Publication | Open Access
On the Performance of the Python Programming Language for Serial and Parallel Scientific Computations
87
Citations
12
References
2005
Year
Cluster ComputingMassively-parallel ComputingScientific ApplicationsEngineeringParallel SoftwarePython Programming LanguageSerial Python CodesProgram AnalysisParallel ProcessingComputer EngineeringComputer ArchitectureParallel ImplementationParallel ProgrammingComputer ScienceParallel Scientific ComputationsParallel Programming ModelParallel ComputingProgramming Languages
This article addresses the performance of scientific applications that use the Python programming language. First, we investigate several techniques for improving the computational efficiency of serial Python codes. Then, we discuss the basic programming techniques in Python for parallelizing serial scientific applications. It is shown that an efficient implementation of the array‐related operations is essential for achieving good parallel performance, as for the serial case. Once the array‐related operations are efficiently implemented, probably using a mixed‐language implementation, good serial and parallel performance become achievable. This is confirmed by a set of numerical experiments. Python is also shown to be well suited for writing high‐level parallel programs.
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