ulti-threaded 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 multi-threaded 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 auto-tuning 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.

On power capping and performance optimization of multithreaded applications

Di Sanzo, Pierangelo;
2021

Abstract

ulti-threaded 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 multi-threaded 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 auto-tuning 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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/160325
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