RUI: Managing Memory Demands of Data Intensive Workloads in Chip Multiprocessors

RUI：管理芯片多处理器中数据密集型工作负载的内存需求

• 批准号: 0702689
• 负责人: Kelly Shaw
• 金额: $ 13.5万
• 依托单位: University of Richmond
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-06-01 至 2011-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0702689&HistoricalAwards=false
• 关键词: RUI; Managing; Memory; Demands; Data

Title: RUI: Managing Memory Demands of Data Intensive Workloads in Chip MultiprocessorsPI: Kelly A. Shaw Until recently, most computer chips contained a single processor; systems with multiple processors were created by using multiple computer chips. Changes in the semiconductor industry are now enabling many, even tens, of processors to reside on a single chip. Placing multiple processors on a given chip makes it possible to execute many different tasks, or processes, on that chip simultaneously, potentially speeding up complex computations. However, it also means that all of those executing tasks must compete for and share all of the other resources on the chip. These resources include locations to store the data used by the processes, wires that enable data to be moved to different locations on the chip, and pins that enable data to be moved on or off of the chip. For applications that use large quantities of data, efficient use of these shared resources will be necessary for fast execution on these chips. The importance of these types of data intensive applications cannot be overstated; financial institutions use them to insure compliance with government standards, scientists use them while performing genome sequence research, and businesses use them to learn about individuals in order to develop new products. This project has two goals. First, this work will quantify the demands these data intensive applications place on a chip's shared resources as more processors are placed on each chip. Understanding the resource needs of these applications will enable identification of problems that prevent these applications from executing quickly on these chips and will expose ways to potentially address these problems. Second, this project will develop and evaluate changes to the chips and to the applications that will help reduce the demands placed on a chip's shared resources. Specifically, the project will examine ways to organize the shared resources on a chip to more closely match how an application uses these resources. Additionally, this work will propose and evaluate techniques that reduce the amount of unneeded data being incidentally brought onto and stored on a chip. Finally, the project will examine ways to use knowledge about the application to restructure the application in a way that reduces the need to move data to different locations on a chip using the shared wires.

标题：RUI：管理芯片多处理器中数据密集型工作负载的内存需求PI：Kelly A。直到最近，大多数计算机芯片都包含一个处理器;多处理器系统是通过使用多个计算机芯片创建的。 半导体行业的变化现在使得许多甚至数十个处理器能够驻留在单个芯片上。 将多个处理器放置在给定的芯片上，可以同时在该芯片上执行许多不同的任务或进程，从而可能加快复杂的计算。 然而，这也意味着所有这些执行任务必须竞争和共享芯片上的所有其他资源。 这些资源包括存储进程使用的数据的位置、使数据能够移动到芯片上不同位置的导线以及使数据能够在芯片上移动或移出芯片的引脚。 对于使用大量数据的应用程序，有效使用这些共享资源对于在这些芯片上快速执行是必要的。 这些类型的数据密集型应用程序的重要性怎么强调都不过分;金融机构使用它们来确保遵守政府标准，科学家在进行基因组序列研究时使用它们，企业使用它们来了解个人以开发新产品。 这个项目有两个目标。 首先，这项工作将量化这些数据密集型应用程序对芯片共享资源的需求，因为每个芯片上放置了更多的处理器。 了解这些应用程序的资源需求将能够识别阻止这些应用程序在这些芯片上快速执行的问题，并将揭示潜在解决这些问题的方法。 其次，该项目将开发和评估芯片和应用程序的变化，这将有助于减少对芯片共享资源的需求。 具体来说，该项目将研究如何组织芯片上的共享资源，以更紧密地匹配应用程序如何使用这些资源。 此外，这项工作将提出和评估技术，减少不必要的数据量被附带带到和存储在芯片上。 最后，该项目将研究如何使用有关应用程序的知识来重组应用程序，以减少使用共享线将数据移动到芯片上不同位置的需要。