Program fracture and recombination for efficient automatic code reuse
Name
hpec15.pdf
Description
Accepted version
Size
126.64 KB
Format
Adobe PDF
Checksum (MD5)
d86fd8701dc4a7d1675d7569a2518475
Author(s)
Amidon, Peter
Davis, Eli
Sidiroglou-Douskos, Stelios
Rinard, Martin C
Date Issued
September 2015
Journal
Proceedings of the 2015 IEEE High Performance Extreme Computing Conference
Publisher
IEEE
Citation
Amidon, Peter, et al. "Program fracture and recombination for efficient automatic code reuse." 2015 IEEE High Performance Extreme Computing Conference, Waltham, MA, USA, September 2015, IEEE, 2015.
Version
Author's final manuscript
Abstract
We present a new code transfer technique, program fracture and recombination, for automatically replacing, deleting, and/or combining code from multiple applications. Benefits include automatic generation of new applications incorporating the best or most desirable functionality developed anywhere, the automatic elimination of errors and security vulnerabilities, effective software rejuvenation, the automatic elimination of obsolete or undesirable functionality, and improved performance, energy efficiency, simplicity, analyzability, and clarity. The technique may be particularly appropriate for high performance computing. The field has devoted years of effort to developing efficient (but complex) implementations of standard linear algebra operations with good numerical properties. At the same time these operations also have very simple but inefficient implementations, often with poor numerical properties. Program fracture and recombination allows developers to work with the simple implementation during development and testing, then use program fracture and recombination to automatically find and deploy the most appropriate implementation for the hardware platform at hand. The benefits include reduced implementation effort, increased code clarity, and the ability to automatically search for and find efficient implementations with good numerical properties.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/hpec.2015.7396314
