We outline how auxiliary-field quantum Monte Carlo (AFQMC) can leverage graphical processing units (GPUs) to accelerate the simulation of solid state systems. 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 speedup 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.

中文翻译：

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使用图形处理单元加速固体的辅助场量子蒙特卡罗模拟。

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）来加速固态系统的仿真。通过利用单电子和二电子积分中晶体动量的守恒，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。我们提供了各种不同优化策略的详细说明，并相对于标准方法对我们的实现进行了介绍，从而证明了CPU实现速度提高了40倍。随着计算能力的提高，我们通过计算钻石结构中碳的内聚能达到实验结果的0.02 eV以内，证明了AFQMC能够相对于基集和系统大小系统地收敛固态计算。