Calling Julia from Python - an experiment on data loading

Overview

Calling Julia from Python - an experiment on data loading

DOI

See the slides.

TLDR

After reading Patrick's blog post, we decided to try to replace C++ with Julia to check:

  • How easy/hard it is
  • How much improvement can be gained with a basic version
  • How much improvement can be gained with an optimized version

A basic version is already an improvement over the pure Python version, and an optimized version was faster than the C++ version.

Reproduction

  • Follow Patrick's blog post to install the C++ part.
  • Install Julia (We've used Julia 1.6.3)
    • I recommend using Jill
    • We'll refer to this Julia as path/to/julia.
  • Install Python
    • Ideally, one dynamically linked to libpython.
    • To test it, use ldd path/to/python and look for libpython3.9. It should exist for the shared version.
    • If you don't have, look into workarounds here
    • Tip: Archlinux's system Python is dynamically linked.
    • We've used Python 3.9.7 from Archlinux.
  • Open Julia and enter the following commands:
    • ENV["PYTHON"] = "path/to/python"
    • using Pkg
    • Pkg.add("PyCall")
    • This will make sure that the packages we are installing use the correct Python version
  • Install juliapy with path/to/python -m pip install julia
  • Run path/to/python and enter
    • import julia
    • julia.install("julia=path/to/julia")
  • Download dataset and store in gen-data folder: Zenodo badge
  • Run scalability_test.py - it should take several hours (over 10) and consume a moderate amount of memory.
  • Run scalability_analysis.py.
You might also like...
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

Apache MXNet (incubating) for Deep Learning Master Docs License Apache MXNet (incubating) is a deep learning framework designed for both efficiency an

Numba-accelerated Pythonic implementation of MPDATA with examples in Python, Julia and Matlab
Numba-accelerated Pythonic implementation of MPDATA with examples in Python, Julia and Matlab

PyMPDATA PyMPDATA is a high-performance Numba-accelerated Pythonic implementation of the MPDATA algorithm of Smolarkiewicz et al. used in geophysical

Python and Julia in harmony.
Python and Julia in harmony.

PythonCall & JuliaCall Bringing Python® and Julia together in seamless harmony: Call Python code from Julia and Julia code from Python via a symmetric

Pythonic particle-based (super-droplet) warm-rain/aqueous-chemistry cloud microphysics package with box, parcel & 1D/2D prescribed-flow examples in Python, Julia and Matlab
Pythonic particle-based (super-droplet) warm-rain/aqueous-chemistry cloud microphysics package with box, parcel & 1D/2D prescribed-flow examples in Python, Julia and Matlab

PySDM PySDM is a package for simulating the dynamics of population of particles. It is intended to serve as a building block for simulation systems mo

QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

Small-bets - Ergodic Experiment With Python

Ergodic Experiment Based on this video. Run this experiment with this command: p

Perspective: Julia for Biologists

Perspective: Julia for Biologists 1. Examples Speed: Example 1 - Single cell data and network inference Domain: Single cell data Methodology: Network

MacroTools provides a library of tools for working with Julia code and expressions.

MacroTools.jl MacroTools provides a library of tools for working with Julia code and expressions. This includes a powerful template-matching system an

✔️ Visual, reactive testing library for Julia. Time machine included.
✔️ Visual, reactive testing library for Julia. Time machine included.

PlutoTest.jl (alpha release) Visual, reactive testing library for Julia A macro @test that you can use to verify your code's correctness. But instead

Comments
  • Fix python versions ~~using poetry~~

    Fix python versions ~~using poetry~~

    To prevent this pull request from becoming too large, I'll merge this and create a new issue to set the python versions.

    Originally posted by @abelsiqueira in https://github.com/abelsiqueira/call-julia-from-python-experiments/issues/1#issuecomment-987970132

    opened by abelsiqueira 1
  • Improve docker-10

    Improve docker-10

    Fixes: #10

    • Changes Ubuntu version to 21.10
    • Adds extra environment variables
    • Removes the Python virtual environment
    • Add make flags to compile the tools faster
    • Remove the downloaded tar files
    • Uninstall dev dependencies
    opened by fdiblen 0
Releases(v0.3.0)
Owner
Abel Siqueira
Abel Siqueira
A project for developing transformer-based models for clinical relation extraction

Clinical Relation Extration with Transformers Aim This package is developed for researchers easily to use state-of-the-art transformers models for ext

uf-hobi-informatics-lab 101 Dec 19, 2022
Garbage Detection system which will detect objects based on whether it is plastic waste or plastics or just garbage.

