Source-code for sparse matrix-dense matrix multiplication and sampled dense-dense matrix multiplication CUDA kernels
Sparse matrix computations are ubiquitous in scientific computing; General-Purpose computing on Grap...
General purpose computation on graphics processing unit (GPU) is prominent in the high performance c...
10.1145/2503210.2503234International Conference for High Performance Computing, Networking, Storage ...
There are many successful applications to take advantages of massive parallelization on GPU for deep...
This repository contains the code and scripts for verifying the claims in the paper "Design Principl...
Sparse matrix–vector multiplication (SpMV) is of singular importance in sparse linear algebra, which...
Sparse matrix–vector multiplication (SpMV) is of singular importance in sparse linear algebra, which...
In this article, we discuss the performance modeling and optimization of Sparse Matrix-Vector Multip...
We apply object-oriented software design patterns to develop code for scientific software involving ...
We implement two novel algorithms for sparse-matrix dense-matrix multiplication (SpMM) on the GPU. O...
International audienceGraphics Processing Units (GPU) feedback on acoustic 3D code, more precisely w...
Abstract. Graphics Processing Units (GPUs) are massive data parallel processors. High performance co...
We apply object-oriented software design patterns to develop code for scientific software involving ...
Efficient processing of Irregular Matrices on Single Instruction, Multiple Data (SIMD)-type architec...
General purpose computing on graphics processing units (GPGPU) is fast becoming a common feature of ...
Sparse matrix computations are ubiquitous in scientific computing; General-Purpose computing on Grap...
General purpose computation on graphics processing unit (GPU) is prominent in the high performance c...
10.1145/2503210.2503234International Conference for High Performance Computing, Networking, Storage ...
There are many successful applications to take advantages of massive parallelization on GPU for deep...
This repository contains the code and scripts for verifying the claims in the paper "Design Principl...
Sparse matrix–vector multiplication (SpMV) is of singular importance in sparse linear algebra, which...
Sparse matrix–vector multiplication (SpMV) is of singular importance in sparse linear algebra, which...
In this article, we discuss the performance modeling and optimization of Sparse Matrix-Vector Multip...
We apply object-oriented software design patterns to develop code for scientific software involving ...
We implement two novel algorithms for sparse-matrix dense-matrix multiplication (SpMM) on the GPU. O...
International audienceGraphics Processing Units (GPU) feedback on acoustic 3D code, more precisely w...
Abstract. Graphics Processing Units (GPUs) are massive data parallel processors. High performance co...
We apply object-oriented software design patterns to develop code for scientific software involving ...
Efficient processing of Irregular Matrices on Single Instruction, Multiple Data (SIMD)-type architec...
General purpose computing on graphics processing units (GPGPU) is fast becoming a common feature of ...
Sparse matrix computations are ubiquitous in scientific computing; General-Purpose computing on Grap...
General purpose computation on graphics processing unit (GPU) is prominent in the high performance c...
10.1145/2503210.2503234International Conference for High Performance Computing, Networking, Storage ...