SOFTWARE: Heterogeneous Cluster MPI: A System for Out-Of-Core, Heterogeneous Data Distribution

软件：异构集群 MPI：核外异构数据分发系统

• 批准号: 0234285
• 负责人: David Lowenthal
• 金额: --
• 依托单位: University of Georgia Research Foundation Inc
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-07-01 至 2006-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0234285&HistoricalAwards=false
• 关键词: SOFTWARE; Heterogeneous; Cluster; MPI; System

Grid computing, or using several potentially heterogeneous computers to execute an application, is becoming increasingly popular. A grid poses significant software challenges for parallel computing; in particular, fundamental parallel computing problems are made more difficult. This project focuses on the data distribution problem, which is to distribute data to processors to minimize application completion time. We will re-examine the data distribution problem on one specific instance of a grid: a local area network of heterogeneous computers. Processors in such a cluster can have different relative CPU speeds, different amounts of available physical memory, and different effective I/O latencies. In addition, we will support the increasing number of out-of-core programs on these clusters.We will address this data distribution problem through the design and implementation of what we call Heterogeneous Cluster MPI (HC-MPI), which will be constructed as extensions and analysis built into MPI. The extensions will (1) assist users in writing adaptable programs and (2) allow HC-MPI to collect enough program information to determine automatically an effective data distribution. The expected impact of this work is to allow computational scientists to execute parallel programs efficiently on a variety of heterogeneous clusters.

网格计算，或使用几个潜在的异构计算机来执行一个应用程序，正变得越来越流行。 网格对并行计算提出了重大的软件挑战，特别是基本的并行计算问题变得更加困难。 这个项目关注的是数据分发问题，即将数据分发到处理器，以最小化应用程序完成时间。 我们将在网格的一个特定实例上重新研究数据分布问题：异构计算机的局域网。 这样的集群中的处理器可以具有不同的相对CPU速度、不同的可用物理内存量和不同的有效I/O延迟。 此外，我们将支持这些集群上越来越多的核外程序，我们将通过设计和实现我们称之为异构集群MPI（HC-MPI）来解决这个数据分布问题，HC-MPI将被构建为MPI的扩展和分析。这些扩展将（1）帮助用户编写可适应的程序，（2）允许HC-MPI收集足够的程序信息，以自动确定有效的数据分布。 这项工作的预期影响是允许计算科学家在各种异构集群上高效地执行并行程序。