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A FLOPs based Model for Performance Analysis and Scheduling of Applications for Single and Multiple CPUs

机译:基于拖鞋的单一和多个CPU应用程序的性能分析和调度

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Optimal resource utilization ever remains a critical problem in any computing environment. Resource utilization merely depends upon an effective scheduling scheme. One approach is to have effective scheduling on the bases of application's performance on different resources. Once we know, the execution time of an application prior to execution, we can schedule it on a particular node in given computing environment, to gain maximum resource utilization. In the high performance computing environment, it is hard to estimate execution time accurately for CPU-oriented applications. So many approaches have been proposed to estimate performance of an application, such as source instrumentation, dynamic instrumentation, binary instrumentation, etc., especially for high computing - scientific applications. Dynamic approach, to model a performance of a scientific application, is based on its execution time itself for a given execution platform. But when the platform itself changed, a model may fail to estimate execution time accurately and hence it is not a platform independent modeling. This poor estimation leads to bad scheduling and ultimately poor resource utilization. We have found a better approach to estimate and model performance of scientific and high-computing applications based on Floating Point Operations (FLOPs). We have targeted basically all High Performance Computing (HPC) and Scientific Applications, which need enormous computing power to produce results in time. In this paper, we explain design architecture of a system, implemented based on proposed idea. This system works for single-CPU and multiple-CPUs applications. In the same flow, we have also integrated usefulness of application modeling with application profiling to schedule on given HPC platform (PC, cluster or GRID)[1] to achieve maximum resource utilization.
机译:最佳资源利用仍然是任何计算环境中的关键问题。资源利用仅仅取决于有效的调度方案。一种方法是有效地调度应用程序在不同资源上的性能基础上。一旦我们知道,在执行之前的应用程序的执行时间,我们可以在给定计算环境中的特定节点上安排它,以获得最大的资源利用率。在高性能计算环境中,对于CPU的应用程序,难以估计执行时间。已经提出了许多方法来估计应用的性能,例如源仪器,动态仪器,二元仪表等,特别是对于高计算 - 科学应用。动态方法,以模拟科学应用程序的性能,基于其执行时间本身,用于给定的执行平台。但是当平台本身改变时,模型可能无法准确估计执行时间,因此它不是平台独立的建模。这种差的估计导致调度不良,最终资源利用率差。我们已经找到了一种更好的方法来估算和模型性能,基于浮点操作(拖鞋)的科学和高计算应用的性能。我们基本上针对所有高性能计算(HPC)和科学应用,需要巨大的计算能力来产生时间的结果。在本文中,我们解释了一个系统的设计架构,基于提出的想法实现。该系统适用于单CPU和多CPU应用程序。在相同的流程中,我们还在给定HPC平台(PC,群集或网格)[1]上以应用程序分析进行了综合应用程序建模,以便实现最大资源利用率。

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