Computer Science
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ISSN 1508-2806
e-ISSN: 2300-7036
Call number
Volume
Vol. 9
Date
2008
Description
Journal
Computer Science
AGH University Press (2004-)
ISSN: 1508-2806 e-ISSN: 2300-7036
ISSN: 1508-2806 e-ISSN: 2300-7036
journal.volume.project
Contains
Journal Issues
Articles
Monte Carlo fitting of data from muon catalyzed fusion experiments in solid hydrogen
(Wydawnictwa AGH, 2008) Filipowicz, Mariusz; Bystrickij, Vâčeslav Mihajlovič; Woźniak, Jan
Applying the classical chi-square fitting procedure for multiparameter systems is in some cases extremely difficult due to the lack of an analytical expression for the theoretical functions describing the system. This paper presents an analysis procedure for experimental data using theoretical functions generated by Monte Carlo method, each corresponding to definite values of the minimization parameters. It was applied for the E742 experiment (TRIUMF, Vancouver, Canada) data analysis with the aim to analyze data from Muon Catalyzed Fusion experiments (extraction muonic atom scattering parameters and parameters of pd fusion in pdµ molecule).
Computation acceleration on SGI RASC: FPGA based reconfigurable computing hardware
(Wydawnictwa AGH, 2008) Jamro, Ernest; Janiszewski, Marcin; Machaczek, Krzysztof; Russek, Paweł; Wiatr, Kazimierz; Wielgosz, Maciej
In this paper a novel method of computation using FPGA technology is presented. In several cases this method provides a calculations speedup with respcct to the General Purpose Processors (GPP). The main concept of this approach is based on such a design of computing hardware architecture to fit algorithm dataflow and best utilize well known computing techniques as pipelining and parallelism. Configurable hardware is used as a implementation platform for custom designed hardware. Paper will present implementation results of algorithms those are used in such areas as cryptography, data analysis and scientific computation. The other promising areas of new technology utilization will also be mentioned, bioinformatics for instance. Mentioned algorithms were designed, tested and implemented on SGI RASC platform. RASC module is a part of Cyfronet's SGI Altix 4700 SMP system. We will also present RASC modern architecture. In principle it consists of FPGA chips and very fast, 128-bit wide local memory. Design tools avaliable for designers will also be presented.
Optimization of tau indentification in ATLAS experiment using multivariate tools
(Wydawnictwa AGH, 2008) Janyst, Łukasz; Kaczmarska, Anna Ewa; Szymocha, Tadeusz; Wolter, Marcin; Zemła, Andrzej
Elementary particle physics experiments, which search for very rare processes, require the efficient analysis and selection algorithms able to separate a signal from the overwhelming background. Four learning machine algorithms have been applied to identify ? leptons in the ATLAS experiment: projective likelihood estimator (LL), Probability Density Estimator with Range Searches (PDE-RS), Neural Network, and the Support Vector Machine (SVM). All four methods have similar performance, which is significantly better than the baseline cut analysis. This indicates that the achieved background rejection is close to the maximal achievable performance.
The ATLAS experiment simulations as the computing challenge for the ACK CYFRONET AGH
(Wydawnictwa AGH, 2008) Kaczmarska, Anna Ewa; Małecki, Paweł; Szymocha, Tadeusz; Richter-Wąs, Elżbieta
The present High Energy Physics (HEP) experiments require unprecedented amount of computing power and storage space. We present the WLCG structure of the LHC computing, which will be used to perform data processing required by the ATLAS collaboration. We also describe the ATLAS detector full simulation chain. Finally, we quantify the computing needs and up-to-date usage of the ACK CYFRONET AGH resources by the ATLAS detector simulations.
Optimization of simulation model parameters for solidification of metals with use of agent-based evolutionary algorithm
(Wydawnictwa AGH, 2008) Kluska-Nawarecka, Stanisława; Smolarek-Grzyb, Agnieszka; Byrski, Aleksander; Wilk-Kołodziejczyk, Dorota
The finite elements method (FEM) is currently widely used for simulation of thermal processes. However, one of still unresolved problems remains proper selection of mathematical model parameters for these processes. As far as modelling of cooling casts in forms is concerned, particular difficulties appear while estimating values of numerous coefficients such as: heat transport coefficient between metal and form, specific heat, metal and form heat conduction coefficient, metal and form density. Coefficients mentioned above depend not only on materials properties but also on temperature. In the paper the idea of optimalization of simulation method parameters based on adaptive adjustment of curve representing simulation result and result obtained in physical experiment is presented along with the idea of evolutionary and agent-based evolutionary optimization system designed to conduct such optimizations. Preliminary results obtained with use of ABAQUS system available in ACK CYFRONET and software developed at AGH-UST conclude the paper.