Parakeet: A Just-In-Time Parallel Accelerator for Python

Authors: 

Alex Rubinsteyn, Eric Hielscher, Nathaniel Weinman, and Dennis Shasha, New York University

Abstract: 

High level productivity languages such as Python or Matlab enable the use of computational resources by nonexpert programmers. However, these languages often sacrifice program speed for ease of use.

This paper proposes Parakeet, a library which provides a just-in-time (JIT) parallel accelerator for Python. Parakeet bridges the gap between the usability of Python and the speed of code written in efficiency languages such as C++ or CUDA. Parakeet accelerates data-parallel sections of Python that use the standard NumPy scientific computing library. Parakeet JIT compiles efficient versions of Python functions and automatically manages their execution on both GPUs and CPUs. We assess Parakeet on a pair of benchmarks and achieve significant speedups.

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BibTeX
@inproceedings {181270,
author = {Alex Rubinsteyn and Eric Hielscher and Nathaniel Weinman and Dennis Shasha},
title = {Parakeet: A Just-In-Time Parallel Accelerator for Python},
booktitle = {Presented as part of the 4th {USENIX} Workshop on Hot Topics in Parallelism},
year = {2012},
address = {Berkeley, CA},
url = {https://www.usenix.org/conference/hotpar12/parakeet-just-time-parallel-accelerator-python},
publisher = {{USENIX}},
}
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