EAGER: Storage-Based Logic Built-In Self-Test with Magnified Test Data

EAGER:基于存储的逻辑内置自测试,具有放大的测试数据

基本信息

  • 批准号:
    2041649
  • 负责人:
  • 金额:
    $ 25万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2020
  • 资助国家:
    美国
  • 起止时间:
    2020-10-01 至 2023-09-30
  • 项目状态:
    已结题

项目摘要

New technologies for manufacturing of electronic chips give rise to new defect mechanisms and increase the prevalence of defect occurrence. At the same time, applications such as automotive systems impose stricter requirements on reliability. Detecting the occurrence of defects is critical to the reliability of electronic chips, and the correct and safe operation of the many products that use them. Test sets used for manufacturing testing of electronic chips need to be comprehensive in their ability to detect and diagnose defects, but at the same time, satisfy cost constraints related to their storage and test application time. Each test needs to be utilized to the maximum to detect as many defects as possible of as many different types as possible to ensure that a cost-limited test set is able to achieve reliability goals. Such a test set is referred to as a focused test set, and is the subject of this project. The project will prepare students for the challenges of designing and manufacturing reliable electronic chips in current and future technologies, which is critical to the many US industries that rely on electronic chips. The PI will provide a role model and encourage women students to pursue degrees in the field of electrical and computer engineering. Through internship opportunities, students will get comprehensive training with both academic and industrial depth.To manage the complexity and variability in defect behaviors, fault models are used as abstract representations of defects, and a comprehensive set of tests targets the detection of faults from different models. However, faults from different models have similar tests, and the added value for defect detection diminishes as additional fault models are considered. Two complementary directions will be explored in this project for generating focused test sets. (1) Different fault models are used for providing comprehensive defect coverage. However, if faults of all types are considered equally important, a large number of tests results, and they are not all necessary for detecting or diagnosing defects. Instead, different faults should be used as complements of each other. The problem that will be considered in this project is how to partition target faults into subsets with similar (but not identical) detection conditions, and similar (but not identical) tests. A procedure for generating a focused test set will select non-similar representatives from each subset as targets for test generation, and thus produce tests that are well-utilized for defect detection and diagnosis. (2) In a basic test data compression scheme, each stored test is used for applying one test. Earlier works showed that the same stored test data can be used in more than one way to apply more tests. This allows the volume of test data to be reduced. The new observation that this project will utilize is that applying more tests based on the same stored test data is useful for improving the quality of a focused test set.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
用于制造电子芯片的新技术产生了新的缺陷机制并增加了缺陷发生的普遍性。同时,汽车系统等应用对可靠性提出了更严格的要求。检测缺陷的发生对于电子芯片的可靠性以及使用它们的许多产品的正确和安全操作至关重要。用于电子芯片的制造测试的测试集需要在其检测和诊断缺陷的能力方面是全面的,但同时满足与其存储和测试应用时间相关的成本约束。每个测试都需要被最大限度地利用,以检测尽可能多的不同类型的尽可能多的缺陷,以确保成本有限的测试集能够实现可靠性目标。这样的测试集被称为聚焦测试集,并且是这个项目的主题。该项目将为学生准备在当前和未来技术中设计和制造可靠的电子芯片的挑战,这对依赖电子芯片的许多美国行业至关重要。PI将提供一个榜样,鼓励女学生攻读电气和计算机工程领域的学位。通过实习机会,学生将获得学术和工业深度的全面培训。为了管理缺陷行为的复杂性和可变性,故障模型被用作缺陷的抽象表示,并且一套全面的测试旨在检测来自不同模型的故障。然而,来自不同模型的故障具有类似的测试,并且当考虑额外的故障模型时,缺陷检测的附加值减小。两个互补的方向将探讨在这个项目中产生集中的测试集。(1)不同的故障模型用于提供全面的缺陷覆盖。然而,如果所有类型的故障都被认为是同等重要的,则会产生大量的测试结果,并且它们对于检测或诊断缺陷并不都是必需的。相反,不同的故障应该作为彼此的补充。本计画所要考虑的问题是如何将目标故障分割成具有相似(但不相同)侦测条件、相似(但不相同)测试的子集。一个程序,用于生成一个集中的测试集将选择不相似的代表,从每个子集作为测试生成的目标,从而产生的测试,充分利用缺陷检测和诊断。(2)在基本测试数据压缩方案中,每个存储的测试用于应用一个测试。早期的工作表明,相同的存储测试数据可以以多种方式使用,以应用更多的测试。这允许减少测试数据的量。该项目将利用的新观察结果是,基于相同的存储测试数据应用更多的测试对于提高重点测试集的质量是有用的。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(8)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Storage-Based Logic Built-in Self-Test With Multicycle Tests
基于存储的逻辑内置自测试和多周期测试
Storage-Based Logic Built-In Self-Test With Cyclic Tests
基于存储的逻辑内置自测试和循环测试
Storage-Based Built-In Self-Test for Gate-Exhaustive Faults
针对栅极穷举故障的基于存储的内置自检
Storage-Based Logic Built-In Self-Test With Partitioned Deterministic Compressed Tests
基于存储的逻辑内置自测试和分区确定性压缩测试
Zoom-In Feature for Storage-Based Logic Built-In Self-Test
基于存储的逻辑内置自检的放大功能
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Irith Pomeranz其他文献

The minimum test set problem for circuits with nonreconvergent fanout

Irith Pomeranz的其他文献

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{{ truncateString('Irith Pomeranz', 18)}}的其他基金

SHF: Small: A Mosaic-Like Approach to the Selection of Fault Models
SHF:小:一种选择故障模型的马赛克式方法
  • 批准号:
    1714147
  • 财政年份:
    2017
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
Collaborative Research: High Quality Tests for Scan Circuits
合作研究:扫描电路的高质量测试
  • 批准号:
    0098091
  • 财政年份:
    2001
  • 资助金额:
    $ 25万
  • 项目类别:
    Continuing Grant
High-Quality Tests for Synchronous Sequential Circuits
同步时序电路的高质量测试
  • 批准号:
    0049081
  • 财政年份:
    2000
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
High-Quality Tests for Synchronous Sequential Circuits
同步时序电路的高质量测试
  • 批准号:
    9725053
  • 财政年份:
    1998
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant
NSF Young Investigator: A New Search Strategy for Design Automation
NSF 青年研究员:设计自动化的新搜索策略
  • 批准号:
    9357581
  • 财政年份:
    1993
  • 资助金额:
    $ 25万
  • 项目类别:
    Continuing Grant
High-Quality Tests for Combinational Circuits
组合电路的高质量测试
  • 批准号:
    9220549
  • 财政年份:
    1993
  • 资助金额:
    $ 25万
  • 项目类别:
    Continuing Grant
RIA: Test Generation for Synchronous Sequential Circuits
RIA:同步时序电路的测试生成
  • 批准号:
    9109568
  • 财政年份:
    1991
  • 资助金额:
    $ 25万
  • 项目类别:
    Standard Grant

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