SHF: Small: Exploring Swarm Intelligence for Design Validation

SHF：小型：探索群体智能以进行设计验证

• 批准号: 1016675
• 负责人: Michael Hsiao
• 金额: $ 36.34万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1016675&HistoricalAwards=false
• 关键词: SHF; Small; Exploring; Swarm; Intelligence

The likelihood of hidden, subtle bugs increases with growing design sizes, and reaching corner cases in large circuits and systems in order to expose such subtle bugs has become a daunting task. Verifying the correctness of the design is now a tremendous bottleneck in the overall design process. Critical to the effectiveness of stimuli generation is the quality of guidance and feedback provided during the search. The objective of this research is to elicit the swarming power to solve this very difficult problem, which has not been done in the past. Individual knowledge acquired during the search is extracted to benefit collective effort. This is enabled via cultivation of knowledge exchange, accumulation, and utilization. The intelligent partitioning and grouping of the state variables allows for the construction of many effective abstract navigation tracks in large designs, benefiting the swarm platform. The development of new theories and algorithms will be an original contribution that will allow for transformative understanding of semi-formal verification and state space exploration, all in a rigorous framework. The theories and practice that will result from this work will not only enable us for a deeper understanding of collective effort, this project will directly promote the education of the involved students. In regard to outreach to under-represented students, the PI currently advises multiple women Ph.D. students (under-represented in engineering), and this project will continue to encourage aspiring female students to participate in the research endeavor. In addition, the PI will actively recruit summer minority interns from programs within Virginia Tech to take part in this project.

隐藏的、细微的错误的可能性随着设计尺寸的增加而增加，并且为了暴露这种细微的错误而达到大型电路和系统中的角落情况已经成为一项艰巨的任务。现在，设计的正确性是整个设计过程中的一个巨大瓶颈。刺激生成的有效性的关键是在搜索过程中提供的指导和反馈的质量。这项研究的目的是引出群集能力来解决这个非常困难的问题，这在过去还没有做过。 在搜索过程中获得的个人知识被提取出来，以利于集体努力。 这是通过培养知识交流、积累和利用来实现的。 状态变量的智能划分和分组允许在大型设计中构建许多有效的抽象导航轨迹，使Swarm平台受益。 新理论和算法的发展将是一个原创性的贡献，将允许在严格的框架下对半形式化验证和状态空间探索进行变革性的理解。这项工作所产生的理论和实践不仅使我们能够更深入地了解集体努力，而且该项目将直接促进参与学生的教育。 关于对代表性不足的学生的宣传，PI目前为多名女博士提供咨询。该项目将继续鼓励有抱负的女学生参与研究奋进。 此外，PI将积极招募弗吉尼亚理工大学项目的暑期少数族裔实习生参加该项目。