Sparse matrix-vector multiplication is an important kernel that often runs inefficiently on superscalar RISC processors. This paper describes techniques that increase instruction-...
Abstract—The Sparse Matrix-Vector Multiplication kernel exhibits limited potential for taking advantage of modern shared memory architectures due to its large memory bandwidth re...
Kornilios Kourtis, Georgios I. Goumas, Nectarios K...
Abstract. We present new performance models and a new, more compact data structure for cache blocking when applied to the sparse matrixvector multiply (SpM×V) operation, y ← y +...
Rajesh Nishtala, Richard W. Vuduc, James Demmel, K...
Floating-point Sparse Matrix-Vector Multiplication (SpMXV) is a key computational kernel in scientific and engineering applications. The poor data locality of sparse matrices sig...
Abstract. We improve the performance of sparse matrix-vector multiplication (SpMV) on modern cache-based superscalar machines when the matrix structure consists of multiple, irregu...