CUDA-enabled Sparse Matrix–Vector Multiplication on GPUs using atomic operations-Reference-Cited by-同舟云学术

CUDA-enabled Sparse Matrix–Vector Multiplication on GPUs using atomic operations

Published:2013-11 Issue:11 Volume:39 Page:737-750
ISSN:0167-8191
Container-title:Parallel Computing
language:en
Short-container-title:Parallel Computing

Author:

Dang Hoang-Vu,Schmidt Bertil

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Graphics and Computer-Aided Design,Computer Networks and Communications,Hardware and Architecture,Theoretical Computer Science,Software

Reference19 articles.

1. N. Bell, M. Garland, Implementing Sparse Matrix–Vector Multiplication on throughput-oriented processors, in: SC, ACM, 2009, pp. 1–11.

2. N. Bell, M. Garland, Cusp: Generic Parallel Algorithms for Sparse Matrix and Graph Computations (2012). , version 0.3.0.

3. Model-driven autotuning of sparse matrix–vector multiply on GPUs;Choi;ACM SIGPLAN Not.,2010

4. Automatically tuning sparse matrix-vector multiplication for GPU architectures;Monakov,2010

5. M.M. Baskaran, R. Bordawekar, Optimizing sparse matrix–vector multiplication on GPUs, Tech. Rep., IBM TJ Watson Research Center, 2008.

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