A Tensorflow to Real-Time Machine Learning (RTML) Compiler

Abstract

This project developed techniques for compiling deep learning models to silicon hardware with a computation mapping and schedule. The key results are (i) a novel technique to effect mapping and scheduling of deep learning model computations on hardware, and (ii) a proof-of-concept energy-efficient hardware implementation capable of both training and inference tasks.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jul 25, 2023
Accession Number
AD1206486

Entities

People

  • Lis Miesko

Organizations

  • University of British Columbia

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Artificial Intelligence
  • Artificial Intelligence Computing
  • Artificial Intelligence Software
  • Computations
  • Computer Architecture
  • Computer Languages
  • Computer Programming
  • Computer Vision
  • Computers
  • Convolutional Neural Networks
  • Deep Learning
  • Image Recognition
  • Information Processing
  • Information Systems
  • Machine Learning
  • Measurement
  • Neural Networks
  • Trees (Data Structures)

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computer Science.
  • Integrated Circuit Design and Technology.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks