利用浮动电荷力场对N-甲基乙酰胺水溶液的分子动力学模拟

利用原子键电负性均衡结合分子力场方法(ABEEM/MM)对N-甲基乙酰胺(NMA)分子的水溶液体系进行了分子动力学模拟. 与经典的力场模型相比, 该方法中的静电势包含了分子内和分子间的静电极化作用, 以及分子内电荷转移影响, 同时加入了化学键等非原子中心电荷位点, 合理体现了分子中的电荷分布. 相对其它极化力场模型, 该模型具有计算量较小的特点. 在该模型下对NMA纯溶液和其水溶液体系进行了分子动力学模拟, 得到的径向分布函数、汽化热和偶极矩等物理量与实验值和其它极化力场方法符合很好, 合理描述了溶质与溶剂之间的静电极化和分子内的电荷转移.     

GPU引发的计算化学革命

综述了图形处理器(GPU)在计算化学中的应用和进展.首先简单介绍了GPU在科学计算中应用的发展,然后分别详细讲述了迄今几个使用GPU和CUDA(compute unified device architecture,显卡厂商Nvidia推出的计算平台)开发工具设计的量子化学计算和分子动力学(MD)模拟的算法和程序,尤其对目前唯一完全使用GPU技术开发的量子化学计算软件TeraChem做了完备的介绍,包括算法、实现的细节和程序目前的功能.此外,本文还对GPU在计算化学上将会发挥的作用做出了极为乐观的展望.     

新型胍盐离子液体剪切粘度性质的预测

[guanidinium]^＋[Tf₂N]^－是一类可应用于锂离子电池电解液的新型胍盐离子液体. 针对该类九种胍盐离子液体, 基于全原子分子力场, 采用非平衡分子动力学(周期性微扰方法)对其剪切粘度进行了计算和预测. 讨论了模拟尺寸、稳态速度场以及力场参数对模拟结果的影响. 计算结果很好的体现出剪切粘度系数随着温度以及分子尺寸大小的变化趋势. 利用周期性微扰线性外推的方法计算得到的粘度系数与实验值吻合良好, 在353 K下的最大偏差在12%以内.     

乙醇醛的分子动态结构

以量子化学计算作为起点, 为最简单的糖类分子——乙醇醛开发了两套分子力学力场参数: 基于肽类的力场和基于醛类的力场. 分子动力学模拟结果表明, 所开发的类醛力场参数能够较好地描述乙醇醛分子在水中的结构以及水分子在其周围的分布. 通过瞬时简正模式分析, 得到了3N-6个模式的瞬时振动频率和振动跃迁偶极矩等振动光谱参数的统计分布及其相关性. 结合量子化学计算和分子动力学模拟对生物分子体系的多元振动光谱参数进行预测和评估, 为从化学键水平出发模拟宽带飞秒二维红外相关光谱提供了一个新方法.     

分子动力学研究2-乙酸苯并噻吩在HIV-1蛋白酶与抑制剂结合中的作用

为了研究别构小分子2-乙酸苯并噻吩(2FX)在HIV-1蛋白酶与抑制剂结合中的作用, 利用分子动力学方法分别对未结合和结合2FX的HIV-1蛋白酶抑制剂体系进行了100 ns的模拟, 模拟计算中对每种体系均采用两种新的分子力场ff99SBildn和ff12SB. 研究了2FX对体系构象的影响和两体系在不同力场下的动力学行为, 分析了两体系的均方根偏差和残基的B因子, 比较了计算结构和晶体结构, 最后采用MM-PB/GBSA两种方法计算了两体系的结合自由能. 研究表明, 两种力场计算的结果虽有差异, 但都说明2FX的结合导致蛋白酶构象的变化, 使得体系更加稳定, 尤其是flap的柔性减弱, 使得蛋白酶和抑制剂的结合更牢固; 另外, 还发现ff12SB力场动力学过程更稳定. 研究结果有助于为设计新的别构抑制剂提供理论依据.     

