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

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| Supervising SRS || Sherry Joy Alvionne S. Baquiran
| Supervising SRS || Sherry Joy Alvionne S. Baquiran
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| rowspan="2" | University Researcher || Fredrick Angelo Galapon
| rowspan="3" | University Researcher || Fredrick Angelo Galapon
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| Allen Jason Tan
| Allen Jason Tan
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|Lawrence Roman Quizon
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| Science Research Specialist || Maria Luz Limun
| Science Research Specialist || Maria Luz Limun
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| Rhandley D. Cajote, PhD
| Rhandley D. Cajote, PhD
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| Lawrence Roman Quizon
| John Francis Chan
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| rowspan="2" | Student Affiliate || Joenard Matanguihan
| rowspan="2" | Student Affiliate || Joenard Matanguihan
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==Activities==
==Activities==
The project has five (5) major activities:
The project will have four (4) major activities:
#Design and implementation WSN machine learning for [[clustering and routing]]
#Design and implementation WSN machine learning for [[clustering and routing]]
#ISA-optimization of [[RISC-V processor for machine learning]]
#ISA-optimization of [[RISC-V processor for machine learning]]
#Design, implementation, and verification of a proof-of-concept [[distributed learning]] in 28nm FDSOI CMOS technology.
#Design, implementation, and verification of a proof-of-concept [[distributed learning]] in 28nm FDSOI CMOS technology.
#Design and implementation of a proof-of-concept [[security module]] using physically unclonable functions (PUF)
#Design and implementation of a proof-of-concept [[security module]] using physically unclonable functions (PUF)
#Establishment of mirror labs
==Resources==
==Resources==
*[[PSHS Internship 2023]]
*[[PSHS Internship 2023]]

Revision as of 20:02, 12 June 2023

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
Lawrence Roman Quizon
Science Research Specialist Maria Luz Limun
Science Aide Patrick Jake Valdez
Project Staff Ryan Albert Antonio
Rhandley D. Cajote, PhD
John Francis Chan
Student Affiliate Joenard Matanguihan
Randolf Tamayo

Activities

The project will have four (4) major activities:

  1. Design and implementation WSN machine learning for clustering and routing
  2. ISA-optimization of RISC-V processor for machine learning
  3. Design, implementation, and verification of a proof-of-concept distributed learning in 28nm FDSOI CMOS technology.
  4. Design and implementation of a proof-of-concept security module using physically unclonable functions (PUF)

Resources

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