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Theory and Methodology for Performance-Driven Automation in RTL and Testbench Debugging

Theory and Methodology for Performance-Driven Automation in RTL and Testbench Debugging
RTL 和测试台调试中性能驱动自动化的理论和方法
批准号:
RGPIN-2014-04275
负责人:
Veneris, Andreas
金额:
$2.26万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2014
资助国家:
加拿大
项目状态:
已结题
起止时间:
2014-01-01 至 2015-12-31

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中文摘要
翻译
半导体行业的产品覆盖国内和国际商业和消费市场的各个方面。它不断创造更小、更快、更强大的集成计算机超大规模集成(VLSI)芯片,从而加速了终端产品的需求。芯片公司面临的挑战是设计出越来越复杂的设备,同时保持成本竞争力。计算机辅助设计(CAD)工具正在不断提高效率,以降低这一成本。在过去的十年中,验证这些系统正确性的努力不成比例地增加,并且占用了整个设计周期的70%,这一趋势创造了验证差距。在半导体行业,验证工程师与设计人员的比例为3:1,这也证实了这一点,预计到2015年,这一趋势将增长近两倍。当验证失败并且设计被证明是不正确时,调试就会随之而来,以确定错误的来源并修复它。今天,这主要是一项手工任务。正如技术路线图和研究表明的那样,资源密集的人工调试已经成为验证差距中最重要的组成部分,占用了总验证时间的32%。也就是说,对于一个典型的18个月的设计周期,今天的工程师要花4-5个月的时间进行手动调试。显然,这会带来不成比例的非经常性成本,并可能危及芯片的交货日期。因此,最大的电子设计自动化CAD工具供应商Synopsys的首席执行官最近宣布调试是未来5-6年验证研发的中心主题也就不足为奇了。十年前,我们是第一个认识到这一新兴趋势的组织。2005年,我们提出了第一个自动化调试理论和方法,今天被世界各地的同行研究小组和行业使用和引用。在本提案中,我们利用这项投资来研究正式CAD工具的新理论和现代芯片验证/调试周期的相应方法。这些工具将利用强大的引擎和专有的数据挖掘算法,对验证产生的大数据进行详尽的分析,以确保设计的正确性。最终的结果将是理论和CAD工具,可以部署在任何工业半导体现场,以帮助工程师在调试期间。这个雄心勃勃的多学科项目承诺重大的理论进步和实际应用,为VLSI的CAD以及其他科学领域(如软件验证,数据挖掘和人工智能)带来好处。此外,由于半导体行业的持续增长,数字VLSI验证/调试方面的高素质人才(HQP)短缺,这在各级教育(博士,MASc, BASc)中仍然很强。因此,毫不奇怪,在加拿大国内,工业、政治和教育方面继续对卫生品质管理相关领域的培训给予大量关注。参与技术开发的每个人都将获得先进的CAD概念,实际的VLSI验证,实践经验和战略规划方面的知识。我们领先的研发环境和与业界的合作将为他们提供无与伦比的创新经验。研究生将在具有严格接受标准的著名科学会议/期刊上发表论文,并将获得国际知名度。正如我们的校友毕业后成功就业所表明的那样,这个HQP将在技术前沿获得知识,他们将以有利于加拿大社会和经济的方式运用这些知识。
英文摘要
The semiconductor industry has products reaching all aspects of commercial and consumer markets domestically and internationally. It consistently creates smaller, faster and more powerful integrated computer Very Large Scale of Integration (VLSI) chips which fuel the accelerated demand of the end products. Chip companies are challenged to design increasingly complex devices while remaining cost competitive. Computer-Aided Design (CAD) tools are continuously improving their efficiency to mitigate this cost. In the past decade, the effort to verify the correctness of these systems has increased disproportionately and takes as much as 70% of the total design cycle, a trend coined the verification gap. This is also confirmed by the 3:1 ratio between the number of verification engineers versus that of designers in the semiconductor industry, a trend that has been projected to increase almost two-fold by 2015. When verification fails and the design is proven to be incorrect, debugging follows to identify the source of the error and fix it. Today, this is a predominantly manual task. As technical roadmaps and research studies indicate, the resource-intensive manual debugging has become the most significant component of the verification gap taking as much as 32% of the total verification time. That is, for a typical design cycle of 18 months, engineers today spend 4-5 months in manual debugging. Evidently, this introduces disproportional non-recurring costs and it may jeopardize the chip delivery day. Consequently, it comes as no surprise that debugging was recently pronounced the central theme in verification R&D for the next 5-6 years by the CEO of Synopsys, the largest Electronic Design Automation CAD tool vendor. Our group was the first to recognize this emerging trend ten years ago. In 2005 we proposed the first automated debugging theory and methodology that today is used and referenced by peer research groups and industry worldwide. In this proposal we leverage this investment to investigate new theories for formal CAD tools and respective methodologies for the modern chip verification/debug cycle. These tools will utilize robust engines and proprietary data mining algorithms to exhaustively analyze the big data generated by verification to ensure correctness of the design. The end result will be the theory and a CAD tool that can be deployed in any industrial semiconductor site to aid the engineers during debugging. This ambitious and multi-disciplinary project promises major theoretical advances and practical applications that instill benefit in CAD for VLSI but also in other fields of science such as software verification, data mining and artificial intelligence. Further, due to the continuous growth of semiconductor industry, there has been a shortage of Highly Qualified Personnel (HQP) in digital VLSI verification/debug that remains strong at all levels of education (PhD, MASc, BASc). Hence, it comes as no surprise that there continues to be much industrial, political and educational attention within Canada devoted in training of HQP in related areas. Everybody involved with the development of the technology will gain knowledge in advanced CAD concepts, practical VLSI verification, hands-on experience and strategic planning. Our pioneering R&D environment and collaboration with the industry will offer them an unparalleled experience in innovation. Graduate students will publish in prominent scientific conferences/journals with strict acceptance criteria and they will gain international visibility. As shown by the post-graduation employment success of our alumnus, this HQP will gain knowledge at the forefront of technology and they will exercise it in a way beneficial to the Canadian society and economy.
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Automated Smart Contract Synthesis and Verification for Distributed Ledger Blockchain Technology
  • 批准号:
    RGPIN-2019-04354
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.04万
  • 财政年份:
    2022
  • 负责人:
    Veneris, Andreas
  • 依托单位:
Automated Smart Contract Synthesis and Verification for Distributed Ledger Blockchain Technology
  • 批准号:
    RGPIN-2019-04354
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.04万
  • 财政年份:
    2021
  • 负责人:
    Veneris, Andreas
  • 依托单位:
Automated Smart Contract Synthesis and Verification for Distributed Ledger Blockchain Technology
  • 批准号:
    RGPIN-2019-04354
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.04万
  • 财政年份:
    2020
  • 负责人:
    Veneris, Andreas
  • 依托单位:
Automated Smart Contract Synthesis and Verification for Distributed Ledger Blockchain Technology
  • 批准号:
    RGPIN-2019-04354
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.04万
  • 财政年份:
    2019
  • 负责人:
    Veneris, Andreas
  • 依托单位:
海外基金