entropy-gpu 0.3.0

Entropy and K-L divergence on GPU via PyOpenCL

# futhark-kullback-liebler

The Kullback-Liebler divergence, Hellinger distance, and alpha-divergence in Futhark.

## Documentation

Documentation is available [here](https://vmchale.github.io/kullback-liebler/).

## Benchmarks

To run the benchmarks:

` make pipenv run python harness.py `

and

` futhark bench information.fut --backend opencl --runs=100 `

### Comparison

Computation | Array Size | Implementation | Time |

———– | ———- | ————– | —- |

Entropy | 10000000 | Futhark | 27.41 ms |

Kullback-Liebler Divergence | 10000000 | Futhark | 19.61 ms |

Entropy | 10000000 | Python + Futhark | 52.80 ms |

Kullback-Liebler Divergence | 10000000 | Python + Futhark | 94.07 ms |

Entropy | 10000000 | Python (SciPy) | 233.45 ms |

Kullback-Liebler Divergence | 10000000 | Python (SciPy) | 340.83 ms |

Entropy | 10000000 | J | 227.37 ms |