Scientists are trending towards usage of
high-level programming languages such as Python.
The convenience of these languages often have a performance cost.
As the amount of data being processed increases this can make using
these languages unfeasible.
Parallelism is a means to achieve better performance, but many
users are unaware of it, or find it difficult to work with.
This thesis presents ParForPy, a means for loop-parallelization to to simplify usage of parallelism in Python for users.
Discussion is included for determining when parallelism
matches well with the problem.
Results are given that indicate that ParForPy is both capable
of improving program execution time and perceived to be a simpler
construct to understand than other techniques for parallelism in Python.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/625320 |
| Date | January 2017 |
| Creators | Gaska, Benjamin James, Gaska, Benjamin James |
| Contributors | Strout, Michelle, Surdeanu, Mihai, Strout, Michelle, Surdeanu, Mihai, Debray, Saumya |
| Publisher | The University of Arizona. |
| Source Sets | University of Arizona |
| Language | en_US |
| Detected Language | English |
| Type | text, Electronic Thesis |
| Rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. |
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