Title :
Briareus: Accelerating Python Applications with Cloud
Author :
Zhaomeng Zhu ; Gongxuan Zhang ; Yongping Zhang ; Jian Guo ; Naixue Xiong
Author_Institution :
Sch. of Comput. Sci. & Eng., Nanjing Univ. of Sci. & Technol., Nanjing, China
Abstract :
Briareus provides convenient tools to make use of computing resources provided by cloud to accelerate Python applications. In this paper, three techniques are presented. First, some of the functions in a Python program can be migrated to cloud and be evaluated using the hardware and software provided by that cloud platform, while the other parts still running locally. Second, Briareus can automatically parallelize specified loops in a program to accelerate it. And third, specified functions can be called asynchronously after being patched, so that two or more functions can be evaluated simultaneously. By combining these three methods, a Python application can make part of itself to run in a remote cloud platform in parallel. To use Briareus, developers do not need to modify the existing source much, but only need to insert some descriptive comments and invoke a patching function at the beginning. Experiments show that Briareus can significantly speed up the running of programs written by Python, especially for those for scientific and engineering computing. The early beta version of Briareus has been developed for testing and all sources are accessible to public via GitHub and installable via PyPI.
Keywords :
cloud computing; high level languages; parallel processing; program control structures; Briareus; Python applications; Python program; cloud platform; loop programs; parallel architectures; Acceleration; Computer architecture; Educational institutions; Hardware; Microprocessors; Software; Standards; Clouds; Computer languages; Distributed computing; Parallel architectures; Software tools;
Conference_Titel :
Parallel and Distributed Processing Symposium Workshops & PhD Forum (IPDPSW), 2013 IEEE 27th International
Conference_Location :
Cambridge, MA
Print_ISBN :
978-0-7695-4979-8
DOI :
10.1109/IPDPSW.2013.161