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Impromptu Data Extraction and Analysis Data Mining and Analytics Framework for VLSI Designs Sandeep P ([email protected]); +91 80 2507 5492 Anand Ananthanarayanan ([email protected]); +91 80 2507 5774 Intel Corporation Author Affiliations 2 Author Affiliation Phone Number Email Address Sandeep P Intel Corporation +91 80 2507 5492 [email protected] Anand Ananthanarayanan Intel Corporation +91 80 2507 5774 [email protected] , FOR INTERNAL USE ONLY Intel Information Technology Abstract Design processes from Logic design, validation, backend implementation and verification require a plethora of CAD tools. These tools generate reports, debug information in its own form and content. Designers need to parse and review data from multiple sources and tools to make design calls. When implementing backend design, a designer or a methodology owner needs to understand the patterns seen in the design. Data like number of paths dominated by low leakage, Slope profile for cells with margin > x ps, Drive strength profile of cells in timing path, etc., are critical to make design decisions, optimize design collaterals and ensure design with robust electrical functionality. Many of the data can be obtained only through data mining of results and logs of multiple tools. Data mining is also a constant activity from technology readiness to execution and post silicon debug phases. Data mining problem gets compounded when data is needed from different PV domains. For example, a designer looking to optimize power would need dynamic power information, path margin and max cap information all generated by different tools in different formats in different locations. Data mining has been historically done by adhoc scripts to parse through different reports, and log files. Data generated is post processed and then visualized. Any requirement change in data mining would need changes in the scripts. There is no data mining model which supports multiple tools with different output formats. There is no methodology which supports cross domain analysis. We present IDEA (Impromptu Data Extraction and Analysis). IDEA is data mining and data analysis framework in a highly interactive web application platform. It supports assimilating data from different tools and formats into one data organization in the form of SQL tables. SQL enables compact organization and faster queries. IDEA framework is built using the Linux-Apache™-Mysql™-Perl (LAMP) packages and uses the R language for performing statistical analysis on the data. R language enables handling huge amount of data with support for different statistical plots like pie-charts, histograms, box plots, scatter plots, Linear regression etc. IDEA data mining completes in minutes compared to hours/days with conventional approaches like scripts. IDEA is highly interactive web application with all the data extraction and plotting functionalities abstracted using highly interactive widgets. IDEA has been used to data mine power savings post Optimization, Analysis of power distribution, Profile the speed paths, Review standard cells usage, Utilization of cell sizes across the design space, RC delays per path stage and has multiple other usages. Large precious unorganized data lies unexploited. Structured Data Mining essential for competitive VLSI design. Increasing complexity makes data analytics a must-have for quality design. No EDA tool exists today to do this critical data mining. IDEA fills this gap and provides valuable data mining capability. It is time to think of Data Mining as a EDA product 3 , FOR INTERNAL USE ONLY Intel Information Technology Design Process Design Reports Timing Reports Extraction reports Route utilization Cell utilization DRC reports Layout Checks Logic Implement Verify Functional Circuit Design Multiple Tools Multiple Reports Multiple Formats Large Data gets generated requiring interpretation and Analysis 4 , FOR INTERNAL USE ONLY Intel Information Technology Data Conundrum Design Quality Increasingly Dependent on Multiple Parameters 5 , FOR INTERNAL USE ONLY Intel Information Technology Data Mining - A Constant Activity Tech Readiness Design execution Post silicon • Data mining is done to generate design heuristics • Data mining is done to determine delta changes on design limits • Data mining needed for optimization • Data mining is done to root cause and understand the PV-Silicon miscorrelation Formal Data Mining Tool or Model Not Currently Available In Industry 6 , FOR INTERNAL USE ONLY Intel Information Technology To solve this Data Mining problem, we present 7 , FOR INTERNAL USE ONLY Intel Information Technology IDEA Impromptu Data Extraction and Analysis (IDEA) is Web application for Data mining on an open architecture Linked Data Caching SQL databases Common Xml interface for data manipulation Statistical analysis capability with ‘R’ Language Practically unlimited capacity with ‘R’ Language Data visualization capability Histograms, pie charts, density/scatter plots, dot charts Faster turn around time (no text parsing scripts) Intuitive, web based user interface Highly Interactive Application for Data Mining 8 , FOR INTERNAL USE ONLY Intel Information Technology IDEA Web Based Data Mining Platform 9 , FOR INTERNAL USE ONLY Intel Information Technology IDEA Architecture Application Tier Presentation Tier DataBase Storage Tier Three Tiered Web Application 10 , FOR INTERNAL USE ONLY Intel Information Technology Architecture – Idea Client Data Extraction Control Center Data Manipulation Data Viewer AJAX Calls JSON for data transfer Experiments Apps Idea Server Report Viewer Statistical Analysis Spreadsheet Generation PDF Converter Simple Client with Powerful Capabilities 11 , FOR INTERNAL USE ONLY Intel Information Technology Basic Usage Flow Open IDEA App 12 Select Project Select Blocks Manipulate Data Generate PDF or export to spreadsheets Run Statistical Analysis and Reports Run pre-selected Queries OR Query interactively , FOR INTERNAL USE ONLY Intel Information Technology IDEA Usage and Benefits Datamine power savings post Optim RC delays per path stage Analysis of power distribution IDEA Usage Utilization of cell sizes across the design space Profile the speed paths Review standard cells usage - Data Mining Simplified 13 , FOR INTERNAL USE ONLY Intel Information Technology Summary • • • • • Large precious unorganized data lies unexploited Structured Data Mining essential for competitive VLSI design Increasing complexity makes data analytics a must-have for quality design No EDA tool exists today to do this critical data mining IDEA fills this gap and provides valuable data mining capability - It is time to think of Data Mining as a EDA product 14 , FOR INTERNAL USE ONLY Intel Information Technology Acknowledgements Everyone at Intel who contributed to this work 15 , FOR INTERNAL USE ONLY Intel Information Technology