Optimizaciones incrementales al problema N-Body con el fin de evaluar y comparar las prestaciones de los traductores de Python en el ámbito de HPC.

Overview

Python HPC

Optimizaciones incrementales de N-Body (all-pairs) con el fin de evaluar y comparar las prestaciones de los traductores de Python en el ámbito de HPC. Este trabajo ha servido como base para las siguientes publicaciones:

@inproceedings{milla_rucci_cacic,
  title={Acelerando c{\'o}digo cient{\'\i}fico en Python usando Numba},
  author={Milla, Andr{\'e}s and Rucci, Enzo},
  booktitle={XXVII Congreso Argentino de Ciencias de la Computaci{\'o}n (CACIC 2021)},
  year={2021}
}
@misc{milla_rucci_pycon,
  address = {PyCon 2021},
  type = {Conferencia},
  title = {Acelerando aplicaciones paralelas en {Python}: {Numba} vs. {Cython}},
  url = {https://eventos.python.org.ar/events/pyconar2021/activity/448/},
  author={Milla, Andr{\'e}s and Rucci, Enzo},
  month = oct,
  year = {2021},
}
  • Tesina de grado - Un Estudio Comparativo entre Traductores de Python para Aplicaciones Paralelas de Memoria Compartida (en proceso)

Organización

El código fuente se encuentra en el directorio src, el cual contiene los siguientes subdirectorios:

  • versions: Contiene el código fuente de cada versión probada.
  • benchmarker: Script para realizar los benchmarks.
  • test: Tests de las versiones desarrolladas.
  • core: Utilidades comunes a los módulos.

Contribución

Requisitos

Paquete Versión
Python 3.8.10
PyPy 7.3.1
Cython 0.29.22
Pip 21.0.1
Virtualenv 20.0.17

En entornos basados en Debian se pueden instalar con el siguiente comando:

apt-get install python3 python3-pip cython pypy3 virtualenv

Ejecución

  1. Instalar las dependencias:

    make install

  2. Configurar los parámetros del benchmark en el archivo config.toml y ejecutar:

    make benchmark

Los resultados podrán verse en el directorio benchmarks.

  • Nota: En caso de no disponer el compilador ICC, se puede optar por otro a través del Makefile.

Contacto

Owner
Andrés Milla
Computer science student - Fullstack developer
Andrés Milla
Rule Extraction Methods for Interactive eXplainability

REMIX: Rule Extraction Methods for Interactive eXplainability This repository contains a variety of tools and methods for extracting interpretable rul

Mateo Espinosa Zarlenga 21 Jan 03, 2023
PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners for self-supervised ViT.

MAE for Self-supervised ViT Introduction This is an unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners for self-sup

36 Oct 30, 2022
Manim is an engine for precise programmatic animations, designed for creating explanatory math videos

Manim is an engine for precise programmatic animations, designed for creating explanatory math videos. Note, there are two versions of manim. This rep

Grant Sanderson 49k Jan 09, 2023
Code for DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents

DeepXML Code for DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents Architectures and algorithms DeepXML supports

Extreme Classification 49 Nov 06, 2022
PyTorch implementation of Constrained Policy Optimization

PyTorch implementation of Constrained Policy Optimization (CPO) This repository has a simple to understand and use implementation of CPO in PyTorch. A

Sapana Chaudhary 25 Dec 08, 2022
A short and easy PyTorch implementation of E(n) Equivariant Graph Neural Networks

Simple implementation of Equivariant GNN A short implementation of E(n) Equivariant Graph Neural Networks for HOMO energy prediction. Just 50 lines of

Arsenii Senya Ashukha 97 Dec 23, 2022
Voice control for Garry's Mod

WIP: Talonvoice GMod integrations Very work in progress voice control demo for Garry's Mod. HOWTO Install https://talonvoice.com/ Press https://i.imgu

Meta Construct 5 Nov 15, 2022
This repo contains source code and materials for the TEmporally COherent GAN SIGGRAPH project.

TecoGAN This repository contains source code and materials for the TecoGAN project, i.e. code for a TEmporally COherent GAN for video super-resolution

Nils Thuerey 5.2k Jan 02, 2023
DeLag: Detecting Latency Degradation Patterns in Service-based Systems

DeLag: Detecting Latency Degradation Patterns in Service-based Systems Replication package of the work "DeLag: Detecting Latency Degradation Patterns

SEALABQualityGroup @ University of L'Aquila 2 Mar 24, 2022
This repository contains the code used in the paper "Prompt-Based Multi-Modal Image Segmentation".

Prompt-Based Multi-Modal Image Segmentation This repository contains the code used in the paper "Prompt-Based Multi-Modal Image Segmentation". The sys

Timo Lüddecke 305 Dec 30, 2022
Open-Domain Question-Answering for COVID-19 and Other Emergent Domains

Open-Domain Question-Answering for COVID-19 and Other Emergent Domains This repository contains the source code for an end-to-end open-domain question

7 Sep 27, 2022
Model that predicts the probability of a Twitter user being anti-vaccination.

stylebody {text-align: justify}/style AVAXTAR: Anti-VAXx Tweet AnalyzeR AVAXTAR is a python package to identify anti-vaccine users on twitter. The

10 Sep 27, 2022
Mercury: easily convert Python notebook to web app and share with others

Mercury Share your Python notebooks with others Easily convert your Python notebooks into interactive web apps by adding parameters in YAML. Simply ad

MLJAR 2.2k Dec 27, 2022
An Inverse Kinematics library aiming performance and modularity

IKPy Demo Live demos of what IKPy can do (click on the image below to see the video): Also, a presentation of IKPy: Presentation. Features With IKPy,

Pierre Manceron 481 Jan 02, 2023
Pytorch implementation for "Density-aware Chamfer Distance as a Comprehensive Metric for Point Cloud Completion" (NeurIPS 2021)

Density-aware Chamfer Distance This repository contains the official PyTorch implementation of our paper: Density-aware Chamfer Distance as a Comprehe

Tong WU 93 Dec 15, 2022
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista

Epistasis Lab at UPenn 8.9k Dec 30, 2022
State-to-Distribution (STD) Model

State-to-Distribution (STD) Model In this repository we provide exemplary code on how to construct and evaluate a state-to-distribution (STD) model fo

<a href=[email protected]"> 2 Apr 07, 2022
Code repository for Self-supervised Structure-sensitive Learning, CVPR'17

Self-supervised Structure-sensitive Learning (SSL) Ke Gong, Xiaodan Liang, Xiaohui Shen, Liang Lin, "Look into Person: Self-supervised Structure-sensi

Clay Gong 219 Dec 29, 2022
Google Brain - Ventilator Pressure Prediction

Google Brain - Ventilator Pressure Prediction https://www.kaggle.com/c/ventilator-pressure-prediction The ventilator data used in this competition was

Samuele Cucchi 1 Feb 11, 2022
Python package for visualizing the loss landscape of parameterized quantum algorithms.

orqviz A Python package for easily visualizing the loss landscape of Variational Quantum Algorithms by Zapata Computing Inc. orqviz provides a collect

Zapata Computing, Inc. 75 Dec 30, 2022