On the Autotuning Potential of Time-Stepping Methods from Scientific Computing
On the Autotuning Potential of Time-Stepping Methods from Scientific Computing
复制标题
论科学计算中时间步进方法的自动调整潜力
DOI：
10.15439/2018f169
复制
发表时间：
2018
期刊：
影响因子：
--
通讯作者：
G. Rünger
中科院分区：
文献类型：
--
作者：
Natalia Kalinnik;R. Kiesel;T. Rauber;Marcel Richter;G. Rünger
由于新提供的硬件的特性不断变化，因此始终需要充分设计和重新设计软件，以满足基本硬件条件。特别是对于成熟的软件，功能性和非功能性属性（诸如运行时性能或能量效率）的容易的可移植性将是有益的，使得软件自动适应给定的硬件条件。在这篇文章中，我们探讨了科学计算中几种方法的自动调整潜力。特别是，我们考虑时间步进的方法，并研究不同方法的相关调整参数的效果。我们还解决了这个问题，离线或在线自动调整方法是否适合特定的方法。从科学计算的方法被认为是粒子模拟方法，微分方程的解决方案的方法，以及稀疏矩阵计算。
Due to the ever changing characteristics of the newly provided hardware, there is the permanent requirement of designing and re-designing software adequately to meet the basic hardware conditions. Especially for well-established software, easy portability of the functional as well as the non-functional properties, such as runtime performance or energy efficiency, would be beneficial, so that the software adapts automatically to the given hardware conditions. In this article, we explore the autotuning potential of several methods from scientific computing. In particular, we consider time-stepping methods and investigate the effect of relevant tuning parameters of the different methods. We also address the question, whether offline or online autotuning approaches are appropriate for the specific method. The methods from scientific computing considered are particle simulation methods, solution methods for differential equations, as well as sparse matrix computations.