A Significance-Driven Programming Framework for Energy-Constrained Approximate Computing

Vassilis Vassiliadis, Charalambos Chalios, Konstantinos Parasyris, Christos D. Antonopoulos, Spyros Lalis, Nikolaos Bellas, Hans Vandierendonck, Dimitrios Nikolopoulos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)
262 Downloads (Pure)

Abstract

Approximate execution is a viable technique for energy-con\-strained environments, provided that applications have the mechanisms to produce outputs of the highest possible quality within the given energy budget.
We introduce a framework for energy-constrained execution with controlled and graceful quality loss. A simple programming model allows users to express the relative importance of computations for the quality of the end result, as well as minimum quality requirements. The significance-aware runtime system uses an application-specific analytical energy model to identify the degree of concurrency and approximation that maximizes quality while meeting user-specified energy constraints. Evaluation on a dual-socket 8-core server shows that the proposed
framework predicts the optimal configuration with high accuracy, enabling energy-constrained executions that result in significantly higher quality compared to loop perforation, a compiler approximation technique.
Original languageEnglish
Title of host publicationProceedings of the ACM International Conference on Computing Frontiers (CF)
PublisherACM
Number of pages8
ISBN (Print)978-1-4503-3358-0
DOIs
Publication statusPublished - May 2015
Event2015 ACM International Conference on Computing Frontiers - Hotel Continental Ischia, Ischia, Italy
Duration: 18 May 201521 May 2015

Conference

Conference2015 ACM International Conference on Computing Frontiers
CountryItaly
CityIschia
Period18/05/201521/05/2015

Fingerprint Dive into the research topics of 'A Significance-Driven Programming Framework for Energy-Constrained Approximate Computing'. Together they form a unique fingerprint.

  • Cite this

    Vassiliadis, V., Chalios, C., Parasyris, K., Antonopoulos, C. D., Lalis, S., Bellas, N., Vandierendonck, H., & Nikolopoulos, D. (2015). A Significance-Driven Programming Framework for Energy-Constrained Approximate Computing. In Proceedings of the ACM International Conference on Computing Frontiers (CF) [9] ACM. https://doi.org/10.1145/2742854.2742857