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Asynchronous Workload Balancing through Persistent Work-Stealing and Offloading for a Distributed Actor Model Library

  • Technische Universität München

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

2 Zitate (Scopus)

Abstract

With dynamic imbalances caused by both software and ever more complex hardware, applications and runtime systems must adapt to dynamic load imbalances. We present a diffusion-based, reactive, fully asynchronous, and decentralized dynamic load balancer for a distributed actor library. With the asynchronous execution model, features such as remote procedure calls, and support for serialization of arbitrary types, UPC++ is especially feasible for the implementation of the actor model. While providing a substantial speedup for small-to medium-sized jobs with both predictable and unpredictable workload imbalances, the scalability of the diffusion-based approaches remains below expectations in most presented test cases.

OriginalspracheEnglisch
TitelProceedings of PAW-ATM 2022
UntertitelParallel Applications Workshop, Alternatives to MPI+X, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten39-51
Seitenumfang13
ISBN (elektronisch)9781665454100
DOIs
PublikationsstatusVeröffentlicht - 2022
Veranstaltung5th Annual IEEE/ACM Parallel Applications Workshop, Alternatives to MPI+X, PAW-ATM 2022 - Dallas, USA/Vereinigte Staaten
Dauer: 13 Nov. 202218 Nov. 2022

Publikationsreihe

NameProceedings of PAW-ATM 2022: Parallel Applications Workshop, Alternatives to MPI+X, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis

Konferenz

Konferenz5th Annual IEEE/ACM Parallel Applications Workshop, Alternatives to MPI+X, PAW-ATM 2022
Land/GebietUSA/Vereinigte Staaten
OrtDallas
Zeitraum13/11/2218/11/22

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