Memory and parallelism analysis using a platform-independent approach

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Abstract

Emerging computing architectures such as near-memory computing (NMC) promise improved performance for applications by reducing the data movement between CPU and memory. However, detecting such applications is not a trivial task. In this ongoing work, we extend the state-of-the-art platform-independent software analysis tool with NMC related metrics such as memory entropy, spatial locality, data-level, and basic-block-level parallelism. These metrics help to identify the applications more suitable for NMC architectures.

Original languageEnglish
Title of host publicationProceedings of the 22nd International Workshop on Software and Compilers for Embedded Systems, SCOPES 2019
EditorsSander Stuijk
Place of PublicationNew York
PublisherAssociation for Computing Machinery, Inc
Pages23-26
Number of pages4
ISBN (Electronic)978-1-4503-6762-2
DOIs
Publication statusPublished - 27 May 2019
Event22nd International Workshop on Software and Compilers for Embedded Systems, (SCOPES2019) - St. Goar, Germany
Duration: 27 May 201928 May 2019
https://scopesconf.org/scopes-19/

Conference

Conference22nd International Workshop on Software and Compilers for Embedded Systems, (SCOPES2019)
Abbreviated titleSCOPES2019
CountryGermany
CitySt. Goar
Period27/05/1928/05/19
Internet address

Keywords

  • Application characterization
  • LLVM IR
  • Memory
  • Near-Memory Computing
  • Parallelism

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