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AEQUITAS: Coordinated Energy Management Across Parallel Applications

Published: 01 June 2016 Publication History

Abstract

A growing number of energy optimization solutions operate at the application runtime level. Despite delivering promising results, these application-scoped optimizations are fundamentally greedy: They assume to have an exclusive access to power management and often perform poorly when multiple power-managing applications co-exist, or different threads of the same application share power management hardware. In this paper, we introduce AEQUITAS, a first step to address this critical yet largely overlooked problem. The insight behind AEQUITAS is that co-existing applications may view power-managing hardware as a shared resource and coordinate power management decisions. As a concrete instance of this philosophy, we evaluated our ideas on top of a state-of-the-art energy-efficient work-stealing runtime. Experiments show that without AEQUITAS, multiple co-existing power-managing application runtimes suffer up to 32% performance loss and negate all power savings. With AEQUITAS, the beneficial energy-performance tradeoff reported in the single-application setting (12.9% energy savings and 2.5% performance loss) can be retained, but in a much more challenging setting where multiple power-managing runtimes co-exist on parallel architectures and multiple CPU cores share the same power domain.

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cover image ACM Conferences
ICS '16: Proceedings of the 2016 International Conference on Supercomputing
June 2016
547 pages
ISBN:9781450343619
DOI:10.1145/2925426
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 June 2016

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Author Tags

  1. DVFS
  2. Energy Management
  3. Parallelism
  4. Work Stealing

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  • (2023)JOSS: Joint Exploration of CPU-Memory DVFS and Task Scheduling for Energy EfficiencyProceedings of the 52nd International Conference on Parallel Processing10.1145/3605573.3605586(828-838)Online publication date: 7-Aug-2023
  • (2023)SYnergy: Fine-grained Energy-Efficient Heterogeneous Computing for Scalable Energy SavingProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis10.1145/3581784.3607055(1-13)Online publication date: 12-Nov-2023
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