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61

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Introduction

## Publications

Publications (61)

Multidimensional multiextremal optimization problems and numerical methods for solving them are studied. The objective function is supposed to satisfy the Lipschitz condition with an a priori unknown constant, which is the only general assumption imposed on it. Problems of this type often arise in applications. Two dimensionality reduction approach...

In the present work, we considered multiextremal optimization problems and a high-performance parallel algorithm for solving these ones. The investigation of the algorithm scalability has been carried out on the problem class, in which the computation costs of the function value evaluations can be varied at different iteration points. The algorithm...

This paper proposes an efficient method for solving complex multicriterial optimization problems, for which the optimality criteria may be multiextremal and the calculations of the criteria values may be time-consuming. The approach involves reducing multicriterial problems to global optimization ones through minimax convolution of partial criteria...

This paper addresses computationally intensive global optimization problems, for solving of which the supercomputing systems with exaflops performance can be required. To overcome such computational complexity, the paper proposes the generalized parallel computational schemes, which may involve numerous efficient parallel algorithms of global optim...

In the present paper, an efficient parallel method for solving complex multicriterial optimization problems, which the optimality criteria can be multiextremal, and the computing of the criteria values can require a large amount of computations in, is proposed. The proposed approach is based on the reduction of the multicriterial problems to the gl...

The rise of computational science has facilitated rapid progress in many areas of science and technology over the last decade. There is a growing demand in computational scientists and engineers capable of efficient collaboration in interdisciplinary groups. Training such specialists includes courses on numerical analysis and parallel computing. In...

In the present paper, an efficient method is proposed for parallel solving of the multicriterial optimization problems with non-convex constraints, where the optimality criteria could be the multiextremal ones and computing the values of the criteria and constraints could require a large amount of computations. The developed approach is based on th...

In this paper, we describe the Globalizer software system for solving global optimization problems. The system implements an approach to solving the global optimization problems using the block multistage scheme of the dimension reduction, which combines the use of Peano curve type evolvents and the multistage reduction scheme. The scheme allows an...

This paper presents an efficient method for solving global optimization problems. The new method unlike previous methods, was developed, based on numerical estimations of derivative values. The effect of using numerical estimations of derivative values was studied and the results of computational experiments prove the potential of such approach.

In the present paper, a novel approach to the constructing of the test global optimization problems with non-convex constraints is considered. The proposed approach is featured by a capability to construct the sets of such problems for carrying out multiple computational experiments in order to obtain a reliable evaluation of the efficiency of the...

In this paper, we describe the Globalizer Lite software system for solving global optimization problems. This system implements an approach to solving global optimization problems applying a block multistage scheme of dimension reduction that combines the use of Peano curve type evolvents and a multistage reduction scheme. The scheme allows for an...

We describe in this article the optimization calculations of spray droplets in a gas injected through a nozzle into a work area, as a part of a research icing on model objects in a small-size climatic wind tunnel. Calculations were performed in a three-dimensional formulation. It is assumed that the drop has some speed, temperature and diameter as...

In the present paper, an efficient method for parallel solving the time-consuming multicriterial optimization problems, where the optimality criteria can be multiextremal, and the computation of the criteria values can require a large amount of computations, is proposed. The proposed scheme of parallel computations allows obtaining several efficien...

In this paper, we describe the Globalizer software system for solving global optimization problems. The system implements an approach to solving the global optimization problems using the block multistage scheme of the dimension reduction, which combines the use of Peano curve type evolvents and the multistage reduction scheme. The scheme allows an...

In this paper, an efficient approach for solving complex multicriterial optimization problems is proposed. For the problems being solved, the optimality criteria may be multiextremal ones, and calculating the criteria values may require a large amount of computations. The proposed approach is based on reducing multicriterial problems to nonlinear p...

Scientific data intensive applications requiring simultaneous use of large amounts of computing resources are becoming quite common. Properties of applications coming from different scientific domains as well as their requirements to the computing resources are varying largely. Many scientific communities have access to different types of computing...

High Energy Physics (HEP) experiments at the LHC collider at CERN were among the first scientific communities with very high computing requirements. Nowadays, researchers in other scientific domains are in need of similar computational power and storage capacity. Solution for the HEP experiments was found in the form of computational grid - distrib...

In this paper we consider the educational and research systems that can be used to estimate the efficiency of parallel computing. ParaLab allows parallel computation methods to be studies. With the ParaLib library, we can compare the parallel programming languages and technologies. The Globalizer Lab system is capable of estimating the efficiency o...

