CSR: Small: Collaborative Research: Pursuing High Performance on Clouds and Other Dynamically Heterogeneous Computing Platforms

CSR：小型：协作研究：追求云和其他动态异构计算平台的高性能

• 批准号: 1217981
• 负责人: Arnold Rosenberg
• 金额: $ 31.55万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-10-01 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1217981&HistoricalAwards=false
• 关键词: CSR; Small; Collaborative; Research; Pursuing

Emerging technologies have led to revolutionary computing platformssuch as computing clouds and many genres of computing grids. Theseplatforms promise to make high-performance computing platformsaccessible to the public. Realizing this promise, though, requiresone to cope with the platforms' dynamic heterogeneity, i.e., the factthat their constituent computers' relative powers and speeds canchange at unpredictable times and in unpredictable ways; for instance,shared computers may slow down or speed up significantly because ofunpredictable changes in workloads. The research of the PIs isdeveloping a transformative computing paradigm that will enablehigh-performance computing on these platforms. The new paradigmreplaces traditional schedulers' attempts to accommodate theparticulars of a computing platform---a goal that dynamicheterogeneity confutes---by orchestrating a complex computation in away that honors the relevant details of the computation's inherentstructure. In this way, the paradigm increases opportunities forexecuting independent tasks in parallel (i.e., simultaneously),thereby completing computations faster. Preliminary assessments---viasimulated competitions with common computation schedulers---suggestthat the new paradigm often completes computations faster thancompeting strategies by double-digit percentages. The challenge is torealize the paradigm in a computationally efficient manner, and thePIs are pursuing a variety of avenues toward achieving suchefficiency. Because of the complexity of dynamically heterogeneousplatforms, this goal requires advances in the technology of bothscheduling algorithms and simulation software. The PIs are uniquelyqualified to produce such advances because of their complementaryexpertise in algorithms, applications, and systems.

新兴技术带来了革命性的计算平台，如计算云和许多类型的计算网格。 这些平台承诺使高性能计算平台向公众开放。 然而，实现这一承诺需要科普平台的动态异构性，即，它们的组成计算机的相对能力和速度可以在不可预测的时间以不可预测的方式改变;例如，共享计算机可能会因为工作负载的不可预测的变化而显著减慢或加速。 PI的研究正在开发一种变革性的计算模式，将在这些平台上实现高性能计算。 新的范例取代了传统的架构师试图适应计算平台的细节-动态异质性的目标-通过编排一个复杂的计算，尊重计算的内在结构的相关细节。 通过这种方式，该范例增加了并行执行独立任务的机会（即，同时），从而更快地完成计算。 初步评估-通过与普通计算器的模拟竞赛-认为新的范例通常比竞争策略快两位数的百分比完成计算。 挑战在于以计算效率高的方式实现这种模式，PI正在寻求各种途径来实现这种效率。 由于动态异构平台的复杂性，这一目标需要调度算法和仿真软件技术的进步。 由于他们在算法、应用程序和系统方面的互补性专业知识，PI完全有资格产生这样的进步。