Amdahl's law in the context of heterogeneous many‐core systems – a survey. Issue 4 (3rd April 2020)

• Record Type: Journal Article
• Authors: Al‐hayanni, Mohammed A. Noaman; Xia, Fei; Rafiev, Ashur; Romanovsky, Alexander; Shafik, Rishad; Yakovlev, Alex
• Is Part Of: IET computers & digital techniques. Volume 14:Issue 4(2020)
• Page Start: 133
• Page End: 148
• Publication Date: 2020-04-03
• Subjects: parallel processing -- power aware computing -- multiprocessing systems; speedup models -- Amdahl's law onwards -- system execution -- heterogeneous many‐core era -- heterogeneous many‐core systems -- hallmark model -- homogeneous parallel computing resources -- heterogeneous core parallel resources -- many‐core parallel resources -- computation speedup -- system heterogeneity -- parallel fraction -- computation capability improvement index -- multifraction extensions; Computers -- Periodicals; Digital electronics -- Periodicals; Computer engineering -- Periodicals; Computer architecture -- Periodicals; Computer organization -- Periodicals; 621.39
• DOI: 10.1049/iet-cdt.2018.5220
• Languages: English
• ISSNs: 1751-8601

Abstract

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 interest in promulgating realistic extensions and assumptions in keeping with newer use cases. This study 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. The authors show that a significant portion of these studies has looked into analysing 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 optimisation of system execution, and these uses are even more important with the advent of the heterogeneous many‐core era.