Academic Journal
Implementation and Evaluation of Parallel Computing Approaches for Large‐Domain, Process‐Based Hydrologic Simulations.
| Τίτλος: | Implementation and Evaluation of Parallel Computing Approaches for Large‐Domain, Process‐Based Hydrologic Simulations. |
|---|---|
| Συγγραφείς: | Guo, Junwei, Clark, Martyn P., Knoben, Wouter J. M., Keshavarz, Kasra, Klenk, Kyle, Van Beusekom, Ashley, Guenter, Victoria, Spiteri, Raymond J. |
| Πηγή: | Journal of Advances in Modeling Earth Systems; Jan2026, Vol. 18 Issue 1, p1-18, 18p |
| Θεματικοί όροι: | Message passing (Computer science), Hydrologic models, Parallel programming, Simulation software, Fault tolerance (Engineering), Parallel processing, Scalability |
| Γεωγραφικοί όροι: | North America |
| Περίληψη: | Process‐based hydrologic simulations in large domains generally require intensive computing resources. In this study, we implement various parallelization approaches within a process‐based hydrologic solver, SUMMA, including the Message Passing Interface (MPI), Open Multi‐Processing (OMP), and the Actor Model, to enable high‐performance computing for large‐domain hydrologic simulations. We provide detailed guidelines on these implementations to assist hydrologists in parallelizing their models effectively. Using a hydrologic simulation over North America as a case study, we compare the scalability, computational cost, input/output performance, and coupling capabilities of these parallel approaches with the original sequential approach. Our results show that the SUMMA‐MPI exhibits linear scaling up to 1,024 cores, whereas SUMMA‐OMP is only recommended for smaller numbers of cores. The MPI approach exhibited a straggler effect, resulting in core utilization of only 80%. To address this, we introduced a load‐balancing calibration based on historical runs, which increases SUMMA‐MPI core usage to 95% and thereby mitigates the straggler effect. With regard to coupling capabilities, MPI is the most effective for large‐scale simulations involving multiple nodes and extensive core counts, supporting strong coupling and synchronization. The Actor Model reveals its excellent fault tolerance that enables automatic modification and recommencement of specific Grouped Response Units (GRUs) rather than restarting the entire simulation in the event of a failure within the simulation. Through this study, the implementation details of multiple parallelization schemes are documented and their advantages and limitations are discussed, which provides parallel computing insights for advancing computational hydrology in the Earth System Science community. Plain Language Summary: We provide detailed guidelines for Earth System Science developers on the implementation and evaluation of multiple parallel computing frameworks for large‐domain process‐based hydrologic simulations, including the Message Passing Interface (MPI), Open Multi‐Processing (OMP), and the Actor Model. As a case study, we conduct a North American hydrologic simulation consisting of 517,315 land units. Among these approaches, SUMMA‐MPI exhibits linear scaling up to 1,024 cores and offers the best synchronization and coupling capabilities. In contrast, SUMMA‐OMP is only recommended for smaller core counts due to significant overhead when scaling to larger allocations. The SUMMA‐Actors application encounters a bottleneck in input/output operations caused by its sequential I/O, a limitation stemming from SUMMA's reliance on the netCDF library. However, SUMMA‐Actors offers excellent fault tolerance by enabling automatic modification and recommencement of specific land units, eliminating the need to restart entire simulations in case of failure. Key Points: We implemented and evaluated Message Passing Interface (MPI), OpenMP, and Actor Model for a process‐based hydrologic solverThe MPI framework demonstrates linear scaling up to 1,024 cores and has excellent coupling capabilities [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Advances in Modeling Earth Systems is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
| FullText | Links: – Type: other Text: Availability: 0 |
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| Header | DbId: edb DbLabel: Complementary Index An: 191184663 RelevancyScore: 1041 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 1041.06604003906 |
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| Items | – Name: Title Label: Title Group: Ti Data: Implementation and Evaluation of Parallel Computing Approaches for Large‐Domain, Process‐Based Hydrologic Simulations. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Guo%2C+Junwei%22">Guo, Junwei</searchLink><br /><searchLink fieldCode="AR" term="%22Clark%2C+Martyn+P%2E%22">Clark, Martyn P.</searchLink><br /><searchLink fieldCode="AR" term="%22Knoben%2C+Wouter+J%2E+M%2E%22">Knoben, Wouter J. M.</searchLink><br /><searchLink fieldCode="AR" term="%22Keshavarz%2C+Kasra%22">Keshavarz, Kasra</searchLink><br /><searchLink fieldCode="AR" term="%22Klenk%2C+Kyle%22">Klenk, Kyle</searchLink><br /><searchLink fieldCode="AR" term="%22Van+Beusekom%2C+Ashley%22">Van Beusekom, Ashley</searchLink><br /><searchLink fieldCode="AR" term="%22Guenter%2C+Victoria%22">Guenter, Victoria</searchLink><br /><searchLink fieldCode="AR" term="%22Spiteri%2C+Raymond+J%2E%22">Spiteri, Raymond J.