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- aggregation classification "A1".
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation date "2005".
- aggregation format "application/pdf".
- aggregation hasFormat 361371.bibtex.
- aggregation hasFormat 361371.csv.
- aggregation hasFormat 361371.dc.
- aggregation hasFormat 361371.didl.
- aggregation hasFormat 361371.doc.
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- aggregation hasFormat 361371.yaml.
- aggregation isPartOf urn:isbn:3-540-28700-0.
- aggregation isPartOf urn:issn:0302-9743.
- aggregation language "eng".
- aggregation publisher "Springer".
- aggregation rights "I have transferred the copyright for this publication to the publisher".
- aggregation subject "Technology and Engineering".
- aggregation title "A detailed study on phase predictors".
- aggregation abstract "Most programs are repetitive, meaning that some parts of a program are executed more than once. As a result, a number of phases can be extracted in which each phase exhibits similar behavior. These phases can then be exploited for various purposes such as hardware adaptation for energy efficiency. Temporal phase classification schemes divide the execution of a program into consecutive (fixed-length) intervals. Intervals showing similar behavior are grouped into a phase. When a temporal scheme is used in an on-line system, phase predictors are necessary to predict when the next phase transition will occur and what the next phase will be. In this paper, we analyze and compare a number of existing state-of-the-art phase predictors using the SPEC CPU2000 benchmarks. The design space we explore is huge. We conclude that the 2-level burst predictor with confidence and conditional update is today's most accurate phase predictor within reasonable hardware budgets.".
- aggregation authorList BK413100.
- aggregation endPage "581".
- aggregation startPage "571".
- aggregation volume "3648".
- aggregation aggregates 1137605.
- aggregation isDescribedBy 361371.
- aggregation similarTo 11549468.
- aggregation similarTo LU-361371.