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 particularly well suited for scientific computing. Special emphasis will be put on the use of Python in parallel programming using the BSP model. © Springer-Verlag 2002.
Cite
CITATION STYLE
Hinsen, K. (2002). High-level scientific programming with python. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2331 LNCS, pp. 691–700). Springer Verlag. https://doi.org/10.1007/3-540-47789-6_72
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
