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13 results on '"National Academy of Sciences of the Republic of Armenia (ARMENIA)"'

1. Data Quality Alerting Model for Big Data Analytics

Author

Eliza Gyulgyulyan, Hrachya Astsatryan, Franck Ravat, Julien Aligon, National Academy of Sciences of the Republic of Armenia [Yerevan] (NAS RA), Systèmes d’Informations Généralisées (IRIT-SIG), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), and National Academy of Sciences of the Republic of Armenia (ARMENIA)

Subjects
Swift, 050101 languages & linguistics, Computer science, Process (engineering), media_common.quotation_subject, Big data, Context (language use), 02 engineering and technology, Component (UML), 0202 electrical engineering, electronic engineering, information engineering, 0501 psychology and cognitive sciences, Quality (business), computer.programming_language, media_common, Big Data analytics, Point (typography), business.industry, 05 social sciences, Data quality, Recherche d'information, Data science, [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], 020201 artificial intelligence & image processing, business, computer, Quality model
Abstract

International audience; During Big Data analytics, correcting all the problems of large, heterogeneous and swift data, in a reasonable time, is a challenge and a costly process. Therefore, organizations are confronted with performing analysis on massive data, potentially of poor quality. This context is the starting point of our current research: how to identify data quality issues and how to notify users without solving these quality issues in advance? To this end, we propose a quality model, as the main component of an alert system, which allow to inform users about data quality issues, during their analysis. This paper discusses about the conceptual and implementation frameworks of the quality model, as well as examples of usage.

Published
2019

2. A New Information-Theoretical Distance Measure for Evaluating Community Detection Algorithms

Author

Josiane Mothe, Karen Mkhitaryan, Mariam Haroutunian, National Academy of Sciences of the Republic of Armenia [Yerevan] (NAS RA), Systèmes d’Informations Généralisées (IRIT-SIG), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Université Toulouse - Jean Jaurès (UT2J), Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), National Academy of Sciences of the Republic of Armenia (ARMENIA), Institut de Recherche en Informatique de Toulouse - IRIT (Toulouse, France), and Institut National Polytechnique de Toulouse - INPT (FRANCE)

Subjects
Community detection, Evaluation measure, Electronic computers. Computer science, [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], Recherche d'information, QA75.5-76.95, evaluation mea, f-divergences
Abstract

International audience; Community detection is a research area from network science dealing withthe investigation of complex networks such as social or biological networks, aimingto identify subgroups (communities) of entities (nodes) thatare more closely relatedto each other inside the community than with the remaining entities in the network.Various community detection algorithms have been developed and used in the literaturehowever evaluating community structures that have been automatically detected isa challenging task due to varying results in different scenarios.Current evaluationmeasures that compare extracted community structures with the reference structure orground truth suffer from various drawbacks; some of them having beenpoint out in theliterature. Information theoretic measures form a fundamental classin this domain andhave recently received increasing interest. However even the well employed measures(NVI and NID) also share some limitations, particularly they are biased toward thenumber of communities in the network. The main contribution ofthis paper is tointroduce a new measure that overcomes this limitation while holding the importantproperties of measures. We review the mathematical properties of our measure based on¿2divergence inspired fromf-divergence measures in information theory. Theoreticalproperties as well as experimental results in various scenarios show the superiority of theproposed measure to evaluate community detection over the ones from the literature.

Published
2019

3. f-Divergence Measures for Evaluation in Community Detection

Author

Haroutunian, Mariam, Mkhitaryan, Karen, Mothe, Josiane, Institute for Informatics and Automation Problems, NAS of Armenia, Systèmes d’Informations Généralisées (IRIT-SIG), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Université Toulouse - Jean Jaurès (UT2J), Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), National Academy of Sciences of the Republic of Armenia (ARMENIA), and Institut National Polytechnique de Toulouse - INPT (FRANCE)

Subjects
Théorie de l'information, Information theory, Community detection, [INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT], f-divergence distance measures
Abstract

