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首页> 外文期刊>Computer physics communications >Multi-GPU accelerated multi-spin Monte Carlo simulations of the 2D Ising model
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Multi-GPU accelerated multi-spin Monte Carlo simulations of the 2D Ising model

机译：2D Ising模型的多GPU加速多旋转蒙特卡洛仿真

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摘要

A Modern Graphics Processing unit (GPU) is able to perform massively parallel scientific computations at low cost. We extend our implementation of the checkerboard algorithm for the two-dimensional Ising model [T. Preis et al., Journal of Chemical Physics 228 (2009) 4468-4477] in order to overcome the memory limitations of a single GPU which enables us to simulate significantly larger systems. Using multi-spin coding techniques, we are able to accelerate simulations on a single GPU by factors up to 35 compared to an optimized single Central Processor Unit (CPU) core implementation which employs multi-spin coding. By combining the Compute Unified Device Architecture (CUDA) with the Message Parsing Interface (MPI) on the CPU level, a single Ising lattice can be updated by a cluster of GPUs in parallel. For large systems, the computation time scales nearly linearly with the number of GPUs used. As proof of concept we reproduce the critical temperature of the 2D Ising model using finite size scaling techniques.
机译：现代图形处理单元（GPU）能够以低成本执行大规模并行的科学计算。我们扩展了二维Ising模型[T. Preis等人，Journal of Chemical Physics 228（2009）4468-4477]，以克服单个GPU的内存限制，这使我们能够模拟明显更大的系统。与采用多主轴编码的优化的单个中央处理器单元（CPU）核心实现相比，使用多主轴编码技术，我们能够将单个GPU上的仿真加速多达35倍。通过在CPU级别上将计算统一设备体系结构（CUDA）与消息解析接口（MPI）相结合，可以由一组GPU并行更新单个Ising晶格。对于大型系统，计算时间几乎与所用GPU的数量成线性比例关系。作为概念验证，我们使用有限尺寸缩放技术来再现2D Ising模型的临界温度。

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