Garbage Detection using Yolov5 on Jetson Nano 2gb Developer Kit. Garbage detection system which will detect objects based on whether it is plastic was

Rishikesh A. Bondade 2 May 13, 2022
Fast Differentiable Matrix Sqrt Root

Fast Differentiable Matrix Sqrt Root Geometric Interpretation of Matrix Square Root and Inverse Square Root This repository constains the official Pyt

YueSong 42 Dec 30, 2022
Official code for the paper: Deep Graph Matching under Quadratic Constraint (CVPR 2021)

QC-DGM This is the official PyTorch implementation and models for our CVPR 2021 paper: Deep Graph Matching under Quadratic Constraint. It also contain

Quankai Gao 55 Nov 14, 2022
Activating More Pixels in Image Super-Resolution Transformer

HAT [Paper Link] Activating More Pixels in Image Super-Resolution Transformer Xiangyu Chen, Xintao Wang, Jiantao Zhou and Chao Dong BibTeX @article{ch

XyChen 270 Dec 27, 2022
IEEE Winter Conference on Applications of Computer Vision 2022 Accepted

SSKT(Accepted WACV2022) Concept map Dataset Image dataset CIFAR10 (torchvision) CIFAR100 (torchvision) STL10 (torchvision) Pascal VOC (torchvision) Im

1 Nov 17, 2022
Code for "Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and Tracking of Object Poses in 3D Space"

Sparse Steerable Convolution (SS-Conv) Code for "Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and

25 Dec 21, 2022
Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle

DOC | Quick Start | 中文 Breaking News !! 🔥 🔥 🔥 OGB-LSC KDD CUP 2021 winners announced!! (2021.06.17) Super excited to announce our PGL team won TWO

1.5k Jan 06, 2023
Outlier Exposure with Confidence Control for Out-of-Distribution Detection

OOD-detection-using-OECC This repository contains the essential code for the paper Outlier Exposure with Confidence Control for Out-of-Distribution De

Nazim Shaikh 64 Nov 02, 2022
Wafer Fault Detection using MlOps Integration

Wafer Fault Detection using MlOps Integration This is an end to end machine learning project with MlOps integration for predicting the quality of wafe

Sethu Sai Medamallela 0 Mar 11, 2022
VLG-Net: Video-Language Graph Matching Networks for Video Grounding

VLG-Net: Video-Language Graph Matching Networks for Video Grounding Introduction Official repository for VLG-Net: Video-Language Graph Matching Networ

Mattia Soldan 25 Dec 04, 2022
PyTorch implementation of DeepLab v2 on COCO-Stuff / PASCAL VOC

DeepLab with PyTorch This is an unofficial PyTorch implementation of DeepLab v2 [1] with a ResNet-101 backbone. COCO-Stuff dataset [2] and PASCAL VOC

Kazuto Nakashima 995 Jan 08, 2023
PyTorch implementation of "ContextNet: Improving Convolutional Neural Networks for Automatic Speech Recognition with Global Context" (INTERSPEECH 2020)

ContextNet ContextNet has CNN-RNN-transducer architecture and features a fully convolutional encoder that incorporates global context information into

Sangchun Ha 24 Nov 24, 2022
JUSTICE: A Benchmark Dataset for Supreme Court’s Judgment Prediction

JUSTICE: A Benchmark Dataset for Supreme Court’s Judgment Prediction CSCI 544 Final Project done by: Mohammed Alsayed, Shaayan Syed, Mohammad Alali, S

Smit Patel 3 Dec 28, 2022
Steer OpenAI's Jukebox with Music Taggers

TagBox Steer OpenAI's Jukebox with Music Taggers! The closest thing we have to VQGAN+CLIP for music! Unsupervised Source Separation By Steering Pretra

Ethan Manilow 34 Nov 02, 2022
Repository for "Space-Time Correspondence as a Contrastive Random Walk" (NeurIPS 2020)

Space-Time Correspondence as a Contrastive Random Walk This is the repository for Space-Time Correspondence as a Contrastive Random Walk, published at

A. Jabri 239 Dec 27, 2022
Supervised forecasting of sequential data in Python.

Supervised forecasting of sequential data in Python. Intro Supervised forecasting is the machine learning task of making predictions for sequential da

The Alan Turing Institute 54 Nov 15, 2022
For IBM Quantum Challenge Africa 2021, 9 September (07:00 UTC) - 20 September (23:00 UTC).

IBM Quantum Challenge Africa 2021 To ensure Africa is able to apply quantum computing to solve problems relevant to the continent, the IBM Research La

Qiskit Community 48 Dec 25, 2022
Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving

Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving This is the source code for our paper Frequency Domain Image Tran

Mu Cai 52 Dec 23, 2022
Python Blood Vessel Topology Analysis

Python Blood Vessel Topology Analysis This repository is not being updated anymore. The new version of PyVesTo is called PyVaNe and is available at ht

6 Nov 15, 2022