Fang, J, Huang, C, Tang, T et al. (1 more author) (2020) Parallel Programming Models for Heterogeneous Many-Cores: A Comprehensive Survey. CCF Transactions on High Performance Computing, 2. pp. 382-400. ISSN 2524-4922
Abstract
Heterogeneous many-cores are now an integral part of modern computing systems ranging from embedding systems to supercomputers. While heterogeneous many-core design offers the potential for energy-efficient high-performance, such potential can only be unlocked if the application programs are suitably parallel and can be made to match the underlying heterogeneous platform. In this article, we provide a comprehensive survey for parallel programming models for heterogeneous many-core architectures and review the compiling techniques of improving programmability and portability. We examine various software optimization techniques for minimizing the communicating overhead between heterogeneous computing devices. We provide a road map for a wide variety of different research areas. We conclude with a discussion on open issues in the area and potential research directions. This article provides both an accessible introduction to the fast-moving area of heterogeneous programming and a detailed bibliography of its main achievements.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © China Computer Federation (CCF) 2020. This is an author produced version of an article, published in CCF Transactions on High Performance Computing. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Heterogeneous computing; Many-core architectures; Parallel programming model |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 16 Apr 2020 11:50 |
Last Modified: | 05 Feb 2022 03:18 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/s42514-020-00039-4 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:159451 |