对高分子体系进行分子动力学模拟方法的研究

以单链聚乙烯为例,研究了多种对高分子体系进行分子动力学模拟的方法.结果表明,不同的力场条件可以导致明显不同的结果.在使用OPLS力场的真空条件下.在100K体系出现了玻璃化现象,在200和300K条件下体系出现了局部结晶现象,而在400和500K体系出现了熔化现象.在给定体系中加入周期性边界和在300K下进行分子动力学模拟,无序和结晶状态都具有一定的稳定性.     

表面活性剂溶液行为的粗粒化模拟

分子动力学模拟技术目前已经成为了研究表面活性剂有序聚集体的不可或缺的工具之一。近几年来,粗粒化模拟方法克服了传统的介观模拟和精细力场模拟的缺点,既能够重现自组装体系的热力学或者结构方面的信息,又极大地拓展了模拟体系所能达到的空间和时间尺度,逐渐成为了计算领域的一个热点。本文综述了近几年来表面活性剂粗粒化分子动力学模拟的最新发展状况,分别就不同粗粒化模型的建模策略、作用势能表达、参数拟合和模型评价等问题作了详细的介绍,并通过实例说明了粗粒化力场对表面活性剂体系的适用性。在此基础上,指出了发展粗粒化力场过程中所面临的一些关键性问题,这对于表面活性剂溶液行为的粗粒化模拟具有重要的意义。     

基本不变量神经网络解析梯度方法的研究

提升势能面的运行速度对于动力学模拟至关重要. 相对于计算简单、 但耗时更长的数值梯度计算, 直接求解势能面梯度的解析公式能够大幅提高势能面的运行效率. 本文发展了基本不变量神经网络解析梯度的生成方法. 计算解析梯度的代码可以通过程序自动生成. 对大量数据点进行测试后, 证明了该方法可以得到正确的势能面梯度输出结果. 通过测试不同势能面的调用时间, 发现采用解析梯度方法能够带来10倍以上的性能提升. 随着体系的增大, 这种性能提升也会越明显.     

基于图形处理单元与密度拟合近似的单精度耦合簇CCSD和CCSD(T)程序

作者此前工作表明, 在耦合簇CCSD (Coupled-Cluster approaches within the singles and doubles approximation)与CCSD(T) (CCSD approaches augmented by a perturbative treatment of triple excitations)计算中结合单精度数与消费型图形处理单元(GPU), 可以显著提高计算速度. 然而由于CCSD(T)计算对内存的巨大需求以及消费型GPU的内存限制, 在利用消费型GPU进行加速时, 不考虑利用空间对称性的情况下, 此前开发的CCSD(T)程序仅能用于计算300~400个基函数的体系. 利用密度拟合(Density-Fitting, DF)处理双电子积分可以显著降低CCSD(T)计算过程中的内存需求, 本工作发展了基于密度拟合近似并结合单精度数进行运算的DF-CCSD(T)程序, 该程序可用于包含700个基函数的无对称性体系的单点能计算, 以及包含1700个基函数的有对称性体系. 本工作所使用的计算节点配置了型号为Intel I9-10900k的CPU和型号为RTX3090的GPU, 与用双精度数在CPU上的计算相比, 利用单精度数结合GPU进行运算可以将CCSD的计算速度提升16倍, (T)部分可提升40倍左右, 而使用单精度数引入的误差可忽略不计. 在程序开发过程中, 作者发展了一套可利用GPU或CPU结合单精度数或双精度数进行含空间对称性的矩阵操作代码库. 基于该套代码库, 可以显著降低开发含空间对称性的耦合簇代码的难度.     

环多肽晶体的浮动电荷极化力场模拟

利用原子键电负性均衡结合分子力场方法(ABEEM/MM)对五种环多肽晶体进行了研究. 与传统力场相比, 该方法中的静电势包含了分子内和分子间的静电极化作用, 以及分子内电荷转移影响, 同时加入了化学键等非原子中心电荷位点, 合理地体现了分子中的电荷分布. 相对其他极化力场模型, 具有计算量较小的特点. 该模型下计算得到的环多肽分子单元相对实验测得的结构的原子位置、氢键长度和二面角的均方根偏差分别为0.009 nm、0.013 nm和5.16°, 能够很好地重复实验结果. 总体上, 其结果优于或相当于其他力场模型, 适用于对实际蛋白质体系的模拟和研究.     

