http://sedici.unlp.edu.ar:80/handle/10915/34499 2026-04-16T02:26:42Z 2026-04-16T02:26:42Z De Giusti, Armando Eduardo http://sedici.unlp.edu.ar:80/handle/10915/34524 2019-06-23T04:03:49Z 2013-12-01T00:00:00Z

Revision Journal of Computer Science & Technology; vol. 13, no. 3 The purpose of this book is to break down proven and mature cloud computing technologies and practices into a series of well-defined concepts, models, architectures and technology mechanisms.

2013-12-01T00:00:00Z The purpose of this book is to break down proven and mature cloud computing technologies and practices into a series of well-defined concepts, models, architectures and technology mechanisms. Méndez, Sandra http://sedici.unlp.edu.ar:80/handle/10915/34523 2019-06-23T04:03:42Z 2013-12-01T00:00:00Z

Revision Journal of Computer Science & Technology; vol. 13, no. 3 Extracting the performance characteristics of the different I/O configurations of the I/O system. These activities are independent. The characterization of application is done off-line and the application I/O model can be applied to analyze different target systems. The application I/O model is defined by three characteristics: metadata, spatial global pattern and temporal global pattern. The I/O model of the application is expressed by I/O phases, where an I/O phase is a repetitive sequence of same pattern on a file for a number of processes of the parallel application. A phase will be significant depending on data transferred that represent its <i>weight</i>.

2013-12-01T00:00:00Z Extracting the performance characteristics of the different I/O configurations of the I/O system. These activities are independent. The characterization of application is done off-line and the application I/O model can be applied to analyze different target systems. The application I/O model is defined by three characteristics: metadata, spatial global pattern and temporal global pattern. The I/O model of the application is expressed by I/O phases, where an I/O phase is a repetitive sequence of same pattern on a file for a number of processes of the parallel application. A phase will be significant depending on data transferred that represent its <i>weight</i>. Costa, André Luiz Lima da Souza, Josemar Rodrigues de http://sedici.unlp.edu.ar:80/handle/10915/34513 2019-06-23T04:03:47Z 2013-12-01T00:00:00Z

Articulo Journal of Computer Science & Technology; vol. 13, no. 3 Given the availability of computer clusters based on multi-core processors, the hybrid programming model has become an important ally of high-performance computing users in improving the performance of their parallel applications. However, creating hybrid applications is a complex task because it requires developers to be familiar with two distinct parallel programming models. Against this background, this article introduces APCM, an auto-parallelism computational model. APCM’s goal is to create hybrid parallel applications, i.e., OpenMP (memory programming) and a message-passing interface (MPI), from MPI applications. This goal is achieved in a simple, automated manner that is transparent for the user while increasing application performance. In the article’s conclusion, we present consistent results that attest the efficacy of the proposed model.

2013-12-01T00:00:00Z Given the availability of computer clusters based on multi-core processors, the hybrid programming model has become an important ally of high-performance computing users in improving the performance of their parallel applications. However, creating hybrid applications is a complex task because it requires developers to be familiar with two distinct parallel programming models. Against this background, this article introduces APCM, an auto-parallelism computational model. APCM’s goal is to create hybrid parallel applications, i.e., OpenMP (memory programming) and a message-passing interface (MPI), from MPI applications. This goal is achieved in a simple, automated manner that is transparent for the user while increasing application performance. In the article’s conclusion, we present consistent results that attest the efficacy of the proposed model. García Garino, Carlos Pacini, Elina Monge, David A. Careglio, Claudio Mirasso, Aníbal http://sedici.unlp.edu.ar:80/handle/10915/34512 2019-06-23T04:04:12Z 2013-12-01T00:00:00Z

Articulo Journal of Computer Science & Technology; vol. 13, no. 3 Cloud computing promises great opportunities for the execution of scienti c and engineering applications. However, the execution of such kind of applications over Cloud infrastructures requires the accomplishment of many complex processes. In this paper we present a Computational Mechanics Software as a Service (SaaS) project which will allow scientists to easily con gure and submit their experiments to be transparently executed on the Cloud. For this purpose, a nite element software called SOGDE is used to perform parametric studies of computational mechanics on the basis of underlying computing resources. Moreover, a web service provides an interface for the abovementioned functionalities allowing the remote execution of scienti c applications in a simple way.

