedex France 

出 版 物：《International Journal of High Speed Computing》 

年 卷 期：1990年第2卷第2期

页      面：101-116页

主　　题：Sparse matrix vector algorithm rows generalized columns diagonals 

摘      要：An important kernel of scientific software is the multiplication of a sparse matrix by a vector. The efficiency of the algorithm on a vector computer depends on the storage scheme. With storage by rows, performances are limited in general by the small vector length. Therefore a storage by so-called generalized columns has been designed, which provides long vectors and consequent good performance. However, it is not suitable for the symmetric case. A new type of storage, by sparse diagonals, has thus been defined. It still exhibits long vectors, with performances as good as previously, but it is also well-suited to symmetric matrices. Results on a CRAY 2, with various sparse matrices, compare the three algorithms and show the efficiency of the storage by sparse diagonals.