gpu上分子力学的迭代诱导偶极子计算

GPGPU-3 Pub Date : 2010-03-14 DOI:10.1145/1735688.1735708
F. Pratas, R. Mata, L. Sousa
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引用次数: 5

摘要

在这项工作中,我们提出了用GPU加速有效实现极化分子力学力场的第一步。这种应用的计算瓶颈是在静电处理中发现的,其中需要高阶多极和极化效应的自洽处理。对于非周期性模拟的情况,我们已经用CUDA编程模型对这些部分进行了编码。结果显示,与串行CPU版本相比,单精度GPU实现的加速因子为21。讨论了优化和参数化步骤。对不同显卡和共享内存并行CPU的实现进行了比较。目前的工作证明了GPU编程在加速这一应用领域的潜在用途。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Iterative induced dipoles computation for molecular mechanics on GPUs
In this work, we present a first step towards the efficient implementation of polarizable molecular mechanics force fields with GPU acceleration. The computational bottleneck of such applications is found in the treatment of electrostatics, where higher-order multipoles and a self-consistent treatment of polarization effects are needed. We have coded these sections, for the case of a non-periodic simulation, with the CUDA programming model. Results show a speedup factor of 21 for a single precision GPU implementation, when comparing to the serial CPU version. A discussion of the optimization and parameterization steps is included. Comparison between different graphic cards and a shared memory parallel CPU implementation is also given. The current work demonstrates the potential usefulness of GPU programming in accelerating this field of applications.
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