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Algorithm and Data Optimization Techniques for Scaling to Massively Threaded Systems
August 2012 (vol. 45 no. 8)
pp. 26-32
John A. Stratton, University of Illinois at Urbana-Champaign
Christopher Rodrigues, University of Illinois at Urbana-Champaign
I-Jui Sung, University of Illinois at Urbana-Champaign
Li-Wen Chang, University of Illinois at Urbana-Champaign
Nasser Anssari, University of Illinois at Urbana-Champaign
Geng Liu, University of Illinois at Urbana-Champaign
Wen-mei W. Hwu, University of Illinois at Urbana-Champaign
Nady Obeid, KLA-Tencor
A study of the implementation patterns among massively threaded applications for many-core GPUs reveals that each of the seven most commonly used algorithm and data optimization techniques can enhance the performance of applicable kernels by 2 to 10× in current processors while also improving future scalability. The featured Web extra is a video interview with author John Stratton, who describes how implementation patterns can improve future scalability. YouTube URL: http://youtu.be/fgn9LJbInMw
Index Terms:
Instruction sets,System-on-a-chip,Bandwidth,Histograms,Optimization,Graphics processing unit,Multithreading,Parboil benchmarks,massively threaded systems,optimization patterns,accelerators,scalability
Citation:
John A. Stratton, Christopher Rodrigues, I-Jui Sung, Li-Wen Chang, Nasser Anssari, Geng Liu, Wen-mei W. Hwu, Nady Obeid, "Algorithm and Data Optimization Techniques for Scaling to Massively Threaded Systems," Computer, vol. 45, no. 8, pp. 26-32, Aug. 2012, doi:10.1109/MC.2012.194
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