Research Initiation Award: Job Scheduling and Memory Management in Message-passing Multicomputers

研究启动奖：消息传递多计算机中的作业调度和内存管理

• 批准号: 9409697
• 负责人: Sanjeev Setia
• 金额: $ 8.84万
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-09-01 至 1998-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9409697&HistoricalAwards=false
• 关键词: Research; Initiation; Award; Job; Scheduling

The main goal of this project is to investigate multiprogramming based task scheduling in multiprocessor environments. This is based on the belief that, like uniprocessors, multicomputers have to be multiprogrammed in order to achieve a performance to cost ratio. Existing policies for resource sharing in a multicomputer among multiple applications are static. This project will examine issues that arise in the design and implementation of alternate job scheduling policies that have a better performance than static policies. As a first step, the workload on multicomputers will be characterized through experimental measurement and analysis. The insights gained from this study will be used in the design and implementation of adaptive and dynamic partitioning policies. In particular, implementation issues involved in making adaptive and dynamic partitioning transparent to the applications programmer will be examined. As a part of the research, a run time system that provides support for application-directed dynamic reconfiguration will be implemented. Another goal of the research is to examine the impact of the introduction of virtual memory in newer multicomputer systems on the performance trade-offs between various scheduling policies. The working set sizes and memory reference patterns of several scientific applications will be determined through simulation and analysis. This information will be used in a simulation based study that examines the interactions between processor allocation, node scheduling and memory management in multicomputers that support virtual memory on each node of the system. ***

本计画的主要目标是研究多处理器环境下，以多道程序设计为基础的任务排程。 这是基于这样一种信念，即像单处理器一样，多计算机必须被多编程，以实现性能成本比。 现有的多应用程序之间的多计算机资源共享策略是静态的。 这个项目将研究在设计和实现替代作业调度策略时出现的问题，这些策略比静态策略具有更好的性能。 作为第一步，多计算机上的工作量将通过实验测量和分析来表征。 从这项研究中获得的见解将用于自适应和动态分区策略的设计和实施。 特别是，实现自适应和动态分区透明的应用程序员所涉及的问题将被检查。 作为研究的一部分，将实现一个运行时系统，为应用程序导向的动态重构提供支持。 研究的另一个目标是研究在新的多计算机系统中引入虚拟内存对各种调度策略之间的性能权衡的影响。 几个科学应用程序的工作集大小和内存引用模式将通过模拟和分析来确定。 这些信息将被用于基于模拟的研究，探讨处理器分配，节点调度和内存管理之间的相互作用，在多台计算机，支持系统的每个节点上的虚拟内存。 ***