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S. Nesmachnow

Universidad de la República (Uruguay), Facultad de Ingeniería, Faculty Member

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Universidad de Extremadura

Roshan Chitrakar

Nepal College of Information Technology

Graduate Center of the City University of New York

The University of Queensland, Australia

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RIVERS STATE POLYTECHNIC

Université de Reims Champagne-Ardenne

Universidade Federal do Pampa

Universidad de la República (Uruguay)

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Papers by S. Nesmachnow

SCCG 2012 Organizing Committee

Workshop Co-chairs Sergio Nesmachnow, Universidad de la República, Uruguay Bernabé Dorronsoro, Un... more Workshop Co-chairs Sergio Nesmachnow, Universidad de la República, Uruguay Bernabé Dorronsoro, University of Luxembourg, Luxembourg ... Publicity Chair Santiago Iturriaga, Universidad de la República, Uruguay ... Program Committee Members Enrique Alba, Universidad de Málaga, Spain Jhon Edgar Amaya, Universidad Nacional Experimental del Tachira, Venezuela Francisco Brasileiro, Universidade Federal de Campina Grande, Brazil Pascal Bouvry, University of Luxembourg, Luxembourg Juan Carlos Burguillo, Universidad de Vigo, Spain Héctor ...

Low-Rank Radiosity Using Sparse Matrices

Proceedings of the International Conference on Computer Graphics Theory and Applications, 2012

Radiosity methods are part of the global illumination techniques, which deal with the problem of ... more Radiosity methods are part of the global illumination techniques, which deal with the problem of generating photorealistic images in 3D scenes with Lambertian surfaces. Low-rank radiosity is a O(nk) method, where n is the number of polygons and k is the rank of the matrix used as a direct transport operator. This method allows calculating, in real-time and with infinite bounces, the illumination of a scene with static geometry and dynamic lighting. In this paper we present a new methodology for low-rank radiosity calculation based on the use of sparse matrices, which significantly reduces the memory storage required and achieves speedup improvements over the original low-rank method. Experimental analysis was performed in both traditional computers and new graphics processing unit architectures. 2 THE RADIOSITY PROBLEM This section starts by introducing the radiosity problem formulation. After that, the main proposals found in the literature related with the pre-computed radiosity and radiance transfer problem are reviewed.

Data analysis approach for characterizing residential energy consumption based on statistics of household appliances ownership

Worldwide, residential electricity demand has increased constantly, expecting to double in 2050 t... more Worldwide, residential electricity demand has increased constantly, expecting to double in 2050 the demand of 2010. Different policies have been proposed to achieve a smart use of electricity. This article presents a data-analysis approach to evaluate the potential household electricity consumption from statistical data. The main axis of the study are statistics of appliance ownership and information of the appliance characteristics, gathered from census surveys and local shops. An index to estimate the electricity consumption is performed. The validation of the proposed index is carried out using real consumption data from the Electricity Consumption Data set of Uruguay and Ordinary Least Square linear regressions. Jupyter notebooks, Python language and well-know libraries such as Pandas and Numpy were used during the implementation. The main results show that administrative regions located on the West/Southwest coastlines present the highest index scores. In turn, census sections/...

Parallel conversion of satellite image information for a wind energy generation forecasting model

CLEI Electronic Journal, 2012

This paper presents an efficient parallel algorithm for the problem of converting satellite image... more This paper presents an efficient parallel algorithm for the problem of converting satellite imagery in binary files. The algorithm was designed to update at global scale the land cover information used by the WRF climate model. We present the characteristics of the implemented algorithm, as well as the results of performance analysis and comparisons between two approaches to implement the algorithm. The performance analysis shows that the implemented parallel algorithm improves substantially against the sequential algorithm that solves the problem, obtaining a linear speedup.

Parallel Computing Applied to Satellite Images Processing for Solar Resource Estimates

CLEI Electronic Journal, 2012

This article presents the application of parallel computing techniques to process satellite image... more This article presents the application of parallel computing techniques to process satellite imagery information for solar resource estimates. A distributed memory parallel algo- rithm is introduced, which is capable to generate the required inputs from visible channel images to feed a statistical solar irradiation model. The parallelization strategy consists in distributing the images within the available processors, and so, every image is accessed only by one process. The experimental analysis demonstrate that a maximum speedup value of 2.32 is achieved when using four computing resources, but beyond that point the performance rather decrease due to hard-disk input/output velocity.