Selective measurements of the states are studied for a single quantum system, viz, a Josephson qubit, by a nonlinear oscillator operating in the mesoscopic regime in which the number of quanta during measurements is varied from a few dozen to several hundreds. The quantum Monte Carlo method is used to simulate the dissipative dynamics of the qubit–...

The work proposed an efficient method for solving computationally difficult multicriterial optimization problems, which are widely used to model complex optimal decision making problems. Under the suggested approach, it is assumed that partial criteria can be multi-extremal and computationally intense, and finding a solution to multicriterial probl...

This work considers a parallel algorithm for solving multidimensional multiextremal optimization problems. This algorithm uses Peano-type space filling curves for dimension reduction. Conditions of non-redundant parallelization of the algorithm are considered. Efficiency of the algorithm on modern computing systems with the use of graphics processi...

The paper contains the results of investigation of a parallel global optimization algorithm combined with a dimension reduction scheme. This allows solving multidimensional problems by means of reducing to data-independent subproblems with smaller dimension solved in parallel. The new element implemented in the research consists in using several gr...

This paper presents an optimized computer simulation of cavitation phenomena that occurs when a piston moves in a closed liquid-filled pipe. We have developed physical and mathematical models in a three-dimensional dynamic setting, found out a dependence of cavitation parameters on vibration parameters and constructed a domain of vibration influenc...

Educational course “Introduction to Parallel Computing” is discussed. A modern method of presentation of the educational materials for simultaneous teaching a large number of attendees (Massive Open Online Course, MOOC) has been applied. The educational course is delivered in the simplest form with a wide use of the presentational materials. Lectur...

This paper considers the problem of vehicle video detection and tracking. A solution based on the partitioning a video into blocks of equal length and detecting objects in the first and last frames of the block is proposed. Matching of vehicle locations in the first and last frames helps detect pairs of locations of the same object. Reconstruction...

This book constitutes the refereed workshop proceedings of the 16th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2016, held in Granada, Spain, in December 2016. The 30 full papers presented were carefully reviewed and selected from 58 submissions. They cover many dimensions of parallel algorithms and arch...

Numerical methods for global optimization of the multidimensional multiextremal functions in the framework of the approach oriented at dimensionality reduction by means of the nested optimization scheme are considered. This scheme reduces initial multidimensional problem to a set of univariate subproblems connected recursively. That enables to appl...

This paper presents an integrated approach to parallel solution of global optimization time-consuming problems. This approach is based on combining several schemes for reducing multidimensional optimization problems to one-dimensional ones. The schemes include using Peano space-filling curves and the recursive nested reduction technique. Finally, b...

Teaching supercomputing technologies is very important and complex task. A wide variety of computer systems and technologies complicate training process. Educational and research systems can help. We are presenting two such systems: ParaLab and ParaLib. User can select task from a predefined list. For a given method, and different initial condition...

Methods for solving the multidimensional multiextremal optimization problems using the nested optimization scheme are considered. A novel approach for solving the multidimensional multiextremal problems based on the adaptive nested optimization has been proposed. This approach enables to develop methods of the global optimum search which are more e...

The work considers a new parallel global search algorithm developed within the framework of the information-statistical approach to multiextremal optimization. The proposed algorithm is intended for maximum possible use of the potential of state-of-the-art high-performance computing systems, in particular, for solving the most computationally inten...

This work considers a parallel algorithm for solving multidimensional multiextremal optimization problems. The issue of implementation of the algorithm on state-of-the-art computing systems using Intel Xeon Phi coprocessor is considered. Speed up of the algorithm using Xeon Phi compared to using only CPU is experimentally confirmed. Computational e...

The scale of changes in the computing world dictates the need to introduce comparably major changes in the education system. Knowledge and skills with a strong foundation in parallelism concepts are becoming key qualities for any modern specialist. The situation cannot be changed by introducing just one training course; progress needs to be achieve...

The paper offers a unified approach to use of accelerators of various types by the example of parallel global search algorithms. In the developed general scheme, the implementation elements depending on specific types of accelerators are encapsulated in a limited number of procedures, which allows to largely reduce expenses and time for software de...

In this paper general methods of object recognition were reviewed. Method of localities was justified for solution of recognition of surface defects of cold-rolling sheets task. Features of defects were subtracted. Peculiar properties of using method of localities were reviewed. Algorithms of learning and recognition, results of experimental resear...

