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Amdahl’s law in the context of heterogeneous many-core systems – a survey

Lookup NU author(s): Mohammed Al-Hayanni, Dr Fei Xia, Dr Ashur Rafiev, Professor Alexander Romanovsky, Dr Rishad Shafik, Professor Alex Yakovlev

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This is the authors' accepted manuscript of an article that has been published in its final definitive form by IET, 2020.

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Abstract

For over 50 years, Amdahl’s Law has been the hallmark model for reasoning about performance bounds for homogeneous parallel computing resources. As heterogeneous, many-core parallel resources continue to permeate into the modern server and embedded domains, there has been growing interests in promulgating realistic extensions and assumptions in keeping with newer use cases. This paper aims to provide a comprehensive review of the purviews and insights provided by the extensive body of work related to Amdahl’s Law to date, focusing on computation speedup. We show that a significant portion of these studies has looked into analyzing the scalability of the model considering both workload and system heterogeneity in real-world applications. The focus has been to improve the definition and semantic power of the two key parameters in the original model: the parallel fraction (f) and the computation capability improvement index (n). More recently, researchers have shown normal-form and multi-fraction extensions that can account for wider ranges of heterogeneity, validated on many-core systems running realistic workloads. Speedup models from Amdahl’s Law onwards have seen a wide range of uses such as the optimization of system execution, and these uses are even more important with the advent of the heterogeneous many-core era.


Publication metadata

Author(s): Al-Hayanni MAN, Xia F, Rafiev R, Romanovsky A, Shafik R, Yakovlev A

Publication type: Article

Publication status: Published

Journal: IET Computers & Digital Techniques

Year: 2020

Volume: 14

Issue: 4

Pages: 133-148

Print publication date: 01/07/2020

Online publication date: 24/02/2020

Acceptance date: 27/01/2020

Date deposited: 07/02/2020

ISSN (print): 1751-8601

ISSN (electronic): 1751-861X

Publisher: IET

URL: https://doi.org/10.1049/iet-cdt.2018.5220

DOI: 10.1049/iet-cdt.2018.5220


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