Improving the performance of the Parallel Ice Sheet Model on a large-scale, distributed supercomputer
In this thesis, we describe our work to understand and improve the performance and scalability of the Parallel Ice Sheet Model (PISM) on the Ranger supercomputer. PISM enables the simulation of large-scale ice sheets, such as those found in Greenland and Antarctica, which are of particular interest...
Main Author: | |
---|---|
Format: | Text |
Language: | unknown |
Published: |
DigitalCommons@UMaine
2013
|
Subjects: | |
Online Access: | https://digitalcommons.library.umaine.edu/etd/1895 https://digitalcommons.library.umaine.edu/context/etd/article/2924/viewcontent/MoreyTJ2013_OCR.pdf |
id |
ftmaineuniv:oai:digitalcommons.library.umaine.edu:etd-2924 |
---|---|
record_format |
openpolar |
spelling |
ftmaineuniv:oai:digitalcommons.library.umaine.edu:etd-2924 2023-06-11T04:06:16+02:00 Improving the performance of the Parallel Ice Sheet Model on a large-scale, distributed supercomputer Morey, Timothy J 2013-05-01T07:00:00Z application/pdf https://digitalcommons.library.umaine.edu/etd/1895 https://digitalcommons.library.umaine.edu/context/etd/article/2924/viewcontent/MoreyTJ2013_OCR.pdf unknown DigitalCommons@UMaine https://digitalcommons.library.umaine.edu/etd/1895 https://digitalcommons.library.umaine.edu/context/etd/article/2924/viewcontent/MoreyTJ2013_OCR.pdf Electronic Theses and Dissertations Ranger supercomputer Scalability Large scale ice sheets Sea level rise Processor counts Computer and Systems Architecture Glaciology text 2013 ftmaineuniv 2023-05-04T18:01:52Z In this thesis, we describe our work to understand and improve the performance and scalability of the Parallel Ice Sheet Model (PISM) on the Ranger supercomputer. PISM enables the simulation of large-scale ice sheets, such as those found in Greenland and Antarctica, which are of particular interest to climate scientists due to their potential to contribute to sea-level rise. PISM has a unique parallel architecture that is designed to take advantage of the computational resources available on state-of-the-art supercomputers. The problem, however, is that even though PISM can run without modifcation on a supercomputer, it is generally unable to do so efficiently. We observed that PISM exhibits rapidly diminishing performance gains as the number of processors is increased, even experiencing an increase in execution time with large processor counts. PISM's inability to make efficient use of the resources available on today's supercomputers presents a challenge to researchers, particularly as larger and higher resolution data sets become available. In this work, we analyzed the reasons for PISM's poor performance and developed techniques to address these issues, resulting in an increase in performance by as much as a factor of 20. Text Antarc* Antarctica Greenland Ice Sheet The University of Maine: DigitalCommons@UMaine Greenland |
institution |
Open Polar |
collection |
The University of Maine: DigitalCommons@UMaine |
op_collection_id |
ftmaineuniv |
language |
unknown |
topic |
Ranger supercomputer Scalability Large scale ice sheets Sea level rise Processor counts Computer and Systems Architecture Glaciology |
spellingShingle |
Ranger supercomputer Scalability Large scale ice sheets Sea level rise Processor counts Computer and Systems Architecture Glaciology Morey, Timothy J Improving the performance of the Parallel Ice Sheet Model on a large-scale, distributed supercomputer |
topic_facet |
Ranger supercomputer Scalability Large scale ice sheets Sea level rise Processor counts Computer and Systems Architecture Glaciology |
description |
In this thesis, we describe our work to understand and improve the performance and scalability of the Parallel Ice Sheet Model (PISM) on the Ranger supercomputer. PISM enables the simulation of large-scale ice sheets, such as those found in Greenland and Antarctica, which are of particular interest to climate scientists due to their potential to contribute to sea-level rise. PISM has a unique parallel architecture that is designed to take advantage of the computational resources available on state-of-the-art supercomputers. The problem, however, is that even though PISM can run without modifcation on a supercomputer, it is generally unable to do so efficiently. We observed that PISM exhibits rapidly diminishing performance gains as the number of processors is increased, even experiencing an increase in execution time with large processor counts. PISM's inability to make efficient use of the resources available on today's supercomputers presents a challenge to researchers, particularly as larger and higher resolution data sets become available. In this work, we analyzed the reasons for PISM's poor performance and developed techniques to address these issues, resulting in an increase in performance by as much as a factor of 20. |
format |
Text |
author |
Morey, Timothy J |
author_facet |
Morey, Timothy J |
author_sort |
Morey, Timothy J |
title |
Improving the performance of the Parallel Ice Sheet Model on a large-scale, distributed supercomputer |
title_short |
Improving the performance of the Parallel Ice Sheet Model on a large-scale, distributed supercomputer |
title_full |
Improving the performance of the Parallel Ice Sheet Model on a large-scale, distributed supercomputer |
title_fullStr |
Improving the performance of the Parallel Ice Sheet Model on a large-scale, distributed supercomputer |
title_full_unstemmed |
Improving the performance of the Parallel Ice Sheet Model on a large-scale, distributed supercomputer |
title_sort |
improving the performance of the parallel ice sheet model on a large-scale, distributed supercomputer |
publisher |
DigitalCommons@UMaine |
publishDate |
2013 |
url |
https://digitalcommons.library.umaine.edu/etd/1895 https://digitalcommons.library.umaine.edu/context/etd/article/2924/viewcontent/MoreyTJ2013_OCR.pdf |
geographic |
Greenland |
geographic_facet |
Greenland |
genre |
Antarc* Antarctica Greenland Ice Sheet |
genre_facet |
Antarc* Antarctica Greenland Ice Sheet |
op_source |
Electronic Theses and Dissertations |
op_relation |
https://digitalcommons.library.umaine.edu/etd/1895 https://digitalcommons.library.umaine.edu/context/etd/article/2924/viewcontent/MoreyTJ2013_OCR.pdf |
_version_ |
1768378111366266880 |