Stepan Kuchar

Multiple Scenarios Computing In The Flood Prediction System FLOREON.

Floods are the most frequent natural disasters affecting the Moravian-Silesian region. Therefore a system that could predict flood extents and help in the operative disaster management was requested. The FLOREON system was created to fulfil these requests. This article describes utilization of HPC (high performance computing) in running multiple hydrometeorological simulations concurrently in the FLOREON system that should predict upcoming floods and warn against them. These predictions are based on the data inputs from NWFS (numerical weather forecast systems) (e.g. ALADIN) that are then used to run the rainfall-runoff and hydrodynamic models. Preliminary results of these experiments are presented in this article.

Harnessing Performance Variability: A HPC-Oriented Application Scenario

The technology scaling towards the 10nm of the silicon manufacturing, is going to introduce variability challenges, mainly due to the growing susceptibility to thermal hot-spots and time-dependent variations (aging) in the silicon chip. The consequences are two-fold: a) unpredictable performance, b) unreliable computing resources. The goal of the HARPA project is to enable next-generation embedded and high-performance heterogeneous many-core processors to effectively address this issues, through a cross-layer approach, involving several component of the system stack. Each component acts at different levels and time granularity. This paper focus on one of the components of the HARPA stack, the HARPA-OS, showing early results of a first integration step of the HARPA approach in a real High-Performance Computing (HPC) application scenario.

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

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.

Automatic calibration of rainfall-runoff models and its parallelization strategies

For successful decision making in disaster management it is necessary to have very accurate information about disaster phenomena and its potential developmentin time. Rainfall-runoff simulations are an integral part of flood warning and decision making processes. To increase their accuracy, it is crucial to periodically updatetheir parametersin a calibration process.Since calibration is very time consuming process an HPC facility is convenient tool for its speed-up. However, required speed-up can be achieved only avoiding any human-computer interaction in so-called automatic calibration.In order to compare possibilities and efficiency of the automatic calibration, three different fully automatic parallel implementationstrategies were created and tested with our in-house rainfall-runoff model.

Dynamic computing resource allocation in online flood monitoring and prediction

This paper presents tools and methodologies for dynamic allocation of high performance computing resources during operation of the Floreon+ online flood monitoring and prediction system. The resource allocation is done throughout the execution of supported simulations to meet the required service quality levels for system operation. It also ensures flexible reactions to changing weather and flood situations, as it is not economically feasible to operate online flood monitoring systems in the full performance mode during non-flood seasons. Different service quality levels are therefore described for different flooding scenarios, and the runtime manager controls them by allocating only minimal resources currently expected to meet the deadlines. Finally, an experiment covering all presented aspects of computing resource allocation in rainfall-runoff and Monte Carlo uncertainty simulation is performed for the area of the Moravian-Silesian region in the Czech Republic.

Flood evolution assessment and monitoring using hydrological modelling techniques: analysis of the inundation areas at a regional scale

The primary objective of this study is to present techniques that cover usage of a hydrodynamic model as the main tool for monitoring and assessment of flood events while focusing on modelling of inundation areas. We analyzed the 2010 flood event (14th May - 20th May) that occurred in the Moravian-Silesian region (Czech Republic). Under investigation were four main catchments: Opava, Odra, Olse and Ostravice. Four hydrodynamic models were created and implemented into the Floreon+ platform in order to map inundation areas that arose during the flood event. In order to study the dynamics of the water, we applied an unsteady flow simulation for the entire area (HEC-RAS 4.1). The inundation areas were monitored, evaluated and recorded semi-automatically by means of the Floreon+ platform. We focused on information about the extent and presence of the flood areas. The modeled flooded areas were verified by comparing them with real data from different sources (official reports, aerial photos and hydrological networks). The study confirmed that hydrodynamic modeling is a very useful tool for mapping and monitoring of inundation areas. Overall, our models detected 48 inundation areas during the 2010 flood event.

Framework for scheduling and resource management in time-constrained HPC application

The silicon technology continues reducing scale following the Moore’s law. Device variability increases due to a lost in controllability during silicon chip fabrication. The current methodologies based on error detection and thread re-execution (roll back) cannot be enough, when the number of errors increase and arrive to a threshold. This dynamic scenario can be very negative if we are executing programs in HPC systems where a correct, accurate and time constraints solution is expected. The objective of the paper is to show preliminary results of Barbeque OpenSource Project (BOSP) and its potential use in HPC systems.

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

This chapter is centered around uncertainty computation with on-demand resource allocation for run-off prediction in a High-Performance Computer environment. Our research stands on a runtime operating system that automatically adapts resource allocation with the computation to provide precise outcomes before the time deadline. In our case, input data comes from several gauging stations, and when newly updated data arrives, models must be re-executed to provide accurate results immediately. Since the models run continuously (24/7), their computational demand is different during various hydrological events (e.g. periods with heavy rain and without any rain) and therefore computational resources have to be balanced according to the event severity. Although these kinds of models should run constantly, they are very computationally demanding during discrete periods of time, for example in the case of heavy rain. Then, the accuracy of the results must be as close as possible to reality. The work relies on the HARPA runtime resource manager that adapts resource allocation to the runtime-variable performance demand of applications. The resource assignment is temperature-aware: the application execution is dynamically migrated to the coolest cores, and this has a positive impact on the system reliability.

The HARPA Approach to Ensure Dependable Performance

The goal of the HARPA solution is to overcome the performance variability (PV) by enabling next-generation embedded and high-performance platforms using heterogeneous many-core processors to provide cost-effectively dependable performance: the correct functionality and (where needed) timing guarantees throughout the expected lifetime of a platform. This must be accomplished in the presence of cycle-by-cycle performance variability due to time-dependent variations in silicon devices and wires under thermal, power, and energy constraints. The common challenge for both embedded and high-performance systems is to harness the unsustainable increases in design and operational margins and yet provide dependable performance. For example, resources that are statically determined based on worst-case execution time for real-time applications or lower clock frequency to satisfy excessive timing margins in high-performance processors.

Earth observation-supported service platform for the development and provision of thematic information on the built environment — the TEP-Urban project

The Sentinel fleet will provide a so-far unique coverage with Earth observation (EO) data and therewith new opportunities for the implementation of methodologies to generate innovative geo-information products and services. It is here where the TEP Urban project is supposed to initiate a step change by providing an open and participatory platform based on modern Information and Communication Technologies (ICTs) that enable any interested user to easily exploit EO data pools, in particular those of the Sentinel missions, and derive thematic information on the status and development of the built environment from these data. Key component of TEP Urban project is the implementation of a web-based platform employing distributed high-level computing infrastructures and providing key functionalities for i) high-performance access to satellite imagery and derived thematic data, ii) modular and generic state-of-the-art pre-processing, analysis, and visualization techniques, iii) customized development and dissemination of algorithms, products and services, and iv) networking and communication. This contribution introduces the main facts about the TEP Urban project, including a description of the general objectives, the platform systems design and functionalities, and the preliminary portfolio products and services available at the TEP Urban platform.