CSR: Small: RUI: Task Mapping for Emerging Network Topologies

CSR：小型：RUI：新兴网络拓扑的任务映射

• 批准号: 1423413
• 负责人: David Bunde
• 金额: $ 25.86万
• 依托单位: Knox College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-12-01 至 2019-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1423413&HistoricalAwards=false
• 关键词: CSR; Small; RUI; Task; Mapping

This project aims to improve the performance of large scientific simulations on next-generation high-performance computing (HPC) systems by developing new strategies for task mapping, the assignment of specific parts of an application to each of the many processing nodes in an HPC system. A key determinant of application performance on HPC systems is the speed of message delivery between related parts of the application. This in turn depends upon the network connecting the processing nodes. Task mapping has the potential to improve network performance by arranging communicating parts of the application in a way that distributes messages more evenly through the network, preventing any part of it from becoming overloaded. The PI has previously shown that task mapping can reduce application running time on current HPC systems by up to 30%. New algorithms are needed for larger next-generation systems, which must use novel network topologies for the internode connections due to power limitations.The specific network topology studied is Dragonfly, two variations of which are used in commercial systems. Dragonfly organizes network switches into groups that form a high-radix "virtual switch". This allows a direct connection between every pair of groups. Together with high connectivity between the switches within a group, this guarantees that every pair of nodes is connected by a short path. The problem is that having only a single direct connection between each pair of groups makes that connection a potential bottleneck. The project will develop task mapping algorithms that balance the goal of localizing related tasks to exploit intra-group connectivity with the need to spread the job across the system so that it can utilize many inter-group links simultaneously. The project will also develop node allocation algorithms to support jobs of varying size, providing each job with nodes that are well-connected while minimizing contention between jobs.By improving application performance on next-generation HPC systems, the project will help realize the full potential of these powerful systems. In addition, the project will heavily involve undergraduate student researchers, who will be trained as future leaders in science and engineering.

该项目旨在通过制定新的任务映射策略，将应用程序的特定部分分配到HPC系统中的许多处理节点中的每个加工节点，从而提高大型科学模拟对下一代高性能计算（HPC）系统的性能。 HPC系统应用程序性能的关键决定因素是应用程序相关部分之间的消息传递速度。 这反过来取决于连接处理节点的网络。 任务映射可以通过安排通过网络更平均分发消息的方式来安排传达应用程序的部分来提高网络性能，从而阻止其任何部分变得过载。 PI先前已经显示，任务映射可以将当前HPC系统上的应用程序运行时间降低30％。 较大的下一代系统需要新的算法，该系统必须使用新颖的网络拓扑用于由于功率限制而导致的节点连接。研究的特定网络拓扑是蜻蜓，其中两个变体用于商业系统。 蜻蜓将网络切换为组成一个高radix“虚拟开关”的组。 这允许每对组之间的直接连接。 加上一个组内的开关之间的高连接性，这可以确保每对节点都通过短路径连接。 问题在于，每对组之间只有一个直接连接使该连接成为潜在的瓶颈。 该项目将开发任务映射算法，以平衡本地化相关任务以利用组内连接的目标，并需要在整个系统中传播作业，以便它可以同时利用许多组间链接。 该项目还将开发节点分配算法以支持不同规模的工作，从而为每个作业提供良好连接的节点，同时最大程度地减少工作之间的争议。通过提高下一代HPC系统的应用程序性能，该项目将有助于实现这些强大系统的全部潜力。 此外，该项目将大量涉及本科生研究人员，他们将接受科学和工程领域的未来领导者培训。

项目成果

Comparing Global Link Arrangements for Dragonfly Networks

• DOI: 10.1109/cluster.2015.57
• 发表时间: 2015-09
• 期刊: 2015 IEEE International Conference on Cluster Computing
• 作者: Emily M. Hastings;David Rincon-Cruz;Marc Spehlmann;S. Meyers;Anda Xu;David P. Bunde;V. Leung

Improving Valiant Routing for Slim Fly Networks

• DOI: 10.1109/icppw.2017.33
• 发表时间: 2017-08
• 期刊: 2017 46th International Conference on Parallel Processing Workshops (ICPPW)
• 作者: Deyu Han;Zhaofeng Wang;David P. Bunde

New Link Arrangements for Dragonfly Networks

蜻蜓网络的新链路安排

• DOI: 10.1109/hipineb.2017.14
• 发表时间: 2017
• 期刊: 2017 IEEE 3rd International Workshop on High-Performance Interconnection Networks in the Exascale and Big-Data Era (HiPINEB
• 作者: Belka, Madison;Doubet, Myra;Meyers, Sofia;Momoh, Rosemary;Rincon-Cruz, David;Bunde, David P.
• 通讯作者: Bunde, David P.