ParForPy: Loop Parallelism in Python

Abstract

Scientists are trending towards usage of high-level programming languages such as Python. The convenience of these languages often have a performance cost. As the amount of data being processed increases this can make using these languages unfeasible. Parallelism is a means to achieve better performance, but many users are unaware of it, or find it difficult to work with. This thesis presents ParForPy, a means for loop-parallelization to to simplify usage of parallelism in Python for users. Discussion is included for determining when parallelism matches well with the problem. Results are given that indicate that ParForPy is both capable of improving program execution time and perceived to be a simpler construct to understand than other techniques for parallelism in Python.