Многомашинные комплексы и многопроцессорные системы
The manual sets out the requirements of science and industry, leading to use of multicomputer systems and multiprocessor systems, which inevitably use the principle of parallel computing, background and state of the art, describes the main approaches to the organization of multiprocessor computer systems, development of parallel algorithms for the numerical solution of problems and parallel programming techniques.
Now we have the need for methodics of teaching the topic "parallel computing" in secondary school. The paper presents a three-year experience of the author in this field: a methodical approach, the selection of materials, the business games, experience of tasks on parallel computing at the contest "TRIZformashka", classes of tasks, examples of tasks, program executors, texts for propaedeutic textbook on informatics.
The book contains selected papers that were presented on PhD Summer schools on Scientific Computing jointly organized by Waterford Institute of Technology, Lomonosov Moscow State University, Kyiv National Taras Shevchenko University, Saint-Petersburg State University and Nanjing University of Technology. The schoold were mainly organized in teleconference mode and linked researchers and PhD students from several countries.
The problems of identifying latent parallelism in the algorithm by explicitly max (the construction of stacked-parallel form of the algorithm graph) and implicit (the method of streaming - DATA-FLOW - calculations), the development of parallel programs in the MPI-paradigm programming and quantitative research strength calculations for the acceleration parallelization on the parameters of a multiprocessor system and the quality of parallel programs. The manual is practical and can be used by students to prepare for the performance of laboratory and practice of the works, of course and diploma projects. Generated by network applications ra-operability in a multiprocessor environment, architecture MPP (Massively Par-allel Processing); particularly on Linux-cluster computing IT department MGUPI 4. Before working to understand whole con-SPECT lectures on 'Parallel Computing'.
The research subject is the computational complexity of the probabilistic neural network (PNN) in the pattern recognition problem for large model databases. We examined the following methods of increasing the efficiency of a neuralnetwork classifier: a parallel multithread realization, reducing the PNN to a criterion with testing of homogeneity of feature histograms of input and reference images, approximate nearestneighbor analyses (BestBin First, directed enumeration methods). The approach was tested in facialrecognition experiments with FERET dataset.
Students' internet usage attracts the attention of many researchers in different countries. Differences in internet penetration in diverse countries lead us to ask about the interaction of medium and culture in this process. In this paper we present an analysis based on a sample of 825 students from 18 Russian universities and discuss findings on particularities of students' ICT usage. On the background of the findings of the study, based on data collected in 2008-2009 year during a project "A сross-cultural study of the new learning culture formation in Germany and Russia", we discuss the problem of plagiarism in Russia, the availability of ICT features in Russian universities and an evaluation of the attractiveness of different categories of ICT usage and gender specifics in the use of ICT.
In this paper we consider choice problems under the assumption that the preferences of the decision maker are expressed in the form of a parametric partial weak order without assuming the existence of any value function. We investigate both the sensitivity (stability) of each non-dominated solution with respect to the changes of parameters of this order, and the sensitivity of the set of non-dominated solutions as a whole to similar changes. We show that this type of sensitivity analysis can be performed by employing techniques of linear programming.