Resolución del problema de radiosidad usando matrices de rango bajo

ABSTRACT

Controlling datacenter power consumption while maintaining temperature and QoS levels

2014 IEEE 3rd International Conference on Cloud Networking (CloudNet), 2014

The large amount of energy used by datacenters impacts both energy cost and the electricity grid.... more The large amount of energy used by datacenters impacts both energy cost and the electricity grid. These issues can be mitigated by dynamically adjusting the power demand of datacenters. However, conflicting objectives have to be considered: workload and cooling can be dynamically reduced, but with a potential impact on quality of service or excursions beyond acceptable temperature bands. In this paper we use a multi-objective evolutionary algorithm to explore the trade-offs between power consumption, temperature, and quality of service when both servers and cooling are controlled holistically in a datacenter.

Multiobjective Energy-Aware Datacenter Planning Accounting for Power Consumption Profiles

Communications in Computer and Information Science, 2014

Energy efficiency is one of the major concerns when operating datacenters nowadays, as the large ... more Energy efficiency is one of the major concerns when operating datacenters nowadays, as the large amount of energy used by parallel computing infrastructures impacts on both the energy cost and the electricity grid. Power consumption can be lowered by dynamically adjusting the power demand of datacenters, but conflicting objectives such as temperature and quality of service must be taken into account. This paper proposes a multiobjective evolutionary approach to solve the energyaware scheduling problem in datacenters, regarding power consumption, temperature, and quality of service when controlling servers and cooling infrastructures. Accurate results are reported for both best solutions regarding each of the problem objectives and best trade-off solutions.

Criptografía cuántica

Parallel evolutionary algorithms for scheduling on heterogeneous computing and grid environments

This thesis studies the application of sequential and parallel evolutionary algorithms to the sch... more This thesis studies the application of sequential and parallel evolutionary algorithms to the scheduling problem in heterogeneous computing and grid environments, a key problem when executing tasks in distributed computing systems. Since the 1990's, this class of systems has been increasingly employed to provide support for solving complex problems using high-performance computing techniques. The scheduling problem in heterogeneous computing systems is an NP-hard optimization problem, which has been tackled using several optimization methods in the past. Among many new techniques for optimization, evolutionary computing methods have been successfully applied to this class of problems. In this work, several evolutionary algorithms in their sequential and parallel variants are specifically designed to provide accurate solutions for the problem, allowing to compute an efficient planning for heterogeneous computing and grid environments. New problem instances, far more complex than those existing in the related literature, are introduced in this thesis in order to study the scalability of the presented parallel evolutionary algorithms. In addition, a new parallel micro-CHC algorithm is developed, inspired by useful ideas from the multiobjective optimization field. Efficient numerical results of this algorithm are reported in the experimental analysis performed on both well-known problem instances and the large instances specially designed in this work. The comparative study including traditional methods and evolutionary algorithms shows that the new parallel micro-CHC is able to achieve a high problem solving efficacy, outperforming previous results already reported for the problem and also having a good scalability behavior when solving high dimension problem instances. In addition, two variants of the scheduling problem in heterogeneous environments are also tackled, showing the versatility of the proposed approach using parallel evolutionary algorithms to deal with both dynamic and multiobjective scenarios.

Planificación de tareas en sistemas cluster, grid y cloud utilizando algoritmos evolutivos

Relevamiento de simuladores 3G-UMTS

Resolución en lınea del problema de viajes compartidos en taxis usando algoritmos evolutivos

Metaheuristics as soft computing techniques for efficient optimization

Solving a Ring Star Problem Generalization

2008 International Conference on Computational Intelligence for Modelling Control & Automation, 2008

The Capacitated m-Ring Star Problem (CmRSP) consists of finding a set of m rings, each of them in... more The Capacitated m-Ring Star Problem (CmRSP) consists of finding a set of m rings, each of them including the central depot, a subset of customers, and a set of optional nodes used to diminish the costs of the network design. The rings must be node-disjoint (except for the central depot) in order to provide node-survivability to the network. Customers that

A Parallel Multilevel Data Decomposition Algorithm for Orientation Estimation of Unmanned Aerial Vehicles

