Exploring Energy Efficiency Model Generalization on Multicore Embedded Platforms

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Abstract

In this paper we investigate the relation between energy efficiency model and workload type executed in modern embedded architectures. From the energy efficiency model obtained in our previous work we select a few configuration points to verify that the prediction in terms of relative energy efficiency is maintained through different workload scenarios. A configuration point is defined as a set of platform tunable metrics, such as DVFS point, DPM level and utilization rate. As workloads, we use a combination of synthetic generators and real world applications from the embedded domain. In our experiments we use two different architectures for testing the model generality, which provide examples of real systems. First we have a comparison of the efficiency obtained by the two architecturally different chips (ARM and INTEL) in different configuration points and different workload scenarios. Second we try to explain the different results through the thermal management done by the two different chips. At the end we show that only in the case of workloads highly composed by integer instructions the results from the two architectures converge and show the need for a specific model trained with integer operations.
Original languageUndefined/Unknown
Title of host publication26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)
PublisherIEEE
Pages494–498
Number of pages5
ISBN (Electronic)978-1-5386-4975-6
ISBN (Print)978-1-5386-4976-3
DOIs
Publication statusPublished - 2018
MoE publication typeA4 Article in a conference publication
EventEuromicro International Conference on Parallel, Distributed and Network-based Processing (PDP) - Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)
Duration: 21 Mar 201823 Mar 2018

Conference

ConferenceEuromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)
Period21/03/1823/03/18

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