Paper Info
Title
Briareus: Accelerating Python Applications with Cloud
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.
Year
DOI
Venue
2013
10.1109/IPDPSW.2013.161
IPDPS Workshops
Keywords
Field
DocType
briareus,accelerating python applications,descriptive comment,parallel processing,python application,engineering computing,python program,parallel architectures,cloud platform,software tools,python applications,high level languages,specified function,remote cloud platform,program control structures,existing source,cloud computing,early beta version,computer languages,convenient tool,loop programs,clouds,distributed computing,acceleration,hardware,computer architecture
Programming language,Computer science,Parallel processing,High-level programming language,Software,Operating system,Python (programming language),Cloud computing,Speedup
Conference
ISBN
Citations 
PageRank 
978-0-7695-4979-8
1
0.40
References 
Authors
3
5
Name
Order
Citations
PageRank
Zhaomeng Zhu152.48
Gongxuan Zhang29419.89
Yongping Zhang319131.82
Jian Guo4597.57
Naixue Xiong52413194.61