ASTRONOMICAL PLATES SPECTRA EXTRACTION OBJECTIVES AND POSSIBLE SOLUTIONS IMPLEMENTED ON DIGITIZED FIRST BYURAKAN SURVEY (DFBS) IMAGES

Astronomical images extraction process with usage of the Source Extractor (SE) tool is presented in this paper. The specificity of DFBS plates is that objects are presented in low-dispersion spectral form. It does not allow extraction tools to detect the objects exact coordinates and there is need of coordinates' correction. Apart thi

Dynamic voltage and frequency scaling for 3D Classical Spin Glass application

International audienceThe 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

Physics and Earth Science User Communities of Armenian National Grid Initiative

The main purpose of this article is to present the results and activities of physics and earth sciences heavy user communities of Armenian National Grid Initiative (ArmNGI) using computational or storage resources of Armenian National Grid infrastructure (ArmGrid)

Energy-efficient Assignment of Applications to Servers by Taking into Account the Influence of Processes on Each Other

Proceedings of: Third International Workshop on Sustainable Ultrascale Computing Systems (NESUS 2016). Sofia (Bulgaria), October, 6-7, 2016.The power consumption of data centers is becoming a crucial challenge in the context of the steadily increasing demand for computation. In this regard finding a way to improve energy efficiency of running applications in data centers is becoming a crucial trend. One method to improve the processor utilization is the consolidation of applications on physical servers. It is possible to run multiple jobs in parallel on the same machine, especially when their requirements regarding computation are smaller than the maximum processor performance. It reduces the number of servers in the data center required to handle multiple requests and therefore leads to energy usage reductions. In this paper, we introduce a realistic model of applications with deadlines executed in parallel on a server and competing for the shared resources and present an energy-aware algorithm which may be used to minimize the overall energy consumption of the servers.European Community's Seventh Framework ProgramThis work is partially supported by EU under the COST Program Action 1305: Network for Sustainable Ultrascale Computing (NESUS). The research presented in this paper is partially funded by a grant from Polish National Science Center under award number 2013/08/A/ST6/00296. This research was supported by the EU Seventh Framework Programme FP7/2007–2013 under grant agreement no. FP7-ICT-2013-10 (609757)

Strengthening Compute and Data intensive Capacities of Armenia

International audienceTraditionally, 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

Exascale machines require new programming paradigms and runtimes

Extreme scale parallel computing systems will have tens of thousands of optionally accelerator-equiped nodes with hundreds of cores each, as well as deep memory hierarchies and complex interconnect topologies. Such Exascale systems will provide hardware parallelism at multiple levels and will be energy constrained. Their extreme scale and the rapidly deteriorating reliablity of their hardware components means that Exascale systems will exhibit low mean-time-between-failure values. Furthermore, existing programming models already require heroic programming and optimisation efforts to achieve high efficiency on current supercomputers. Invariably, these efforts are platform-specific and non-portable. In this paper we will explore the shortcomings of existing programming models and runtime systems for large scale computing systems. We then propose and discuss important features of programming paradigms and runtime system to deal with large scale computing systems with a special focus on data-intensive applications and resilience. Finally, we also discuss code sustainability issues and propose several software metrics that are of paramount importance for code development for large scale computing systems

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

International audienceScientific 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

Weather Data Visualization and Analytical Platform

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

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

International audienceThe 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

On defining a web interface for linear algebra tasks over computational grids

International audienc