An Xdata Architecture for Federated Graph Models and Multi-tier Asymmetric Computing

Abstract

Scalable, data-parallel graph analytics on GPUs is a fundamentally hard problem that goes beyond the current state of the art. Scalable graph analytics are critical for a large range of application domains with a vital impact on both national security and the national economy. CPU graph algorithms are known to scale poorly due to non-locality and limited memory bandwidth. Our research shows that GPUs provide a high-performance, data-parallel, commodity hardware platform for graph analytics.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2014
Accession Number
ADA598040

Entities

People

  • Bryan Thompson
  • Michael Personick

Tags

Communities of Interest

  • Autonomy
  • Cyber
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Central Processing Units
  • Commerce
  • Commodities
  • Computer Programming
  • Computer Programs
  • Computers
  • Data Mining
  • Graphics Processing Unit
  • High Performance Computing
  • Information Science
  • National Security
  • Parallel Computing
  • Parallel Processing
  • Social Media

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development