Comparing Three Clustering-based Scheduling Methods for Energy-Aware Rapid Design of MP2SoCs

Ammar, M.; Baklouti, Mouna; Pelcat, Maxime; Desnos, Karol; Abid, Mohamed

doi:10.1007/s11265-017-1261-7

Cited by 1 publication

(1 citation statement)

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“…YARTISS [4,5] evaluates scheduling algorithms considering overheads and effects due to the target hardware platform; in this simulator, energy consumption is an optional parameter associated with each task. Finally, the EWARDS framework [1] explores at design time the performance and energy capabilities of modern Massively Parallel Multi-Processors Systemon-Chip (MP2SoC) architectures. It combines power management techniques with clustering-based scheduling and extends MARTE with power aspects typical of MP2SoC systems, with the ultimate goal of saving energy at runtime.…”

Section: Related Workmentioning

confidence: 99%

Simulating execution time and power consumption of real-time tasks on embedded platforms

Ara

Cucinotta

Mascitti

2022

Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing

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In this paper, we present PARTSim, an open-source power/thermalaware simulator for embedded real-time systems. This tool is a fork of the well-known RTSim simulator, which can simulate the timing behavior of a set of real-time tasks with various characteristics when running on a multi-processor platform in presence of a number of real-time scheduling policies. PARTSim extends the functionality of RTSim by introducing support for power-aware embedded platforms exhibiting frequency scaling and specific architectural patterns like the ARM big.LITTLE and DynamIQ ones. Experimental results that compare simulated data against execution profiles collected on real platforms show a simulation error under 10 % for both execution time and power consumption at 90th percentile when simulating the effects of DVFS. CCS CONCEPTS• Computer systems organization ✙ Embedded systems; Realtime system architecture; • Software and its engineering ✙Scheduling; Power management; • Hardware ✙ Temperature simulation and estimation; Power estimation and optimization;

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Section: Related Workmentioning

confidence: 99%