2013-12-01T00:00:00Z Cloud computing promises great opportunities for the execution of scienti c and engineering applications. However, the execution of such kind of applications over Cloud infrastructures requires the accomplishment of many complex processes. In this paper we present a Computational Mechanics Software as a Service (SaaS) project which will allow scientists to easily con gure and submit their experiments to be transparently executed on the Cloud. For this purpose, a nite element software called SOGDE is used to perform parametric studies of computational mechanics on the basis of underlying computing resources. Moreover, a web service provides an interface for the abovementioned functionalities allowing the remote execution of scienti c applications in a simple way. Expósito, Roberto R. Taboada, Guillermo L. Pardo, Xoán C. Touriño, Juan Doallo, Ramón http://sedici.unlp.edu.ar:80/handle/10915/34511 2019-06-23T04:04:11Z 2013-12-01T00:00:00Z

Articulo Journal of Computer Science & Technology; vol. 13, no. 3 Amazon Web Services (AWS) is a well-known public Infrastructure-as-a-Service (IaaS) provider whose Elastic Computing Cloud (EC2) o ering includes some instances, known as cluster instances, aimed at High-Performance Computing (HPC) applications. In previous work, authors have shown that the scalability of HPC communication-intensive applications does not bene t from using higher computational power cluster instances as much as it could be expected. Cost analysis recommends using lower computational power cluster instances unless high memory requirements preclude their use. Moreover, it has been observed that scalability is very poor when more than one instance is used due to network virtualization overhead. Based on those results, this paper gives more insight into the performance of running scienti c applications on the Amazon EC2 platform evaluating ve (of which two have been recently released) of the higher computational power instances in terms of single instance performance, intra-VM (Virtual Machine) scalability and cost-e ciency. The evaluation has been carried out using both an HPC benchmark suite and a real High-Troughput Computing (HTC) application.

2013-12-01T00:00:00Z Amazon Web Services (AWS) is a well-known public Infrastructure-as-a-Service (IaaS) provider whose Elastic Computing Cloud (EC2) o ering includes some instances, known as cluster instances, aimed at High-Performance Computing (HPC) applications. In previous work, authors have shown that the scalability of HPC communication-intensive applications does not bene t from using higher computational power cluster instances as much as it could be expected. Cost analysis recommends using lower computational power cluster instances unless high memory requirements preclude their use. Moreover, it has been observed that scalability is very poor when more than one instance is used due to network virtualization overhead. Based on those results, this paper gives more insight into the performance of running scienti c applications on the Amazon EC2 platform evaluating ve (of which two have been recently released) of the higher computational power instances in terms of single instance performance, intra-VM (Virtual Machine) scalability and cost-e ciency. The evaluation has been carried out using both an HPC benchmark suite and a real High-Troughput Computing (HTC) application. Murazzo, María Antonia Rodríguez, Nelson R. Villafañe, Daniela A. González, Facundo http://sedici.unlp.edu.ar:80/handle/10915/34510 2019-06-23T04:03:58Z 2013-12-01T00:00:00Z

Articulo Journal of Computer Science & Technology; vol. 13, no. 3 Nowadays it is easy for the users who live in a digital era, to access social networks not only from their computers, but also from their mobile phones, to upload pictures instantaneously, to send messages on Whatsapp or to share their location with other users. At the same time, the business world is also changing at highspeed. Dematerialization has already affected different business sectors; it has even put an end to a model that has been used for years. Cloud Computing allows technology to access in the economy and society, not only allowing users to be connected to this new digital world through their mobile devices, but also to do it through any kind of device, which is commonly called Internet of Things. This will create a large amount of digital information which will need the storage and processing capacity of large volumes known as Big Data. The aim of this work is to determine the ideas of investigation to allow a proper analysis of large volumes of data which has been created to improve the efficiency and effectiveness of the decision making system.

