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Proceedings of the 22nd International Conference on Parallel Architectures and Compilation Techniques (2005)
St. Louis, Missouri
Sept. 17, 2005 to Sept. 21, 2005
ISSN: 1089-795X
ISBN: 0-7695-2429-X
pp: 87-98
Weifeng Zhang , Department of Computer Science and Engineering University of California, San Diego
Brad Calder , Department of Computer Science and Engineering University of California, San Diego
Dean M. Tullsen , Department of Computer Science and Engineering University of California, San Diego
ABSTRACT
<p>Dynamic optimization has the potential to adapt the program?s behavior at run-time to deliver performance improvements over static optimization. Dynamic optimization systems usually perform their optimization in series with the application?s execution. This incurs overhead which reduces the benefit of dynamic optimization, and prevents some aggressive optimizations from being performed.</p> <p>In this paper we propose a new dynamic optimization framework called Trident. Concurrent with the program?s execution, the framework uses hardware support to identify optimization opportunities, and uses spare threads on a multithreaded processor to perform dynamic optimizations for these optimization events. We evaluate the benefit of using Trident to guide code layout, basic compiler optimizations, and value specialization. Our results show that using Trident with these optimizations achieves an average 20% speedup, and is complementary with other memory latency tolerant techniques, such as prefetching.</p>
INDEX TERMS
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CITATION
Weifeng Zhang, Brad Calder, Dean M. Tullsen, "An Event-Driven Multithreaded Dynamic Optimization Framework", Proceedings of the 22nd International Conference on Parallel Architectures and Compilation Techniques, vol. 00, no. , pp. 87-98, 2005, doi:10.1109/PACT.2005.7
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