@inproceedings{476a9292a42e481bab9b246cf290b207,
title = "PUMA-V: An interactive visual tool for code optimization and parallelization based on the polyhedral model",
abstract = "Taking advantage of multi-core processing has become crucial in realizing significant performance gains for most applications. When it comes to performance optimization, this has led to a delicate balancing act between parallelism and locality. Furthermore, exposing parallelism can require some non-trivial transformations. Although tools exist to automatically identify good transformations, a user guided exploration can often yield substantially better performance. We have developed a visualization interface, called PUMA-V, which combines user and machine efforts to optimize parallel code performance. By conveying information related to the structure of the code and performance characteristics, the user can focus on a subset of transformations to alleviate performance bottlenecks. Combining automatic optimization techniques with interactive visualizations helps the user perform this exploration rapidly.",
keywords = "optimization, polyhedral model, visualization",
author = "Eric Papenhausen and Klaus Mueller and Harper Langston and Benoit Meister and Richard Lethin",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 New York Scientific Data Summit, NYSDS 2016 ; Conference date: 14-08-2016 Through 17-08-2016",
year = "2016",
month = nov,
day = "17",
doi = "10.1109/NYSDS.2016.7747826",
language = "English",
series = "2016 New York Scientific Data Summit, NYSDS 2016 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2016 New York Scientific Data Summit, NYSDS 2016 - Proceedings",
}