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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: 38-50
Hussam Mousa , Computer Science Department University of California, Santa Barbara
Chandra Krintz , Computer Science Department University of California, Santa Barbara
ABSTRACT
<p>Key to understanding and optimizing complex applications, is our ability to dynamically monitor executing programs with low overhead and high accuracy. Toward this end, we present HPS, a Hybrid Profiling Support system. HPS employs a hardware/software approach to program sampling that transparently, efficiently,and dynamically samples an executing instruction stream.Our system is an extension and application of Dynamic Instruction Stream Editing (DISE), a hardware technique that macro-expands instructions in the pipeline decode stage at runtime.</p> <p>HPS toggles profiling to sample the executing program as required by the profile consumer, e.g. a dynamic optimizer. Our system requires few hardware resources and introduces no "basic" overhead — the execution of instructions that triggers profiling. We use HPS to investigate the tradeoffs between overhead and accuracy of different profile types as well as different profiling schemes. In particular,we empirically evaluate hot data stream, hot call pair, and hot method identification using a number of parameterizations of bursty tracing, a popular sampling scheme used in dynamic optimization systems.</p>
INDEX TERMS
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CITATION
Hussam Mousa, Chandra Krintz, "HPS: Hybrid Profiling Support", Proceedings of the 22nd International Conference on Parallel Architectures and Compilation Techniques, vol. 00, no. , pp. 38-50, 2005, doi:10.1109/PACT.2005.24
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