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A new task scheduling method for distributed programs that require memory management

机译:一种需要内存管理的分布式程序的新任务调度方法

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In parallel and distributed applications, it is very likely that object-oriented languages, such as Java and Ruby, and large-scale semistructured -data written in XML will be employed. However, because of their inherent dynamic memory management, parallel and distributed applications must sometimes suspend the execution of all tasks running on the processors. This adversely affects their execution on the parallel and distributed platform. In this paper, we propose a new task scheduling method called CP/MM (Critical Path/Memory Management) which can efficiently schedule tasks for applications requiring memory management. The underlying concept is to consider the cost due to memory management when the task scheduling system allocates ready (executable) coarse-grain tasks, or macro-tasks, to processors. We have developed three task scheduling modules, including CP/MM, for a task scheduling system which is implemented on a Java RMI (Remote Method Invocation) communication infrastructure. Our experimental results show that CP/MM can successfully prevent high-priority macro-tasks from being affected by the garbage collection arising from memory management, so that CP/MM can efficiently schedule distributed programs whose critical paths are relatively long.
机译:在并行和分布式应用程序中,很有可能会采用Java和Ruby等面向对象的语言以及以XML编写的大规模半结构化数据。但是,由于并行和分布式应用程序固有的动态内存管理,因此有时必须中止在处理器上运行的所有任务的执行。这不利地影响了它们在并行和分布式平台上的执行。在本文中,我们提出了一种新的任务调度方法,称为CP / MM(关键路径/内存管理),它可以为需要内存管理的应用程序高效地调度任务。基本概念是当任务调度系统将就绪(可执行)的粗粒度任务或宏任务分配给处理器时,要考虑由于内存管理而导致的成本。我们为在Java RMI(远程方法调用)通信基础结构上实现的任务调度系统开发了三个任务调度模块,包括CP / MM。我们的实验结果表明,CP / MM可以成功地防止高优先级的宏任务受到内存管理产生的垃圾回收的影响,从而CP / MM可以有效地调度关键路径较长的分布式程序。

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