https://github.com/bsc-wdc/pycompss_bda

https://github.com/bsc-wdc/pycompss_bda

Science Score: 26.0%

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Last synced: 7 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: bsc-wdc
  • License: apache-2.0
  • Language: Python
  • Default Branch: master
  • Size: 225 KB
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Created over 7 years ago · Last pushed over 7 years ago
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Readme License

README.md

PyCOMPSs Big Data Analytics

Available applications in the repository:

  • Cascade Support Vector Machines
  • K-means

The applications are implemented using both PyCOMPSs and K-means for comparison purposes.

To know more check:

Running the Apps

The folder ./scripts contains samples to run the for implementaions.

The scripts named run_APP_IMPLEMENTATION.sh are used to run the applications locally.

The scripts named enqueue_APP_IMPLEMENTATION.sh are used to run the applications in a supercomputer.

In the case of PyCOMPSs version, the script can be used out-of-the-gox in many supercomputers. The MPI version is tied to SLURM Queueing systems because MPI is not platform-agnostic as PyCOMPSs.

Computing Complexity

In order to compute the complexity metrics of the K-means and C-SVM applications for both MPI and PyCOMPSs run the script:

./scripts/get_complexities.sh

This script reports 3 complexity metrics:

  • Source Lines of Code (SLOC)
  • Cyclomatic complexity
  • NPath complexity

Requirements:

This script uses Babelfish tools to compute the Cyclomatic and NPath complexities, and cloc for the SLOC.

Owner

  • Name: Workflows and Distributed Computing
  • Login: bsc-wdc
  • Kind: organization
  • Email: distributed_computing@bsc.es
  • Location: Barcelona

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