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CUDA implementation of application classification via belief propagation

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application_classification

Implementation of ApplicationClassification workflow.

Produces identical results to PNNL code on georgiy and rmat example datasets.

TODO

  • Optimize performance
  • Fuse kernels
  • Get rid of transposes
  • Segmented reduce instead of reduce by key?
  • Could probably improve memory usage
  • Profiling
  • optional more correctness checking

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