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The Journal of Supercomputing
Erschienen in: The Journal of Supercomputing 2/2021

28.05.2020

A systematic literature review on hardware implementation of artificial intelligence algorithms

verfasst von: Manar Abu Talib, Sohaib Majzoub, Qassim Nasir, Dina Jamal

Erschienen in: The Journal of Supercomputing | Ausgabe 2/2021

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Abstract

Artificial intelligence (AI) and machine learning (ML) tools play a significant role in the recent evolution of smart systems. AI solutions are pushing towards a significant shift in many fields such as healthcare, autonomous airplanes and vehicles, security, marketing customer profiling and other diverse areas. One of the main challenges hindering the AI potential is the demand for high-performance computation resources. Recently, hardware accelerators are developed in order to provide the needed computational power for the AI and ML tools. In the literature, hardware accelerators are built using FPGAs, GPUs and ASICs to accelerate computationally intensive tasks. These accelerators provide high-performance hardware while preserving the required accuracy. In this work, we present a systematic literature review that focuses on exploring the available hardware accelerators for the AI and ML tools. More than 169 different research papers published between the years 2009 and 2019 are studied and analysed.
Vorheriger Artikel High throughput BLAST algorithm using spark and cassandra
Nächster Artikel TAMER: an adaptive task allocation method for aging reduction in multi-core embedded real-time systems

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Metadaten
Titel
A systematic literature review on hardware implementation of artificial intelligence algorithms
verfasst von
Manar Abu Talib
Sohaib Majzoub
Qassim Nasir
Dina Jamal
Publikationsdatum
28.05.2020
Verlag
Springer US
Erschienen in
The Journal of Supercomputing / Ausgabe 2/2021
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-020-03325-8

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