Communications in Computer and Information Science, 2014

Fast orientation estimation of unmanned aerial vehicles is important for maintain stable flight a... more Fast orientation estimation of unmanned aerial vehicles is important for maintain stable flight as well as to perform more complex task like obstacle avoidance, search, mapping, etc. The orientation estimation can be performed by means of the fusion of different sensors like accelerometers, gyroscopes and magnetometers, however magnetometers suffer from high distortion in indoor flights, therefore information from cameras can be used as a replacement. This article presents a multilevel decomposition method to process images sent from an unmanned aerial vehicle to a ground station composed by an heterogeneous set of desktop computers. The multilevel decomposition is performed using an alternative hierarchy called Master/Taskmaster/Slaves in order to minimize the network latency. Results shows that using this hierarchy the speed of traditional Master/Slave can be doubled.

An empirical time analysis of evolutionary algorithms as C programs

Software: Practice and Experience, 2013

This article presents an empirical study devoted to characterize the computational efficiency beh... more This article presents an empirical study devoted to characterize the computational efficiency behavior of an evolutionary algorithm (usually called canonical) as a C program. The study analyzes the effects of several implementation decisions on the execution time of the resulting evolutionary algorithm. The implementation decisions studied include: memory utilization (using dynamic vs. static variables and local vs. global variables), methods for ordering the population, code substitution mechanisms, and the routines for generating pseudorandom numbers within the evolutionary algorithm. The results obtained in the experimental analysis allow us to conclude that significant improvements in efficiency can be gained by applying simple guidelines to best program an evolutionary algorithm in C.

Granular physics in low-gravity environments using discrete element method

Monthly Notices of the Royal Astronomical Society, 2012

Granular materials of different sizes are present on the surface of several atmosphereless Solar ... more Granular materials of different sizes are present on the surface of several atmosphereless Solar system bodies. The phenomena related to granular materials have been studied in the framework of the discipline called granular physics, both experimentally and, over the last few decades, by numerical simulations. The discrete element method simulates the mechanical behaviour of a medium formed by a set of particles which interact through their contact points. The difficulty in reproducing vacuum and low-gravity environments makes numerical simulations the most promising technique in the study of granular media under these conditions. In this work, relevant processes in minor bodies of the Solar system are studied using the discrete element method. Results of simulations of size segregation in low-gravity environments in the cases of the asteroids Eros and Itokawa are presented. The segregation of particles with different densities was analysed, in particular, the case of comet P/Hartley 2. The surface shaking in these different gravity environments could produce the ejection of particles from the surface at very low relative velocities. The shaking causing the above processes is due to impacts and explosions such as the release of energy by the liberation of internal stresses or the re-accommodation of material. Simulations of the passage of impact-induced seismic waves through a granular medium were also performed. We present several applications of the discrete element methods for the study of the physical evolution of agglomerates of rocks under low-gravity environments.

Parallel multiobjective evolutionary algorithms for batch scheduling in heterogeneous computing and grid systems

Computational Optimization and Applications, 2013

This article presents six parallel multiobjective evolutionary algorithms applied to solve the sc... more This article presents six parallel multiobjective evolutionary algorithms applied to solve the scheduling problem in distributed heterogeneous computing and grid systems. The studied evolutionary algorithms follow an explicit multiobjective approach to tackle the simultaneous optimization of a system-related (i.e. makespan) and a user-related (i.e. flowtime) objectives. Parallel models of the proposed methods are developed in order to efficiently solve the problem. The experimental analysis demonstrates that the proposed evolutionary algorithms are able to efficiently compute accurate results when solving standard and new large problem instances. The best of the proposed methods outperforms both deterministic scheduling heuristics and single-objective evolutionary methods previously applied to the problem.

A hybrid GRASP and Tabu Search algorithm for the Capacitated m-Ring Star Problem

SCCG 2012 Organizing Committee

Workshop Co-chairs Sergio Nesmachnow, Universidad de la República, Uruguay Bernabé Dorronsoro, Un... more Workshop Co-chairs Sergio Nesmachnow, Universidad de la República, Uruguay Bernabé Dorronsoro, University of Luxembourg, Luxembourg ... Publicity Chair Santiago Iturriaga, Universidad de la República, Uruguay ... Program Committee Members Enrique Alba, Universidad de Málaga, Spain Jhon Edgar Amaya, Universidad Nacional Experimental del Tachira, Venezuela Francisco Brasileiro, Universidade Federal de Campina Grande, Brazil Pascal Bouvry, University of Luxembourg, Luxembourg Juan Carlos Burguillo, Universidad de Vigo, Spain Héctor ...

