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Introduction

This repository is intended for Cython+OpenMP practice of matrix-level pairwise distance calculation. It has been empirically proved that Cython version is faster than Numba version, and is close to Scipy implementation.

We also try to integrate C++20 new features jthread in our implementation for acceleration.

Environment

Windows/Linux

Quick Start

Update: this demo has been uploaded on Pypi and can be installed via pip.

To use new features, you need to install gcc-10 and g++-10. Please following these commands for installation.

sudo add-apt-repository ppa:ubuntu-toolchain-r/test
sudo apt-get update
sudo apt install gcc-10
sudo apt install g++-10

After that, navigate to the folder of fastdist_cython and compile the source code with

python setup.py build_ext --inplace

Once you get the success message, run the test code with

python test.py

Performance

  • Inputs for matrix to matrix distance calculation: matrix_a: (200, 1024) & matrix_b: (1500, 1024)

    Fastdist (Numba) Scipy (cdist) Ours (Cython)
    0.4691 sec 0.3250 sec 0.3225 sec

  • With jthread in 16-core GCP Virtual Machine

    Scipy (cdist) Ours (Cython+jthread*16)
    0.1582 sec 0.0014 sec

  • Input for pairwise distance calculation: matrix: (512, 1024)

    Fastdist (Numba) Scipy (pdist) Ours (Cython)
    0.3154 sec 0.1266 sec 0.1236 sec