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http://hdl.handle.net/11375/19112
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DC Field | Value | Language |
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dc.contributor.advisor | Nicolici, Nicola | - |
dc.contributor.author | Shi, Xiaobing | - |
dc.date.accessioned | 2016-04-20T19:55:03Z | - |
dc.date.available | 2016-04-20T19:55:03Z | - |
dc.date.issued | 2016 | - |
dc.identifier.uri | http://hdl.handle.net/11375/19112 | - |
dc.description.abstract | Due to the growing complexity of integrated circuits, significant efforts are undertaken to ensure the design and implementation meet the specification and quality requirements both at the pre-silicon verification stage (before tape-out), as well as at the post-silicon validation stage (on the silicon prototypes). In particular, the constrained-random methods, which subject the design to a large volume of random, yet functionally-compliant stimuli, are widely employed during the pre-silicon stage. Hardware description languages, such as SystemVerilog, have standardized and well-defined features to formalize the constraints including format, sequence control and distribution. Nonetheless, it is not obvious how such features can be efficiently leveraged at the post-silicon stage. In this dissertation, a systematic methodology is proposed to support constrained-random generation and application during post-silicon validation. This includes both software algorithms and on-chip hardware structures. The proposed software translates functional constraints from SystemVerilog into a cube-based representation. A method to design in-field programmable signal generators, which are placed on-chip, can directly expand compacted cubes to extensive random, yet functionally compliant, sequences for post-silicon validation. This approach is extended to also support sequential constraints, as well as the control of the stimuli distribution. | en_US |
dc.language.iso | en | en_US |
dc.title | Constrained-Random Stimuli Generation for Post-Silicon Validation | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Electrical and Computer Engineering | en_US |
dc.description.degreetype | Dissertation | en_US |
dc.description.degree | Doctor of Philosophy (PhD) | en_US |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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Shi_Xiaobing_201604_PhD.pdf | Main dissertation | 3.98 MB | Adobe PDF | View/Open |
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