International audience; Community detection is a research area from network science dealing with the investigation of complex networks such as biological, social and computer networks, aiming to identify subgroups (communities) of entities (nodes) that are more closely related to each other than with remaining entities in the network [1]. Various community detection algorithms are used in the literature however the evaluation of their derived community structure is a challenging task due to varying results on different networks. In searching good community detection algorithms diverse comparison measures are used actively [2]. Information theoretic measures form a fundamental class in this discipline and have recently received increasing interest [3]. In this paper we first mention the usual evaluation measures used for community detection evaluation We then review the properties of f -divergence measures and propose the ones that can serve community detection evaluation. Preliminary experiments show the advantage of these measures in the case of large number of communities.

Published
2018

4. Working set size estimation techniques in virtualized environments: One size does not fit all

Author

AstsatryanHrachya, HagimontDaniel, NituVlad, KocharyanAram, TchanaAlain, YayaHannas, Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), National Academy of Sciences of the Republic of Armenia (ARMENIA), and Institute for Informatics and Automation Problems - IIAP (Yerevan, Armenie)

Subjects
Software_OPERATINGSYSTEMS, Computer Networks and Communications, Computer science, Distributed computing, Système d'exploitation, Réseaux et télécommunications, Cloud computing, 02 engineering and technology, computer.software_genre, Architectures Matérielles, Virtualization, 0202 electrical engineering, electronic engineering, information engineering, Computer Science (miscellaneous), Resource management, Safety, Risk, Reliability and Quality, Energy consumption optimization, business.industry, Working set size, 020207 software engineering, Energy consumption, Systèmes embarqués, 020202 computer hardware & architecture, Hardware and Architecture, Virtual machine, business, computer
Abstract

Energy consumption is a primary concern for datacenters? management. Numerous datacenters are relying on virtualization, as it provides flexible resource management means such as virtual machine (VM) checkpoint/restart, migration and consolidation. However, one of the main hindrances to server consolidation is physical memory. In nowadays cloud, memory is generally statically allocated to VMs and wasted if not used. Techniques (such as ballooning) were introduced for dynamically reclaiming memory from VMs, such that only the needed memory is provisioned to each VM. However, the challenge is to precisely monitor the needed memory, i.e., the working set of each VM. In this paper, we thoroughly review the main techniques that were proposed for monitoring the working set of VMs. Additionally, we have implemented the main techniques in the Xen hypervisor and we have defined different metrics in order to evaluate their efficiency. Based on the evaluation results, we propose Badis, a system which combines several of the existing solutions, using the right solution at the right time. We also propose a consolidation extension which leverages Badis in order to pack the VMs based on the working set size and not the booked memory. The implementation of all techniques, our proposed system, and the benchmarks we have used are publicly available in order to support further research in this domain.

Published
2018

5. Weather Data Visualization and Analytical Platform

Author

Hrachya Astsatryan, Julien Aligon, Rita Abrahamyan, Anush Hakobyan, Hayk Grogoryan, Zarmandukht Petrosyan, Wahi Narsisian, Vladimir Sahakyan, Eliza Gyulgyulyan, Aram Kocharyan, Yuri Shoukourian, Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - INPT (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), National Academy of Sciences of the Republic of Armenia (ARMENIA), Armstatehydromet (ARMENIA), Institut de Recherche en Informatique de Toulouse - IRIT (Toulouse, France), Université Toulouse III - Paul Sabatier - UPS (FRANCE), Institute for Informatics and Automation Problems - IIAP (Yerevan, Armenie), and Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)

Subjects
Service (systems architecture), Web-based visualization, Observational data, 010504 meteorology & atmospheric sciences, General Computer Science, Computer science, Numerical weather prediction, 02 engineering and technology, 01 natural sciences, Satellite image processing, 0202 electrical engineering, electronic engineering, information engineering, Hydrometeorology, Relative humidity, Interactive visualization, Physics::Atmospheric and Oceanic Physics, 0105 earth and related environmental sciences, Remote sensing, OLAP, Online analytical processing, Visualization, Weather data, 13. Climate action, Base de données, 020201 artificial intelligence & image processing
Abstract

