CAREER: Leveraging Heterogeneous Manycore Systems for Scalable Modeling, Simulation and Verification of Nanoscale Integrated Circuits

这个职业研究项目的目标是最大限度地释放新兴的异质多核CPU-GPU计算平台的力量。这将需要革命性的下一代电子设计自动化(EDA)工具来处理涉及数十亿个组件的电路的前所未有的复杂性，使其建模、分析和验证任务成为可能，而使用目前使用的方法，这些任务将成本高得令人望而却步，甚至难以处理。在这项研究中获得的经验也可能有助于在科学和工程的其他领域使用计算的进步，从而影响到复杂系统建模和模拟、计算流体动力学、社会计算和系统生物学等领域。PI将促进本科生和代表性不足的学生的研究，以及K-12教育扩展，以激励学生在STEM领域追求高级工程教育或职业生涯。此外，该中心将把研究成果纳入本科生和研究生课程开发，并利用跨学科、行业和国际合作，有效促进拟议的研究工作并广泛传播研究成果。未来的纳米级集成电路(IC)子系统，如时钟分配、功率传输网络、嵌入式存储器阵列以及模拟和混合信号系统，可能会达到前所未有的复杂程度，涉及数十亿个电路元件，使得它们的建模、分析和验证任务变得极其昂贵，并且使用现有的EDA工具难以完成。另一方面，新兴的异质多核计算系统，如多核CPU-GPU计算平台，将几个大型但耗电的通用处理器与大量更薄但更节能的图形处理器集成在一起，理论上可以提供万亿次浮点运算的计算能力。该提案旨在加速EDA研究向更节能的异质计算体系的范式转变。为此，PI将开发系统的硬件/软件方法，通过发明不同的CAD算法和数据结构，以及利用特定于硬件和特定领域的运行时性能建模和优化方法，实现可扩展的集成电路建模、仿真和验证。

The goal of this CAREER research project is to best unleash the power of emerging heterogeneous manycore CPU-GPU computing platforms. This will require revolutionizing the next-generation Electronic Design Automation (EDA) tools to deal with unprecedented complexity of circuits involving billions of components, making possible their modeling, analysis and verification tasks which would be prohibitively expensive and even intractable with methods in use today. The experience acquired in this research is also likely to contribute to advances in the use of computing in other areas of science and engineering, thus impacting areas such as complex system modeling and simulation, computational fluid dynamics, social computing, and systems biology. The PI will promote undergraduate and underrepresented student research, as well as K-12 education outreach, to motivate students in pursuing advanced engineering education or a career in STEM areas. Additionally, the PI will integrate the research outcomes into undergraduate and graduate curriculum development, and leverage interdisciplinary, industrial and international collaborations to effectively facilitate the proposed research work and broadly disseminate the results. Future nanoscale Integrated Circuit (IC) subsystems, such as clock distributions, power delivery networks, embedded memory arrays, as well as analog and mixed-signal systems, may reach an unprecedented complexity involving billions of circuit components, making their modeling, analysis and verification tasks prohibitively expensive and intractable with existing EDA tools. On the other hand, emerging heterogeneous manycore computing systems, such as the manycore CPU-GPU computing platforms that integrate a few large yet power-consuming general purpose processors with massive number of much slimmer but more energy-efficient graphics processors, can theoretically delivery teraflops of computing power. The proposal aims to accelerate a paradigm shift in EDA research to more energy-efficient heterogeneous computing regimes. Towards this end, the PI will develop systematic hardware/software approaches to achieve scalable integrated circuit modeling, simulation and verifications by inventing heterogeneous CAD algorithms and data structures, as well as exploiting hardware-specific and domain-specific runtime performance modeling and optimization approaches.