SupermarQ: A Scalable Quantum Benchmark Suite

Teague Tomesh, Pranav Gokhale, Victory Omole, Gokul Subramanian Ravi, Kaitlin N. Smith, Joshua Viszlai, Xin Chuan Wu, Nikos Hardavellas, Margaret R. Martonosi, Frederic T. Chong

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

5 Scopus citations

Abstract

The emergence of quantum computers as a new computational paradigm has been accompanied by speculation concerning the scope and timeline of their anticipated revolutionary changes. While quantum computing is still in its infancy, the variety of different architectures used to implement quantum computations make it difficult to reliably measure and compare performance. This problem motivates our introduction of SupermarQ, a scalable, hardware-agnostic quantum benchmark suite which uses application-level metrics to measure performance. SupermarQ is the first attempt to systematically apply techniques from classical benchmarking methodology to the quantum domain. We define a set of feature vectors to quantify coverage, select applications from a variety of domains to ensure the suite is representative of real workloads, and collect benchmark results from the IBM, IonQ, and AQT@LBNL platforms. Looking forward, we envision that quantum benchmarking will encompass a large cross-community effort built on open source, constantly evolving benchmark suites. We introduce SupermarQ as an important step in this direction.

Original languageEnglish (US)
Title of host publicationProceedings - 2022 IEEE International Symposium on High-Performance Computer Architecture, HPCA 2022
PublisherIEEE Computer Society
Pages587-603
Number of pages17
ISBN (Electronic)9781665420273
DOIs
StatePublished - 2022
Event28th Annual IEEE International Symposium on High-Performance Computer Architecture, HPCA 2022 - Virtual, Online, Korea, Republic of
Duration: Apr 2 2022Apr 6 2022

Publication series

NameProceedings - International Symposium on High-Performance Computer Architecture
Volume2022-April
ISSN (Print)1530-0897

Conference

Conference28th Annual IEEE International Symposium on High-Performance Computer Architecture, HPCA 2022
Country/TerritoryKorea, Republic of
CityVirtual, Online
Period4/2/224/6/22

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture

Keywords

  • Benchmarking
  • Program Characterization
  • Quantum Computing

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