This article aims to present a web-based interactive visualization and analytical platform for weather data in Armenia by integrating the three existing infrastructures for observational data, numerical weather prediction, and satellite image processing. The weather data used in the platform consists of near-surface atmospheric elements including air temperature, pressure, relative humidity, wind and precipitation. The visualization and analytical platform has been implemented for 2-m surface temperature. The platform gives Armenian State Hydrometeorological and Monitoring Service analytical capabilities to analyze the in-situ observations, model and satellite image data per station and region for a given period.

Published
2018
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6. Community detection: Comparison of state of the art algorithms

Author

Josiane Mothe, Mariam Haroutunian, Karen Mkhitaryan, Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), National Academy of Sciences of the Republic of Armenia (ARMENIA), Systèmes d’Informations Généralisées (IRIT-SIG), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Université Toulouse - Jean Jaurès (UT2J), Institute for Informatics and Automation Problems, NAS of Armenia, and Institut National Polytechnique de Toulouse - INPT (FRANCE)

Subjects
Théorie de l'information, Community detection, Network science, Approximation algorithm, Recherche d'information, 02 engineering and technology, Stochastic block mode, Complex network, 01 natural sciences, Task (project management), [INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT], Stochastic block model, [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], 020204 information systems, 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, State (computer science), 010306 general physics, Cluster analysis, Social network analysis, Algorithm
Abstract

International audience; Real world complex networks may contain hidden structures called communities or groups. They are composed of nodes being tightly connected within those groups and weakly connected between them. Detecting communities has numerous applications in different sciences such as biology, social network analysis, economics and computer science. Since there is no universally accepted definition of community, it is a complicated task to distinguish community detection algorithms as each of them use a different approach, resulting in different outcomes. Thus large number of articles are devoted to investigating community detection algorithms, implementation on both real world and artificial data sets and development of evaluation measures. In this article several state of the art algorithms and evaluation measures are studied which are used in clustering and community detection literature. The main focus of this article is to survey recent work and evaluate them using artificially generated networks.

Published
2017

7. SaaS for Energy Efficient Utilization of HPC Resources of Linear Algebra Calculations

Author

Georges Da Costa, Wahi Narsisian, Hrachya Astsatryan, Institute for Informatics and Automation Problems, NAS of Armenia, Système d’exploitation, systèmes répartis, de l’intergiciel à l’architecture (IRIT-SEPIA), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Université Toulouse III - Paul Sabatier (UT3), Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), National Academy of Sciences of the Republic of Armenia (ARMENIA), and Institut National Polytechnique de Toulouse - INPT (FRANCE)

Subjects
[INFO.INFO-AR]Computer Science [cs]/Hardware Architecture [cs.AR], Service (systems architecture), General Computer Science, Computer science, Real-time computing, Système d'exploitation, Réseaux et télécommunications, Cloud computing, 7. Clean energy, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], Architectures Matérielles, Cloud service, DVFS, Linear algebra, Energy efficient utilization, business.industry, Software as a service, Supercomputer, Systèmes embarqués, Energy accounting, Reliability engineering, HPC, Alternative energy, [INFO.INFO-ES]Computer Science [cs]/Embedded Systems, [INFO.INFO-OS]Computer Science [cs]/Operating Systems [cs.OS], business, Energy (signal processing), Efficient energy use
Abstract

International audience; The most important factor of High performance computing (HPC) systems nowadays is to limit or decrease the power consumption while preserving a high utilization. And with the availability of alternative energy, which powers such systems, there is a need to maximize the usage of alternative energy over brown power. For now, the usage of alternative energy is varying in time due to different factors such as sunny days, the wind, etc. and it is crucial to have an energy-aware algorithm to maximize the usage of this energy. In this paper a SaaS service is presented to optimize a usage of alternative energy, to reduce the power consumption and to preserve a best possible percentage of resource utilization.

