Spintronic Stochastic Dataflow Computing

Abstract

This program addressed the memory bottleneck problem in traditional Von Neumann computing architecture. This particularly challenging problem limits advances in artificial intelligence applications because they have an insatiable need for memory. This effort focused on two novel approaches to overcome the bottleneck: new magnetic memory technology and a stochastic computing framework.

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Document Details

Document Type
Technical Report
Publication Date
Jun 12, 2024
Accession Number
AD1229897

Entities

People

  • Alexander Graening
  • Haoran He
  • Haris Suhail
  • Jiyue Yang
  • Kang L. Wang
  • Puneet Gupta
  • Sudhakar Pamarti
  • Vinod K. Jacob

Organizations

  • University of California, Los Angeles

Tags

Fields of Study

  • Computer science

Readers

  • Mathematical Modeling and Probability Theory.
  • Military Science and Technology Research and Modernization.
  • Parallel and Distributed Computing.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Machine Learning Algorithms
  • Microelectronics