MCDA: Collaborative Research: A Multi-Element and Multi-Objective Optimization Approach for Allocating tasks to Multi-Core Processors

MCDA：协作研究：一种将任务分配给多核处理器的多元素和多目标优化方法

• 批准号: 0903456
• 负责人: Ishfaq Ahmad
• 金额: $ 17万
• 依托单位: University of Texas at Arlington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2012-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0903456&HistoricalAwards=false
• 关键词: MCDA; Collaborative; Research; Multi; Element

The objective of the proposed research is to design innovative algorithms and tools for energy-aware scheduling and mapping of tasks onto homogeneous and heterogeneous multi-core processor (HeMP) architectures. The research proposes to develop a new theoretical and experimental framework, called multi-element and multi-objective (MEMO) optimization, that will simultaneously and flexibly optimize the goals of energy minimization and performance maximization while taking into account constraints due to multiple architectural elements such as cores and caches of current and emerging multi-core processors. The project will develop CorePac, a toolkit that will provide a flexible and friendly environment to schedule task-parallel applications on HeMPs under various performance/energy trade-offs and demonstrate the usefulness of the algorithms and CorePac. Benchmarking of the algorithms will be conducted using a diverse suite of scientific, multimedia, and bioinformatics applications.Through its production of new algorithms and software toolkit, this work will have a direct and immediate impact on a number of communities. At the collaborating institutions, this project will have an educational impact by involving undergraduate and graduate students. This situation also presents excellent opportunities for interaction with postdoctoral researchers as well as with colleagues in academic, government and industry research labs. The CorePac software toolkit will be the basis for subsequent development of production quality software for energy-performance tradeoffs. Developing means to manage energy consumption in computers is imperative from both environmental and economical perspectives.

提出的研究目标是设计创新的算法和工具，用于能量感知调度和任务映射到同构和异构多核处理器（HeMP）架构上。该研究提出了一种新的理论和实验框架，称为多元素和多目标（MEMO）优化，该框架将同时灵活地优化能源最小化和性能最大化的目标，同时考虑到当前和新兴多核处理器的多个架构元素（如核心和缓存）的约束。该项目将开发CorePac，该工具包将提供一个灵活友好的环境，以在各种性能/能源权衡下调度hemp上的任务并行应用程序，并展示算法和CorePac的有用性。算法的基准测试将使用不同的科学、多媒体和生物信息学应用程序套件进行。通过其新算法和软件工具包的生产，这项工作将对许多社区产生直接和立即的影响。在合作院校，该项目将通过涉及本科生和研究生产生教育影响。这种情况也为博士后研究人员以及学术、政府和行业研究实验室的同事提供了极好的互动机会。CorePac软件工具包将成为后续开发用于能源性能权衡的产品质量软件的基础。从环境和经济的角度来看，开发管理计算机能耗的方法势在必行。