Shimojo Fuyuki, Hattori Shinnosuke, Kalia Rajiv K, Kunaseth Manaschai, Mou Weiwei, Nakano Aiichiro, Nomura Ken-ichi, Ohmura Satoshi, Rajak Pankaj, Shimamura Kohei, Vashishta Priya
Collaboratory for Advanced Computing and Simulations, Department of Physics and Astronomy, Department of Computer Science, and Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, California 90089-0242, USA.
J Chem Phys. 2014 May 14;140(18):18A529. doi: 10.1063/1.4869342.
We introduce an extension of the divide-and-conquer (DC) algorithmic paradigm called divide-conquer-recombine (DCR) to perform large quantum molecular dynamics (QMD) simulations on massively parallel supercomputers, in which interatomic forces are computed quantum mechanically in the framework of density functional theory (DFT). In DCR, the DC phase constructs globally informed, overlapping local-domain solutions, which in the recombine phase are synthesized into a global solution encompassing large spatiotemporal scales. For the DC phase, we design a lean divide-and-conquer (LDC) DFT algorithm, which significantly reduces the prefactor of the O(N) computational cost for N electrons by applying a density-adaptive boundary condition at the peripheries of the DC domains. Our globally scalable and locally efficient solver is based on a hybrid real-reciprocal space approach that combines: (1) a highly scalable real-space multigrid to represent the global charge density; and (2) a numerically efficient plane-wave basis for local electronic wave functions and charge density within each domain. Hybrid space-band decomposition is used to implement the LDC-DFT algorithm on parallel computers. A benchmark test on an IBM Blue Gene/Q computer exhibits an isogranular parallel efficiency of 0.984 on 786 432 cores for a 50.3 × 10(6)-atom SiC system. As a test of production runs, LDC-DFT-based QMD simulation involving 16 661 atoms is performed on the Blue Gene/Q to study on-demand production of hydrogen gas from water using LiAl alloy particles. As an example of the recombine phase, LDC-DFT electronic structures are used as a basis set to describe global photoexcitation dynamics with nonadiabatic QMD (NAQMD) and kinetic Monte Carlo (KMC) methods. The NAQMD simulations are based on the linear response time-dependent density functional theory to describe electronic excited states and a surface-hopping approach to describe transitions between the excited states. A series of techniques are employed for efficiently calculating the long-range exact exchange correction and excited-state forces. The NAQMD trajectories are analyzed to extract the rates of various excitonic processes, which are then used in KMC simulation to study the dynamics of the global exciton flow network. This has allowed the study of large-scale photoexcitation dynamics in 6400-atom amorphous molecular solid, reaching the experimental time scales.
我们引入了一种分治算法范式的扩展,称为分治重组(DCR),用于在大规模并行超级计算机上进行大型量子分子动力学(QMD)模拟,其中原子间力是在密度泛函理论(DFT)框架下通过量子力学计算的。在DCR中,分治阶段构建全局信息丰富的重叠局部域解,这些解在重组阶段被合成到一个包含大时空尺度的全局解中。对于分治阶段,我们设计了一种精简分治(LDC)DFT算法,通过在分治域的周边应用密度自适应边界条件,显著降低了N个电子的O(N)计算成本的前置因子。我们的全局可扩展且局部高效的求解器基于一种混合实空间 - 倒易空间方法,该方法结合了:(1)用于表示全局电荷密度的高度可扩展实空间多重网格;以及(2)用于每个域内局部电子波函数和电荷密度的数值高效平面波基。混合空间带分解用于在并行计算机上实现LDC - DFT算法。在一台IBM Blue Gene/Q计算机上对一个50.3×10⁶原子的SiC系统进行的基准测试显示,在786432个核心上的等粒度并行效率为0.984。作为生产运行测试,在Blue Gene/Q上进行了基于LDC - DFT的涉及16661个原子的QMD模拟,以研究使用锂铝合金颗粒从水中按需生产氢气。作为重组阶段的一个例子,LDC - DFT电子结构被用作基组,用非绝热QMD(NAQMD)和动力学蒙特卡罗(KMC)方法描述全局光激发动力学。NAQMD模拟基于线性响应含时密度泛函理论来描述电子激发态,并采用表面跳跃方法来描述激发态之间的跃迁。采用了一系列技术来有效计算长程精确交换校正和激发态力。对NAQMD轨迹进行分析以提取各种激子过程的速率,然后将其用于KMC模拟以研究全局激子流网络的动力学。这使得能够研究6400原子非晶分子固体中的大规模光激发动力学,达到了实验时间尺度。