We implement a promising algorithm for sparse-matrix sparse-vector multiplication (SpMSpV) on the GPU. An efficient k-way merge lies at the heart of finding a fast parallel SpMSpV algorithm. We ...

Furthermore, we optimize the GPU implementation of our matrix multiplication paradigm, enhancing performance through out-of-order execution and memory management. This repository contains all the ...

Implementations of sparse matrix multiplication (SpMM) algorithms optimized for the Cerebras WSE-2. It explores performance trade-offs in spatial computing and finds applications in deep learning ...

Matrix inversion can be reduced to matrix multiplication via divide-and-conquer, and this reduction was shown to be stable when the word size for representing numbers b is increased by a factor of O ( ...

From Programming Parallel Algorithms. Communications of the ACM, 39(3), ... Sparse Matrix Multiplication. Sparse matrices, which are common in scientific applications, are matrices in which most ...

Sparse matrix-vector multiplication benchmark. Figure 9 shows the performance achieved on the final benchmark, sparse matrix-vector multiplication. The ordering of the results is the same as for the ...