Reducing post-silicon coverage monitoring overhead with emulation and statistical analysis

With increasing design complexity, post-silicon validation has become a critical problem. In pre-silicon validation, coverage is the primary metric of validation effectiveness, but in post-silicon, the lack of observability makes coverage measurement problematic. On-chip coverage monitors are a poss...

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Main Author: Ochoa Gallardo, Ricardo
Language:English
Published: University of British Columbia 2015
Online Access:http://hdl.handle.net/2429/54393
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spelling ndltd-UBC-oai-circle.library.ubc.ca-2429-543932018-01-05T17:28:24Z Reducing post-silicon coverage monitoring overhead with emulation and statistical analysis Ochoa Gallardo, Ricardo With increasing design complexity, post-silicon validation has become a critical problem. In pre-silicon validation, coverage is the primary metric of validation effectiveness, but in post-silicon, the lack of observability makes coverage measurement problematic. On-chip coverage monitors are a possible solution, where a coverage monitor is a hardware circuit that sets to one when the coverage event of interest occurs. However, prior research has shown that the overhead is prohibitive for anything beyond a small number of coverage monitors. In this thesis, I explore techniques that reduce the number of instrumented coverage monitors, while still being able to imply full coverage with high probability. These techniques use a deterministic forward feature selection algorithm with the objective functions based on statistical information. For gathering the required statistical information, the method relies on emulation, where all coverage monitors of interest are instrumented on a version of the design. On this emulator, such as an FPGA, I stress the design with randomly generated tests to collect the data from the instrumented coverage monitors. I propose three objective functions for the feature selection algorithm: the first estimates the probability of a coverage monitor being set during a test; the next objective function builds a Bayesian Network (BN), then takes advantage of the relationship information between nodes (coverage monitors), which the network provides; the last objective function directly estimates the conditional probability of coverage from the gathered data. I demonstrate these techniques on a non-trivial system-on-chip, by measuring the code coverage achieved after executing randomly generated test programs. Depending on the objective function, results show a 67.7% to 95.5% reduction in the number of required coverage monitors. In the ASIC implementation, this would translate into an impact of 0.33-1.96% in silicon area overhead and 0.40-2.70% in static power overhead. These results show my technique works, by proving it is possible to track a smaller number of coverage events that statistically represent the whole set. Applied Science, Faculty of Electrical and Computer Engineering, Department of Graduate 2015-08-13T14:41:27Z 2015-08-13T14:41:27Z 2015 2015-09 Text Thesis/Dissertation http://hdl.handle.net/2429/54393 eng Attribution-NonCommercial-NoDerivs 2.5 Canada http://creativecommons.org/licenses/by-nc-nd/2.5/ca/ University of British Columbia
collection NDLTD
language English
sources NDLTD
description With increasing design complexity, post-silicon validation has become a critical problem. In pre-silicon validation, coverage is the primary metric of validation effectiveness, but in post-silicon, the lack of observability makes coverage measurement problematic. On-chip coverage monitors are a possible solution, where a coverage monitor is a hardware circuit that sets to one when the coverage event of interest occurs. However, prior research has shown that the overhead is prohibitive for anything beyond a small number of coverage monitors. In this thesis, I explore techniques that reduce the number of instrumented coverage monitors, while still being able to imply full coverage with high probability. These techniques use a deterministic forward feature selection algorithm with the objective functions based on statistical information. For gathering the required statistical information, the method relies on emulation, where all coverage monitors of interest are instrumented on a version of the design. On this emulator, such as an FPGA, I stress the design with randomly generated tests to collect the data from the instrumented coverage monitors. I propose three objective functions for the feature selection algorithm: the first estimates the probability of a coverage monitor being set during a test; the next objective function builds a Bayesian Network (BN), then takes advantage of the relationship information between nodes (coverage monitors), which the network provides; the last objective function directly estimates the conditional probability of coverage from the gathered data. I demonstrate these techniques on a non-trivial system-on-chip, by measuring the code coverage achieved after executing randomly generated test programs. Depending on the objective function, results show a 67.7% to 95.5% reduction in the number of required coverage monitors. In the ASIC implementation, this would translate into an impact of 0.33-1.96% in silicon area overhead and 0.40-2.70% in static power overhead. These results show my technique works, by proving it is possible to track a smaller number of coverage events that statistically represent the whole set. === Applied Science, Faculty of === Electrical and Computer Engineering, Department of === Graduate
author Ochoa Gallardo, Ricardo
spellingShingle Ochoa Gallardo, Ricardo
Reducing post-silicon coverage monitoring overhead with emulation and statistical analysis
author_facet Ochoa Gallardo, Ricardo
author_sort Ochoa Gallardo, Ricardo
title Reducing post-silicon coverage monitoring overhead with emulation and statistical analysis
title_short Reducing post-silicon coverage monitoring overhead with emulation and statistical analysis
title_full Reducing post-silicon coverage monitoring overhead with emulation and statistical analysis
title_fullStr Reducing post-silicon coverage monitoring overhead with emulation and statistical analysis
title_full_unstemmed Reducing post-silicon coverage monitoring overhead with emulation and statistical analysis
title_sort reducing post-silicon coverage monitoring overhead with emulation and statistical analysis
publisher University of British Columbia
publishDate 2015
url http://hdl.handle.net/2429/54393
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