We analyze the problem of sparse-matrix dense-vector multiplication (SpMV) in the I/O model. In the SpMV, the objective is to compute y = Ax, where A is a sparse matrix and x and y are vectors. We give tight upper and lower bounds on the number of block transfers as a function of the sparsity k, the number of nonzeros in a column of A. Parameter k is a knob that bridges the problems of permuting (k = 1) and dense matrix multiplication (k = N). When the nonzero elements of A are stored in column-major order, SpMV takes O mi
We design and develop a work-efficient multithreaded algorithm for sparse matrix-sparse vector multi...
We present new performance models and a new, more compact data structure for cache blocking when ap...
In this work we present a heuristic to select the appropriate compressed storage format when computi...
We analyze the problem of sparse-matrix dense-vector mul-tiplication (SpMV) in the I/O-model. The ta...
Sparse matrix-vector multiplication (shortly SpMV) is one of most common subroutines in the numerica...
AbstractThe matrix-vector multiplication operation is the kernel of most numerical algorithms.Typica...
Abstract. Sparse matrix-vector multiplication is an important computational kernel that tends to per...
Sparse matrix-vector multiplication (SpMxV) is one of the most important computational kernels in sc...
Sparse matrix-vector multiplication (SpMxV) is a kernel operation widely used in iterative linear so...
Sparse matrix-vector multiplication (SpMxV) is one of the most important computational kernels in sc...
Abstract. Many applications based on finite element and finite difference methods include the soluti...
Due to copyright restrictions, the access to the full text of this article is only available via sub...
Abstract—In this paper we present two algorithms for perform-ing sparse matrix-dense vector multipli...
An important kernel of scientific software is the multiplication of a sparse matrix by a vector. The...
DASP: Specific Dense Matrix Multiply-Accumulate Units Accelerated General Sparse Matrix-Vector Multi...
We design and develop a work-efficient multithreaded algorithm for sparse matrix-sparse vector multi...
We present new performance models and a new, more compact data structure for cache blocking when ap...
In this work we present a heuristic to select the appropriate compressed storage format when computi...
We analyze the problem of sparse-matrix dense-vector mul-tiplication (SpMV) in the I/O-model. The ta...
Sparse matrix-vector multiplication (shortly SpMV) is one of most common subroutines in the numerica...
AbstractThe matrix-vector multiplication operation is the kernel of most numerical algorithms.Typica...
Abstract. Sparse matrix-vector multiplication is an important computational kernel that tends to per...
Sparse matrix-vector multiplication (SpMxV) is one of the most important computational kernels in sc...
Sparse matrix-vector multiplication (SpMxV) is a kernel operation widely used in iterative linear so...
Sparse matrix-vector multiplication (SpMxV) is one of the most important computational kernels in sc...
Abstract. Many applications based on finite element and finite difference methods include the soluti...
Due to copyright restrictions, the access to the full text of this article is only available via sub...
Abstract—In this paper we present two algorithms for perform-ing sparse matrix-dense vector multipli...
An important kernel of scientific software is the multiplication of a sparse matrix by a vector. The...
DASP: Specific Dense Matrix Multiply-Accumulate Units Accelerated General Sparse Matrix-Vector Multi...
We design and develop a work-efficient multithreaded algorithm for sparse matrix-sparse vector multi...
We present new performance models and a new, more compact data structure for cache blocking when ap...
In this work we present a heuristic to select the appropriate compressed storage format when computi...