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A novel parallel finite element procedure for nonlinear dynamic problems using GPU and mixed-precision algorithm

机译:一种新的PPU和混合精密算法非线性动态问题的新颖平行有限元过程

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PurposeThe purpose of this paper is to improve the computational speed of solving nonlinear dynamics by using parallel methods and mixed-precision algorithm on graphic processing units (GPUs). The computational efficiency of traditional central processing units (CPUs)-based computer aided engineering software has been difficult to satisfy the needs of scientific research and practical engineering, especially for nonlinear dynamic problems. Besides, when calculations are performed on GPUs, double-precision operations are slower than single-precision operations. So this paper implemented mixed precision for nonlinear dynamic problem simulation using Belytschko-Tsay (BT) shell element on GPU.Design/methodology/approachTo minimize data transfer between heterogeneous architectures, the parallel computation of the fully explicit finite element (FE) calculation is realized using a vectorized thread-level parallelism algorithm. An asynchronous data transmission strategy and a novel dependency relationship link-based method, for efficiently solving parallel explicit shell element equations, are used to improve the GPU utilization ratio. Finally, this paper implements mixed precision for nonlinear dynamic problems simulation using the BT shell element on a GPU and compare it to the CPU-based serially executed program and a GPU-based double-precision parallel computing program.FindingsFor a car body model containing approximately 5.3 million degrees of freedom, the computational speed is improved 25 times over CPU sequential computation, and approximately 10% over double-precision parallel computing method. The accuracy error of the mixed-precision computation is small and can satisfy the requirements of practical engineering problems.Originality/valueThis paper realized a novel FE parallel computing procedure for nonlinear dynamic problems using mixed-precision algorithm on CPU-GPU platform. Compared with the CPU serial program, the program implemented in this article obtains a 25 times acceleration ratio when calculating the model of 883,168 elements, which greatly improves the calculation speed for solving nonlinear dynamic problems.
机译:本文的目的目的是通过使用平行方法和图形处理单元(GPU)上的混合精密算法来提高非线性动力学的计算速度。基于中央加工单元(CPU)的计算机辅助工程软件的计算效率难以满足科研实用工程的需求,特别是对于非线性动态问题。此外,当对GPU进行计算时,双精度操作比单精度操作慢。因此,本文利用GPU.Design/Methodology/ApproChto最小化异构架构之间的数据传输,实现了对非线性动态问题模拟的混合精度,使用Belytschko-Tsay(BT)shell元素来最大限度地减少了异构架构之间的数据传输使用矢量化线程并行算法。用于有效地解决并行显式外壳元件方程的异步数据传输策略和基于新颖的依赖关系链路的方法来提高GPU利用率。最后,本文使用GPU上的BT Shell元件实现了非线性动态问题的混合精度,并将其与基于CPU的串行执行程序和基于GPU的双精度并行计算程序进行比较.FindingsFor Afta 530万自由度,计算速度超过CPU顺序计算的25倍,并且通过双精度并行计算方法大约10%。混合精密计算的精度误差很小,可以满足实际工程问题的要求。以CPU-GPU平台的混合精密算法实现了用于非线性动态问题的新型FE Parallic动态问题的新型FEParate计算过程。与CPU串行程序相比,本物品中实施的程序在计算883,168元素的型号时获得了25倍的加速度,这大大提高了解决非线性动态问题的计算速度。

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