Alexander Sysoyev

N. I. Lobachevsky State University of Nizhny Novgorod · Institute of Information Technology, Mathematics and Mechanics

The paper considers a time-efficient implementation of the k nearest neighbours (kNN) algorithm. A well-known approach for accelerating the kNN algorithm is to utilise dimensionality reduction methods based on the use of space-filling curves. In this paper, we take this approach further and propose an algorithm that employs multiple space-filling c...

One of the most effective ways to enhance students’ learning in programming disciplines is carrying out practical assignments covering all key topics on their own. Ideally, a student deals with an individual set of tasks. While the relevance of such an approach is self-evident, its practical implementation is no easy matter. The main difficulty enc...

In order to evaluate efficiency of some global optimization method or compare efficiency of different methods, it is necessary to select a set of test problems, define comparison measures, and, finally, choose a way of visual presentation of the computational results. In this paper, a wide set of test optimization problems is considered including a...

The paper proposes a method for solving computationally time-consuming multidimensional global optimization problems. The developed method combines the use of a nested dimensional reduction scheme and numerical estimates of the objective function derivatives. Derivatives significantly reduce the cost of solving global optimization problems, however...

Modern applied science is becoming increasingly interdisciplinary, creating a priority demand for highly qualified scientists and engineers capable of generating new ideas and transferring advanced scientific developments to the industry. Often, breakthrough results arise at the interface of sciences as a result of the coordinated work of specialis...

Recently, the number of machine learning based water demand forecasting solutions has been significantly increasing. Different case studies have already reported practical results proving that accurate forecasts may support optimization of operations in Water Distribution Networks (WDN). However, tuning the hyper-parameters of machine leaning algor...

Modern applied science is becoming increasingly interdisciplinary, creating a priority demand for highly qualified scientists and engineers capable of generating new ideas and transferring advanced scientific developments to the industry. Often, breakthrough results arise at the interface of sciences as a result of the coordinated work of specialis...

In the present work, further development of an approach to constructing test global optimization problems with nonlinear constraints is considered. In the generated problems, the location of the global minimum is known. The considered generator is featured by an option of specifying desired number of constraints and the fraction of feasible domain...

Training specialists capable of applying models, methods, technologies and tools of parallel computing to solve problems is of great importance for further progress in many areas of modern science and technology. Qualitative training of such engineers requires the development of appropriate curriculum, largely focused on practice. In this paper, we...

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 this paper, we describe the Globalizer software system for solving the global optimization problems. The system is designed to maximize the use of computational potential of the modern high-performance computational systems in order to solve the most time-consuming optimization problems. The highly parallel computations are facilitated using var...

The Multiscale Modelling and Simulation approach is a powerful methodological way to identify sub-models and classify their interaction. The execution order and interaction of computational modules are described in the form of workflow. This workflow can be executed as a single HPC cluster job if there is a middleware which schedule modules executi...

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 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, 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...

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 describes an algorithm for solving multidimensional multiextremal optimization problems. This algorithm uses Peano-type space-filling curves for dimension reduction. It has been used for solving problems at GENeralization-based contest in global OPTimization (GENOPT). Computational experiments are carried out on 1800 multidimensional pro...

In this work we present our experience of optimization for Intel Xeon and Intel Xeon Phi. Calculation of fair prices of the set of European options is considered as the basic task. We have chosen this task for the following reasons. First, this task is traditionally used as a benchmark for checking of capabilities of new architectures. Second, it i...

This paper discusses parallelization of the computationally intensive numerical factorization phase of sparse Cholesky factorization on shared memory systems. We propose and compare two parallel algorithms based on the multifrontal method. Both algorithms are implemented in a task-based fashion employing dynamic load balance. The first algorithm as...

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...