Reimplementation of the Math1D Rainfall-Runoff Model for HPC Execution

Import 05/08/2014Hlavním cílem této práce je popsat novou implementaci srážko-odtokového modelu Math1D, čím se liší od té původní a z jakého důvodu a za jakým účelem byla vytvořena. Prezentovány jsou rovněž technologie použité pro zrychlení běhu modelu a jeho dalších součástí, jakým způsobem byly použity a jaké jejich užití přineslo výsledky. Představeno je také prostředí pro běh, postup spouštění a možnosti využití nově vzniklé aplikace včetně rozhraní pro parametrizaci schematizací modelu Math1D.The main objective of this thesis is to describe a new implementation of the rainfall-runoff model Math1D, how it differs from the original one and why and for what purpose it was created. Presented are also technologies used to increase the operating speed of the model and its other components, how they were used and what results their use has brought. Introduced is also an environment for running, launch procedure and possibilities of using newly developed application including interface for parametrization of Math1D model schematizations.460 - Katedra informatikyvelmi dobř

Implementation of Online Card Game Using the Technologies HTML5 and Websocket

Import 03/08/2012Hlavním cílem této bakalářské práce je seznámení se s technologiemi nově vznikajícího standardu HTML5, který by měl přinést vylepšené postupy pro tvorbu a prezentaci moderního webového obsahu a poskytnout nové možnosti pro komplexní webové aplikace. Při této příležitosti bylo mým úkolem navrhnout a implementovat online webovou karetní hru BANG! pro více hráčů dle modelu klient - server s využitím WebSockets a dalších HTML5 technologií.The main aim of this bachelor thesis is to get familiar with the technologies of newly emerging HTML5 standard, which should bring improved methods for development and presentation of modern web content, and should provide new features for complex web applications. On this occasion it was my job to design and implement multiplayer online web card game BANG! according to the model client - server using HTML5 WebSockets and other technologies.460 - Katedra informatikyvýborn

Efficient methods of automatic calibration for rainfall-runoff modelling in the Floreon+ system

Calibration of rainfall-runoff model parameters is an inseparable part of hydrological simulations. To achieve more accurate results of these simulations, it is necessary to implement an efficient calibration method that provides sufficient refinement of the model parameters in a reasonable time frame. In order to perform the calibration repeatedly for large amount of data and provide results of calibrated model simulations for the flood warning process in a short time, the method also has to be automated. In this paper, several local and global optimization methods are tested for their efficiency. The main goal is to identify the most accurate method for the calibration process that provides accurate results in an operational time frame (typically less than 1 hour) to be used in the flood prediction Floreon(+) system. All calibrations were performed on the measured data during the rainfall events in 2010 in the Moravian-Silesian region (Czech Republic) using our in-house rainfall-runoff model.Web of Science27441339

Precision-Aware application execution for Energy-optimization in HPC node system

Power consumption is a critical consideration in high performance computing systems and it is becoming the limiting factor to build and operate Petascale and Exascale systems. When studying the power consumption of existing systems running HPC workloads, we find that power, energy and performance are closely related which leads to the possibility to optimize energy consumption without sacrificing (much or at all) the performance. In this paper, we propose a HPC system running with a GNU/Linux OS and a Real Time Resource Manager (RTRM) that is aware and monitors the healthy of the platform. On the system, an application for disaster management runs. The application can run with different QoS depending on the situation. We defined two main situations. Normal execution, when there is no risk of a disaster, even though we still have to run the system to look ahead in the near future if the situation changes suddenly. In the second scenario, the possibilities for a disaster are very high. Then the allocation of more resources for improving the precision and the human decision has to be taken into account. The paper shows that at design time, it is possible to describe different optimal points that are going to be used at runtime by the RTOS with the application. This environment helps to the system that must run 24/7 in saving energy with the trade-off of losing precision. The paper shows a model execution which can improve the precision of results by 65% in average by increasing the number of iterations from 1e3 to 1e4. This also produces one order of magnitude longer execution time which leads to the need to use a multi-node solution. The optimal trade-off between precision vs. execution time is computed by the RTOS with the time overhead less than 10% against a native execution

A massively parallel and memory-efficient FEM toolbox with a hybrid total FETI solver with accelerator support

In this article, we present the ExaScale PaRallel finite element tearing and interconnecting SOlver (ESPRESO) finite element method (FEM) library, which includes an FEM toolbox with interfaces to professional and open-source simulation tools, and a massively parallel hybrid total finite element tearing and interconnecting (HTFETI) solver which can fully utilize the Oak Ridge Leadership Computing Facility Titan supercomputer and achieve superlinear scaling. This article presents several new techniques for finite element tearing and interconnecting (FETI) solvers designed for efficient utilization of supercomputers with a focus on (i) performance—we present a fivefold reduction of solver runtime for the Laplace equation by redesigning the FETI solver and offloading the key workload to the accelerator. We compare Intel Xeon Phi 7120p and Tesla K80 and P100 accelerators to Intel Xeon E5-2680v3 and Xeon Phi 7210 central processing units; and (ii) memory efficiency—we present two techniques which increase the efficiency of the HTFETI solver 1.8 times and push the limits of the largest possible problem ESPRESO that can solve from 124 to 223 billion unknowns for problems with unstructured meshes. Finally, we show that by dynamically tuning hardware parameters, we can reduce energy consumption by up to 33%