SHF: Small: Collaborative Research: Experimental-based Research on Effective Models of Parallel Application Execution Time, Power, and Resilience

SHF：小型：协作研究：基于实验的并行应用程序执行时间、功耗和弹性有效模型的研究

• 批准号: 1618776
• 负责人: Zhiling Lan
• 金额: $ 20万
• 依托单位: Illinois Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1618776&HistoricalAwards=false
• 关键词: SHF; Small; Collaborative; Research; Experimental

The increasing scale and complexity of parallel systems present enormous challenges to parallel applications. One such challenge is the integration and balancing of execution time, power, and resilience for parallel applications. The MuMMI_R project seeks to advance the scientific understanding of the interdependence among power, execution time, and resilience for various application-system configurations. The broader impacts include training of undergraduate and graduate students and the participation in programs such as REUs, CREU, and DREU to increase the participation of students from underrepresented groups in the project.The MuMMI_R research aims to develop effective techniques for quantifying the complicated tradeoffs among execution time, power, and resilience, and to provide a tuning mechanism for user-defined metrics. Toward this goal, the research focuses on three interrelated research thrusts: (1) experimental research to conduct extensive experiments of a suite of representative application under different resilience strategies on various parallel architectures, (2) application-level co-modeling to develop analytical models and colored Petri net based simulation for quantifying the correlations and tradeoffs between execution time, power, and resilience, and (3) model-based analysis to examine the tradeoffs among resilience, execution time, and power for different application-system configurations, and to tune application implementations for a user-defined target metric on current and future systems. The resulting framework, MuMMI_R, will provide valuable insights into application-system interactions and aid in the design of efficient parallel applications (with respect to execution time, power requirements, and resilience), runtime systems, and computer architectures.

平行系统的规模和复杂性的增加对并行应用提出了巨大的挑战。一个这样的挑战是对并行应用程序的执行时间，功率和弹性的集成和平衡。 Mummi_r项目旨在提高对各种应用程序配置的功率，执行时间和弹性之间相互依赖性的科学理解。更广泛的影响包括对本科生和研究生的培训，以及参与REUS，CREU和DREU等计划，以增加项目中代表性不足的小组的学生的参与。Mummi_R研究旨在开发有效的技术，以量化执行时间，权力，稳定性和互补的机制，并提供一种调整的方法，以量化复杂的交易。为了实现这一目标，该研究集中于三个相互关联的研究推力：（1）实验研究，以对各种平行体系结构的不同复原力策略进行一套代表性应用的广泛实验，（2）应用程序级别的共同建模，以开发分析模型和有色PETRI净基于petri net的模型，以量化质量和竞争的模型，以量化（量化），以量化（Quormity oferction和Reseftion），以量化（Quartifials和Reser）的势力，（3在不同应用程序系统配置的弹性，执行时间和功率中，以及针对当前和将来系统上用户定义的目标度量的应用程序实现。最终的框架Mummi_r将提供对应用程序系统交互的宝贵见解，并有助于设计有效的并行应用程序（关于执行时间，功率要求和弹性），运行时系统和计算机体系结构。

项目成果

Union: An Automatic Workload Manager for Accelerating Network Simulation

Union：用于加速网络仿真的自动工作负载管理器

• DOI: 10.1109/ipdps47924.2020.00089
• 发表时间: 2020
• 期刊: 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS
• 作者: Wang, Xin;Mubarak, Misbah;Kang, Yao;Ross, Robert B.;Lan, Zhiling
• 通讯作者: Lan, Zhiling