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 ...

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 ...

Algorithm Analysis of Sparse Matrix Multiplication Abstract: Matrix is widely used in telecommunication, cryptography, computer science and other field. Especially in wireless sensor network data ...

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 ...

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 ...

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 ( ...

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 ...