A collection of C programs for creating, displaying and converting sparse matrices into efficient formats - jackr276/Sparse-Matrix-Utilities ...

Sparse Matrix-Multivector (SpMM) multiplication is a key kernel for deep learning models and scientific computing applications. However, achieving high performance for SpMM on GPUs is challenging ...

Sparse linear arrays serve as the fundamental basis for sparse signal processing and have demonstrated remarkable direction-of-arrival (DOA) estimation performance. Due to the merit of resolving more ...

A novel AI-acceleration paper presents a method to optimize sparse matrix multiplication for machine learning models, particularly focusing on structured sparsity. Structured sparsity involves a ...