2013-12-01T00:00:00Z Nowadays it is easy for the users who live in a digital era, to access social networks not only from their computers, but also from their mobile phones, to upload pictures instantaneously, to send messages on Whatsapp or to share their location with other users. At the same time, the business world is also changing at highspeed. Dematerialization has already affected different business sectors; it has even put an end to a model that has been used for years. Cloud Computing allows technology to access in the economy and society, not only allowing users to be connected to this new digital world through their mobile devices, but also to do it through any kind of device, which is commonly called Internet of Things. This will create a large amount of digital information which will need the storage and processing capacity of large volumes known as Big Data. The aim of this work is to determine the ideas of investigation to allow a proper analysis of large volumes of data which has been created to improve the efficiency and effectiveness of the decision making system. Rodríguez, Nelson R. Murazzo, María Antonia Chávez, Susana Beatriz Valenzuela, Francisca Adriana Martín, Adriana Elizabeth Villafañe, Daniela A. http://sedici.unlp.edu.ar:80/handle/10915/34509 2019-06-23T04:03:43Z 2013-12-01T00:00:00Z

Articulo Journal of Computer Science & Technology; vol. 13, no. 3 Mobile networking has changed people's lifestyles and the business world drastically. It can be widely implemented and with the ability to use this mobile computing, companies can increase their productivity greatly through this practice. Devices and mobile networks have limitations, such as battery life or processing speed, these further hinder the utilization of this method of work. Cloud Computing is an application that reduces the impact of the limitations that mobile computing presents. However, besides the characteristics of mobile computing as well as the technological advances, such as mobile TV or workplaces that implement BYOD, clearly differentiate even more Cloud Computing from traditional mobile computing. Due to the impact that this kind of computing brings to society one must rethink the solutions that developer propose while creating and developing of new applications for Mobile Cloud Computing.

2013-12-01T00:00:00Z Mobile networking has changed people's lifestyles and the business world drastically. It can be widely implemented and with the ability to use this mobile computing, companies can increase their productivity greatly through this practice. Devices and mobile networks have limitations, such as battery life or processing speed, these further hinder the utilization of this method of work. Cloud Computing is an application that reduces the impact of the limitations that mobile computing presents. However, besides the characteristics of mobile computing as well as the technological advances, such as mobile TV or workplaces that implement BYOD, clearly differentiate even more Cloud Computing from traditional mobile computing. Due to the impact that this kind of computing brings to society one must rethink the solutions that developer propose while creating and developing of new applications for Mobile Cloud Computing. Santos, Juan Enrique Gauzellino, Patricia Mercedes Savioli, Gabriela B. Martínez Corredor, Robiel http://sedici.unlp.edu.ar:80/handle/10915/34508 2020-07-03T20:58:15Z 2013-12-01T00:00:00Z

Articulo Journal of Computer Science & Technology; vol. 13, no. 3 This paper presents a collection of finite element procedures to model seismic wave propagation at the macroscale taking into account the effects caused by heterogeneities occuring at the mesoscale. For this purpose we first apply a set of compressibility and shear experiments to representative samples of the heterogeneous fluid saturated material. In turn these experiments yield the effective coefficients of an anisotropic macroscopic medium employed for numerical simulations at the macroscale. Numerical experiments illustrate the implementation of the proposed methodology to model wave propagation at the macroscale in a patchy brine-CO2 saturated porous medium containing a dense set of parallel fractures.

