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Volumn , Issue , 2010, Pages 1154-1157

Auto-tuning CUDA parameters for sparse matrix-vector multiplication on GPUs

Author keywords

CUDA; GPU; Performance; Sparse matrix vector multiplication

Indexed keywords

AUTOTUNING; CO-PROCESSORS; CRITICAL OPERATIONS; CUDA; GPU; GRAPHICS PROCESSING UNIT; OPTIMAL PERFORMANCE; PERFORMANCE; PROCESSING CAPABILITY; SCIENTIFIC AND ENGINEERING APPLICATIONS; SCIENTIFIC COMPUTING; SPARSE MATRIX-VECTOR MULTIPLICATION;

EID: 79952428965     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCIS.2010.285     Document Type: Conference Paper
Times cited : (45)

References (11)
  • 7
    • 77953998137 scopus 로고    scopus 로고
    • Sparse matrix solvers on the GPU: Conjugate gradients and multigrid
    • J. Bolz, I. Farmer, E. Grinspun, and P. Schroder. Sparse matrix solvers on the GPU: conjugate gradients and multigrid. ACM Trans. Graph., 22(3):917-924, 2003.
    • (2003) ACM Trans. Graph. , vol.22 , Issue.3 , pp. 917-924
    • Bolz, J.1    Farmer, I.2    Grinspun, E.3    Schroder, P.4
  • 10
    • 60649099576 scopus 로고    scopus 로고
    • Optimizing matrix multiplication for a short-vector simd architecture-cell processor
    • J. Kurzak, W. Alvaro, and J. Dongarra. Optimizing matrix multiplication for a short-vector simd architecture-cell processor. Parallel Comput. 35(3):138-150, 2009.
    • (2009) Parallel Comput. , vol.35 , Issue.3 , pp. 138-150
    • Kurzak, J.1    Alvaro, W.2    Dongarra, J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.