%0 Journal Article
%A Costero Valero, Luis María
%A Igual Peña, Francisco Daniel
%A Olcoz Herrero, Katzalin
%T Dynamic power budget redistribution under a power cap on multi-application environments
%D 2023
%@ 2210-5379
%U https://hdl.handle.net/20.500.14352/98387
%X We present a two-level implementation of an infrastructure that allows performance maximization under a power-cap on multi-application environments with minimal user intervention. At the application level, we integrate bar (Power Budget-Aware Runtime Scheduler) into existing task-based runtimes, e.g. OpenMP; bar implements combined software/hardware techniques (thread malleability and DVFS) to maximize the application performance without violating a granted power budget. At a higher level, we introduce barman (Power Budget-Aware Resource Manager), a system-wide software able to manage resources globally, gathering power needs of registered applications, and redistributing the available overall power budget across them. The combination and co-operative operation of both pieces of software yields performance and energy efficiency improvements on environments in which power capping is established globally, and also granted asymmetrically to different co-existing applications. This behaviour is demonstrated to be stable under different workloads (a selection of task-based scientific applications and PARSEC benchmarks are tested) and different levels of power capping.
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