2013-12-01T00:00:00Z This paper presents a collection of finite element procedures to model seismic wave propagation at the macroscale taking into account the effects caused by heterogeneities occuring at the mesoscale. For this purpose we first apply a set of compressibility and shear experiments to representative samples of the heterogeneous fluid saturated material. In turn these experiments yield the effective coefficients of an anisotropic macroscopic medium employed for numerical simulations at the macroscale. Numerical experiments illustrate the implementation of the proposed methodology to model wave propagation at the macroscale in a patchy brine-CO2 saturated porous medium containing a dense set of parallel fractures. Balladini, Javier Muresano, Ronal Suppi, Remo Rexachs del Rosario, Dolores Luque Fadón, Emilio http://sedici.unlp.edu.ar:80/handle/10915/34507 2019-06-23T04:03:50Z 2013-12-01T00:00:00Z

Articulo Journal of Computer Science & Technology; vol. 13, no. 3 Over the last decade, the computing clusters have been updated in order to satisfy the increasing demand of greater computational power for running applications. However, this increasing is transformed in more system en- ergy consumption, which results in financial, environmental and in some cases with social consequences. Hence, the ideal is to achieve an scenario that allows the system admin- istrator to find a trade-off between time and energy-efficiency for parallel algorithms on virtualized environments. The main objective of this work is based on developing an analytical model to predict the energy consumption and energy delay product (EDP) for SPMD applications on virtual environments. The SPMD applications selected are designed through a message passing interface (MPI) library with high communication volumes, which can generate im- balance issues that affect seriously the execution time and also the energy-efficiency. Our method is composed by four phases (characterization, tile distribution model, mapping and scheduling). This method has been validated using scientific applications and we observe that the minimum Energy and EDP values are located close to the values calculated with our analytical model with an error rate between 4% and 9%.

2013-12-01T00:00:00Z Over the last decade, the computing clusters have been updated in order to satisfy the increasing demand of greater computational power for running applications. However, this increasing is transformed in more system en- ergy consumption, which results in financial, environmental and in some cases with social consequences. Hence, the ideal is to achieve an scenario that allows the system admin- istrator to find a trade-off between time and energy-efficiency for parallel algorithms on virtualized environments. The main objective of this work is based on developing an analytical model to predict the energy consumption and energy delay product (EDP) for SPMD applications on virtual environments. The SPMD applications selected are designed through a message passing interface (MPI) library with high communication volumes, which can generate im- balance issues that affect seriously the execution time and also the energy-efficiency. Our method is composed by four phases (characterization, tile distribution model, mapping and scheduling). This method has been validated using scientific applications and we observe that the minimum Energy and EDP values are located close to the values calculated with our analytical model with an error rate between 4% and 9%. Muresano, Ronal Wong, Alvaro Rexachs del Rosario, Dolores Luque Fadón, Emilio http://sedici.unlp.edu.ar:80/handle/10915/34505 2019-06-23T04:04:08Z 2013-12-01T00:00:00Z

Articulo Journal of Computer Science & Technology; vol. 13, no. 3 Progress in the parallel programming field has allowed scientific applications to be developed with more complexity and accuracy. However, such precision requires greater computational power in order to be executed. How- ever, updating the local systems could be considered an expensive decision. For this reason, cloud computing is emerging as a commercial infrastructure that allows us to eliminate maintaining the computing hardware. For this reason, cloud is promising to be a computing alternative to clusters, grids and supercomputing for executing these applications. In this sense, this work is focused on describing the manner of migrating our prediction tool PAS2P (parallel application signature for performance prediction), and how we have to analyze our method for executing SPMD ap- plications efficiently on these cloud environments. In both cases, cloud could be considered a huge challenge due to the environment virtualization and the communication heterogeneities, which can seriously affect the application performance. However, our experimental evaluations make it clear that our prediction tool can predict with an error rate lower than 6,46%, considering that the signature for prediction represents a small portion of the execution time. On the other hand, analyzing the application parameters over the cloud computing allows us to find through an analytical model, which is the ideal number of virtual cores needed to obtain the maximum speedup under a defined efficiency. In this case the error rate was lower that 9% for the application tested.

