Skip navigation

DSpace

機構典藏 DSpace 系統致力於保存各式數位資料(如:文字、圖片、PDF)並使其易於取用。

點此認識 DSpace
DSpace logo
English
中文
  • 瀏覽論文
    • 校院系所
    • 出版年
    • 作者
    • 標題
    • 關鍵字
    • 指導教授
  • 搜尋 TDR
  • 授權 Q&A
    • 我的頁面
    • 接受 E-mail 通知
    • 編輯個人資料
  1. NTU Theses and Dissertations Repository
  2. 電機資訊學院
  3. 電子工程學研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/94275
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor黃鐘揚zh_TW
dc.contributor.advisorChung-Yang Huangen
dc.contributor.author陳孟宏zh_TW
dc.contributor.authorMeng-Hung Chenen
dc.date.accessioned2024-08-15T16:34:13Z-
dc.date.available2024-08-16-
dc.date.copyright2024-08-15-
dc.date.issued2024-
dc.date.submitted2024-08-06-
dc.identifier.citation[1] Binod Kumar, V. S. Vineesh, Puneet Nemade, and Masahiro Fujita. Aries: A semiformal technique for fine-grained bug localization in hardware designs. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 41(12):5709–5721, 2022.
[2] Hasini Witharana, Yangdi Lyu, Subodha Charles, and Prabhat Mishra. A survey on assertion-based hardware verification. ACM Comput. Surv., 54(11s), sep 2022.
[3] Stuart Sutherland. Who put assertions in my rtl code? and why? how rtl design engineers can benefit from the use of systemverilog assertions. https://sutherland-hdl.com/papers/2015-SNUG-SV_SVA-for-RTL-Designers_ paper.pdf, 2015. SNUG Silicon Valley 2015.
[4] Shobha Vasudevan, David Sheridan, Sanjay Patel, David Tcheng, Bill Tuohy, and Daniel Johnson. Goldmine: Automatic assertion generation using data mining and static analysis. In 2010 Design, Automation Test in Europe Conference Exhibition (DATE 2010), pages 626–629, 2010.
[5] Lingyi Liu, David Sheridan, Viraj Athavale, and Shobha Vasudevan. Automatic generation of assertions from system level design using data mining. In Ninth ACM/IEEE International Conference on Formal Methods and Models for Codesign (MEMPCODE2011), pages 191–200, 2011.
[6] Lingyi Liu, Chen-Hsuan Lin, and Shobha Vasudevan. Word level feature discovery to enhance quality of assertion mining. In Proceedings of the International Conference on Computer-Aided Design, ICCAD ’12, page 210–217, New York, NY, USA, 2012. Association for Computing Machinery.
[7] Alessandro Danese, Tara Ghasempouri, and Graziano Pravadelli. Automatic extraction of assertions from execution traces of behavioural models. In 2015 Design, Automation Test in Europe Conference Exhibition (DATE), pages 67–72, 2015.
[8] Tong Zhang, Daniel Saab, and Jacob A. Abraham. Automatic assertion generation for simulation, formal verification and emulation. In 2017 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), pages 471–476, 2017.
[9] Nicola Bombieri, Riccardo Filippozzi, Graziano Pravadelli, and Francesco Stefanni. Rtl property abstraction for tlm assertion-based verification. In 2015 Design, Automation Test in Europe Conference Exhibition (DATE), pages 85–90, 2015.
[10] Tara Ghasempouri, Alessandro Danese, Graziano Pravadelli, Nicola Bombieri, and Jaan Raik. Rtl assertion mining with automated rtl-to-tlm abstraction. In 2019 Forum for Specification and Design Languages (FDL), pages 1–8, 2019.
[11] Hasini Witharana, Aruna Jayasena, Andrew Whigham, and Prabhat Mishra. Automated generation of security assertions for rtl models. J. Emerg. Technol. Comput. Syst., 19(1), jan 2023.
[12] Alessandro Danese, Nicolò Dalla Riva, and Graziano Pravadelli. A-team: Automatic template-based assertion miner. In 2017 54th ACM/EDAC/IEEE Design Automation Conference (DAC), pages 1–6, 2017.
