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Analyze Physical Design Process Using Big Data Tool: Hidden Patterns, Performance Measures, Predictive Analysis and Classifying Logs

Analyze Physical Design Process Using Big Data Tool: Hidden Patterns, Performance Measures, Predictive Analysis and Classifying Logs

Waseem Ahmed, Lisa Fan
Copyright: © 2015 |Volume: 7 |Issue: 2 |Pages: 19
ISSN: 1942-9045|EISSN: 1942-9037|EISBN13: 9781466677388|DOI: 10.4018/IJSSCI.2015040102
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MLA

Ahmed, Waseem, and Lisa Fan. "Analyze Physical Design Process Using Big Data Tool: Hidden Patterns, Performance Measures, Predictive Analysis and Classifying Logs." IJSSCI vol.7, no.2 2015: pp.31-49. http://doi.org/10.4018/IJSSCI.2015040102

APA

Ahmed, W. & Fan, L. (2015). Analyze Physical Design Process Using Big Data Tool: Hidden Patterns, Performance Measures, Predictive Analysis and Classifying Logs. International Journal of Software Science and Computational Intelligence (IJSSCI), 7(2), 31-49. http://doi.org/10.4018/IJSSCI.2015040102

Chicago

Ahmed, Waseem, and Lisa Fan. "Analyze Physical Design Process Using Big Data Tool: Hidden Patterns, Performance Measures, Predictive Analysis and Classifying Logs," International Journal of Software Science and Computational Intelligence (IJSSCI) 7, no.2: 31-49. http://doi.org/10.4018/IJSSCI.2015040102

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Abstract

Physical Design (PD) Data tool is designed mainly to help ASIC design engineers in achieving chip design process quality, optimization and performance measures. The tool uses data mining techniques to handle the existing unstructured data repository. It extracts the relevant data and loads it into a well-structured database. Data archive mechanism is enabled that initially creates and then keeps updating an archive repository on a daily basis. The logs information provide to PD tool is a completely unstructured format which parse by regular expression (regex) based data extraction methodology. It converts the input data into the structured tables. This undergoes the data cleansing process before being fed into the operational DB. PD tool also ensures data integrity and data validity. It helps the design engineers to compare, correlate and inter-relate the results of their existing work with the ones done in the past which gives them a clear picture of the progress made and deviations that occurred. Data analysis can be done using various features offered by the tool such as graphical and statistical representation.

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