Low-Rank Radiosity Using Sparse Matrices

Proceedings of the International Conference on Computer Graphics Theory and Applications, 2012

Radiosity methods are part of the global illumination techniques, which deal with the problem of ... more Radiosity methods are part of the global illumination techniques, which deal with the problem of generating photorealistic images in 3D scenes with Lambertian surfaces. Low-rank radiosity is a O(nk) method, where n is the number of polygons and k is the rank of the matrix used as a direct transport operator. This method allows calculating, in real-time and with infinite bounces, the illumination of a scene with static geometry and dynamic lighting. In this paper we present a new methodology for low-rank radiosity calculation based on the use of sparse matrices, which significantly reduces the memory storage required and achieves speedup improvements over the original low-rank method. Experimental analysis was performed in both traditional computers and new graphics processing unit architectures. 2 THE RADIOSITY PROBLEM This section starts by introducing the radiosity problem formulation. After that, the main proposals found in the literature related with the pre-computed radiosity and radiance transfer problem are reviewed.

Data analysis approach for characterizing residential energy consumption based on statistics of household appliances ownership

Worldwide, residential electricity demand has increased constantly, expecting to double in 2050 t... more Worldwide, residential electricity demand has increased constantly, expecting to double in 2050 the demand of 2010. Different policies have been proposed to achieve a smart use of electricity. This article presents a data-analysis approach to evaluate the potential household electricity consumption from statistical data. The main axis of the study are statistics of appliance ownership and information of the appliance characteristics, gathered from census surveys and local shops. An index to estimate the electricity consumption is performed. The validation of the proposed index is carried out using real consumption data from the Electricity Consumption Data set of Uruguay and Ordinary Least Square linear regressions. Jupyter notebooks, Python language and well-know libraries such as Pandas and Numpy were used during the implementation. The main results show that administrative regions located on the West/Southwest coastlines present the highest index scores. In turn, census sections/...

Parallel conversion of satellite image information for a wind energy generation forecasting model

CLEI Electronic Journal, 2012

This paper presents an efficient parallel algorithm for the problem of converting satellite image... more This paper presents an efficient parallel algorithm for the problem of converting satellite imagery in binary files. The algorithm was designed to update at global scale the land cover information used by the WRF climate model. We present the characteristics of the implemented algorithm, as well as the results of performance analysis and comparisons between two approaches to implement the algorithm. The performance analysis shows that the implemented parallel algorithm improves substantially against the sequential algorithm that solves the problem, obtaining a linear speedup.

Parallel Computing Applied to Satellite Images Processing for Solar Resource Estimates

CLEI Electronic Journal, 2012

This article presents the application of parallel computing techniques to process satellite image... more This article presents the application of parallel computing techniques to process satellite imagery information for solar resource estimates. A distributed memory parallel algo- rithm is introduced, which is capable to generate the required inputs from visible channel images to feed a statistical solar irradiation model. The parallelization strategy consists in distributing the images within the available processors, and so, every image is accessed only by one process. The experimental analysis demonstrate that a maximum speedup value of 2.32 is achieved when using four computing resources, but beyond that point the performance rather decrease due to hard-disk input/output velocity.

Resolución del problema de radiosidad usando matrices de rango bajo

ABSTRACT

Controlling datacenter power consumption while maintaining temperature and QoS levels

2014 IEEE 3rd International Conference on Cloud Networking (CloudNet), 2014

The large amount of energy used by datacenters impacts both energy cost and the electricity grid.... more The large amount of energy used by datacenters impacts both energy cost and the electricity grid. These issues can be mitigated by dynamically adjusting the power demand of datacenters. However, conflicting objectives have to be considered: workload and cooling can be dynamically reduced, but with a potential impact on quality of service or excursions beyond acceptable temperature bands. In this paper we use a multi-objective evolutionary algorithm to explore the trade-offs between power consumption, temperature, and quality of service when both servers and cooling are controlled holistically in a datacenter.

