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International Symposium on Code Generation and Optimization (CGO'05)
Performance of Runtime Optimization on BLAST
San Jose, California
March 20-March 23
ISBN: 0-7695-2298-X
Abhinav Das, University of Minnesota
Jiwei Lu, University of Minnesota
Howard Chen, University of Minnesota
Jinpyo Kim, University of Minnesota
Pen-Chung Yew, University of Minnesota
Wei-Chung Hsu, University of Minnesota
Dong-Yuan Chen, Intel Corporation
Optimization of a real world application BLAST is used to demonstrate the limitations of static and profile-guided optimizations and to highlight the potential of runtime optimization systems. We analyze the performance profile of this application to determine performance bottlenecks and evaluate the effect of aggressive compiler optimizations on BLAST. We find that applying common optimizations (e.g. O3) can degrade performance. Profile guided optimizations do not show much improvement across the board, as current implementations do not address critical performance bottlenecks in BLAST. In some cases, these optimizations lower performance significantly due to unexpected secondary effects of aggressive optimizations. We also apply runtime optimization to BLAST using the ADORE framework. ADORE is able to detect performance bottlenecks and deploy optimizations resulting in performance gains up to 58% on some queries using data cache prefetching.
Citation:
Abhinav Das, Jiwei Lu, Howard Chen, Jinpyo Kim, Pen-Chung Yew, Wei-Chung Hsu, Dong-Yuan Chen, "Performance of Runtime Optimization on BLAST," cgo, pp.86-96, International Symposium on Code Generation and Optimization (CGO'05), 2005
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