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 ...

In many simulation applications, the solving of the sparse matrix-vector multiplication (SpMV) is critical for high performing computing. A sparse matrix contains a high percentage of zero’s, (as ...

If \(A\) is a \(3\times 3\) matrix then we can apply a linear transformation to each rgb vector via matrix multiplication, where \([r,g,b]\) are the original values ...

A novel AI-acceleration paper presents a method to optimize sparse matrix multiplication for machine learning models ... which are often performed on vector processors or custom matrix engines.