PeriPy - A high performance OpenCL peridynamics package
PeriPy - A high performance OpenCL peridynamics package
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PeriPy - 高性能 OpenCL 近场动力学软件包
DOI：
10.1016/j.cma.2021.114085
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发表时间：
2021
影响因子：
7.2
通讯作者：
Boys B
中科院分区：
文献类型：
--
作者：
Boys B
本文介绍了一个轻量级的，开源的，高性能的Python包，用于解决固体力学中的周波问题。该求解器的开发是出于对快速分析工具的需求，以实现“外环”应用所需的大量模拟，包括灵敏度分析，不确定性量化和优化。我们的python软件工具箱利用了OpenCL的异构性，因此它可以在任何具有CPU或GPU内核的平台上执行。我们通过一系列的工业动机的例子，这应该使其他研究人员建立和扩展求解器在自己的应用程序中使用说明包的使用。在执行速度和功能上的改进步骤超过现有的技术。这个求解器和现有的OpenCL实现在文献中的比较，测试的基准测试与数十万到数千万的节点。我们展示了NVIDIA的GeForce RTX 2080 TiGPU上的求解器的可扩展性，并分析了内存限制。在所有测试用例中，该实现比文献中类似的现有GPU实现快1.4到10.0倍。特别是，这种改进是通过利用GPU上的本地存储器实现的。
This paper presents a lightweight, open-source and high-performance python package for solving peridynamics problems in solid mechanics. The development of this solver is motivated by the need for fast analysis tools to achieve the large number of simulations required for‘outer-loop’applications, including sensitivity analysis, uncertainty quantification and optimisation. Our python software toolbox utilises the heterogeneous nature ofOpenCLso that it can be executed on any platform with CPU or GPU cores. We illustrate the package use through a range of industrially motivated examples, which should enable other researchers to build on and extend the solver for use in their own applications. Step improvements in execution speed and functionality over existing techniques are presented. A comparison between this solver and an existingOpenCLimplementation in the literature is presented, tested on benchmarks with hundreds of thousands to tens of millions of nodes. We demonstrate the scalability of the solver on the GeForce RTX 2080 TiGPU from NVIDIA, and the memory-bound limitations are analysed. In all test cases, the implementation is between 1.4 and 10.0 times faster than a similar existing GPU implementation in the literature. In particular, this improvement has been achieved by utilising local memory on the GPU.