Sparse Matrix-Matrix Multiplication (SpMM) is a fundamental operation in neural networks and high performance graph algorithms. Most popular solutions to S pMM adhere to ahead-of-time (AOT) ...

Improving on this has been an open problem even for sparse linear systems with poly (n) condition number. In this paper, we present an algorithm that solves linear systems in sparse matrices ...

Sparse matrix multiplication is widely used in various practical applications. Different accelerators have been proposed to speed up sparse matrix-dense vector multiplication (SpMV), sparse ...

cs213 programming assignment 2 spmv. Contribute to xiaolinj/Sparse-Matrix-Vector-Multiplication-SpMV-with-OpenMP development by creating an account on GitHub.

Real PIM systems can provide high levels of parallelism, large aggregate memory bandwidth and low memory access latency, thereby being a good fit to accelerate the widely-used, memory-bound Sparse ...

SpMV_benchmark A benchmark of sparse matrix dense vector multiplication in C++ using homebuilt and pre-packaged methods.

In particular, we extend the DBCSR sparse matrix library, which is the basic building block for linear scaling electronic structure theory and low scaling correlated methods in CP2K. The library is ...