Experimental Study of Power Consumption of Basic Parallel Programs

Parallelism is now a standard from the hardware standpoint considering the multicore nature of current processors and their vector processing feature. Beside somehow following Moore's Law and/or running faster, the design of multicore processors was also driven by energy concern. With an increasing number of cores per chip and wider SIMD capabilities, the question of how the corresponding parallelism is related to power consumption is important for energy-aware parallel implementation. The goal of this work is to provide from experimentation some basic insights on the power consumption pattern related to the aforementioned levels of parallelism including accelerated-computing with GPUs.

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Published
2024-11-13
DOI
https://doi.org/10.1109/sbac-padw64858.2024.00016
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Experimental Study of Power Consumption of Basic Parallel Programs

Claude Tadonki, Roblex Nana Tchakoute
Parallel Computing and Optimization Techniques
article

Experimental Study of Power Consumption of Basic Parallel Programs

Claude Tadonki, Roblex Nana Tchakoute
article en

Abstract

Parallelism is now a standard from the hardware standpoint considering the multicore nature of current processors and their vector processing feature. Beside somehow following Moore's Law and/or running faster, the design of multicore processors was also driven by energy concern. With an increasing number of cores per chip and wider SIMD capabilities, the question of how the corresponding parallelism is related to power consumption is important for energy-aware parallel implementation. The goal of this work is to provide from experimentation some basic insights on the power consumption pattern related to the aforementioned levels of parallelism including accelerated-computing with GPUs.

Centre de Recherche en Informatique (FR)
Centre National de la Recherche Scientifique, Université de Recherche Paris Sciences et Lettres
Affordable and clean energy
Openalex Percentile: Top 78%
Parallel Computing and Optimization Techniques
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