This work is concerned with the integration of the NSF/IEEE TCPP Curriculum Initiative on Parallel and Distributed Computing propositions into the curriculum for bachelors in Applied Mathematics and Informatics at the State University of Nizhni Novgorod (UNN). The article compares the NSF/IEEE TCPP Curriculum with the recommendations developed with...

In this paper the problems of multidimensional multiextremal optimization and parallel methods of their solution are considered. Only a general assumption is made regarding the optimizable function: the function is preset algorithmically (in the form of an algorithm of computation of values by input parameters) and satisfies the Lipschitz condition...

This paper presents the results of the development of a biomedical software system at the Nizhni Novgorod State University High Performance Computing Competence Center. We consider four main fields: plasma simulation, heart activity simulation, brain sensing simulation, molecular dynamics simulation. The software system is aimed at large-scale simu...

Описано практическое приложение информационно-статистического подхода к минимизации многоэкстремальных функций при невыпуклых ограничениях для решения задачи идентификации параметров моделей региональной экономики, разработанных в Вычислительном центре им. А.А. Дородницына РАН. В общем виде задача идентификации математической модели состоит в поиск...

Clusters became the de-facto standard in modern high-performance computing. At present it is rather often when a single organization
has a few clusters and wants to connect them into a multicluster to benefit from reduced task waiting time and increased total
available processing power. This paper studies one of possible approaches to the problem o...

In this paper we introduce a software system which allows to carry out and visualize computational experiments for studying and researching the parallel algorithms of solving complicated computational problems in imitation mode on one single sequential computer. User can “assemble” a parallel computational system of cluster type that consists of mu...

A new physico-mathematical model of the accelerated calculation of characteristics of deep sub-micron (≃100 nm) MOSFETs, which are being studied and used in modern microelectronics, is suggested. This model combines the advanced quasi-hydrodynamic description of high-field electron drift which is taken into account for thermo-diffusion component of...

This paper presents a new scheme for parallel computations on cluster systems for time consuming problems of globally optimal
decision making. This uniform scheme (without any centralized control processor) is based on the idea of multidimensional
problem reduction. Using same new multiple mappings (of the Peano curve type), a multidimensional prob...

This paper presents a new scheme for parallel computations on cluster systems for time-consuming problems of globally optimal decision making. This uniform scheme (without any centralized control processor) is based on the idea of multidimensional problem reduction. Using same new multiple mappings (of the Peano curve type), a multidimensional prob...

k+1 = G k (y 1 ; y 2 ; : : : ; y k ; z 1 ; z 2 ; : : : ; z k ); (2) where z i ; 1 i k, are the values of the function f(y) at the points y i , 1 i k. That is, when a new iteration point is selected the method uses function values calculated in previous iterations. It is important to note that reducing the number of iteration points taken into accou...

In this paper, sequential and parallel algorithms using derivatives for solving unconstrained one-dimensional global optimization problems are described. Sufficient conditions of convergence to all global minimizers are established for both methods. Parallel algorithm conditions, which guarantee significant speed up in comparison to the sequential...

In this paper we propose a new multi-dimensional method to solve unconstrained global optimization problems with Lipschitzian first derivatives. The method is based on a partition scheme that subdivides the search domain into a set of hypercubes in the course of optimization. This partitioning is regulated by the decision rule that provides evaluat...

A new algorithm for minimizing one-dimensional multiextremum functions whose first derivative satisfies the Lipschitz condition is proposed. The search for a global minimum is based on constructing minorants of the function to be minimized, taking into account values of the function and its first derivative calculated during the optimization. Suffi...

The system for multiextremal optimization (SYMOP) described here is a program package [7] oriented for using in the computer-aided design (CAD)_as some invariant software tool of making efficient design decisions. Besides, it is possible to use this system independently for solving various optimization problems and systems of nonlinear algebraic eq...

This paper deals with a new parallel method for solving one-dimensional global optimization problems. We present the formulation of the decision rules of this method, the conditions for its nonredundant parallelization, the generalization for solving multi-dimensional problems and its implementation on a transputer system. There is also an account...

1 Abstract In this paper a procedure for global optimisation is presented. The procedure combines on two methods, viz. the Multipoint Approximation based on Response Surface fitting (MARS) Method and a global optimisation method. The MARS method is based on the approximation concepts according to which the original minimization problem is replaced...

## Projects

Projects (5)

The goal of the project is the development of new methods and educational materials for HPC education.