Abstract: Efficiently synthesizing an entire application that consists of multiple algorithms for hardware implementation is a very difficult and unsolved problem. One of the main challenges is the ...

Sparse matrix-matrix multiplication (SpMM) is a crucial kernel in various applications, including sparse deep neural networks [1]–[6], graph analytics [7], triangle counting [8], and linear algebra ...

This article will take single-precision matrix multiplication (Sgemm) as an example to discuss the optimization and acceleration of CUDA performance, and use the basic knowledge of CUDA optimization ...

Sparse general matrix-matrix multiplication (SpGEMM) is fundamental to numerous scientific applications. Traditional hash-based approaches fail to strike a trade-off between reducing hash collisions ...

You can do a lot to take care of yourself and give your body what it needs. Still, as you get older, your body changes in ways you can't always control. For most men, one of those changes is that the ...