Performance of heterogeneous computing with graphics processing unit and many integrated core for hartree potential calculations on a numerical grid

We investigated the performance of heterogeneous computing with graphics processing units (GPUs) and many integrated core (MIC) with 20 CPU cores (20×CPU). As a practical example toward large scale electronic structure calculations using grid‐based methods, we evaluated the Hartree potentials of silver nanoparticles with various sizes (3.1, 3.7, 4.9, 6.1, and 6.9 nm) via a direct integral method supported by the sinc basis set. The so‐called work stealing scheduler was used for efficient heterogeneous computing via the balanced dynamic distribution of workloads between all processors on a given architecture without any prior information on their individual performances. 20×CPU + 1GPU was up to ～1.5 and ～3.1 times faster than 1GPU and 20×CPU, respectively. 20×CPU + 2GPU was ～4.3 times faster than 20×CPU. The performance enhancement by CPU + MIC was considerably lower than expected because of the large initialization overhead of MIC, although its theoretical performance is similar with that of CPU + GPU. © 2016 Wiley Periodicals, Inc.     

GPU accelerated implementation of NCI calculations using promolecular density

The NCI approach is a modern tool to reveal chemical noncovalent interactions. It is particularly attractive to describe ligand–protein binding. A custom implementation for NCI using promolecular density is presented. It is designed to leverage the computational power of NVIDIA graphics processing unit (GPU) accelerators through the CUDA programming model. The code performances of three versions are examined on a test set of 144 systems. NCI calculations are particularly well suited to the GPU architecture, which reduces drastically the computational time. On a single compute node, the dual‐GPU version leads to a 39‐fold improvement for the biggest instance compared to the optimal OpenMP parallel run (C code, icc compiler) with 16 CPU cores. Energy consumption measurements carried out on both CPU and GPU NCI tests show that the GPU approach provides substantial energy savings. © 2017 Wiley Periodicals, Inc.     

Accelerating VASP electronic structure calculations using graphic processing units

We present a way to improve the performance of the electronic structure Vienna Ab initio Simulation Package (VASP) program. We show that high-performance computers equipped with graphics processing units (GPUs) as accelerators may reduce drastically the computation time when offloading these sections to the graphic chips. The procedure consists of (i) profiling the performance of the code to isolate the time-consuming parts, (ii) rewriting these so that the algorithms become better-suited for the chosen graphic accelerator, and (iii) optimizing memory traffic between the host computer and the GPU accelerator. We chose to accelerate VASP with NVIDIA GPU using CUDA. We compare the GPU and original versions of VASP by evaluating the Davidson and RMM-DIIS algorithms on chemical systems of up to 1100 atoms. In these tests, the total time is reduced by a factor between 3 and 8 when running on n (CPU core + GPU) compared to n CPU cores only, without any accuracy loss. © 2012 Wiley Periodicals, Inc.     

Massively parallel algorithm and implementation of RI‐MP2 energy calculation for peta‐scale many‐core supercomputers

A new parallel algorithm and its implementation for the RI‐MP2 energy calculation utilizing peta‐flop‐class many‐core supercomputers are presented. Some improvements from the previous algorithm (J. Chem. Theory Comput. 2013, 9, 5373) have been performed: (1) a dual‐level hierarchical parallelization scheme that enables the use of more than 10,000 Message Passing Interface (MPI) processes and (2) a new data communication scheme that reduces network communication overhead. A multi‐node and multi‐GPU implementation of the present algorithm is presented for calculations on a central processing unit (CPU)/graphics processing unit (GPU) hybrid supercomputer. Benchmark results of the new algorithm and its implementation using the K computer (CPU clustering system) and TSUBAME 2.5 (CPU/GPU hybrid system) demonstrate high efficiency. The peak performance of 3.1 PFLOPS is attained using 80,199 nodes of the K computer. The peak performance of the multi‐node and multi‐GPU implementation is 514 TFLOPS using 1349 nodes and 4047 GPUs of TSUBAME 2.5. © 2016 Wiley Periodicals, Inc.     

