Quantum Chemistry for Solvated Molecules on Graphical Processing Units Using Polarizable Continuum Models
Quantum Chemistry for Solvated Molecules on Graphical Processing Units Using Polarizable Continuum Models
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DOI：
10.1021/acs.jctc.5b00370
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发表时间：
2015-07-01
影响因子：
5.5
通讯作者：
Martinez, Todd J.
中科院分区：
文献类型：
--
作者：
Liu, Fang;Luehr, Nathan;Martinez, Todd J.
类导体极化模型（C-PCM）是一种广泛应用于化学模拟的隐式溶剂化模型。然而，它在大规模生物分子系统的量子力学计算中的应用可能受到气相电子结构和溶剂化相互作用的计算费用的限制。我们以前使用图形处理单元（GPU）来加速这些步骤中的第一步。在这里，我们扩展了GPU的使用，以加速电子结构计算，包括C-PCM拯救。在GPU上实施可以显着加速C-PCM所需积分的生成。我们进一步提出了两种策略，以提高所需的线性方程组的解决方案：动态收敛阈值和随机块雅可比预条件。这些策略并不特定于GPU，预计对CPU和GPU实现都有好处。我们使用溶剂环境中的20多种小蛋白质对新实现的性能进行基准测试。使用一个单一的GPU，我们的方法评估的C-PCM相关的积分及其导数超过10倍的速度比传统的基于CPU的实现。我们对线性求解器的改进提供了进一步的3倍加速。对于中等基组和分子表面离散化水平，包括C-PCM溶剂化的总体计算通常需要比其气相对应物多20-40%的努力。C-PCM溶剂化校正的相对成本随着基组和/或腔半径的增加而降低。因此，该模型对溶剂化反应的描述应是常规的。我们还讨论了淀粉样纤维的构象景观的研究应用。
The conductor-like polarization model (C-PCM) with switching/Gaussian smooth discretization is a widely used implicit solvation model in chemical simulations. However, its application in quantum mechanical calculations of large-scale biomolecular systems can be limited by computational expense of both the gas phase electronic structure and the solvation interaction. We have previously used graphical processing units (GPUs) to accelerate the first of these steps. Here, we extend the use of GPUs to accelerate electronic structure calculations including C-PCM salvation. Implementation on the GPU leads to significant acceleration of the generation of the required integrals for C-PCM. We further propose two strategies to improve the solution of the required linear equations: a dynamic convergence threshold and a randomized block-Jacobi preconditioner. These strategies are not specific to GPUs and are expected to be beneficial for both CPU and GPU implementations. We benchmark the performance of the new implementation using over 20 small proteins in solvent environment. Using a single GPU, our method evaluates the C-PCM related integrals and their derivatives more than 10X faster than that with a conventional CPU-based implementation. Our improvements to the linear solver provide a further 3x acceleration. The overall calculations including C-PCM solvation require, typically, 20-40% more effort than that for their gas phase counterparts for a moderate basis set and molecule surface discretization level. The relative cost of the C-PCM solvation correction decreases as the basis sets and/or cavity radii increase. Therefore, description of solvation with this model should be routine. We also discuss applications to the study of the conformational landscape of an amyloid fibril.