Gaussian Synapses for Probabilistic Neural Network, Thrust Area: Novel Methods of Computing

Abstract

The recent decline in energy, size, and complexity scaling of Si complementary metal oxide semiconductor (CMOS) technology and the associated von Neumann architecture poses a significant challenge towards achieving Exascale Computing infrastructure, which is essential for defense and national security, healthcare, education, and agriculture

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Document Details

Document Type
Technical Report
Publication Date
Apr 10, 2023
Accession Number
AD1210896

Entities

People

  • Saptarshi Das

Organizations

  • Pennsylvania State University

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence Software
  • Bayesian Networks
  • Chemistry
  • Computational Science
  • Computer Languages
  • Computer Programming
  • Computer Vision
  • Data Mining
  • Health Services
  • Information Processing
  • Information Science
  • Integrated Circuits
  • Logic Gates
  • Machine Learning
  • Materials Science
  • Network Science
  • Neural Networks
  • Random Variables
  • Semiconductors
  • Transducers
  • Two-Dimensional Materials

Readers

  • Distributed Systems and Data Platform Development
  • Economics
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • Microelectronics