Published
2017

8. Energy Optimization Methodology for e-Infrastructure Providers

Author

Astsatryan, Hrachya, Narsisian, Wahi, Kocharyan, Aram, Da Costa, Georges, Hankel, Albert, Oleksiak, Ariel, Institute for Informatics and Automation Problems, NAS of Armenia, Système d’exploitation, systèmes répartis, de l’intergiciel à l’architecture (IRIT-SEPIA), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Université Toulouse III - Paul Sabatier (UT3), SURFnet (Utrecht, Pays-Bas), SURFnet (NETHERLANDS), Poznan Supercomputing and Networking Center (PSNC), Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - INPT (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), National Academy of Sciences of the Republic of Armenia (ARMENIA), Poznan Supercomputing and Networking Center - PSNC (POLAND), and Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)

Subjects
[INFO.INFO-AR]Computer Science [cs]/Hardware Architecture [cs.AR], Système d'exploitation, Réseaux et télécommunications, Systèmes embarqués, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], Architectures Matérielles, Green ICT, Virtualization, Nesus, E-infrastructure, [INFO.INFO-ES]Computer Science [cs]/Embedded Systems, DVFS, [INFO.INFO-OS]Computer Science [cs]/Operating Systems [cs.OS], Energy optimisation, Memory ballooning
Abstract

International audience; The environmental protection is a dominant concern for all types of industries, organizations, and governments. In this regard, the reduction of the energy consumption is substantial in bringing down the CO2 gas emission, which is considered as an important factor causing global warming. The e-infrastructure service providers, such as National Research and Education Networks or National Grid Initiatives have crucial role in the context of energy awareness because the energy consumption of the networking, data, and computational infrastructures keeps increasing exponentially over the time. In addition to this, scientific gateways and cloud services are becoming more significant to tackle scientific and societal challenges. Therefore, there is a need to provide robust and reliable services taking into account energy consumption aspect of e-infrastructures. The aim of the article is to introduce an energy optimization methodology for the beneficiaries of the e-infrastructures to explore, optimize, and report the energy consumption and CO2 emission of data, computing, and networking facilities. The suggested methodology has been implemented within the Armenian e-infrastructure aiming at the reduction of the energy consumption and thereby the CO2 emission.

Published
2017

9. Strengthening compute and data intensive capacities of Armenia

Author

Hrachya Astsatryan, Jack Dongarra, Yuri Shoukourian, Vladimir Sahakyan, Per Öster, Pierre-Henri Cros, Michel Daydé, Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - INPT (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), National Academy of Sciences of the Republic of Armenia (ARMENIA), CSC - IT Center for Science (FINLAND), University of Tennessee - UT (USA), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), National Academy of Sciences of the Republic of Armenia [Yerevan] (NAS RA), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées, Algorithmes Parallèles et Optimisation (IRIT-APO), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Institut National Polytechnique (Toulouse) (Toulouse INP), The University of Tennessee [Knoxville], and IT Center for Science [Espoo] (CSC)

Subjects
Big Data, Economic growth, Decision support system, Computer science, media_common.quotation_subject, Big data, ArmNGI, Armenina, 02 engineering and technology, Computer security, computer.software_genre, The Republic, State (polity), 0202 electrical engineering, electronic engineering, information engineering, E-infrastructures, media_common, Government, Armenian, business.industry, Information technology, 021001 nanoscience & nanotechnology, language.human_language, Calcul parallèle, distribué et partagé, Informatics, HPC, language, Position (finance), ASNET-AM, 020201 artificial intelligence & image processing, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], 0210 nano-technology, business, computer
Abstract

