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Volumn 45, Issue 5, 2010, Pages 105-114

An adaptive performance modeling tool for GPU architectures

Author keywords

Analytical model; GPU; Parallel programming; Performance estimation

Indexed keywords

ABSTRACT INTERPRETATIONS; ANALYTICAL MODEL; ANALYTICAL PERFORMANCE MODEL; AUTOTUNING; COMPUTE UNIFIED DEVICE ARCHITECTURES; CONTROL FLOWS; DATA PARALLEL; EXECUTION TIME; GPU; GPU ARCHITECTURES; MEMORY ACCESS; MICRO ARCHITECTURES; PERFORMANCE BOTTLENECKS; PERFORMANCE ESTIMATION; PERFORMANCE MODEL; PERFORMANCE MODELING; SCRATCH PAD MEMORY; SYSTEM COMPLEXITY; WORK-FLOWS;

EID: 77957561221     PISSN: 15232867     EISSN: None     Source Type: Journal    
DOI: 10.1145/1837853.1693470     Document Type: Conference Paper
Times cited : (143)

References (21)
  • 1
    • 77957561336 scopus 로고    scopus 로고
    • ATI Stream Computing
    • ATI Stream Computing. http://developer.amd.com/gpu-assets/Stream- Computing-Overview.pdf.
  • 2
    • 74049163483 scopus 로고    scopus 로고
    • Optimizing sparse matrix-vector multiplication on GPUs
    • December
    • M. Baskaran and R. Bordawekar. Optimizing Sparse Matrix-Vector multiplication on GPUs. IBM Research Report, December 2008.
    • (2008) IBM Research Report
    • Baskaran, M.1    Bordawekar, R.2
  • 5
    • 77957551892 scopus 로고    scopus 로고
    • University of Florida Sparse Matrix Collection
    • T. Davis. University of Florida Sparse Matrix Collection. http://www.cise.u.edu/research/sparse/matrices/.
    • Davis, T.1
  • 6
    • 77749296353 scopus 로고    scopus 로고
    • Understanding the efficiency of GPU algorithms for matrix-matrix multiplication
    • August
    • K. Fatahalian, J. Sugerman, and P. Hanrahan. Understanding the Efficiency of GPU Algorithms for Matrix-matrix Multiplication. In Conference on Graphics Hardware, August 2004.
    • (2004) Conference on Graphics Hardware
    • Fatahalian, K.1    Sugerman, J.2    Hanrahan, P.3
  • 10
    • 70450231944 scopus 로고    scopus 로고
    • Anmodel for a GPU architecture withmemorylevel and thread-level parallelism awareness
    • June
    • S. Hong and H. Kim. Anmodel for a GPU Architecture withMemorylevel and Thread-level Parallelism Awareness. In International Symposium on Computer Architecture, June 2009.
    • (2009) International Symposium on Computer Architecture
    • Hong, S.1    Kim, H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.