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

Abstract

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.

Harnessing Performance Variability: A HPC-Oriented Application Scenario

“…The quality of service (QoS) of the RR model is expressed in terms of accuracy, that is proportional to the number of Montecarlo iterations; and the expected execution time [11], [13]. Accordingly, each of the three flood warning levels can be mapped to a given quality of service level: …”

Computer simulation of the safety of radio electronics production in an emergency situation

“…As an example, consider the model "Calculation of thermal radiation from a strait fire". A number of works are known in which the processes of ensuring security in emergency situations are modeled [4][5][6][7][8][9]. The authors conducted research in this area to create mathematical models describing the impact of damaging factors on protected objects.…”