AccelWattch: A power modeling framework for modern GPUs

Vijay Kandiah, Scott Peverelle, Mahmoud Khairy, Junrui Pan, Amogh Manjunath, Timothy G. Rogers, Tor M. Aamodt, Nikos Hardavellas

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

1 Scopus citations

Abstract

Graphics Processing Units (GPUs) are rapidly dominating the accelerator space, as illustrated by their wide-spread adoption in the data analytics and machine learning markets. At the same time, performance per watt has emerged as a crucial evaluation metric together with peak performance. As such, GPU architects require robust tools that will enable them to model both the performance and the power consumption of modern GPUs. However, while GPU performance modeling has progressed in great strides, power modeling has lagged behind. To mitigate this problem we propose AccelWattch, a configurable GPU power model that resolves two long-standing needs: the lack of a detailed and accurate cycle-level power model for modern GPU architectures, and the inability to capture their constant and static power with existing tools. Accel- Wattch can be driven by emulation and trace-driven environments, hardware counters, or a mix of the two, models both PTX and SASS ISAs, accounts for power gating and control-flow divergence, and supports DVFS. We integrate AccelWattch with GPGPU-Sim and Accel-Sim to facilitate its widespread use. We validate Accel- Wattch on a NVIDIA Volta GPU, and show that it achieves strong correlation against hardware power measurements. Finally, we demonstrate that AccelWattch can enable reliable design space exploration: by directly applying AccelWattch tuned for Volta on GPU configurations resembling NVIDIA Pascal and Turing GPUs, we obtain accurate power models for these architectures.

Original languageEnglish (US)
Title of host publicationMICRO 2021 - 54th Annual IEEE/ACM International Symposium on Microarchitecture, Proceedings
PublisherIEEE Computer Society
Pages738-753
Number of pages16
ISBN (Electronic)9781450385572
DOIs
StatePublished - Oct 18 2021
Event54th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2021 - Virtual, Online, Greece
Duration: Oct 18 2021Oct 22 2021

Publication series

NameProceedings of the Annual International Symposium on Microarchitecture, MICRO
ISSN (Print)1072-4451

Conference

Conference54th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2021
Country/TerritoryGreece
CityVirtual, Online
Period10/18/2110/22/21

Keywords

  • GPGPU/GPU Computing
  • Power Modeling and Simulation

ASJC Scopus subject areas

  • Hardware and Architecture

Fingerprint

Dive into the research topics of 'AccelWattch: A power modeling framework for modern GPUs'. Together they form a unique fingerprint.

Cite this