Energy Efficient Machine Learning Hardware Co-design: Difference between revisions

From Center for Integrated Circuits and Devices Research (CIDR)
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(Created page with "This  component  project  of  the  CIDR  program tackles  the  co-design  of  energy-efficient  machine  learning algorithms and hardware. Methodologies to integrate machine learning on-chip for distributed data processing, network lifespan improvement and security will be explored. These methodologies will likewise pave the way for automated hardware generation for the accelerator needed to perform these tasks. ==Personnel== *Project Leader:...")
 
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==Personnel==
==Personnel==
*Project Leader:                    Anastacia B. Alvarez, PhD
{| class="wikitable"
*Supervising SRS:                Sherry Joy Alvionne S. Baquiran
| Project Leader || Anastacia B. Alvarez, PhD
*University Researcher:        Fredrick Angelo Galapon
|-
Allen Jason Tan
| Supervising SRS || Sherry Joy Alvionne S. Baquiran
*Science Research SpecialistMaria Luz Limun
|-
*Project Staff:                      Ryan Albert Antonio
| University Researcher || Fredrick Angelo Galapon
Rhandley D. Cajote, PhD
|-
 
| || Allen Jason Tan
Lawrence Roman Quizon
|-
| Science Research Specialist || Maria Luz Limun
|-
| Project Staff || Ryan Albert Antonio
|-
| || Rhandley D. Cajote, PhD
|-
| || Lawrence Roman Quizon
|}


==Activities==
==Activities==

Revision as of 09:26, 29 September 2022

This  component  project  of  the  CIDR  program tackles  the  co-design  of  energy-efficient  machine  learning algorithms and hardware. Methodologies to integrate machine learning on-chip for distributed data processing, network lifespan improvement and security will be explored. These methodologies will likewise pave the way for automated hardware generation for the accelerator needed to perform these tasks.

Personnel

Project Leader Anastacia B. Alvarez, PhD
Supervising SRS Sherry Joy Alvionne S. Baquiran
University Researcher Fredrick Angelo Galapon
Allen Jason Tan
Science Research Specialist Maria Luz Limun
Project Staff Ryan Albert Antonio
Rhandley D. Cajote, PhD
Lawrence Roman Quizon

Activities

The project will have three major activities:

  1. The development of IR-UWB transmitter system models for analysis, energy optimization, and automated circuit generation,
  2. The design, implementation, and verification of IR-UWB transmitter building blocks, and
  3. The design, implementation, and verification of a proof-of-concept IR-UWB transmitter, all in 28nm fully-depleted silicon-on-insulator (FDSOI) CMOS technology.

Resources

  • Tutorials
  • Scripts
  • Presentations
  • Papers