dc.contributor.advisor |
Malony, Allen |
en_US |
dc.contributor.author |
Ozog, David |
en_US |
dc.date.accessioned |
2013-10-03T23:31:43Z |
|
dc.date.available |
2013-10-03T23:31:43Z |
|
dc.date.issued |
2013-10-03 |
|
dc.identifier.uri |
http://hdl.handle.net/1794/13239 |
|
dc.description.abstract |
While the message-passing paradigm, seen in programming models such as MPI and UPC, has provided a solution for efficiently programming on distributed memory computer systems, this approach is not a panacea for the needs of all scientists. The traditional method of developing parallel applications in C/C++ and Fortran potentially leaves behind high-level and heterogeneous environments which are the most conducive for supporting
modern computational science endeavors. PRESTO alleviates this problem with an easy-to-use framework which provides multi-language adapters to a flexible MPI middleware supporting common computational models such as the asynchronous master/worker and ring pipeline in heterogeneous environments. |
en_US |
dc.language.iso |
en_US |
en_US |
dc.publisher |
University of Oregon |
en_US |
dc.rights |
All Rights Reserved. |
en_US |
dc.title |
PRESTO: A Parallel Runtime Environment for Scalable Task-Oriented Computations |
en_US |
dc.type |
Electronic Thesis or Dissertation |
en_US |
thesis.degree.name |
M.S. |
en_US |
thesis.degree.level |
masters |
en_US |
thesis.degree.discipline |
Department of Computer and Information Science |
en_US |
thesis.degree.grantor |
University of Oregon |
en_US |