Multiobjective Energy-Aware Datacenter Planning Accounting for Power Consumption Profiles

Communications in Computer and Information Science, 2014

Energy efficiency is one of the major concerns when operating datacenters nowadays, as the large ... more Energy efficiency is one of the major concerns when operating datacenters nowadays, as the large amount of energy used by parallel computing infrastructures impacts on both the energy cost and the electricity grid. Power consumption can be lowered by dynamically adjusting the power demand of datacenters, but conflicting objectives such as temperature and quality of service must be taken into account. This paper proposes a multiobjective evolutionary approach to solve the energyaware scheduling problem in datacenters, regarding power consumption, temperature, and quality of service when controlling servers and cooling infrastructures. Accurate results are reported for both best solutions regarding each of the problem objectives and best trade-off solutions.

Criptografía cuántica

Parallel evolutionary algorithms for scheduling on heterogeneous computing and grid environments

This thesis studies the application of sequential and parallel evolutionary algorithms to the sch... more This thesis studies the application of sequential and parallel evolutionary algorithms to the scheduling problem in heterogeneous computing and grid environments, a key problem when executing tasks in distributed computing systems. Since the 1990's, this class of systems has been increasingly employed to provide support for solving complex problems using high-performance computing techniques. The scheduling problem in heterogeneous computing systems is an NP-hard optimization problem, which has been tackled using several optimization methods in the past. Among many new techniques for optimization, evolutionary computing methods have been successfully applied to this class of problems. In this work, several evolutionary algorithms in their sequential and parallel variants are specifically designed to provide accurate solutions for the problem, allowing to compute an efficient planning for heterogeneous computing and grid environments. New problem instances, far more complex than those existing in the related literature, are introduced in this thesis in order to study the scalability of the presented parallel evolutionary algorithms. In addition, a new parallel micro-CHC algorithm is developed, inspired by useful ideas from the multiobjective optimization field. Efficient numerical results of this algorithm are reported in the experimental analysis performed on both well-known problem instances and the large instances specially designed in this work. The comparative study including traditional methods and evolutionary algorithms shows that the new parallel micro-CHC is able to achieve a high problem solving efficacy, outperforming previous results already reported for the problem and also having a good scalability behavior when solving high dimension problem instances. In addition, two variants of the scheduling problem in heterogeneous environments are also tackled, showing the versatility of the proposed approach using parallel evolutionary algorithms to deal with both dynamic and multiobjective scenarios.

Planificación de tareas en sistemas cluster, grid y cloud utilizando algoritmos evolutivos

Relevamiento de simuladores 3G-UMTS

Resolución en lınea del problema de viajes compartidos en taxis usando algoritmos evolutivos

Metaheuristics as soft computing techniques for efficient optimization

Solving a Ring Star Problem Generalization

2008 International Conference on Computational Intelligence for Modelling Control & Automation, 2008

The Capacitated m-Ring Star Problem (CmRSP) consists of finding a set of m rings, each of them in... more The Capacitated m-Ring Star Problem (CmRSP) consists of finding a set of m rings, each of them including the central depot, a subset of customers, and a set of optional nodes used to diminish the costs of the network design. The rings must be node-disjoint (except for the central depot) in order to provide node-survivability to the network. Customers that

A Parallel Multilevel Data Decomposition Algorithm for Orientation Estimation of Unmanned Aerial Vehicles

Communications in Computer and Information Science, 2014

Fast orientation estimation of unmanned aerial vehicles is important for maintain stable flight a... more Fast orientation estimation of unmanned aerial vehicles is important for maintain stable flight as well as to perform more complex task like obstacle avoidance, search, mapping, etc. The orientation estimation can be performed by means of the fusion of different sensors like accelerometers, gyroscopes and magnetometers, however magnetometers suffer from high distortion in indoor flights, therefore information from cameras can be used as a replacement. This article presents a multilevel decomposition method to process images sent from an unmanned aerial vehicle to a ground station composed by an heterogeneous set of desktop computers. The multilevel decomposition is performed using an alternative hierarchy called Master/Taskmaster/Slaves in order to minimize the network latency. Results shows that using this hierarchy the speed of traditional Master/Slave can be doubled.

