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Bypass aware instruction scheduling for register file power reduction
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Source Language, Compiler and Tool Support for Embedded Systems archive
Proceedings of the 2006 ACM SIGPLAN/SIGBED conference on Language, compilers, and tool support for embedded systems table of contents
Ottawa, Ontario, Canada
SESSION: Low power issues table of contents
Pages: 173 - 181  
Year of Publication: 2006
ISBN:1-59593-362-X
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Authors
Sanghyun Park  Seoul National University, Korea
Aviral Shrivastava  University of California, Irvine
Nikil Dutt  University of California, Irvine
Alex Nicolau  University of California, Irvine
Yunheung Paek  Seoul National University, Korea
Eugene Earlie  Intel
Sponsors
ACM: Association for Computing Machinery
SIGBED: ACM Special Interest Group on Embedded Systems
SIGPLAN: ACM Special Interest Group on Programming Languages
Publisher
ACM  New York, NY, USA
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ABSTRACT

Since register files suffer from some of the highest power densities within processors, designers have investigated several architectural strategies for register file power reduction, including "On Demand RF Read" where the register file is read only if the operand value is not available from the bypasses. However, we show in this paper that significant additional reductions in the register file power consumption can be obtained by scheduling instructions so that they transfer the operands via bypasses, rather than reading from the register file. Such instruction scheduling requires the compiler to be cognizant of the bypasses in the processor pipeline. In this paper, we develop several bypass aware instruction scheduling heuristics varying in time complexity, and study their effectiveness on the Intel XScale processor pipeline running MiBench benchmarks. Our experimental results show additional power consumption reductions of up to 26% and on average 12% over and above the register file power reduction achieved through existing techniques.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Sanghyun Park: colleagues
Aviral Shrivastava: colleagues
Nikil Dutt: colleagues
Alex Nicolau: colleagues
Yunheung Paek: colleagues
Eugene Earlie: colleagues