A cross-platform Sparse Matrix Vector Multiplication (SpMV) framework for many-core architectures (GPUs and Xeon Phi).

Sparsification technology is crucial for deploying convolutional neural networks in resource-constrained environments. However, the efficiency of sparse models is hampered by irregular memory access ...

Operations related to Sparse matrix multiplication are frequently used in scientific computing area, and these operations usually become a performance bottleneck because of their high operational ...

Therefore, sparse matrix multiplication is the most time-consuming step in the density matrix purification algorithm for linear-scaling DFT calculations. We propose to use the MPI_Allgather function ...

The library is specifically designed to efficiently perform block-sparse matrix-matrix multiplication of matrices with a relatively large occupation. Here, we compare the performance of the original ...

SparseP software package provides 25 SpMV kernels for real PIM systems supporting the four most widely used compressed matrix formats, and a wide range of data types. Our extensive evaluation provides ...