Software Engineering with Transactional Memory Versus Locks in Practice
Name
224_2013_9452_ReferencePDF.pdf
Size
858.67 KB
Format
Adobe PDF
Checksum (MD5)
b2d1f4339da8ea7a73f4334f4c9f4142
Author(s)
Pankratius, Victor
Adl-Tabatabai, Ali-Reza
Date Issued
March 2013
Journal
Theory of Computing Systems
Publisher
Springer Science+Business Media
Citation
Pankratius, Victor, and Ali-Reza Adl-Tabatabai. “Software Engineering with Transactional Memory Versus Locks in Practice.” Theory Comput Syst 55, no. 3 (March 3, 2013): 555–590.
Version
Author's final manuscript
Abstract
Transactional Memory (TM) promises to simplify parallel programming by replacing locks with atomic transactions. Despite much recent progress in TM research, there is very little experience using TM to develop realistic parallel programs from scratch. In this article, we present the results of a detailed case study comparing teams of programmers developing a parallel program from scratch using transactional memory and locks. We analyze and quantify in a realistic environment the development time, programming progress, code metrics, programming patterns, and ease of code understanding for six teams who each wrote a parallel desktop search engine over a fifteen week period. Three randomly chosen teams used Intel’s Software Transactional Memory compiler and Pthreads, while the other teams used just Pthreads. Our analysis is exploratory: Given the same requirements, how far did each team get? The TM teams were among the first to have a prototype parallel search engine. Compared to the locks teams, the TM teams spent less than half the time debugging segmentation faults, but had more problems tuning performance and implementing queries. Code inspections with industry experts revealed that TM code was easier to understand than locks code, because the locks teams used many locks (up to thousands) to improve performance. Learning from each team’s individual success and failure story, this article provides valuable lessons for improving TM.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1007/s00224-013-9452-5
