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首页> 外文会议>2011 Eighth International Conference on Quantitative Evaluation of Systems >GPA - A Tool for Fluid Scalability Analysis of Massively Parallel Systems
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GPA - A Tool for Fluid Scalability Analysis of Massively Parallel Systems

机译：GPA-大规模并行系统的流体可扩展性分析工具

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Recent ordinary differential equation (ODE) based techniques allow efficient analysis of Markovian population models with extremely large state spaces. In most cases of realistic scale, they provide the only alternative to stochastic simulation. Moreover, numerical solution of the ODEs is cheaper computationally than simulation by orders of magnitude. We present the Grouped PEPA Analyser (GPA) tool with new functionality to exploit computationally inexpensive fluid analysis techniques to allow the exploration of large numbers of system configurations in models with large state spaces. GPA provides an efficient implementation of the fluid analysis techniques for models described in a stochastic process algebra. It implements recently developed extensions allowing specifications of complex reward measures using combinations of state based, rate accumulated and impulse rewards. Combined with the ability to efficiently capture various passage time metrics, GPA can be used to solve optimisation problems with a reward objective function under different service level agreement type constraints.
机译：最近的基于常微分方程（ODE）的技术可以有效分析具有极大状态空间的马尔可夫种群模型。在实际规模的大多数情况下，它们是随机模拟的唯一替代方法。而且，ODE的数值解在计算上比模拟要便宜几个数量级。我们提供具有新功能的分组PEPA分析仪（GPA）工具，以利用计算上便宜的流体分析技术，允许在具有大状态空间的模型中探索大量系统配置。 GPA为随机过程代数中描述的模型提供了流体分析技术的有效实现。它实现了最近开发的扩展，允许使用基于状态，费率累积和冲动奖励的组合来指定复杂奖励措施的规范。结合有效捕获各种通过时间指标的能力，GPA可用于解决在不同服务水平协议类型约束下具有奖励目标函数的优化问题。

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