Using an advanced Monte Carlo method, Caltech researchers found a way to tame the infinite complexity of Feynman diagrams and ...

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 ...

Accelerating matrix multiplication is crucial to achieve high performance in many application domains, including neural networks, graph analytics, and scientific computing. These applications process ...