Enhancing speed and scalability of the ParFlow simulation code
This page lists all metadata that was entered for this dataset. Only registered users of the TR32DB may download this file.
Feature
Request download
Citation
Citation Options
Identification
| Title: | Main Title: Enhancing speed and scalability of the ParFlow simulation code |
| Description: | Abstract: Regional hydrology studies are often supported by high resolution simulations of subsurface flow that require expensive and extensive computations. Efficient usage of the latest high performance parallel computing systems becomes a necessity.The simulation software ParFlow has been demonstrated to meet this requirement and shown to have excellent solver scalability for up to 16,384 processes. In the present work we show that the code requires further enhancements in order to fully take advantage of current petascale machines. We identify ParFlow’s way of parallelization of the computational mesh as a central bottleneck. We propose to reorganize this subsystem using fast mesh partition algorithms provided by the parallel adaptive mesh refinement library p4est. We realize this in a minimally invasive manner by modifying selected parts of the code to reinterpret the existing mesh data structures. We evaluate the scaling performance of the modified version of ParFlow, demonstrating good weak and strong scaling up to 458k cores of the Juqueen supercomputer, and test an example application at large scale. |
Responsible Party
| Creators: | Carsten Burstedde (Principal Investigator), Jose A. Fonseca (Author), Stefan Kollet (Principal Investigator) |
| Publisher: | Springer |
| Publication Year: | 2017 |
Topic
| TR32 Topic: | Other |
| Related Subproject: | D8 |
| Subjects: | Keywords: Parallel Computing, Numerical Simulation, Groundwater Flow Model |
File Details
| Filename: | pf_paper.pdf |
| Data Type: | Text - Article |
| File Size: | 1.1 MB |
| Date: | Issued: 02.02.2018 |
| Mime Type: | application/pdf |
| Data Format: | |
| Language: | English |
| Status: | Completed |
Constraints
| Download Permission: | Only Project Members |
| General Access and Use Conditions: | According to the TR32DB data policy agreement. |
| Access Limitations: | According to the TR32DB data policy agreement. |
| Licence: | [TR32DB] Data policy agreement |
Geographic
Specific Information - Publication
| Publication Status: | Published |
| Review Status: | Peer reviewed |
| Publication Type: | Article |
| Article Type: | Journal |
| Source: | Computational Geosciences |
| Source Website: | https://link.springer.com/journal/10596 |
| Issue: | 1 |
| Volume: | 22 |
| Number of Pages: | 15 (347 - 361) |
Metadata Details
| Metadata Creator: | Jose Fonseca |
| Metadata Created: | 03.04.2017 |
| Metadata Last Updated: | 03.04.2017 |
| Subproject: | D8 |
| Funding Phase: | 3 |
| Metadata Language: | English |
| Metadata Version: | V50 |
Metadata Export
| Metadata Schema: |
Dataset Statistics
| Page Visits: | 782 |
| Metadata Downloads: | 0 |
| Dataset Downloads: | 1 |
Dataset Activity
Feature
DownloadBy downloading this dataset you accept the license terms of [TR32DB] Data policy agreement and TR32DB Data Protection Statement
Adequate reference when this dataset will be discussed or used in any publication or presentation is mandatory. In this case please contact the dataset creator.
Adequate reference when this dataset will be discussed or used in any publication or presentation is mandatory. In this case please contact the dataset creator.
