CUDA 在计算物理学方面的进展

Delia Spiridon
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引用次数: 0

摘要

图形处理器(GPU)的发展为软件开发人员提供了通过使用 GPU 编程对算法进行大规模并行化来提高程序执行速度的机会。英伟达公司开发了一种用于并行计算的架构,名为 "计算统一设备架构"(CUDA),其中包括一套CUDA指令和用于并行计算的硬件。计算物理学是一个正在不断发展的跨学科领域,它研究、开发和优化数值算法和计算技术,并将其应用于解决各种物理问题。计算物理学适用于物理学的所有分支和相关领域,如:生物物理学、天体物理学、等离子体物理学、生物力学、流体物理学等。此外,随着过去几十年技术的发展,这一相对较新的领域有助于快速获得这些领域的成果,促进理论物理与实验物理之间的联系。本文回顾了利用 CUDA 架构 GPU 计算在计算物理学领域取得的一些最新研究和成果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advances in CUDA for computational physics
Advances in the graphics processing unit (GPU) development led to the opportunity for software developers to increase the execution speed for their programs by massive parallelization of the algorithms using GPU programming. NVIDIA company developed an arhitecture for parallel computing named Compute Unified Device Architecture (CUDA) which includes a set of CUDA instructions and the hardware for parallel computing. Computational Physics is an interdisciplinary field which is in continuous progress and which studies, develops and optimizes numerical algorithms and computational techniques for their application in solving various physics problems. Computational Physics has applicability in all sub-branches of physics and related fields such as: biophysics, astrophysics, plasma physics, biomechanics, fluid physics, etc. Moreover, with the evolution of technology in the last few decades, this relatively new field has helped to quickly obtain results in these fields, facilitating the connection between theoretical and experimental physics. In this paper, some of the latest researches and results obtained in computational physics by using GPU computing with CUDA architecture are reviewed.
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