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A hybrid computing method of SpMV on CPU–GPU heterogeneous computing systems

  • Published:2017-06 Issue: Volume:104 Page:49-60
  • ISSN:0743-7315
  • Container-title:Journal of Parallel and Distributed Computing
  • language:en
  • Short-container-title:Journal of Parallel and Distributed Computing

Author:

Yang Wangdong,Li Kenli,Li Keqin

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture,Theoretical Computer Science,Software

Reference31 articles.

1. Optimizing sparse matrix vector multiplication on GPUs, Research Report RC24704, IBM TJ Watson Research Center, Tech. Rep.;Baskaran,2008

2. Pattern-based sparse matrix representation for memory-efficient SMVM kernels;Belgin,2009

3. Exact sparse matrix–vector multiplication on GPU’s and multicore architectures;Boyer,2010

4. Graphics processing unit (GPU) programming strategies and trends in GPU computing;Brodtkorb;J. Parallel Distrib. Comput.,2013

5. Concurrent number cruncher: a GPU implementation of a general sparse linear solver;Buatois;Int. J. Parallel Emerg. Distrib. Syst.,2009

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