Application-Level Scheduling with AppLeS

快速网络使聚合分布式CPU、内存、存储和数据成为可能，以提供超越任何单个系统的应用程序性能的潜力。然而，事实证明，在这些元计算系统上实现性能是困难的。目前，应用程序开发人员使用定制的应用程序调度来实现元计算机上的性能。在给定应用程序的资源要求、系统资源的性能能力以及由在元计算机上执行的竞争应用程序引起的时变争用影响的情况下，这种调度基于对应用程序将如何执行的预测。该项目的目标是使用从元计算应用程序开发人员的实践中产生的以应用程序为中心的调度范例，作为调度软件的基础，从而提高元计算系统上的应用程序性能。为此，PI将为单个元计算应用程序设计和实现以应用程序为中心的调度代理-称为APPLE(应用程序级调度程序)代理。Apple代理将根据每个资源可以提供的动态变化的性能，在非专用系统上调度单个并行应用程序的组件。

Fast networks have made it possible to aggregate distributed CPU, memory, storage, and data to provide the potential for application performance superior to that attainable on any single system. However, achieving performance on these metacomputing systems has proven difficult. Currently, application developers use customized application schedules to achieve performance on a metacomputer. Such schedules are based on a prediction of how the application will execute, given its resource requirements, the performance capabilities of the system resources, and the time-varying contention effects caused by competing applications executing on the metacomputer. This project's goal is to use the application-centric scheduling paradigm that is emerging from the practices of metacomputing applications developers as the basis for scheduling software which promotes application performance on metacomputing systems. To do this, the PIs will design and implement application-centric scheduling agents - called AppLeS (Application Level Scheduler) agents - for individual metacomputing applications. AppLeS agents will schedule the components of an individual parallel application on a non-dedicated system according to the dynamically changing performance each resource can deliver.