论文标题
加速辅助场量子蒙特卡洛模拟与图形处理单元的固体模拟
Accelerating Auxiliary-Field Quantum Monte Carlo Simulations of Solids with Graphical Processing Unit
论文作者
论文摘要
我们概述了辅助场量子蒙特卡洛（AFQMC）如何利用图形处理单元（GPU）来加速固态系统的模拟。通过利用单电子积分和两电子积分中晶体动量的保存，我们展示了如何有效地制定算法以最佳利用当前的GPU架构。我们提供了有关不同优化策略的详细描述，并介绍了相对于标准方法的实施，证明了CPU实施的速度为40倍。随着计算能力的这种增加，我们证明了AFQMC通过计算钻石结构中碳的粘性能量到实验结果的0.02 eV，从而相对于基集和系统大小有系统收敛的固态计算的能力。
We outline how auxiliary-field quantum Monte Carlo (AFQMC) can leverage graphical processing units (GPUs) to accelerate the simulation of solid state sytems. By exploiting conservation of crystal momentum in the one- and two-electron integrals we show how to efficiently formulate the algorithm to best utilize current GPU architectures. We provide a detailed description of different optimization strategies and profile our implementation relative to standard approaches, demonstrating a factor of 40 speed up over a CPU implementation. With this increase in computational power we demonstrate the ability of AFQMC to systematically converge solid state calculations with respect to basis set and system size by computing the cohesive energy of Carbon in the diamond structure to within 0.02 eV of the experimental result.
