Cluster Restoration-Based Trace Signal Selection for Post-Silicon Debug.

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Title: Cluster Restoration-Based Trace Signal Selection for Post-Silicon Debug.
Authors: Cheng, Yun1 chengyun@ict.ac.cn, Li, Huawei1 lihuawei@ict.ac.cn, Wang, Ying1 wangying2009@ict.ac.cn, Li, Xiaowei1 lxw@ict.ac.cn
Source: IEEE Transactions on Computer-Aided Design of Integrated Circuits & Systems. Apr2019, Vol. 38 Issue 4, p767-779. 13p.
Subjects: Computer debugging software, Debugging, Computer workstation clusters, Microsoft Windows (Operating system), Logic circuits
Abstract: Trace signal selection is of great importance for post-silicon debug. Debuggers traditionally use state restoration to improve the observability of the trace data, and state restoration ratio (SRR) is computed after state restoration. In this paper, we exploit the combination of snapshot states and trace states to improve the observability. First, we propose a novel state restoration method, called cluster restoration. It uses both the snapshot states of flip-flop clusters at the beginning of tracing, and the tracing states of the clusters’ inputs during the tracing window to deterministically restore all states of these clusters during the tracing window. We also present a cluster restoration-based trace signal selection method to select clusters instead of trace signals directly, which includes two stages: 1) cluster generation and 2) cluster evaluation. For cluster generation, feedback loop-based cluster generation and backward tracing-based cluster generation techniques are proposed. For cluster evaluation, a new metric, called the global state restoration improvement is proposed to evaluate the candidate clusters. The experimental results show that in comparison to prior trace signal selection methods, our method can improve the SRR and reduce the runtime of trace signal selection as well. [ABSTRACT FROM AUTHOR]
Copyright of IEEE Transactions on Computer-Aided Design of Integrated Circuits & Systems is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Cluster Restoration-Based Trace Signal Selection for Post-Silicon Debug.
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  Data: <searchLink fieldCode="DE" term="%22Computer+debugging+software%22">Computer debugging software</searchLink><br /><searchLink fieldCode="DE" term="%22Debugging%22">Debugging</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+workstation+clusters%22">Computer workstation clusters</searchLink><br /><searchLink fieldCode="DE" term="%22Microsoft+Windows+%28Operating+system%29%22">Microsoft Windows (Operating system)</searchLink><br /><searchLink fieldCode="DE" term="%22Logic+circuits%22">Logic circuits</searchLink>
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  Data: Trace signal selection is of great importance for post-silicon debug. Debuggers traditionally use state restoration to improve the observability of the trace data, and state restoration ratio (SRR) is computed after state restoration. In this paper, we exploit the combination of snapshot states and trace states to improve the observability. First, we propose a novel state restoration method, called cluster restoration. It uses both the snapshot states of flip-flop clusters at the beginning of tracing, and the tracing states of the clusters’ inputs during the tracing window to deterministically restore all states of these clusters during the tracing window. We also present a cluster restoration-based trace signal selection method to select clusters instead of trace signals directly, which includes two stages: 1) cluster generation and 2) cluster evaluation. For cluster generation, feedback loop-based cluster generation and backward tracing-based cluster generation techniques are proposed. For cluster evaluation, a new metric, called the global state restoration improvement is proposed to evaluate the candidate clusters. The experimental results show that in comparison to prior trace signal selection methods, our method can improve the SRR and reduce the runtime of trace signal selection as well. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of IEEE Transactions on Computer-Aided Design of Integrated Circuits & Systems is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1109/TCAD.2018.2818690
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      – Code: eng
        Text: English
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        PageCount: 13
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        Type: general
      – SubjectFull: Debugging
        Type: general
      – SubjectFull: Computer workstation clusters
        Type: general
      – SubjectFull: Microsoft Windows (Operating system)
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      – SubjectFull: Logic circuits
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      – TitleFull: Cluster Restoration-Based Trace Signal Selection for Post-Silicon Debug.
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            NameFull: Cheng, Yun
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            NameFull: Li, Huawei
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            NameFull: Wang, Ying
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            – D: 01
              M: 04
              Text: Apr2019
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              Y: 2019
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