Automatic calibration of rainfall-runoff models and its parallelization strategies

Vavrik, Radim; Theuer, Matyáš; Golasowski, Martin; Kuchař, Štěpán; Podhoranyi, Michal; Vondrák, Vít

doi:10.1063/1.4913040

Cited by 3 publications

(3 citation statements)

References 4 publications

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“…A model used in this paper is a rainfall-runoff model developed as part of the Floreon + system (Golasowski, Litschmannova, Kuchar, Podhoranyi & Martinovic 2015), (Vavrik, Theuer, Golasowski, Kuchar, Podhoranyi & Vondrak 2015). The RR models transforms precipitation to water discharge levels by modelling individual parts of the rainfall-runoff process.…”

Section: Flood Monitoring and Prediction Modelmentioning

confidence: 99%

Flood Prediction Model Simulation With Heterogeneous Trade-Offs In High Performance Computing Framework

Portero¹,

Vavrik

Kuchař

et al. 2015

ECMS 2015 Proceedings Edited By: Valeri M. Mladenov, Petia Georgieva, Grisha Spasov, Galidiya Petrova

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In this paper, we propose a safety-critical system with a run-time resource management that is used to operate an application for flood monitoring and prediction. This application can run with different Quality of Service (QoS) levels depending on the current hydrometeorological situation. The system operation can follow two main scenarios-standard or emergency operation. The standard operation is active when no disaster occurs, but the system still executes shortterm prediction simulations and monitors the state of the river discharge and precipitation intensity. Emergency operation is active when some emergency situation is detected or predicted by the simulations. The resource allocation can either be used for decreasing power consumption and minimizing needed resources in standard operation, or for increasing the precision and decreasing response times in emergency operation. This paper shows that it is possible to describe different optimal points at design time and use them to adapt to the current quality of service requirements during run-time.

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Section: Flood Monitoring and Prediction Modelmentioning

confidence: 99%

Flood Prediction Model Simulation With Heterogeneous Trade-Offs In High Performance Computing Framework

Portero¹,

Vavrik

Kuchař

et al. 2015

ECMS 2015 Proceedings Edited By: Valeri M. Mladenov, Petia Georgieva, Grisha Spasov, Galidiya Petrova

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“…One of the applications that are used to develop, test and validate the HARPA architecture is the Floreon+ system [11,12]. It is an automatized flood prediction system for the Moravian-Silesian region in Czech Republic developed at IT4Innovations National Supercomputing Centre.…”

Section: Critical Modules and Their Operation In Hpc Environment Casmentioning

confidence: 99%

“…This process cannot correctly support automatic runs in the system that have to behave accordingly to dynamic changes in weather and current state of the river and its catchment areas. The correct setting of model parameters can be done by inverse modelling and calibration methods, but these methods require repeated executions of the model with different parameters that converge to optimal configuration of these parameters in the model for current situation [12]. Taking these specifics into account, we identified two main application scenarios that support the different workload of the system based on the flood emergency situation.…”

Section: Critical Modules and Their Operation In Hpc Environment Casmentioning

confidence: 99%

System and Application Scenarios for Disaster Management Processes, the Rainfall-Runoff Model Case Study

Portero

Kuchař

Vavrik

et al. 2014

Computer Information Systems and Industrial Management

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Part 5: Industrial Management and Other ApplicationsInternational audienceIn the future, the silicon technology will continue to reduce following the Moore’s law. Device variability is going to increase due to a loss in controllability during silicon chip fabrication. Then, the mean time between failures is also going to decrease. The current methodologies based on error detection and thread re-execution (roll back) can not be enough, when the number of errors increases and arrives to a specific threshold. This dynamic scenario can be very negative if we are executing programs in HPC systems where a correct, accurate and time constrained solution is expected. The objective of this paper is to describe and analyse the needs and constraints of different applications studied in disaster management processes. These applications fall mainly in the domains of the High Performance Computing (HPC). Even if this domain can have differences in terms of computation needs, system form factor and power consumption, it nevertheless shares some commonalities

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Floreon+ Modules: A Real-World HARPA Application in the High-End HPC System Domain

Portero¹,

Vavrik²,

Golasowski³

et al. 2018

Harnessing Performance Variability in Embedded and High-Performance Many/Multi-Core Platforms

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Automatic calibration of rainfall-runoff models and its parallelization strategies

Cited by 3 publications

References 4 publications

Flood Prediction Model Simulation With Heterogeneous Trade-Offs In High Performance Computing Framework

Flood Prediction Model Simulation With Heterogeneous Trade-Offs In High Performance Computing Framework

System and Application Scenarios for Disaster Management Processes, the Rainfall-Runoff Model Case Study

Floreon+ Modules: A Real-World HARPA Application in the High-End HPC System Domain

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