13th Conference of Open Innovations Association FRUCT
The main goal of this work is to present the developed research tool to find, investigate and analyze hidden dependences between parameters of the hardware/software platforms (such as influence of NUMA architecture, memory page size, etc) and the performance of block data processing algorithms. The new toolset (STAND) allows performance estimation and comparison of block data processing algorithms (for example, encryption/compression algorithms) running in kernel space. The primary application area of the developed technology and toolset is performance estimation and comparison of 'black box' libraries on particular hardware/software platform rather than research of mathematical or software implementation of algorithms. The main advantage of the presented toolset is that no source codes of algorithm implementation are needed (providing that an abstraction layer with known API is available). Linux operating system and computing nodes with ccNUMA architecture was selected as basic software/hardware platform. In this paper, the architecture of STAND is described. The methods for generating system load and comparison results for encryption algorithms AES (CBC), AES (CTR), and compression algorithms LZO, quicklz and bCodec are also presented.
The need for transmission and storage of large amounts of scientific data in the project space radio telescope ”Radioastron” required us to organize a reliable communication channel between the tracking station in Pushchino and treatment centers in Moscow. Network management data requires us to an integrated approach and covers the organization secure access to manage network devices, timely replacement of equipment and software upgrades, backups, as well as documentation of the network infrastructure. The reliability of the channel is highly dependent on continuous monitoring of network and server equipment and communication lines.
The publication contains materials of the conference dedicated scientific-technical problems in the field of Radioelectronics, telecommunications and computer engineering.
The publication is intended for researchers, engineers and graduate students.
This paper is devoted to the impact of ICT on the economy. Originally formulated ICT definition, consider the structure of the global ICT market. A comparison with the Russian market, we find the points of divergence and convergence trends.
Preface International conference “Data Analytics and Management in Data Intensive Domains” (DAMDID/RCDL’2015) of this year is held on October 13 – 16 in the town of Obninsk, Kaluga region of the Russian Federation. The conference is hosted by the Obninsk education Institute for Nuclear Power Engineering affiliated with the National Research University MEPhI. Obninsk is the first town of science created in USSR in which now many academic and research centers dealing with intensive data analysis in various fields (nuclear physics, modern medicine, oncology, radiology, geophysics, meteorology) are located. «Data Analytics and Management in Data Intensive Domains» conference (DAMDID) is planned as an interdisciplinary forum of researchers and practitioners from various domains of science and research promoting cooperation and exchange of ideas in the area of data analysis and management in data intensive domains. Approaches to data analysis and management being developed in specific data intensive domains of X-informatics (such as X = astro, bio, chemo, geo, medicine, neuro, physics, etc.), social sciences, as well as in various branches of informatics, industry, new technologies, finance and business are expected to contribute to the conference content. The program of the DAMDID/RCDL’2015 conference alongside with traditional data management topics reflects a rapid move into the direction of data science and data intensive analytics. Three conference keynotes form the pivot of the conference program. In the keynote of Peter Wittenburg (Max Planck Data and Compute Center) that opens the conference a survey of the current projects on development of data infrastructures enabling data intensive sciences is given. The second day of the conference is open by the keynote of David Pease (IBM Almaden Research Center). This talk considers objectives and experience of the recently organized IBM Research Lab specifically designed to facilitate complex analytic projects by tackling the challenges of data-intensive scientific discovery. Finally the program of the third day starts with the keynote by Michael Brodie (CSAIL Lab, MIT) in which the author gives analysis and characteristics of the data science as an emerging discipline for data intensive discovery. Three plenary sessions of the conference can be reckoned as the points of reference of the conference program pivot formed by the keynotes. These are: the invited session on IBM Cognitive Systems with Watson System solutions overview and Watson application examples, particularly in medicine; the panel prepared by the researchers from the eight scientific institutes of the RF devoted to the data access challenges for data intensive research in Russia; and the last session of the conference considering infrastructure solutions intended for support of scientific data and processes. More than 40 presentations at the scientific sessions at the twelve scientific sessions of the conference cover the problems of data heterogeneity and integration, information extraction from the multistructured data, subject domains modeling (including formation of knowledge bases in medicine), efficiency of computations, semantics of the large textual collections, as well as the specificity of the systems for data analysis (separate session is devoted to the problems of big data analysis in physics), approaches for data intensive problems solving. The majority of these presentations reflect the results of research made in the research institutes, centers and universities located at the different places on the territory of Russia, including: Briansk, Chernogolovka, Dubna, Irkutsk, Jaroslavl, Kazan, Moscow, Nizhny Novgorod, Novosibirsk, Obninsk, Omsk, Pereslavl Zalessky, Saint Petersburg, Tomsk, Chelyabinsk, Vladivostok. Besides that, the conference includes also several associated events, such as the tutorial on large-scale statistics with MonetDB and R (organized by Hannes Mühleisen (Amsterdam University); PhD Workshop that includes ten talks related to PhD researches and starts with the keynote by Michael Brodie (CSAIL Lab, MIT) entitled “A 21st Century Applied Computer Science PhD “; open workshop devoted to the social network data analysis. Special features of the conference DAMDID/RCDL’2015 organization (comparing to previous RCRDL conferences) include creation of a new site as well as transfer to the CMT system use. The chairs of the Program Committee and Organizing Committee of DAMDID/RCDL’2015 express their gratitude to Alexey Vovchenko for the development of the conference site and to Nikolay Skvortsov for the qualified application of the CMT at all stages of the conference preparation. The chairs of the Organizing Committee and Program Committee of DAMDID/RCDL’2015 express their gratitude to the authors of the submissions as well as to the Russian Foundation for Basic Research and the Department of Nanotechnologies and Information Technologies of the Russian Academy of Sciences for the support of the Conference. The Coordinating committee of the DAMDID/RCDL conferences thanks Director and employees of the Institute for Nuclear Power Engineering of the National Research Nuclear University MEPhI for their hard and responsible work on preparing and carrying out of the Conference as well as the members of the Program Committee for their important work on reviewing and selection of submissions. Co-chairs of the Program committee Co-chairs of the Organizing committee Leonid A. Kalinichenko Natalia G. Ayrapetova (IPI FRC CSC RAS) (INPE NRNU MEPhI) Sergey O. Starkov Victor N. Zakharov (INPE NRNU MEPhI) (IPI FRC CSC RAS)
The article suggests the integration of a neural network as a parallel element base in a telecommunication system. In this case, the ability to learn or adapt to external conditions is applied as the main advantage. For telecommunication systems in conditions when it is possible, this ability will improve noise immunity, reliability, operability, etc. The article considers an example of the integration of a neural network into a discrete matched signal filter. It is noted that the use of parallel mathematical methods in signal processing leads to the maximum effect of increasing the quality parameters of such telecommunication elements