DURIP: Building a GPU Computational Infrastructure Platform for Heterogeneous Big Data Analysis and Understanding

Abstract

In this proposed effort, we plan on building a powerful and flexible GPU computational infrastructure platform which consists of (i) a GPU cluster with more than 79,000 GPU cores and around 80 CPU cores including three requested cutting-edge GPU supercomputers and ten existing desktops, and (ii) a mobile base with on-board computer for robots. The platform will be used by both the Vision, Information, and Statistical Signal Theories and Applications (VISSTA) lab directed by the co-PI Krim, and the Interpretable Visual Modeling and Computing Lab(iVMCL) currently created by the PI Wu in the department of Electrical and Computer Engineering at NC State University (NCSU). The proposed computational platform will enable the two to address ongoing research projects on heterogeneous Big Data analysis and deep understanding, as well as to smoothly prepare for future ones.

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Document Details

Document Type
Technical Report
Publication Date
Aug 29, 2019
Accession Number
AD1090581

Entities

People

  • Hamid Krim
  • Tianfu Wu

Organizations

  • North Carolina State University

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Artificial Intelligence Software
  • Artificial Neural Networks
  • Big Data
  • Cognitive Science
  • Computational Science
  • Computer Languages
  • Computer Programming
  • Computer Programs
  • Computer Vision
  • Computers
  • Computing System Architectures
  • Convolutional Neural Networks
  • Data Analysis
  • Deep Learning
  • Detection
  • Detectors
  • Information Systems
  • Machine Learning
  • Neural Networks
  • Pattern Recognition
  • Recognition
  • Reinforcement Learning

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development
  • Research Science/Academic Research

Technology Areas

  • AI & ML
  • Autonomy