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Funded Research

Fast, Accurate PPA Model-Extraction, Center for Advanced Electronics through Machine Learning (CAEML) Core Project 3A2 funded with industry membership dues.

Sponsored by University of Illinois - Urbana-Champaign

William R. Davis
Paul D. Franzon
Dror Zeev Baron

Project runs from 01/01/2019 to 12/31/2020
$109,386

This project researches methods for extracting fast and accurate estimators from System-Level Architecture to Power, performance, and area (SLA2PPA) in digital integrated circuits. Specifically, this project focuses on elimination of the complicated gate-level simulations needed to make accurate predictions of power, which typically occur very late in the design process. Extraction of system-level power models is extremely difficult, because the data-points are so few and so noisy, while the number of possible model parameters is so huge. This project will develop a comprehensive data-mining methodology to maximize the accuracy of PPA predictions while minimizing the data-collection effort.

Paul Franzon

Paul Franzon

Cirrus Logic Distinguished Professor
Director of Graduate Programs

 Monteith Research Center (MRC) 443
  paulf@ncsu.edu
  Website
Dror Baron

Dror Baron

Associate Professor

 Engineering Building II (EB2) 2097
  dzbaron@ncsu.edu
  Website

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Department of Electrical and Computer Engineering

890 Oval Drive
3114 Engineering Building II
Raleigh, NC 27606

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