JOURNAL ARTICLE

Mitigating execution unit contention in parallel applications using instruction‐aware mapping.

  • Published In: Concurrency & Computation: Practice & Experience, 2023, v. 35, n. 17. P. 1 1 of 3

  • Database: Applied Science & Technology Source Ultimate 2 of 3

  • Authored By: Serpa, Matheus S.; Cruz, Eduardo H. M.; Diener, Matthias; Lorenzon, Arthur F.; Beck, Antonio C. S.; Navaux, Philippe O. A. 3 of 3

Abstract

Summary: Parallel applications running on simultaneous multithreading (SMT) processors naturally compete for execution units when their threads are mapped to the same core. This issue is further aggravated when such threads execute similar instructions that stress the same execution unit type, making their execution to behave very similarly as if the threads were running sequentially. This, in turn, will lead to performance degradation and underutilization of hardware resources. This work proposes a completely transparent framework (no modifications to the source code are necessary) that automatically maps threads of multiple parallel applications on SMT processors. The framework focuses on improving performance by mitigating the contention on execution units, considering each thread's instruction types, which are detected at runtime by our framework. Results show performance gains of 21% (geometric mean), compared to the native scheduler of the operating system. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Concurrency & Computation: Practice & Experience. 2023/08, Vol. 35, Issue 17, p1
  • Document Type:Article
  • Subject Area:Computer Science
  • Publication Date:2023
  • ISSN:15320626
  • DOI:10.1002/cpe.6819
  • Accession Number:164877561
  • Copyright Statement:Copyright of Concurrency & Computation: Practice & Experience is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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