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

职业：利用异构众核系统进行纳米级集成电路的可扩展建模、仿真和验证

• 批准号: 2041519
• 负责人: Zhuo Feng
• 金额: $ 14.02万
• 依托单位: Stevens Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2041519&HistoricalAwards=false
• 关键词: CAREER; Leveraging; Heterogeneous; Manycore; Systems

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.

该职业研究项目的目标是最好地释放新兴异构众核 CPU-GPU 计算平台的力量。这将需要彻底改变下一代电子设计自动化（EDA）工具，以处理涉及数十亿个元件的前所未有的复杂电路，从而使它们的建模、分析和验证任务成为可能，而这些任务对于当今使用的方法来说是非常昂贵的，甚至是棘手的。这项研究中获得的经验也可能有助于其他科学和工程领域的计算应用的进步，从而影响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研究以及 K-12 教育推广，以激励学生追求高级工程教育或 STEM 领域的职业。此外，PI还将把研究成果整合到本科生和研究生课程开发中，并利用跨学科、行业和国际合作来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，例如时钟分配、电力传输网络、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性，涉及数十亿个电路元件，这使得它们的建模、分析和验证变得更加困难。使用现有的 EDA 工具来完成极其昂贵且棘手的任务。另一方面，新兴的异构众核计算系统，例如众核CPU-GPU计算平台，将一些大型但耗电的通用处理器与大量更轻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 研究向更节能的异构计算体系的范式转变。为此，PI 将开发系统的硬件/软件方法，通过发明异构 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。