Mayes K R, Luján M, Riley G D, Chin J, Coveney P V, Gurd J R
Centre for Novel Computing, School of Computer Science, University of Manchester, Manchester, UK.
Philos Trans A Math Phys Eng Sci. 2005 Aug 15;363(1833):1793-805. doi: 10.1098/rsta.2005.1607.
Advances in computational Grid technologies are enabling the development of simulations of complex biological and physical systems. Such simulations can be assembled from separate components--separately deployable computation units of well-defined functionality. Such an assemblage can represent an application composed of interacting simulations or might comprise multiple instances of a simulation executing together, each running with different simulation parameters. However, such assemblages need the ability to cope with heterogeneous and dynamically changing execution environments, particularly where such changes can affect performance. This paper describes the design and implementation of a prototype performance control system (PerCo), which is capable of monitoring the progress of simulations and redeploying them so as to optimize performance. The ability to control performance by redeployment is demonstrated using an assemblage of lattice Boltzmann simulations running with and without control policies. The cost of using PerCo is evaluated and it is shown that PerCo is able to reduce overall execution time.
计算网格技术的进步推动了复杂生物和物理系统模拟的发展。此类模拟可由单独的组件组装而成，这些组件是具有明确功能的可单独部署的计算单元。这样的组合可以表示一个由相互作用的模拟组成的应用程序，或者可能包含一起执行的模拟的多个实例，每个实例都使用不同的模拟参数运行。然而，这样的组合需要具备应对异构且动态变化的执行环境的能力，尤其是在这种变化会影响性能的情况下。本文描述了一个原型性能控制系统（PerCo）的设计与实现，该系统能够监控模拟的进度并重新部署它们以优化性能。通过使用一组在有控制策略和无控制策略情况下运行的格子玻尔兹曼模拟，展示了通过重新部署来控制性能的能力。对使用PerCo的成本进行了评估，结果表明PerCo能够减少总体执行时间。
