SHF: Small: Uncertainty Modeling and Design Methods for Heterogeneous Embedded Systems

SHF：小型：异构嵌入式系统的不确定性建模和设计方法

• 批准号: 1524909
• 负责人: Cristinel Ababei
• 金额: $ 25.11万
• 依托单位: Marquette University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1524909&HistoricalAwards=false
• 关键词: SHF; Small; Uncertainty; Modeling; Design

Future embedded systems will contain tens and projected hundreds of heterogeneous cores. The increased complexity and heterogeneity, however, come with new design and optimization challenges including increased design uncertainties due to process, voltage, and temperature variations and poor reliability due to elevated rates of faults. Therefore, it is imperative to rethink existing embedded system design approaches in order to directly consider these issues during the design and optimization processes. To address these challenges, this research develops a new design method to address the increased uncertainties and to improve reliability and performance of future complex embedded systems. This new design method is developed with both general probabilistic and non-probabilistic uncertainty models. These uncertainty models are used to develop a multi-objective computer-aided design automation framework, which incorporates several algorithmic innovations based on Monte Carlo techniques and evolutionary algorithms. At the heart of the proposed design flow lies the hardware/software co-synthesis or mapping problem, which is solved with enhanced evolutionary algorithms. By bridging several areas of research including uncertainty modeling, hardware/software co-synthesis of embedded systems, robust multi-objective optimization, and design automation tools development, the proposed design method enables the development of better embedded systems, which have an increasingly dramatic impact on society via applications ranging from automotive and consumer electronics to military and space. The proposed research is also closely integrated with a broad and diverse education and outreach plan aimed at inspiring female students to pursue careers in science, technology, engineering, and mathematics. More broadly, the results of this project impact significantly the design of future integrated systems by building the foundation for subsequent studies aimed at establishing robust multi-objective optimization for next-generation embedded systems.

未来的嵌入式系统将包含数十个和预计数百个异构核心。然而，增加的复杂性和异质性带来了新的设计和优化挑战，包括由于工艺、电压和温度变化而增加的设计不确定性以及由于故障率升高而导致的可靠性差。因此，必须重新思考现有的嵌入式系统设计方法，以便在设计和优化过程中直接考虑这些问题。为了应对这些挑战，本研究开发了一种新的设计方法，以解决增加的不确定性，并提高未来复杂的嵌入式系统的可靠性和性能。这种新的设计方法是与一般的概率和非概率不确定性模型。这些不确定性模型被用来开发一个多目标的计算机辅助设计自动化框架，它结合了几个算法的创新，基于蒙特卡罗技术和进化算法。在所提出的设计流程的核心在于硬件/软件协同综合或映射问题，这是解决增强的进化算法。通过桥接几个研究领域，包括不确定性建模，嵌入式系统的硬件/软件协同合成，鲁棒多目标优化和设计自动化工具开发，所提出的设计方法使更好的嵌入式系统的开发成为可能，通过从汽车和消费电子到军事和太空的应用，对社会产生越来越大的影响。拟议的研究还与旨在激励女学生从事科学、技术、工程和数学职业的广泛多样的教育和外联计划紧密结合。更广泛地说，该项目的结果显着影响未来的集成系统的设计，为后续的研究，旨在建立强大的多目标优化下一代嵌入式系统的基础。