课题基金 / 基金详情

Formal methods for the generation of power-safe test sets for digital circuits

Formal methods for the generation of power-safe test sets for digital circuits
生成数字电路电源安全测试装置的形式方法
批准号:
290826165
负责人:
Professor Dr. Rolf Drechsler, since 10/2017
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
2016
资助国家:
德国
项目状态:
已结题
起止时间:
2015-12-31 至 2018-12-31

项目摘要

项目成果

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
The aim of this project is the development of a methodology for the generation of a power-safe test set for the production test of digital circuits. The test set should comply to the functional power specification of the circuit and prevent faults based on non functional power usage. Additionally, the test set should cover faults caused by high functional power peaks. Fault coverage loss should be prevented. A special focus should lie on the integration of layout information, which enables the incooperation of regional switching activity to prevent local IR drop. In order to guarantee a high fault coverage for hard to test circuits, SAT-based (optimization) methods should be developed as the underlying ATPG engine. It is assumed that these methods are able to process the large number of additional constraints more efficiently and, consequently, generate tests of higher quality than structural ATPG algorithms.
期刊论文(6)
专著(0)
科研奖励(0)
会议论文
SAT-based post-processing for regional capture power reduction in at-speed scan test generation
基于 SAT 的后处理,可降低全速扫描测试生成中的区域捕获功率
DOI: 10.1109/ets.2016.7519327
发表时间: 2016
期刊: 2016 21th IEEE European Test Symposium (ETS)
影响因子: --
作者: [S. Eggersglüß, K. Miyase, X. Wen]
通讯作者: X. Wen
Machine learning based test pattern analysis for localizing critical power activity areas
基于机器学习的测试模式分析,用于本地化关键电力活动区域
DOI: 10.1109/dft.2017.8244464
发表时间: 2017
期刊: 2017 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT)
影响因子: --
作者: [H. Dhotre, S. Eggersglüß, M. Dehbashi, U. Pfannkuchen, R. Drechsler]
通讯作者: R. Drechsler
Machine Learning-based Prediction of Test Power
基于机器学习的测试功率预测
DOI: 10.1109/ets.2019.8791548
发表时间: 2019
期刊: 2019 IEEE European Test Symposium (ETS)
影响因子: --
作者: [H. Dhotre, S. Eggersglüß, K. Chakrabarty, R. Drechsler]
通讯作者: R. Drechsler
DOI: 10.1109/tcad.2016.2552822
发表时间: 2016-12
期刊: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
影响因子: 2.9
作者: [Stephan Eggersglüß;K. Schmitz;Rene Krenz-Baath;R. Drechsler]
通讯作者: Stephan Eggersglüß;K. Schmitz;Rene Krenz-Baath;R. Drechsler
6
    国内基金
    海外基金
    复杂图像处理中的自由非连续问题及其水平集方法研究
    • 批准号:
      60872130
    • 项目类别:
      面上项目
    • 资助金额:
      28.0万元
    • 批准年份:
      2008
    • 负责人:
      刘国才
    • 依托单位:
    Computational Methods for Analyzing Toponome Data