3.9 Article Proceedings Paper

Maximizing Performance Under a Power Cap: A Comparison of Hardware, Software, and Hybrid Techniques

Journal

ACM SIGPLAN NOTICES
Volume 51, Issue 4, Pages 545-559

Publisher

ASSOC COMPUTING MACHINERY
DOI: 10.1145/2954679.2872375

Keywords

Performance; Design; Experimentation; Adaptive Systems; Power Management; Decision-tree

Funding

  1. U.S. Government under the DARPA BRASS program
  2. Dept. of Energy under DOE [DE-AC02-06CH11357]
  3. NSF [CCF 1439156]
  4. DOE Early Career Award
  5. Division of Computing and Communication Foundations
  6. Direct For Computer & Info Scie & Enginr [1439156] Funding Source: National Science Foundation

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Power and thermal dissipation constrain multicore performance scaling. Modern processors are built such that they could sustain damaging levels of power dissipation, creating a need for systems that can implement processor power caps. A particular challenge is developing systems that can maximize performance within a power cap, and approaches have been proposed in both software and hardware. Software approaches are flexible, allowing multiple hardware resources to be coordinated for maximum performance, but software is slow, requiring a long time to converge to the power target. In contrast, hardware power capping quickly converges to the the power cap, but only manages voltage and frequency, limiting its potential performance. In this work we propose PUPiL, a hybrid software/hardware power capping system. Unlike previous approaches, PUPiL combines hardware's fast reaction time with software's flexibility. We implement PUPiL on real Linux/x86 platform and compare it to Intel's commercial hardware power capping system for both single and multiapplication workloads. We find PUPiL provides the same reaction time as Intel's hardware with significantly higher performance. On average, PUPiL outperforms hardware by from 1.18-2.4x depending on workload and power target. Thus, PUPiL provides a promising way to enforce power caps with greater performance than current state-of-the-art hardware-only approaches.

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