pycompss

A Programming Model for Hybrid Workflows: combining Task-based Workflows and Dataflows all-in-one

In the past years, e-Science applications have evolved from large-scale simulations executed in a single cluster to more complex workflows where these simulations are combined with Artificial Intelligence (AI) and High-Performance Data Analytics …

Orchestration of Software Packages in Data Science Workflows

Délivré par 6th BSC Severo Ochoa Doctoral Symposium Titre Orchestration de software hétérogène dans des flux de Data Science Titre Original Orchestration of Software Packages in Data Science Workflows

Automatic Task-based Parallelization of Python Codes

Délivré par MS12 - Task-based Programming for Scientific Computing: Runtime Support - Part I of II SIAM - CSE19 Titre Parallelisation automatique en taches de codes Python Titre Original Automatic Task-based Parallelization of Python Codes

Distributed Stream Library

La Distributed Stream Library (DistroStreamLib) exécute des fluxes de travaux hibrids formées de taches et donnés.

Demo on the use of PyCOMPSs in PyMDSetup

Délivré par SuperComputing 2018 - SC18 Barcelona Supercomputing Center - Booth #2038 Titre Demo de l’utilisation de PyCOMPSs avec PyMDSetup Titre Original Demo on the use of PyCOMPSs in PyMDSetup

AutoParallel: A Python Module for Automatic Parallelization and Distributed Execution of Affine Loop Nests

Délivré par 8th Workshop on Python for High-Performance and Scientific Computing Titre AutoParallel: Un module de Python pour paralléliser automatiquement boucles affines et les exécuter sur des environnements distribués Titre Original AutoParallel: A Python Module for Automatic Parallelization and Distributed Execution of Affine Loop Nests

AutoParallel: A Python module for automatic parallelization and distributed execution of affine loop nests

The last improvements in programming languages, programming models, and frameworks have focused on abstracting the users from many programming issues. Among others, recent programming frameworks include simpler syntax, automatic memory management and …

Boosting Atmospheric Dust Forecast with PyCOMPSs

This paper describes the success story of the adaptation of the NMMB-MONARCH online multi-scale atmospheric dust model to PyCOMPSs in order to exploit its inherent parallelism with the minimal developer effort. The paper also includes an evaluation …

Enabling Python to execute efficiently in heterogeneous distributed infrastructures with PyCOMPSs

Python has been adopted as programming language by a large number of scientific communities. Additionally to the easy programming interface, the large number of libraries and modules that have been made available by a large number of contributors, …

AutoParallel

AutoParallel parallelise de forme automatique boucles affines pour des applications Python.