</searchLink> – Name: TitleSource Label: Source Group: Src Data: Journal of Advances in Modeling Earth Systems; Jan2026, Vol. 18 Issue 1, p1-18, 18p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Message+passing+%28Computer+science%29%22">Message passing (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Hydrologic+models%22">Hydrologic models</searchLink><br /><searchLink fieldCode="DE" term="%22Parallel+programming%22">Parallel programming</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation+software%22">Simulation software</searchLink><br /><searchLink fieldCode="DE" term="%22Fault+tolerance+%28Engineering%29%22">Fault tolerance (Engineering)</searchLink><br /><searchLink fieldCode="DE" term="%22Parallel+processing%22">Parallel processing</searchLink><br /><searchLink fieldCode="DE" term="%22Scalability%22">Scalability</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22North+America%22">North America</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Process‐based hydrologic simulations in large domains generally require intensive computing resources. In this study, we implement various parallelization approaches within a process‐based hydrologic solver, SUMMA, including the Message Passing Interface (MPI), Open Multi‐Processing (OMP), and the Actor Model, to enable high‐performance computing for large‐domain hydrologic simulations. We provide detailed guidelines on these implementations to assist hydrologists in parallelizing their models effectively. Using a hydrologic simulation over North America as a case study, we compare the scalability, computational cost, input/output performance, and coupling capabilities of these parallel approaches with the original sequential approach. Our results show that the SUMMA‐MPI exhibits linear scaling up to 1,024 cores, whereas SUMMA‐OMP is only recommended for smaller numbers of cores. The MPI approach exhibited a straggler effect, resulting in core utilization of only 80%. To address this, we introduced a load‐balancing calibration based on historical runs, which increases SUMMA‐MPI core usage to 95% and thereby mitigates the straggler effect. With regard to coupling capabilities, MPI is the most effective for large‐scale simulations involving multiple nodes and extensive core counts, supporting strong coupling and synchronization. The Actor Model reveals its excellent fault tolerance that enables automatic modification and recommencement of specific Grouped Response Units (GRUs) rather than restarting the entire simulation in the event of a failure within the simulation. Through this study, the implementation details of multiple parallelization schemes are documented and their advantages and limitations are discussed, which provides parallel computing insights for advancing computational hydrology in the Earth System Science community. Plain Language Summary: We provide detailed guidelines for Earth System Science developers on the implementation and evaluation of multiple parallel computing frameworks for large‐domain process‐based hydrologic simulations, including the Message Passing Interface (MPI), Open Multi‐Processing (OMP), and the Actor Model. As a case study, we conduct a North American hydrologic simulation consisting of 517,315 land units. Among these approaches, SUMMA‐MPI exhibits linear scaling up to 1,024 cores and offers the best synchronization and coupling capabilities. In contrast, SUMMA‐OMP is only recommended for smaller core counts due to significant overhead when scaling to larger allocations. The SUMMA‐Actors application encounters a bottleneck in input/output operations caused by its sequential I/O, a limitation stemming from SUMMA's reliance on the netCDF library. However, SUMMA‐Actors offers excellent fault tolerance by enabling automatic modification and recommencement of specific land units, eliminating the need to restart entire simulations in case of failure. Key Points: We implemented and evaluated Message Passing Interface (MPI), OpenMP, and Actor Model for a process‐based hydrologic solverThe MPI framework demonstrates linear scaling up to 1,024 cores and has excellent coupling capabilities [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Journal of Advances in Modeling Earth Systems is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1029/2025MS005064 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 1 Subjects: – SubjectFull: North America Type: general – SubjectFull: Message passing (Computer science) Type: general – SubjectFull: Hydrologic models Type: general – SubjectFull: Parallel programming Type: general – SubjectFull: Simulation software Type: general – SubjectFull: Fault tolerance (Engineering) Type: general – SubjectFull: Parallel processing Type: general – SubjectFull: Scalability Type: general Titles: – TitleFull: Implementation and Evaluation of Parallel Computing Approaches for Large‐Domain, Process‐Based Hydrologic Simulations. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Guo, Junwei – PersonEntity: Name: NameFull: Clark, Martyn P. – PersonEntity: Name: NameFull: Knoben, Wouter J. M. – PersonEntity: Name: NameFull: Keshavarz, Kasra – PersonEntity: Name: NameFull: Klenk, Kyle – PersonEntity: Name: NameFull: Van Beusekom, Ashley – PersonEntity: Name: NameFull: Guenter, Victoria – PersonEntity: Name: NameFull: Spiteri, Raymond J. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: Jan2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 19422466 Numbering: – Type: volume Value: 18 – Type: issue Value: 1 Titles: – TitleFull: Journal of Advances in Modeling Earth Systems Type: main |
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