Collaborative Research: CSR-AES: REEact: A Robust Execution Environment for Fragile Multicore Systems

本研究的重点是一个先进的执行系统，称为REEact的设计，实施和评估（强大的执行环境），其动态地使应用程序的执行适应于源自下一代多核（CMP）中的异构性源的运行时资源景观，感兴趣的异质性的来源是由影响各个核和存储器块的最大性能的工艺变化引起的那些，来自诸如DFVS之类的功率优化，其导致内核性能随时间变化以及由于热紧急情况而导致内核关闭;以及来自可靠性影响，其导致内核由于在现场发生的永久性故障而必须被禁用。 REEact是一种虚拟执行环境（VEE），它调解、控制和适应应用程序的执行。 它采用多种技术的组合来调整硬件资源和应用程序的软件代码，以适应CMP的异构性质，从而在并非所有CMP内核和/或存储器块都可用的情况下提供最佳性能和功率解决方案。 这项研究通过将这些架构用于高性能计算来影响CMP技术。有了管理异质性的有效策略，科学家、消费者和商业人士将更有效地使用高性能应用程序，从而在制药开发、金融市场预测和环境科学建模等领域取得更大进步。这项研究影响本科生和研究生通过他们参与研究项目，并通过课程和课程模块中医药。

This research focuses on the design, implementation, and evaluation of an advanced execution system, called REEact (Robust Execution Environment), which dynamically adapts an application's execution to the runtime resources landscape originating from the sources of heterogeneity in a next generation multi-core (CMP) chip.The sources of heterogeneity of interest are those that arise from process variation that impacts the maximum performance of individual cores and memory blocks, from power optimizations such as DFVS that result in varying core performance over time and core shut down due to thermal emergencies, and from reliability effects resulting in cores that must be disabled due to permanent faults that occur in the field. REEact is a type of virtual execution environment (VEE) that mediates, controls, and adapts the application's execution. It employs a combination of techniques to adapt both the hardware resources and the application's software code to accommodate the heterogeneous nature of the CMP to provide the best performance and power solution where not all of the CMP cores and/or memory blocks are available. This research impacts CMP technology by enabling the use of these architectures for high performance computing. With effective strategies for managing heterogeneity, scientists, consumers and business people will more effectively use high-performance applications, leading to greater advances in areas such as pharmaceutical development, financial market forecasting, and environmental science model¬ing. This research impacts both undergraduate and graduate students through their involvement in the research projects and through courses and course modules on CMPs.