Wyniki wyszukiwania - BazTech

1

Energy Efficient Scheduling Methods for Computational Grids and Clouds

Jakóbik A., Grzonka D., Kołodziej J., Chis A. E., González-Vélez H.

Journal of Telecommunications and Information Technology

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2017

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nr 1

56--64

EN

This paper presents an overview of techniques developed to improve energy efficiency of grid and cloud computing. Power consumption models and energy usage proles are presented together with energy efficiency measuring methods. Modeling of computing dynamics is discussed from the viewpoint of system identication theory, indicating basic experiment design problems and challenges. Novel approaches to cluster and network-wide energy usage optimization are surveyed, including multi-level power and software control systems, energy-aware task scheduling, resource allocation algorithms and frameworks for backbone networks management. Software-development techniques and tools are also presented as a new promising way to reduce power consumption at the computing node level. Finally, energy-aware control mechanisms are presented. In addition, this paper introduces the example of batch scheduler based on ETC matrix approach.

2

Application of selected supervised classification methods to bank marketing campaign

Grzonka D., Borowik B., Suchacka G.

Information Systems in Management

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2016

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Vol. 5, No. 1

36--48

EN

Supervised classification covers a number of data mining methods based on training data. These methods have been successfully applied to solve multi-criteria complex classification problems in many domains, including economical issues. In this paper we discuss features of some supervised classification methods based on decision trees and apply them to the direct marketing campaigns data of a Portuguese banking institution. We discuss and compare the following classification methods: decision trees, bagging, boosting, and random forests. A classification problem in our approach is defined in a scenario where a bank’s clients make decisions about the activation of their deposits. The obtained results are used for evaluating the effectiveness of the classification rules.

3

The Analysis of OpenStack Cloud Computing Platform: Features and Performance

Grzonka D.

Journal of Telecommunications and Information Technology

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2015

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nr 3

52--57

EN

Over the decades the rapid development of broadly defined computer technologies, both software and hardware is observed. Unfortunately, software solutions are regularly behind in comparison to the hardware. On the other hand, the modern systems are characterized by a high demand for computing resources and the need for customization for the end users. As a result, the traditional way of system construction is too expensive, inflexible and it doesn’t have high resources utilization. Present article focuses on the problem of effective use of available physical and virtual resources based on the OpenStack cloud computing platform. A number of conducted experiments allowed to evaluate computing resources utility and to analyze performance depending on the allocated resources. Additionally, the paper includes structural and functional analysis of the OpenStack cloud platform.

4

Application of high-performance techniques for solving linear systems of algebraic equations

Grzonka D.

Journal of Telecommunications and Information Technology

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2013

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nr 4

85--91

EN

Solving many problems in mechanics, engineering, medicine and other (e.g., diffusion tensor magnetic resonance imaging or finite element modeling) requires the efficient solving of algebraic equations. In many cases, such systems are very complex with a large number of linear equations, which are symmetric positive-defined (SPD). This paper is focused on improving the computational efficiency of the solvers dedicated for the linear systems based on incomplete and noisy SPD matrices by using preconditioning technique – Incomplete Cholesky Factorization, and modern set of processor instructions – Advanced Vector Extension. Application of these techniques allows to fairly reduce the computational time, number of iterations of conventional algorithms and improve the speed of calculation.