Octave and Python: High-Level Scripting Languages Productivity and Performance Evaluation

Authors:
Juan Carlos Chaves;John Nehrbass;Brian Guilfoos;Judy Gardiner;Stanley Ahalt;Ashok Krishnamurthy;Jose Unpingco;Alan Chalker;Andy Warnock;Siddharth Samsi
Affiliations:
Ohio Supercomputer Center, Columbus, OH;Ohio Supercomputer Center, Columbus, OH;Ohio Supercomputer Center, Columbus, OH;Ohio Supercomputer Center, Columbus, OH;Ohio Supercomputer Center, Columbus, OH;Ohio Supercomputer Center, Columbus, OH;Ohio Supercomputer Center, Columbus, OH;Ohio Supercomputer Center, Columbus, OH;Ohio Supercomputer Center, Columbus, OH;Ohio Supercomputer Center, Columbus, OH
Venue:
HPCMP-UGC '06 Proceedings of the HPCMP Users Group Conference
Year:
2006

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Abstract

Octave and Python are open source alternatives to MATLAB, which is widely used by the High Performance Computing Modernization Program (HPCMP) community. These languages are two well known examples of high-level scripting languages that promise to increase productivity without compromising performance on HPC systems. In this paper, we report our work and experience with these two non-traditional programming languages at the HPCMP Centers. We used a representative sample of SIP codes for the study, with special emphasis given to the understanding of issues such as portability, degree of complexity, productivity and suitability of Octave and Python to address Signal/Image Processing (SIP) problems on the HPCMP HPC platforms.