Big Data tool integration in physical design process find hidden patterns, predictive analysis and classifying Big Data

Abstract

Physical Design (PD) Big Data tool is designed primarily to assist chip design engineers in achieving design optimization. It uses data mining techniques to handle the existing unstructured data repository. The tool extracts the relevant data and loads it into a well-structured database. It also has an archive mechanism that initially creates and then keeps updating an archive repository on a daily basis. The original input to the PD tool is a completely unstructured datasource which are read by the tool using regular expression based data extraction methodology. By doing this, PD tool converts the input data into the structured tables. This undergoes the data cleansing process before being fed into the operational DB. By maintaining an archive repository of this, PD tool also ensures data integrity and data validity. PD tool 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.