A Compiler for Parallel Exeuction of Numerical Python Programs on ...

Chapter 3<strong>Python</strong> and the proposedprogramming modelThe objective <strong>of</strong> this thesis is to provide a high-productivity programming model to thescientific programmer which is portable to both GPUs and multi-core CPUs. Increasingly,scientific programmers are choosing high-level programming languages such as Matlab and<strong>Python</strong> over languages such as C and Fortran. For parallel programming, shared-memoryparadigms, such as OpenMP, are popular with C/C++ programmers.This thesis provides the programmer with a programming model based on a combination<strong>of</strong> <strong>Python</strong> and the concept <strong>of</strong> parallel loops inspired by OpenMP parallel loops. The choice<strong>of</strong> <strong>Python</strong> was based on multiple reasons.1. Unlike special-purpose languages such as Matlab, <strong>Python</strong> is a fully featured generalpurposeprogramming language well known <strong>for</strong> its simplicity and productivity. NumPyis a multi-dimensional array library <strong>for</strong> <strong>Python</strong> providing a very flexible array abstractionwith concise notations <strong>for</strong> operations such as slicing. <strong>Python</strong> in combination withNumPy is well suited <strong>for</strong> rapidly developing full applications in a wide variety <strong>of</strong>domains.2. <strong>Python</strong> and NumPy are both open source and there<strong>for</strong>e it was much easier to understandthe inner workings <strong>of</strong> <strong>Python</strong> and NumPy.3. <strong>Python</strong>, in combination with NumPy, is becoming popular in the scientific and numericcomputation community because <strong>of</strong> simplicity and productivity. A library collectionaimed at scientific computation <strong>for</strong> <strong>Python</strong>, called SciPy, and built upon NumPy isalso available. SciPy includes libraries <strong>for</strong> tasks such as function optimization. Anactive community is <strong>for</strong>ming around NumPy and SciPy. Various mailing lists, wikisand project listings can be found at the scipy.org website.This chapter introduces the relevant features <strong>of</strong> <strong>Python</strong> and NumPy followed by theproposed extensions to <strong>Python</strong> and NumPy.18