International audience; Traditionally, Armenia has had a leading position within the computer science and Information Technology sectors in the South Caucasus region and beyond. Information Technology (IT) is also one of the fastest growing industries of the Armenian economy [1]. In 2000, the Government of Armenia recognized the IT sector as the primary constituent of the country's economic progress. Armenia is, more than ever, in need of cutting-edge and relevant e-infrastructures and e-services to tackle today's societal and scientific challenges. The Institute for Informatics and Automation Problems (IIAP) of the National Academy of Sciences of the Republic of Armenia (NAS RA) [2] is the only state supported structure for software, hardware, and brainware technologies in Armenia. The institute is responsible for Armenia's National research and education network (Academic Scientific Research Computer Network of Armenia, ASNET-AM) [3] and the National Grid Initiative (ArmNGI) [4], and provides computational and networking facilities and advanced services to users. The main objective of this article is to highlight key activities that will spur Armenia to strengthen its scientific computing capacity thanks to the analysis made of the current trends of e-Infrastructures in Europe and the USA.

Published
2015
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10. Dynamic voltage and frequency scaling for 3D Classical Spin Glass application

Author

Tom Gurout, Hakob Abajyan, Hrachya Astsatryan, Georges Da Costa, Wahi Narsisian, Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), National Academy of Sciences of the Republic of Armenia (ARMENIA), Institut National Polytechnique de Toulouse - INPT (FRANCE), Institute for Informatics and Automation Problems, NAS of Armenia, Système d’exploitation, systèmes répartis, de l’intergiciel à l’architecture (IRIT-SEPIA), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, and Université Toulouse III - Paul Sabatier (UT3)

Subjects
[INFO.INFO-AR]Computer Science [cs]/Hardware Architecture [cs.AR], Engineering, Spin glass, Système d'exploitation, Réseaux et télécommunications, Context (language use), 7. Clean energy, 01 natural sciences, 010305 fluids & plasmas, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], Architectures Matérielles, 0103 physical sciences, Electronic engineering, DVFS, 010306 general physics, Frequency scaling, business.industry, Mode (statistics), Energy consumption, Spin-chains, Supercomputer, Systèmes embarqués, Energy efficiency, Embedded system, HPC, [INFO.INFO-ES]Computer Science [cs]/Embedded Systems, [INFO.INFO-OS]Computer Science [cs]/Operating Systems [cs.OS], business, Voltage, Efficient energy use, 3D
Abstract

International audience; The power consumption of large-scale high performance computing (HPC) systems is becoming a crucial challenge in the context of increasing the performance regardless of energy consumption [1]. Therefore, finding ways to improve energy efficiency has become a main issue for HPC applications. Dynamic voltage and frequency scaling (DVFS) is a widely used and powerful technique for reducing energy consumption in modern processors. The present paper investigates energy efficiency of 3D Classical Spin Glass [2], [3] application using the performance, ondemand and powersave modes of DVFS method. The series of experiments show that the execution time of OnDemand and PowerSave is the same, while the OnDemand mode is better due to the power consumption and frequency balance for the system.

Published
2015

11. On the Easy Use of Scientific Computing Services for Large Scale Linear Algebra and Parallel Decision Making with the P-Grade Portal

Author

Ronan Guivarch, Michel Daydé, Hrachya Astsatryan, Harutyun Terzyan, Levon Hovhannisyan, Yuri Shoukouryan, Vladimir Sahakyan, Aurélie Hurault, Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), National Academy of Sciences of the Republic of Armenia (ARMENIA), State Engineering University of Armenia - SEUA (ARMENIA), Institute for Informatics and Automation Problems, NAS of Armenia, Algorithmes Parallèles et Optimisation (IRIT-APO), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Institut National Polytechnique (Toulouse) (Toulouse INP), Assistance à la Certification d’Applications DIstribuées et Embarquées (IRIT-ACADIE), Institut de recherche en informatique de Toulouse ( IRIT ), Institut National Polytechnique [Toulouse] ( INP ) -Université Toulouse 1 Capitole ( UT1 ) -Université Toulouse 2 ( UT2 ) -Université Paul Sabatier - Toulouse 3 ( UPS ) -Centre National de la Recherche Scientifique ( CNRS ), Institut National Polytechnique de Toulouse - INPT (FRANCE), Université Toulouse III - Paul Sabatier - UPS (FRANCE), Institute for Informatics and Automation Problems - IIAP (Yerevan, Armenie), and Institut de Recherche en Informatique de Toulouse - IRIT (Toulouse, France)