2013-12-01T00:00:00Z Progress in the parallel programming field has allowed scientific applications to be developed with more complexity and accuracy. However, such precision requires greater computational power in order to be executed. How- ever, updating the local systems could be considered an expensive decision. For this reason, cloud computing is emerging as a commercial infrastructure that allows us to eliminate maintaining the computing hardware. For this reason, cloud is promising to be a computing alternative to clusters, grids and supercomputing for executing these applications. In this sense, this work is focused on describing the manner of migrating our prediction tool PAS2P (parallel application signature for performance prediction), and how we have to analyze our method for executing SPMD ap- plications efficiently on these cloud environments. In both cases, cloud could be considered a huge challenge due to the environment virtualization and the communication heterogeneities, which can seriously affect the application performance. However, our experimental evaluations make it clear that our prediction tool can predict with an error rate lower than 6,46%, considering that the signature for prediction represents a small portion of the execution time. On the other hand, analyzing the application parameters over the cloud computing allows us to find through an analytical model, which is the ideal number of virtual cores needed to obtain the maximum speedup under a defined efficiency. In this case the error rate was lower that 9% for the application tested. Rodríguez, Christian Adrián Molinari, Lía Hebe Díaz, Francisco Javier http://sedici.unlp.edu.ar:80/handle/10915/34502 2019-06-23T04:03:53Z 2013-12-01T00:00:00Z

Articulo Journal of Computer Science & Technology; vol. 13, no. 3 The coexistence of multiple platforms and the implementation of different virtualization models makes server administration more complex every day. The undeniable benefits both methodologies offer in terms of performance optimization and energy saving can be overshadowed if clear guidelines are not established for configuration and maintenance in accordance with the needs of increasingly agile development models that demand quick responses. DevOps is a possible solution to this situation. However, it demands a new perspective in traditional roles within technology areas.

2013-12-01T00:00:00Z The coexistence of multiple platforms and the implementation of different virtualization models makes server administration more complex every day. The undeniable benefits both methodologies offer in terms of performance optimization and energy saving can be overshadowed if clear guidelines are not established for configuration and maintenance in accordance with the needs of increasingly agile development models that demand quick responses. DevOps is a possible solution to this situation. However, it demands a new perspective in traditional roles within technology areas. Barrionuevo, Mercedes Britos, Luis Bustos, Fabricio H. Gil Costa, Graciela Verónica Lopresti, Mariela Mancini, Virginia Miranda, Natalia Carolina Ochoa, César Piccoli, María Fabiana Printista, Alicia Marcela Reyes, Nora Susana http://sedici.unlp.edu.ar:80/handle/10915/34500 2019-06-23T04:04:01Z 2013-12-01T00:00:00Z

Articulo Journal of Computer Science & Technology; vol. 13, no. 3 With the technology advance and the growth of Internet, the information that can be found in this net, as well as the number of users that access to look for specific data is bigger. Therefore, it is desirable to have a search system that allows to retrieve information at a reasonable time and in an efficient way. In this paper we show two computing paradigms appropriate to apply in the treatment of large amounts of data consisting of objects such as images, text, sound and video, using hybrid computing over MPI+OpenMP and GPGPU. The proposal is developed through experience gained in the construction of various indexes and the subsequent search, through them, of multimedia objects.

2013-12-01T00:00:00Z With the technology advance and the growth of Internet, the information that can be found in this net, as well as the number of users that access to look for specific data is bigger. Therefore, it is desirable to have a search system that allows to retrieve information at a reasonable time and in an efficient way. In this paper we show two computing paradigms appropriate to apply in the treatment of large amounts of data consisting of objects such as images, text, sound and video, using hybrid computing over MPI+OpenMP and GPGPU. The proposal is developed through experience gained in the construction of various indexes and the subsequent search, through them, of multimedia objects.