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## Building web-based services for practical exercises in parallel and distributed computing

The paper presents an approach to the design and implementation of web-based environments for practical exercises in parallel and distributed computing (PDC). The presented approach introduces minimal development and operational costs by relying on Everest, a general-purpose platform for building computational web services. The flexibility of proposed service-oriented architecture enables the development of different types of services targeting various use cases and PDC topics. The generic execution services support the execution of different types of parallel and distributed programs on corresponding computing systems, while the assignment evaluation services implement the execution and evaluation of solutions to programming assignments. As was demonstrated by teaching two introductory PDC courses, the presented approach helps to enhance students’ practical experience while avoiding low-level interfaces, reducing the grading time and providing a level of automation necessary for scaling the course to a large number of students. In contrast to other efforts, the exploited Platform as a Service model provides the ability to quickly reuse this approach by other PDC educators without installation of the Everest platform.

This chapter describes an economic model for independent job flow management in distributed computing environments with non-dedicated resources. The model is based on the concept of fair resource distribution between users and owners of computational nodes by means of economic mechanisms in a virtual organization. Scheduling is performed in cycles in accordance with dynamically updated schedules on local processor nodes. Schedule optimization is performed using dynamic programming methods using the set of criteria in accordance with the economic policy of the virtual organization.

This book constitutes the proceedings of the 12th International Conference on Parallel Computing Technologies, PaCT 2013, held in St. Petersburg, Russia, during September 30-October 4, 2013. The 41 full papers presented together with 2 invited papers were carefully reviewed and selected from 83 submissions. The papers are organized in topical sections on all technological aspects of the applications of parallel computer systems High level parallel programming languages and systems, methods and tools for parallel solution of large-scale problems, languages, environments and software tools supporting parallel processing, operating systems, scheduling, mapping, load balancing, general architectural concepts, cellular automata, performance measurement and analysis tools, teaching parallel processing, software for grid and cloud computing, scalable computing, fragmentation and aggregation of algorithms and programs as well as programs assembling and reuse.

This chapter describes an economic model for independent job flow management in distributed computing environments with non-dedicated resources. The model is based on the concept of fair resource distribution between users and owners of computational nodes by means of economic mechanisms in a virtual organization. Scheduling is performed in cycles in accordance with dynamically updated schedules on local processor nodes. Schedule optimization is performed using dynamic programming methods using the set of criteria in accordance with the economic policy of the virtual organization.

This work presents slot selection algorithms in economic models for independent job batch scheduling in distributed computing with non-dedicated resources. Existing approaches towards resource co-allocation and multiprocessor job scheduling in economic models of distributed computing are based on search of time-slots in resource occupancy schedules. The sought time-slots must match requirements of necessary span, computational resource properties, and cost. Usually such scheduling methods consider only suited variant of time-slot set. This work discloses a scheduling scheme that features multi-variant search. Two algorithms of linear complexity for search of alternative variants are proposed and compared. Having several optional resource configurations for each job makes an opportunity to perform an optimization of execution of the whole batch of jobs and to increase overall efficiency of scheduling.

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'.

In this work, we present slot selection algorithms for job batch scheduling in distributed computing with non-dedicated resources. Jobs are parallel applications and these applications are independent. Existing approaches towards resource co-allocation and parallel job scheduling in economic models of distributed computing are based on search of time-slots in resource occupancy schedules. The sought time-slots must match requirements of necessary span, computational resource properties, and cost. Usually such scheduling methods consider only one suited variant of time-slot set. This work discloses a scheduling scheme that features multi-variant search. Two algorithms of linear complexity for search of alternative variants are proposed. Having several optional resource configurations for each job makes an opportunity to perform an optimization of execution of the whole batch of jobs and to increase overall efficiency of scheduling.

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.

A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.

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

The geographic information system (GIS) is based on the first and only Russian Imperial Census of 1897 and the First All-Union Census of the Soviet Union of 1926. The GIS features vector data (shapefiles) of allprovinces of the two states. For the 1897 census, there is information about linguistic, religious, and social estate groups. The part based on the 1926 census features nationality. Both shapefiles include information on gender, rural and urban population. The GIS allows for producing any necessary maps for individual studies of the period which require the administrative boundaries and demographic information.

It is well-known that the class of sets that can be computed by polynomial size circuits is equal to the class of sets that are polynomial time reducible to a sparse set. It is widely believed, but unfortunately up to now unproven, that there are sets in EXPNP, or even in EXP that are not computable by polynomial size circuits and hence are not reducible to a sparse set. In this paper we study this question in a more restricted setting: what is the computational complexity of sparse sets that are *selfreducible*? It follows from earlier work of Lozano and Torán (in: Mathematical systems theory, 1991) that EXPNP does not have sparse selfreducible hard sets. We define a natural version of selfreduction, tree-selfreducibility, and show that NEXP does not have sparse tree-selfreducible hard sets. We also construct an oracle relative to which all of EXP is reducible to a sparse tree-selfreducible set. These lower bounds are corollaries of more general results about the computational complexity of sparse sets that are selfreducible, and can be interpreted as super-polynomial circuit lower bounds for NEXP.