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Abstract
We introduce a task-based programming model and runtime system that exploit the observation that not all parts of a program are equally significant for the accuracy of the end-result, in order to trade off the quality of program outputs for increased energy-efficiency. This is done in a structured and flexible way, allowing for easy exploitation of different points in the quality/energy space, without adversely affecting application performance. The runtime system can apply a number of different policies to decide whether it will execute less-significant tasks accurately or approximately.
The experimental evaluation indicates that our system can achieve an energy reduction of up to 83% compared with a fully accurate execution and up to 35% compared with an approximate version employing loop perforation. At the same time, our approach always results in graceful quality degradation.
The experimental evaluation indicates that our system can achieve an energy reduction of up to 83% compared with a fully accurate execution and up to 35% compared with an approximate version employing loop perforation. At the same time, our approach always results in graceful quality degradation.
Original language | English |
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Title of host publication | Proceedings of the 20th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP) |
Publisher | ACM |
Number of pages | 2 |
ISBN (Print) | 978-1-4503-3205-7 |
DOIs | |
Publication status | Published - Feb 2015 |
Event | 20th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming - San Francisco, United States Duration: 07 Feb 2015 → 11 Feb 2015 |
Conference
Conference | 20th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming |
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Country/Territory | United States |
City | San Francisco |
Period | 07/02/2015 → 11/02/2015 |
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R6394CSC: Software management of hybrid DRAM/NVRAM memory systems
Nikolopoulos, D. & Vandierendonck, H.
01/08/2012 → …
Project: Research
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R6396CSC: SCORPIO: Significance-Based Computing for Reliability and Power Optimization
Nikolopoulos, D. & Karakonstantis, G.
01/08/2012 → 31/05/2016
Project: Research