Wyniki 1-2 spośród 2 dla zapytania: authorDesc:"Artur KRUPA"

High-resolution scatter analyse using cloud computing DOI:10.15199/48.2015.12.35

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Cloud computing is the newest approach to solve computationally challenging problems. It is oriented on optimization of processing costs using low-budget, standard computers. Algorithmic scheme for such problems is MapReduce. We will show how to use MapReduce architecture to efficiently solve high number of independent analysis needed for scatter plots. Presented case study is based on simple student problem solved using FEM. High-resolution scatter plot image introduce new quality in visualization of results. Streszczenie. Chmura obliczeniowa (ang. cloud computing) to najnowsze podejście do rozwiązywania problemów złożonych obliczeniowo. Jest to architektura zorientowana na optymalizację kosztów przetwarzania przy użyciu niskobudżetowych, standardowych komputerów. Algorytmem obliczeniowym dla takich problemów jest MapReduce. W niniejszym artykule pokażemy jak wykorzystać MapReduce do efektywnego rozwiązywania dużej liczby niezależnych analiz, które zostaną zobrazowane przy pomocy wykresu zmienności. Zaprezentowany przykład jest prostym studenckim problemem MES. Wysokiej rozdzielczości analiza wprowadzaj nową jakość w wizualizacji wyników. (Wysokiej rozdzielczości analiza zmienności parametrów przy wykorzystaniu chmury obliczeniowej). Keywords: cloud computing, electric field simulation, scatter analyse, MapReduce model. Słowa kluczowe: chmura obliczeniowa, symulacja pola elektrycznego, analiza zmienności parametrów, model MapReduce. Introduction The aim of the scatter analysis is to visualize variability of solutions as a function of input parameters. To prepare such plot, problem has to be analysed many times for different values of parameters. Scatter plot helps to understand relations within the problem, so it is one of the most popular scientific tools. Data required for scatter plot could be acquired from different sources. The simplest one is to observe natural variability of measured quantity. This approach is usually taken fo[...]

Optimization of coil geometry using Monte Carlo method with HTCondor and Microsoft Azure technologies DOI:10.15999/48.2019.05.28

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An important trend in modern computational science is certainly cloud computing. Although this term has been created by the marketing departments in early 2000’s, and a history of distributed and parallel processing in computer science is much longer, one could realize novelty in cloud computing approach. Utilization of commercially managed resources for scientific tasks has significant advantages, such as a flexibility to use different hardware, no need for infrastructure investments. On the other hand, important challenges are raised [1] and it is known that not all types the computing problems benefit from a loosely coupled architecture in the same way. Groups of problems, which could be easily transferred into the cloud infrastructure are independent simulations, sometimes called as an ’embarrassingly parallel’ problems. Sensitivity analysis [2], stochastic simulations [3] are just examples of the problems which require a large number of simulations. Another are DNA alignment in bioinformatics, 3D scene rendering in computer graphics or Monte Carlo methods, which are the main subject of this article. The Monte Carlo methods are based on probing parameters space with the use of a random generator. Applications of such simple but robust solution are wide, and they are especially compatible with the structure of the cloud services [4]. Stochastic optimization using Monte Carlo sampling is one of them [5]. In this paper, stochastic optimization technique is used to design the magnetic coil system. The developed simulation platform is constructed using HTCondor embedded in the Microsoft Azure environment as presented in Fig. 1. Finite element method solver has been constructed using FEniCS library as described later in the paper. Coil design problem is a test case, which could be also successfully solved using gradient optimization techniques. However it should be treated as a benchmarking tool to study e[...]

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