Subjects
Computer Networks and Communications, Iterative method, Computer science, Interface (computing), Distributed computing, Parallel Decision Making, Cloud computing, 010103 numerical & computational mathematics, 02 engineering and technology, computer.software_genre, 01 natural sciences, Computational science, [ INFO.INFO-DC ] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], 0202 electrical engineering, electronic engineering, information engineering, 0101 mathematics, Advanced Trading, Block (data storage), Sparse Linear Algebra Solvers, business.industry, P-grade Portal, Grid, Calcul parallèle, distribué et partagé, Grid computing, Hardware and Architecture, Linear algebra, 020201 artificial intelligence & image processing, Single sign-on, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], business, computer, Software, Information Systems
Abstract

International audience; Scientific research is becoming increasingly dependent on the large-scale analysis of data using distributed computing infrastructures (Grid, cloud, GPU, etc.). Scientific computing (Petitet et al. 1999) aims at constructing mathematical models and numerical solution techniques for solving problems arising in science and engineering. In this paper, we describe the services of an integrated portal based on the P-Grade (Parallel Grid Run-time and Application Development Environment) portal (http://www.p-grade.hu) that enables the solution of large-scale linear systems of equations using direct solvers, makes easier the use of parallel block iterative algorithm and provides an interface for parallel decision making algorithms. The ultimate goal is to develop a single sign on integrated multi-service environment providing an easy access to different kind of mathematical calculations and algorithms to be performed on hybrid distributed computing infrastructures combining the benefits of large clusters, Grid or cloud, when needed.

Published
2013

12. A Multi-User and Multi-Purpose CA Simulator

Author

Jean-Pierre Jessel, Suren S. Poghosyan, Hayk E. Nahapetyan, Yuri Shoukourian, Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), National Academy of Sciences of the Republic of Armenia (ARMENIA), Real Expression Artificial Life (IRIT-REVA), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, and Institut National Polytechnique de Toulouse - INPT (FRANCE)

Subjects
Multi-user, Computer science, Distributed computing, Work support, [INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE], Solid modeling, Public network, C#, 01 natural sciences, 010305 fluids & plasmas, 0103 physical sciences, ASM, Génie logiciel, 010306 general physics, Visualization, CA, Abelian sandpile model, Modélisation et simulation, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Cellular automaton, Automaton, Net, Simulation
Abstract

International audience; In this paper, a software package for cellular automata simulation, 2D/3D visualization with a shared work support system was introduced, that was designed considering the needs of researchers in both local and virtual laboratories. As an example of cellular automata, abelian sandpile model has been chosen. An appropriate software package has been developed using Microsoft .Net and C# enabling users to work at the same time on the same models independent of the geographical location of users within the public network.

