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Volumn , Issue , 2010, Pages 1146-1151

Improving the performance of the sparse matrix vector product with GPUs

Author keywords

[No Author keywords available]

Indexed keywords

ACCELERATION FACTORS; COMPARATIVE EVALUATIONS; COMPUTATIONAL ARCHITECTURE; ENGINEERING DISCIPLINES; GRAPHICS PROCESSING UNITS; IRREGULAR COMPUTATIONS; KEY OPERATIONS; MATRIX; SCIENTIFIC COMPUTING; SPARSE MATRICES; STORAGE FORMATS; TEST MATRIX; WIDE SPECTRUM;

EID: 78249244772     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIT.2010.208     Document Type: Conference Paper
Times cited : (106)

References (15)
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    • 77956260008 scopus 로고    scopus 로고
    • Implementing sparse matrix-vector multiplication on throughput-oriented processors
    • Bell N, Garland M. Implementing Sparse Matrix-Vector Multiplication on Throughput-Oriented Processors Proceedings of SC'09. http://www.nvidia.com/ object/nvidia-research-pub-013.html.
    • Proceedings of SC'09
    • Bell, N.1    Garland, M.2
  • 5
  • 6
    • 60649099576 scopus 로고    scopus 로고
    • Optimizing matrix multiplication for a short-vector SIMD architecture - CELL processor
    • Kurzak J, Alvaro W, Dongarra J. Optimizing matrix multiplication for a short-vector SIMD architecture - CELL processor. Parallel Computing 2009; 35(3):138-150.
    • (2009) Parallel Computing , vol.35 , Issue.3 , pp. 138-150
    • Kurzak, J.1    Alvaro, W.2    Dongarra, J.3
  • 8
    • 0004141533 scopus 로고    scopus 로고
    • Math Kernel Library
    • Intel. Math Kernel Library. Reference Manual http://software.intel.com/ sites/products/documentation/hpc/mkl/mklman.pdf.
    • Reference Manual
  • 10
    • 77949577730 scopus 로고    scopus 로고
    • Automatically tuning sparse matrix-vector multiplication for GPU architectures
    • LNCS 5952
    • Monakov, A; Lokhmotov, A; and Avetisyan, A. Automatically Tuning Sparse Matrix-Vector Multiplication for GPU Architectures Proceedings of HiPEAC 2010, LNCS 5952, pp. 111- 125, 2010.
    • (2010) Proceedings of HiPEAC 2010 , pp. 111-125
    • Monakov, A.1    Lokhmotov, A.2    Avetisyan, A.3
  • 11
    • 77953086053 scopus 로고    scopus 로고
    • Version 2.3, August
    • NVIDIA, CUDA Programming guide. Version 2.3, August, 2009. http://developer.download.nvidia.com/compute/cuda/2-3/toolkit/docs/ NVIDIA-CUDA-Programming-Guide-2.3.pdf.
    • (2009) CUDA Programming Guide
  • 12
  • 13
    • 0031269220 scopus 로고    scopus 로고
    • Improving the memory-system performance of sparse-matrix vector multiplication
    • Toledo S. Improving the memory-system performance of sparse-matrix vector multiplication. IBM Journal of Research and Development. 1997; 41(6):711-725.
    • (1997) IBM Journal of Research and Development , vol.41 , Issue.6 , pp. 711-725
    • Toledo, S.1
  • 14
    • 77950518538 scopus 로고    scopus 로고
    • A matrix approach to tomographic reconstruction and its implementation on GPUs
    • Vázquez F, Garzón EM, Fernández JJ. A matrix approach to tomographic reconstruction and its implementation on GPUs. Journal of Structural Biology, 2010; 170:146-151.
    • (2010) Journal of Structural Biology , vol.170 , pp. 146-151
    • Vázquez, F.1    Garzón, E.M.2    Fernández, J.J.3
  • 15
    • 60949098907 scopus 로고    scopus 로고
    • Optimization of sparse matrix-vector multiplication on emerging multicore platforms
    • Williams S, Oliker L, Vuduc R, Shalf J, Yelick K, Demmel J. Optimization of sparse matrix-vector multiplication on emerging multicore platforms. Parallel Computing 2009; 35(3):178-194.
    • (2009) Parallel Computing , vol.35 , Issue.3 , pp. 178-194
    • Williams, S.1    Oliker, L.2    Vuduc, R.3    Shalf, J.4    Yelick, K.5    Demmel, J.6


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.