cusparse: FFI bindings to the CUDA Sparse BLAS library

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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.

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Modules

[Index]

Foreign
- CUDA
  - BLAS
    - Foreign.CUDA.BLAS.Sparse

Downloads

cusparse-0.1.0.1.tar.gz [browse] (Cabal source package)
Package description (as included in the package)

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Package maintainers

TrevorMcDonell, tomsmeding

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Candidates

0.3.0.0

Versions [RSS]	0.1.0.0, 0.1.0.1, 0.2.0.0, 0.3.0.0
Change log	CHANGELOG.md
Dependencies	base (>=4 && <5), 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 2018-03-12T10:14:00Z
Distributions
Reverse Dependencies	1 direct, 1 indirect [details]
Downloads	2442 total (5 in the last 30 days)
Rating	(no votes yet) [estimated by Bayesian average]
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Status	Docs uploaded by user [build log] All reported builds failed as of 2018-03-12 [all 1 reports]

Readme for cusparse-0.1.0.1

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Haskell FFI Bindings to cuSPARSE

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