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On power capping and performance optimization of multithreaded applications
Author(s) -
Conoci Stefano,
Di Sanzo Pierangelo,
Pellegrini Alessandro,
Ciciani Bruno,
Quaglia Francesco
Publication year - 2021
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.6205
Subject(s) - computer science , software portability , multi core processor , workload , distributed computing , benchmark (surveying) , limiting , heuristic , power (physics) , multithreading , efficient energy use , computer engineering , embedded system , computer architecture , parallel computing , operating system , thread (computing) , artificial intelligence , engineering , mechanical engineering , physics , geodesy , quantum mechanics , geography , electrical engineering
Summary Multithreaded applications facilitate the exploitation of the computing power of multicore architectures. On the other hand, these applications can become extremely energy‐intensive, in contrast with the need for limiting the energy usage of computing systems. In this article, we explore the design of techniques enabling multithreaded applications to maximize their performance under a power cap. We consider two control parameters: the number of cores used by the application, and the core power state. We target the design of an autotuning power‐capping technique with minimal intrusiveness and high portability, which is agnostic about the workload profile of the application. We investigate two different approaches for building the strategy for selecting the best configuration of the parameters under control, namely a heuristic approach and a model‐based approach. Through an extensive experimental study, we evaluate the effectiveness of the proposed technique considering two different selection strategies, and we compare them with existing solutions.