High-performance transformation of protein structure representation from internal to Cartesian coordinates

We present a highly parallel algorithm to convert internal coordinates of a polymeric molecule into Cartesian coordinates. Traditionally, converting the structures of polymers (e.g., proteins) from internal to Cartesian coordinates has been performed serially, due to an inherent linear dependency along the polymer chain. We show this dependency can be removed using a tree-based concatenation of coordinate transforms between segments, and then parallelized efficiently on graphics processing units (GPUs). The conversion algorithm is applicable to protein engineering and fitting protein structures to experimental data, and we observe an order of magnitude speedup using parallel processing on a GPU compared to serial execution on a CPU.     

Acceleration of a QM/MM‐QMC simulation using GPU

We accelerated an ab initio molecular QMC calculation by using GPGPU. Only the bottle‐neck part of the calculation is replaced by CUDA subroutine and performed on GPU. The performance on a (single core CPU + GPU) is compared with that on a (single core CPU with double precision), getting 23.6 (11.0) times faster calculations in single (double) precision treatments on GPU. The energy deviation caused by the single precision treatment was found to be within the accuracy required in the calculation, ～10^?5 hartree. The accelerated computational nodes mounting GPU are combined to form a hybrid MPI cluster on which we confirmed the performance linearly scales to the number of nodes. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011     

Acceleration of the GAMESS‐UK electronic structure package on graphical processing units

The approach used to calculate the two‐electron integral by many electronic structure packages including generalized atomic and molecular electronic structure system‐UK has been designed for CPU‐based compute units. We redesigned the two‐electron compute algorithm for acceleration on a graphical processing unit (GPU). We report the acceleration strategy and illustrate it on the (ss|ss) type integrals. This strategy is general for Fortran‐based codes and uses the Accelerator compiler from Portland Group International and GPU‐based accelerators from Nvidia. The evaluation of (ss|ss) type integrals within calculations using Hartree Fock ab initio methods and density functional theory are accelerated by single and quad GPU hardware systems by factors of 43 and 153, respectively. The overall speedup for a single self consistent field cycle is at least a factor of eight times faster on a single GPU compared with that of a single CPU. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011     

GPU accelerated numerical simulations of viscoelastic phase separation model

We introduce a complete implementation of viscoelastic model for numerical simulations of the phase separation kinetics in dynamic asymmetry systems such as polymer blends and polymer solutions on a graphics processing unit (GPU) by CUDA language and discuss algorithms and optimizations in details. From studies of a polymer solution, we show that the GPU-based implementation can predict correctly the accepted results and provide about 190 times speedup over a single central processing unit (CPU). Further accuracy analysis demonstrates that both the single and the double precision calculations on the GPU are sufficient to produce high-quality results in numerical simulations of viscoelastic model. Therefore, the GPU-based viscoelastic model is very promising for studying many phase separation processes of experimental and theoretical interests that often take place on the large length and time scales and are not easily addressed by a conventional implementation running on a single CPU.     

Accelerated Simulation Study of Space Charge Effects in Quadrupole Ion Traps Using GPU Techniques

Space charge effects play important roles in the performance of various types of mass analyzers. Simulation of space charge effects is often limited by the computation capability. In this study, we evaluate the method of using graphics processing unit (GPU) to accelerate ion trajectory simulation. Simulation using GPU has been compared with multi-core central processing unit (CPU), and an acceleration of about 390 times have been obtained using a single computer for simulation of up to 10⁵ ions in quadrupole ion traps. Characteristics of trapped ions can be investigated at detailed levels within a reasonable simulation time. Space charge effects on the trapping capacities of linear and 3D ion traps, ion cloud shapes, ion motion frequency shift, mass spectrum peak coalescence effects between two ion clouds of close m/z are studied with the ion trajectory simulation using GPU.     

Numerical Simulation of the Distribution Function and Free Energy of a Single Wormlike Polymer Confined between Hard Walls

We focus on the distribution and free energy of a wormlike polymer confined between two parallel hard walls.The variation in the distribution and free energy of the wormlike chain as the spacing between the walls decreases(or as the total contour length of the wormlike chain increases or as the persistence length of the chain increases)is simulated.The main reason for these changes is a degradation of the long wormlike chain into a Gaussian long chain under weak confinement.