Abstract

Simulations of systems with quenched disorder are extremely demanding, suffering from the combined effect of slow relaxation and the need of performing the disorder average. As a consequence, new algorithms and improved implementations in combination with alternative and even purpose-built hardware are often instrumental for conducting meaningful studies of such systems. The ensuing demands regarding hardware availability and code complexity are substantial and sometimes prohibitive. We demonstrate how with a moderate coding effort leaving the overall structure of the simulation code unaltered as compared to a CPU implementation, very significant speed-ups can be achieved from a parallel code on GPU by mainly exploiting the trivial parallelism of the disorder samples and the near-trivial parallelism of the parallel tempering replicas. A combination of this massively parallel implementation with a careful choice of the temperature protocol for parallel tempering as well as efficient cluster updates allows us to equilibrate comparatively large systems with moderate computational resources.

Graphical abstract

中文翻译：

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无序系统的大规模并行仿真

摘要

具有慢速失调和需要执行平均失调的综合影响，具有淬灭性失调系统的仿真非常苛刻。结果，新算法和改进的实现方案与替代甚至专门构建的硬件相结合，通常有助于进行此类系统的有意义的研究。有关硬件可用性和代码复杂性的随之而来的需求是巨大的，有时甚至是禁止的。我们展示了如何通过适度的编码工作而使仿真代码的整体结构与CPU实现相比保持不变，主要通过利用无序样本和随机代码的琐碎并行性，在GPU上的并行代码可以实现非常显着的加速。平行回火副本的近似平凡平行度。

图形概要