An empirical time analysis of evolutionary algorithms as C programs

Software: Practice and Experience, 2013

This article presents an empirical study devoted to characterize the computational efficiency beh... more This article presents an empirical study devoted to characterize the computational efficiency behavior of an evolutionary algorithm (usually called canonical) as a C program. The study analyzes the effects of several implementation decisions on the execution time of the resulting evolutionary algorithm. The implementation decisions studied include: memory utilization (using dynamic vs. static variables and local vs. global variables), methods for ordering the population, code substitution mechanisms, and the routines for generating pseudorandom numbers within the evolutionary algorithm. The results obtained in the experimental analysis allow us to conclude that significant improvements in efficiency can be gained by applying simple guidelines to best program an evolutionary algorithm in C.

Granular physics in low-gravity environments using discrete element method

Monthly Notices of the Royal Astronomical Society, 2012

Granular materials of different sizes are present on the surface of several atmosphereless Solar ... more Granular materials of different sizes are present on the surface of several atmosphereless Solar system bodies. The phenomena related to granular materials have been studied in the framework of the discipline called granular physics, both experimentally and, over the last few decades, by numerical simulations. The discrete element method simulates the mechanical behaviour of a medium formed by a set of particles which interact through their contact points. The difficulty in reproducing vacuum and low-gravity environments makes numerical simulations the most promising technique in the study of granular media under these conditions. In this work, relevant processes in minor bodies of the Solar system are studied using the discrete element method. Results of simulations of size segregation in low-gravity environments in the cases of the asteroids Eros and Itokawa are presented. The segregation of particles with different densities was analysed, in particular, the case of comet P/Hartley 2. The surface shaking in these different gravity environments could produce the ejection of particles from the surface at very low relative velocities. The shaking causing the above processes is due to impacts and explosions such as the release of energy by the liberation of internal stresses or the re-accommodation of material. Simulations of the passage of impact-induced seismic waves through a granular medium were also performed. We present several applications of the discrete element methods for the study of the physical evolution of agglomerates of rocks under low-gravity environments.

Parallel multiobjective evolutionary algorithms for batch scheduling in heterogeneous computing and grid systems

Computational Optimization and Applications, 2013

This article presents six parallel multiobjective evolutionary algorithms applied to solve the sc... more This article presents six parallel multiobjective evolutionary algorithms applied to solve the scheduling problem in distributed heterogeneous computing and grid systems. The studied evolutionary algorithms follow an explicit multiobjective approach to tackle the simultaneous optimization of a system-related (i.e. makespan) and a user-related (i.e. flowtime) objectives. Parallel models of the proposed methods are developed in order to efficiently solve the problem. The experimental analysis demonstrates that the proposed evolutionary algorithms are able to efficiently compute accurate results when solving standard and new large problem instances. The best of the proposed methods outperforms both deterministic scheduling heuristics and single-objective evolutionary methods previously applied to the problem.

A hybrid GRASP and Tabu Search algorithm for the Capacitated m-Ring Star Problem

Historias de la Informática en América Latina y el Caribe: inicios, desarrollos y rupturas - (2015) Luis Germán Rodríguez Leal (Coordinador General) Raúl Carnota (Coordinador Temática)

by Luis German Rodriguez Leal, Márcia R Barros da Silva, Manuel Dávila Sguerra, Marcelo Savio, Marta Eunice Calderón Campos, S. Nesmachnow, and Marta Sananes

Los trabajos incluidos en esta publicación conforman una visión sobre lo acontecido en diversos p... more Los trabajos incluidos en esta publicación conforman una visión sobre lo acontecido en diversos países de América Latina y el Caribe durante el continuo proceso de incorporación de las tecnologías de la información y la comunicación (TIC) en sus respectivos contextos. Aquí están presentes las iniciativas y los conflictos técnicos, sociales y políticos, surgidos en el esfuerzo por alcanzar la apropiación de estas tecnologías de 23 países diferentes y, claro está, las personas e instituciones que, desde la Academia, las organizaciones de la sociedad civil, el sector público y las empresas privadas motorizaron aquellas iniciativas. Relatos testimoniales, documentos inéditos, investigaciones originales, enfoques heterodoxos, todo contribuye a que esta obra, en la que confluyen desde informáticos hasta historiadores, sea un verdadero acontecimiento en un campo moldeado habitualmente por la inmediatez de las innovaciones y el instantáneo olvido del pasado.