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.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability