cusparse: FFI bindings to the CUDA Sparse BLAS library

[ bsd3, foreign, library ] [ Propose Tags ]

The cuSPARSE library contains a set of basic linear algebra subroutines for handling sparse matrices on NVIDIA GPUs. Sparse vectors and matrices are those where the majority of elements are zero. Sparse BLAS routines are specifically implemented to take advantage of this sparsity. This package provides FFI bindings to the functions of the cuSPARSE library. You will need to install the CUDA driver and developer toolkit:

http://developer.nvidia.com/cuda-downloads

See the travis-ci.org build matrix for tested CUDA library versions.


[Skip to Readme]
Versions 0.1.0.0, 0.1.0.1
Change log CHANGELOG.md
Dependencies base (==4.*), cuda (>=0.8), half (>=0.1), storable-complex (>=0.2) [details]
License BSD-3-Clause
Copyright Copyright (c) [2017]. Trevor L. McDonell <tmcdonell@cse.unsw.edu.au>
Author Trevor L. McDonell
Maintainer Trevor L. McDonell <tmcdonell@cse.unsw.edu.au>
Category Foreign
Source repo head: git clone https://github.com/tmcdonell/cusparse
this: git clone https://github.com/tmcdonell/cusparse(tag 0.1.0.1)
Uploaded by TrevorMcDonell at Mon Mar 12 10:14:00 UTC 2018
Distributions NixOS:0.1.0.1
Downloads 276 total (15 in the last 30 days)
Rating (no votes yet) [estimated by rule of succession]
Your Rating
  • λ
  • λ
  • λ
Status Docs uploaded by user [build log]
All reported builds failed as of 2018-03-12 [all 1 reports]
Hackage Matrix CI

Modules

[Index]

Downloads

Maintainer's Corner

For package maintainers and hackage trustees


Readme for cusparse-0.1.0.1

[back to package description]

Haskell FFI Bindings to cuSPARSE

Travis build status AppVeyor build status Stackage LTS Stackage Nightly Hackage

The cuSPARSE library contains a set of basic linear algebra subroutines for handling sparse matrices. Sparse vectors and matrices are those where the majority of elements are zero. Sparse BLAS routines are specifically implemented to take advantage of this sparsity. This package provides FFI bindings to the functions of the cuSPARSE library. You will need to install the CUDA driver and developer toolkit:

http://developer.nvidia.com/cuda-downloads

http://docs.nvidia.com/cuda/cusparse/index.html