13. Search for photon-linelike signatures from dark matter annihilations with H.E.S.S.

Author

Abramowski A, Acero F, Aharonian F, Akhperjanian AG, Anton G, Balenderan S, Balzer A, Barnacka A, Becherini Y, Becker Tjus J, Bernlöhr K, Birsin E, Biteau J, Bochow A, Boisson C, Bolmont J, Bordas P, Brucker J, Brun F, Brun P, Bulik T, Carrigan S, Casanova S, Cerruti M, Chadwick PM, Chaves RC, Cheesebrough A, Colafrancesco S, Cologna G, Conrad J, Couturier C, Dalton M, Daniel MK, Davids ID, Degrange B, Deil C, deWilt P, Dickinson HJ, Djannati-Ataï A, Domainko W, Drury LO, Dubus G, Dutson K, Dyks J, Dyrda M, Egberts K, Eger P, Espigat P, Fallon L, Farnier C, Fegan S, Feinstein F, Fernandes MV, Fernandez D, Fiasson A, Fontaine G, Förster A, Füßling M, Gajdus M, Gallant YA, Garrigoux T, Gast H, Giebels B, Glicenstein JF, Glück B, Göring D, Grondin MH, Häffner S, Hague JD, Hahn J, Hampf D, Harris J, Heinz S, Heinzelmann G, Henri G, Hermann G, Hillert A, Hinton JA, Hofmann W, Hofverberg P, Holler M, Horns D, Jacholkowska A, Jahn C, Jamrozy M, Jung I, Kastendieck MA, Katarzyński K, Katz U, Kaufmann S, Khélifi B, Klepser S, Klochkov D, Kluźniak W, Kneiske T, Komin N, Kosack K, Kossakowski R, Krayzel F, Krüger PP, Laffon H, Lamanna G, Lefaucheur J, Lemoine-Goumard M, Lenain JP, Lennarz D, Lohse T, Lopatin A, Lu CC, Marandon V, Marcowith A, Masbou J, Maurin G, Maxted N, Mayer M, McComb TJ, Medina MC, Méhault J, Menzler U, Moderski R, Mohamed M, Moulin E, Naumann CL, Naumann-Godo M, de Naurois M, Nedbal D, Nekrassov D, Nguyen N, Niemiec J, Nolan SJ, Ohm S, de Oña Wilhelmi E, Opitz B, Ostrowski M, Oya I, Panter M, Parsons RD, Paz Arribas M, Pekeur NW, Pelletier G, Perez J, Petrucci PO, Peyaud B, Pita S, Pühlhofer G, Punch M, Quirrenbach A, Raue M, Reimer A, Reimer O, Renaud M, de Los Reyes R, Rieger F, Ripken J, Rob L, Rosier-Lees S, Rowell G, Rudak B, Rulten CB, Sahakian V, Sanchez DA, Santangelo A, Schlickeiser R, Schulz A, Schwanke U, Schwarzburg S, Schwemmer S, Sheidaei F, Skilton JL, Sol H, Spengler G, Stawarz L, Steenkamp R, Stegmann C, Stinzing F, Stycz K, Sushch I, Szostek A, Tavernet JP, Terrier R, Tluczykont M, Trichard C, Valerius K, van Eldik C, Vasileiadis G, Venter C, Viana A, Vincent P, Völk HJ, Volpe F, Vorobiov S, Vorster M, Wagner SJ, Ward M, White R, Wierzcholska A, Wouters D, Zacharias M, Zajczyk A, Zdziarski AA, Zech A, and Zechlin HS

Abstract

Gamma-ray line signatures can be expected in the very-high-energy (E(γ)>100 GeV) domain due to self-annihilation or decay of dark matter (DM) particles in space. Such a signal would be readily distinguishable from astrophysical γ-ray sources that in most cases produce continuous spectra that span over several orders of magnitude in energy. Using data collected with the H.E.S.S. γ-ray instrument, upper limits on linelike emission are obtained in the energy range between ∼ 500 GeV and ∼ 25 TeV for the central part of the Milky Way halo and for extragalactic observations, complementing recent limits obtained with the Fermi-LAT instrument at lower energies. No statistically significant signal could be found. For monochromatic γ-ray line emission, flux limits of (2 × 10(-7) -2 × 10(-5)) m(-2) s(-1) sr(-1) and (1 × 10(-8) -2 × 10(-6)) m(-2) s(-1)sr(-1) are obtained for the central part of the Milky Way halo and extragalactic observations, respectively. For a DM particle mass of 1 TeV, limits on the velocity-averaged DM annihilation cross section ⟨σv⟩(χχ → γγ) reach ∼ 10(-27) cm(3)s(-1), based on the Einasto parametrization of the Galactic DM halo density profile.

Published
2013
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