Parallel programming models for heterogeneous many-cores: a comprehensive survey

Jianbin Fang, Chun Huang, Tao Tang, Zheng Wang
<span title="2020-07-31">2020</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/oyzrfqv3i5ghbipholgpvqu37y" style="color: black;">CCF Transactions on High Performance Computing</a> </i> &nbsp;
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
more &raquo; ... 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.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s42514-020-00039-4">doi:10.1007/s42514-020-00039-4</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nn56xhjm6rcu7kya6gfnyjg66q">fatcat:nn56xhjm6rcu7kya6gfnyjg66q</a> </span>
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