[13] Samuele Germiniani and Graziano Pravadelli. Harm: A hint-based assertion miner. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 41(11):4277–4288, 2022.
[14] Marcelo Orenes-Vera, Margaret Martonosi, and David Wentzlaff. Using llms to facilitate formal verification of rtl. https://arxiv.org/abs/2309.09437, 2023.
[15] Viraj Athavale, Sai Ma, Samuel Hertz, and Shobha Vasudevan. Code coverage of assertions using rtl source code analysis. In 2014 51st ACM/EDAC/IEEE Design Automation Conference (DAC), pages 1–6, 2014.
[16] Alessandro Danese, Francesca Filini, Tara Ghasempouri, and Graziano Pravadelli. Automatic generation and qualification of assertions on control signals: A time window-based approach. volume 483, pages 193–221, 09 2016.
[17] Tara Ghasempouri, Siavoosh Payandeh Azad, Behrad Niazmand, and Jaan Raik. An automatic approach to evaluate assertions’ quality based on data-mining metrics. In 2018 IEEE International Test Conference in Asia (ITC-Asia), pages 61–66, 2018.
[18] Hui-Na Chao, Hua-Wei Li, Xiaoyu Song, Tian-Cheng Wang, and Xiao-Wei Li. Evaluating and constraining hardware assertions with absent scenarios. Journal of Computer Science and Technology, 35(5):1198–1216, 2020.
[19] DebjitPal,SpencerOffenberger,andShobhaVasudevan.Assertionrankingusingrtl source code analysis. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 39(8):1711–1724, 2020.
[20] Mohammad Reza Heidari Iman, Jaan Raik, Maksim Jenihhin, Gert Jervan, and Tara Ghasempouri. An automated method for mining high-quality assertion sets. Microprocessors and Microsystems, 97:104773, 2023.
[21] Tai-Ying Jiang, C.-N.J. Liu, and Jing-Yang Jou. Effective error diagnosis for rtl designs in hdls. In Proceedings of the 11th Asian Test Symposium, 2002. (ATS ’02)., pages 362–367, 2002.
[22] Saeed Mirzaeian, Feijun Zheng, and K.-T. Tim Cheng. Rtl error diagnosis using a word-level sat-solver. In 2008 IEEE International Test Conference, pages 1–8, 2008.
[23] Mehdi Dehbashi and Görschwin Fey. Debug automation for synchronization bugs at rtl. In 2014 27th International Conference on VLSI Design and 2014 13th International Conference on Embedded Systems, pages 44–49, 2014.
[24] V. S. Vineesh, Binod Kumar, Rushikesh Shinde, Neelam Sharma, Masahiro Fujita, and Virendra Singh. Enhanced design debugging with assistance from guidance-based model checking. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 40(5):985–998, 2021.
[25] Neil Veira, Zissis Poulos,and Andreas Veneris. Suspect set prediction in rtl bug hunting. In 2018 Design, Automation Test in Europe Conference Exhibition (DATE), pages 1544–1549, 2018.
[26] Sanjay Rajashekar. A study on machine learning-based hardware bug localization, 2020. Available at https://oaktrust.library.tamu.edu/handle/1969.1/191832.
[27] Debjit Pal and Shobha Vasudevan. Symptomatic bug localization for functional debug of hardware designs. In 2016 29th International Conference on VLSI Design and 2016 15th International Conference on Embedded Systems (VLSID), pages 517– 522, 2016.
[28] Vighnesh Iyer, Donggyu Kim, Borivoje Nikolic, and Sanjit A. Seshia. Rtl bug localization through ltl specification mining (wip). MEMOCODE ’19, New York, NY, USA, 2019. Association for Computing Machinery.
[29] Samuele Germiniani and Graziano Pravadelli. Harm: A hint-based assertion miner. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 41(11):4277–4288, 2022.
[30] Doulos. Systemverilog assertions tutorial. https://www.doulos.com/knowhow/systemverilog/systemverilog-tutorials/systemverilog-assertions-tutorial/.
[31] ChipVerify. Uvm tutorial. https://www.chipverify.com/tutorials/uvm.
