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SBIR Phase I: Speculative Compilation for Energy Efficency

Award Information
Agency: National Science Foundation
Branch: N/A
Contract: 0231492
Agency Tracking Number: 0231492
Amount: $100,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Solicitation Year: N/A
Award Year: 2003
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
28 Dana Street
Amherst, MA 01002
United States
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Csaba Moritz
 () -
Business Contact
Phone: () -
Research Institution

This Small Business Innovation Research Phase I project will outline a plan to commercialize the retargetable power-aware compilation technology that we have developed over the past several years. The central thesis of this proposal is that much speculative information about a program can be extracted at compile time that is currently not exploited. This information can then be exposed and used in making operational decisions (such as throttling various system sub- units) to reduce power consumption with minimal (or no) impact on performance. Our approach relies primarily on compiler-based energy reductions, rather than on circuit and architectural techniques. The key difference between our work and that of others is that we do not require all our compiler-derived information to be provably correct: all that we require is that predictions are correct often enough that they can be usefully exploited in making resource-control decisions. Relaxing the requirement to be provably correct in making predictions (of, for instance, the instruction-level parallelism of certain portions of a program) greatly reduces the complexity of otherwise highly sophisticated analysis techniques (e.g., flow-sensitive alias analysis) and expands their scope to large and complex applications.
Extensive preliminary work has been carried out to validate this approach. We believe this approach is orthogonal to many other power-aware approaches currently being used, and that its effects can be additive to these traditional approaches. Further, the nature of our approach lends it to being retrofitted to current technology. Extensive analysis of the significant power-aware computing market indicates the high level of applicability of our techniques to a very wide range of applications.

* Information listed above is at the time of submission. *

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