Using B SP and Python to simplify parallel programming

Authors:
Konrad Hinsen;Hans Petter Langtangen;Ola Skavhaug;smund Ødegård
Affiliations:
Centre de Biophysique Moléculaire, UPR 4301 CNRS, Rue Charles Sadron, 45071 Orleans Cedex 2, France;Simula Research Laboratory (SRL), P.O. Box 134, 1325 Lysaker, Norway;Simula Research Laboratory (SRL), P.O. Box 134, 1325 Lysaker, Norway;Simula Research Laboratory (SRL), P.O. Box 134, 1325 Lysaker, Norway
Venue:
Future Generation Computer Systems
Year:
2006

Citing 1
Cited 2

BSPlib: The BSP programming library

Parallel Computing

OSL: Optimized Bulk Synchronous Parallel Skeletons on Distributed Arrays

APPT '09 Proceedings of the 8th International Symposium on Advanced Parallel Processing Technologies
High-performance parallel computations using python as high-level language

Euro-Par 2010 Proceedings of the 2010 conference on Parallel processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Scientific computing is usually associated with compiled languages for maximum efficiency. However, in a typical application program, only a small part of the code is time-critical and requires the efficiency of a compiled language. It is often advantageous to use interpreted high-level languages for the remaining tasks, adopting a mixed-language approach. This will be demonstrated for Python, an interpreted object-oriented high-level language that is well suited for scientific computing. Particular attention is paid to high-level parallel programming using Python and the BSP model. We explain the basics of BSP and how it differs from other parallel programming tools like MPI. Thereafter we present an application of Python and BSP for solving a partial differential equation from computational science, utilizing high-level design of libraries and mixed-language (Python-C or Python-Fortran) programming.