Jianguo Liang , Rong Hua , Wenqiang Zhu , Yuxi Ye , You Fu , Hao Zhang
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引用次数: 1
Abstract
The Silicon-Crystal application based on molecular dynamics (MD) is used to simulate the thermal conductivity of the crystal, which adopts the Tersoff potential to simulate the trajectory of the silicon crystal. Based on the OpenACC version, to better solve the problem of discrete memory access and write dependency, task pipeline optimization and the interval graph coloring scheduling method are proposed. Also, the part of codes on CPEs is vectorized by the SIMD command to further improve the computational performance. After the collaborative development of OpenACC+Athread, the performance has been improved by 16.68 times and achieves 2.34X speedup compared with the OpenACC version. Moreover, the application is expanded to 66,560 cores and can simulate reactions of 268,435,456 silicon atoms.
期刊介绍：
Parallel Computing is an international journal presenting the practical use of parallel computer systems, including high performance architecture, system software, programming systems and tools, and applications. Within this context the journal covers all aspects of high-end parallel computing from single homogeneous or heterogenous computing nodes to large-scale multi-node systems.
Parallel Computing features original research work and review articles as well as novel or illustrative accounts of application experience with (and techniques for) the use of parallel computers. We also welcome studies reproducing prior publications that either confirm or disprove prior published results.
Particular technical areas of interest include, but are not limited to:
-System software for parallel computer systems including programming languages (new languages as well as compilation techniques), operating systems (including middleware), and resource management (scheduling and load-balancing).
-Enabling software including debuggers, performance tools, and system and numeric libraries.
-General hardware (architecture) concepts, new technologies enabling the realization of such new concepts, and details of commercially available systems
-Software engineering and productivity as it relates to parallel computing
-Applications (including scientific computing, deep learning, machine learning) or tool case studies demonstrating novel ways to achieve parallelism
-Performance measurement results on state-of-the-art systems
-Approaches to effectively utilize large-scale parallel computing including new algorithms or algorithm analysis with demonstrated relevance to real applications using existing or next generation parallel computer architectures.
-Parallel I/O systems both hardware and software
-Networking technology for support of high-speed computing demonstrating the impact of high-speed computation on parallel applications
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