[32] VLSI Verify. Uvm introduction. https://vlsiverify.com/uvm/.
[33] Chuang Bo-Han. Rtl bug localization via sequential design matching, 2023. Available at http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/88888.
[34] Samuele Germiniani and Graziano Pravadelli. Harm source code (github). https://github.com/SamueleGerminiani/harm.
[35] Shinya Takamaeda-Yamazaki. Pyverilog: A python-based hardware design processing toolkit for verilog hdl. volume 9040, pages 451–460, 04 2015.
[36] Shinya Takamaeda-Yamazaki. Pyverilog source code (github). https://github.com/PyHDI/Pyverilog.
[37] Stephen Williams. Icarus verilog official documentation. https://steveicarus.github.io/iverilog/.
[38] Stephen Williams. Icarus verilog source code (github). https://github.com/steveicarus/iverilog.
[39] Synopsys. Vcs official website. https://www.synopsys.com/verification/simulation/vcs.html.
[40] Synopsys. Vcs official user guide documentation. http://cc.ee.ntu.edu.tw/~ric/teaching/SoC_Verification/S06/Homework/HW1/vcs.pdf.
[41] Synopsys. Vcf official website. https://www.synopsys.com/verification/static-and-formal-verification/vc-formal.html.
-
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/94275-
dc.description.abstract由於 IC 設計規模和複雜度的不斷增長,RTL 設計中的除錯變得越來越具有挑戰性。傳統上,工程師會生成測試模式並分析密集的波形文件,以追踪模擬結果,並與參考模型的正確結果進行比較。這個過程非常耗時且困難,因為涉及的信號眾多,包括輸入信號、輸出信號、內部信號和存儲器端口信號。
本論文介紹了我們的錯誤定位工具,可以自動過濾不相關的信號並突出顯示最有可能與錯誤相關的信號。通過根據信號的懷疑程度進行排序,並識別這些信號影響條件語句的控制路徑,該工具引導工程師找到最可能的問題區域。這顯著減少了除錯的時間和精力,使工程師能夠專注於最相關的信號和控制路徑,從而簡化了除錯密集波形和廣泛信號數據的複雜任務。這種方法將傳統上艱巨的 RTL 除錯任務轉變為更加可管理和高效的過程。
zh_TW
dc.description.abstractDebugging in RTL design is increasingly challenging due to the growing scale and complexity of IC designs. Traditionally, designers generate test patterns and analyze dense waveform files to trace simulation results and compare them with the golden results from a reference model. This process is time-consuming and difficult because of the numerous signals involved, including input, output, internal, and memory port signals.
This thesis introduces a novel bug localization tool that automates the filtering of unrelated signals and highlights those most likely associated with bugs. By ranking signals based on their suspected degrees and identifying the control paths where these signals influence conditional statements, the tool guides designers to the most likely problem areas. This significantly reduces debugging time and effort by allowing designers to focus on the most relevant signals and control paths, thereby simplifying the complex task of debugging dense waveforms and extensive signal data. This approach transforms RTL debugging from a traditionally arduous task into a more manageable and efficient process.
