Work

Enabling Python to execute efficiently in heterogeneous distributed infrastructures with PyCOMPSs

Year: 2017

Type: conference-paper

Abstract: 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, have taken this language to the top of the list of the most popular programming languages in scientific applications. However, one main drawback of Python is the lack of support for concurrency or parallelism. PyCOMPSs is a proved approach to support task-based parallelism in Python that enables applications to be executed in parallel in distributed computing platforms.

Source: Workshop on Python for High-Performance and Scientific Computing (PyHPC)

DOI: 10.1145/3149869.3149870

Authors: Ramon Amela, Cristian Ramon-Cortes, Jorge Ejarque, Javier Conejero, Rosa M. Badia

Institutions: Barcelona Supercomputing Center, Consejo Superior de Investigaciones Científicas

Language: English

Topic: Distributed and Parallel Computing Systems

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: European Commission, Generalitat de Catalunya, Ministerio de Economía y Competitividad, Ministerio de Ciencia e Innovación