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Clustering Algorithms for Massively Parallel Architectures Including GPU Nodes

eagle-i ID


Resource Type

  1. Software


  1. Resource Description
    The CAMPAIGN projects goals are to modularize and parallelize clustering algorithms and explore new clustering approaches, with special concentration on running on GPUs. This project s results are intended, among others, to be used with the FEATURE project at Stanford. Keywords: clustering
  2. Contact
    Kohlhoff, Kai
  3. Contact
    Hsu, Bill
  4. Contact
    Sosnick, Marc
  5. Used by
    Stanford University
  6. Operating System
  7. Operating System
    Mac OS X
Provenance Metadata About This Resource Record

Copyright © 2016 by the President and Fellows of Harvard College
The eagle-i Consortium is supported by NIH Grant #5U24RR029825-02 / Copyright 2016