标题： 通过性能和准确性建模加速科学代码 显示英文标题

标题： Accelerating scientific codes by performance and accuracy modeling

摘要： 科学软件通常由多个影响准确性和性能的参数驱动。 由于找到这些参数的最佳配置是一个高度复杂的任务，因此软件通常以次优方式使用。 在典型的场景中，会施加准确性要求，并通过次优性能来实现。 在本文中，我们提出了一种用于模拟代码参数自动选择的方法，以及相应的原型工具。 为了适用于我们的方法，目标代码必须暴露影响准确性和性能的参数，并且必须有可用于底层方法的误差界和计算复杂度的公式。 作为案例研究，我们考虑了LAMMPS套件中用于分子动力学的粒子-粒子-网格方法（PPPM），并使用我们的工具来识别在最短执行时间内达到给定准确性的输入参数配置。 与专家用户建议的配置相比，我们的工具选择的参数使求解时间减少了10%到60%。 换句话说，对于典型的场景，即分配固定数量的核心小时数，并要运行固定数量的时间步数的模拟，使用我们的工具可能允许运行多达两倍的模拟。 虽然我们使用LAMMPS作为计算框架，并以PPPM方法作为色散的案例研究来发展我们的想法，但该方法是通用的，适用于一系列软件工具和方法。 显示英文摘要

摘要： Scientific software is often driven by multiple parameters that affect both accuracy and performance. Since finding the optimal configuration of these parameters is a highly complex task, it extremely common that the software is used suboptimally. In a typical scenario, accuracy requirements are imposed, and attained through suboptimal performance. In this paper, we present a methodology for the automatic selection of parameters for simulation codes, and a corresponding prototype tool. To be amenable to our methodology, the target code must expose the parameters affecting accuracy and performance, and there must be formulas available for error bounds and computational complexity of the underlying methods. As a case study, we consider the particle-particle particle-mesh method (PPPM) from the LAMMPS suite for molecular dynamics, and use our tool to identify configurations of the input parameters that achieve a given accuracy in the shortest execution time. When compared with the configurations suggested by expert users, the parameters selected by our tool yield reductions in the time-to-solution ranging between 10% and 60%. In other words, for the typical scenario where a fixed number of core-hours are granted and simulations of a fixed number of timesteps are to be run, usage of our tool may allow up to twice as many simulations. While we develop our ideas using LAMMPS as computational framework and use the PPPM method for dispersion as case study, the methodology is general and valid for a range of software tools and methods.