en
dc.description.provenanceSubmitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-08-15T16:34:13Z
No. of bitstreams: 0
en
dc.description.provenanceMade available in DSpace on 2024-08-15T16:34:13Z (GMT). No. of bitstreams: 0en
dc.description.tableofcontentsAcknowledgements i
中文摘要 iv
Abstract v
Contents vii
List of Figures x
List of Tables xiii
Chapter1 Introduction 1
1.1 Problem Statement and Motivation 1
1.2 Related Works 3
1.3 Contributions 6
1.4 Thesis Organization 8
Chapter2 Background Knowledge 10
2.1 Terminology Definitions 10
2.2 SystemVerilog Assertions 12
2.3 Verification Approaches for RTL Designs 13
2.3.1 Simulation-Based Verification 14
2.3.2 Formal-Based Verification 14
2.3.3 Assertion-Based Verification 15
2.4 UVM 16
2.5 Third Party Tools Utilized in Our Flow 20
2.5.1 SDM – Output Matcher 21
2.5.2 HARM – Assertion Miner 21
2.5.3 Pyverilog – Code Analyzer 21
2.5.4 Icarus Verilog – Simulator 22
2.5.5 Synopsys VCS – Simulator 22
2.5.6 Synopsys VC Formal – Formal Verifier 23
Chapter3 Overview of the Bug Localization Flow 24
3.1 How Our Tool Guides Designers to Debug 24
3.2 The Architecture of Our Framework 25
3.3 Relation between the Design and Assertions 29
3.4 Assumptions to the Design 31
3.5 Basic Categories for RTL Designs 33
Chapter4 Preparation Phase : Configuration File Setting 38
4.1 Configuration File Parameters 38
4.2 Setting the Configuration File through User Interface 46
Chapter5 Assertion Generation Phase : Valid Assertion Mining from the DUV 49
5.1 Overview of the Assertion Mining Algorithm 49
5.2 Assertion Mining by HARM 51
5.3 Formal Verifying Assertions by VC Formal 54
Chapter6 Assertion Validation Phase : Suspected Assertion Screening 58
6.1 Overview of the Suspected Assertion Screening Algorithm 58
6.2 Assertion Pattern Generation Algorithm 60
6.3 Automatic Testbench Generation Algorithm 65
6.4 Results Comparison with the Reference Model 70
Chapter7 Bug Localization Phase : Bug Localizing in RTL Codes 79
7.1 Mapping Suspected Assertions to RTL Codes 80
7.2 Weighting Hint Signals 82
7.3 Bug Localization Results and Debugging Hints for Designers 87
Chapter8 Experimental Results 90
8.1 A Brief Overview of the Blind Test Case 90
8.2 A Brief Overview of the Demo Cases 94
8.3 Results 102
Chapter9 Conclusion and Future Work 107
9.1 Conclusion 107
9.2 Future Work 108
References 110
Appendix A - Input Pattern Format 116
Appendix B - Output Result Format 118
-
dc.language.isoen-
dc.subject錯誤偵測zh_TW
dc.subject斷言zh_TW
dc.subject通用驗證方法學zh_TW
dc.subject驗證環境zh_TW
dc.subject積體電路設計zh_TW
dc.subjectUVMen
dc.subjectBug Diagnosingen
dc.subjectAssertionen
dc.subjectIntegrated Circuit Designen
dc.subjectVerification Environmenten
dc.title利用約束測試模式和斷言驗證進行 RTL Bug 自動定位zh_TW
dc.titleAutomatic RTL Bug Localization by Constrained Pattern Generation and Assertion Validationen
dc.typeThesis-
dc.date.schoolyear112-2-
dc.description.degree碩士-
dc.contributor.oralexamcommittee李建模;黃紹倫;莊咸和zh_TW
dc.contributor.oralexamcommitteeJian-Mo Li;Shao-Lun Huang;Xian-Huo Zhuangen
dc.subject.keyword錯誤偵測,斷言,通用驗證方法學,驗證環境,積體電路設計,zh_TW
dc.subject.keywordBug Diagnosing,Assertion,UVM,Verification Environment,Integrated Circuit Design,en
dc.relation.page119-
dc.identifier.doi10.6342/NTU202403664-
dc.rights.note同意授權(全球公開)-
dc.date.accepted2024-08-10-
dc.contributor.author-college電機資訊學院-
dc.contributor.author-dept電子工程學研究所-
顯示於系所單位:電子工程學研究所

文件中的檔案:
檔案 大小格式 
ntu-112-2.pdf36.73 MBAdobe PDF檢視/開啟
顯示文件簡單紀錄


系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。

社群連結
聯絡資訊
10617臺北市大安區羅斯福路四段1號
No.1 Sec.4, Roosevelt Rd., Taipei, Taiwan, R.O.C. 106
Tel: (02)33662353
Email: ntuetds@ntu.edu.tw
意見箱
相關連結
館藏目錄
國內圖書館整合查詢 MetaCat
臺大學術典藏 NTU Scholars
臺大圖書館數位典藏館
本站聲明
© NTU Library All Rights Reserved