CPA-DA: Efficient Sequential Synthesis and Optimization for High-Performance Circuits

主要研究者：周海提案编号：0811270标题：CPA-DA：高性能电路的高效顺序综合与优化研究机构：西北大学摘要处理速度和功耗已成为现代高性能VLSI电路最重要的设计标准。它们不仅依赖于组合部分，而且依赖于存储元件（锁存器和触发器）和时钟机制。在该项目中，我们开发了一个有效的顺序合成和优化框架的基础上增量重定时和其他网络流技术。该框架是基于结构操作，如重定时，重新合成，扫描，这是覆盖几乎所有可能的顺序变换。基于增量重定时、约束时钟偏差调度和顺序布局规划的有效算法的顺序优化套件被开发出来，并将向公众提供。研究和教育活动相结合的结果提高了所有类型的纳米VLSI电路的性能和设计生产力，从高速微处理器到PDA、手机、和更多.性能和设计生产力的提高转化为客户的更低成本和更好的功能，从而使所有消费者，特别是社会经济弱势群体，能够获得负担得起的信息技术。此外，通过优化性能和提高设计效率而增强的高性能计算机将有助于其他重要科学领域的研究，如遗传学，生物信息学和医学。

PI: Zhou, HaiProposal No: 0811270Title: CPA-DA: Efficient Sequential Synthesis and Optimization for High-Performance CircuitsInstitution: Northwestern UniversityABSTRACTProcessing speed and power consumption have become the most important design criteria in modern high-performance VLSI circuits. They are not only dependent on the combinational part but also on the memory elements (latches and flip-flops) and the clocking mechanism. In the project, we develop an efficient sequential synthesis and optimization framework based on incremental retiming and other network flow techniques. The framework is based on structural operations such as retiming, re-synthesis, and sweep, which are shown to cover almost all possible sequential transformations. A sequential optimization suite based on efficient algorithms for incremental retiming, constrained clock skew scheduling, and sequential floor-planning is developed and will be made available to the public.The outcomes of combined research and education activities improve the performance and design productivity of nanometer VLSI circuits of all types, from high-speed microprocessors to the omnipresent systems-on-a-chips (SOCs) found in PDAs, cell phones, and more. The improvement on performance and design productivity translates to lower cost and better functionality to customers, thus giving all consumers, particularly socio-economically disadvantaged, access to affordable information technology. Furthermore, the high performance computers, enhanced by optimized performance and improved design productivity, will aid research in other important scientific areas such as genetics, bioinformatics, and medicine.