Abstract
The author presents a new parallel matrix multiplication algorithm on distributed memory concurrent computers, which is fast and scalable, and whose performance is independent of data distribution on processors, and calls it DIMMA (Distribution-Independent Matrix Multiplication Algorithm). The algorithm is based on two new ideas; it uses a modified pipelined communication scheme to overlap computation and communication effectively and exploits the LCM block concept to obtain the maximum performance of the sequential BLAS routine in each processor even when the block size is very small as well as very large. The algorithm is implemented and compared with SUMMA on the Intel Paragon computer.
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