Classification of difference-iterative algorithms

This article presents a general classification of difference-iterative algorithms (DIA) which are increasingly being used in microprocessor control systems for industrial, scientific, and technical objects. The classification is based on taking into account the features of the DIA structures (the method of organizing convergence, the order of generating the next increments of iterated quantities, cascading and interaction of several DIA, etc.). The objective of the presented DIA classification is to give microprocessor algorithmic software developers an orientation when choosing known algorithms and prospects when developing new DIA for a specific purpose.

Application of intelligent technologies for modeling of controlled switching systems

The development of instrumental and methodological support for modeling nonlinear control systems with switching is an urgent problem. Various modifications of numerical optimization methods and artificial intelligence technologies are used to solve this problem. The purpose of this article is to develop algorithmic software for modeling controlled switching systems based on the use of intelligent technologies and numerical optimization methods. Algorithmic software for the synthesis of feedback controls using a PID controller is developed. Intelligent technologies for modeling controlled switching systems are characterized. An algorithm using global parametric optimization methods is proposed for tuning the PID controller. Models of nonlinear dynamic switching systems are studied. An algorithm for finding optimal trajectories based on neural network automata is proposed. The basis for further research is developed, in which it is planned to create a software implementation of the switching algorithm and the neural network algorithm. The practical significance of the results is that the developed algorithmic software will allow analyzing the influence of various parameters on the quality and speed of functioning of intelligent control switching systems. The obtained results can be used in various problems of modeling and global optimization of controlled systems: technical systems with switching modes of operation, transport systems, as well as in problems of neural network modeling and machine learning.

Mathematical model and algorithm for solving the problem of planning the operation of multiphase systems with heterogeneous resources and time limits

The object of this research is the modern service and production systems, the specific functioning of which lies in a set of sequential and parallel operations with a random duration. A fundamental peculiarity of such systems is the stochastic nature of the duration of a single operation, which depends not only on the external random factors, but also on the choice of resources, and namely on the operator. This substantiates the parallel solution of the task on making a schedule of mutually dependent operations and the task on assigning the operators. In the conditions of resource and time limits, this task is NP difficult and requires the development of algorithms for developing the solution that is close to optimal in the limited time. For the development of mathematical and algorithmic software to solve this task, the author used the critical path method and PERT method, incident wave method, and methods for solving the assignment tasks. As a result, the author acquired a mathematical model that considers the stochastic nature of the duration of a single operation, which depends not only on random factors, but also on the operators. Based on such model, is formulated the optimization task that allows finding the launch time and the corresponding operators to gain the most profit. Based on the analysis of existing approaches and the specificity of the task at hand, the author proposes the algorithm for solving the task founded on successive refinement of the time characteristics of operations.

On improving the efficiency of mathematical modeling of the problem of stability of construction

Algorithmic software for mathematical modeling of structural stability is considered, which is reduced to solving a partial generalized eigenvalues problem of sparse matrices, with automatic parallelization of calculations on modern parallel computers with graphics processors. Peculiarities of realization of parallel algorithms for different structures of sparse matrices are presented. The times of solving the problem of stability of composite materialsusing a three-dimensional model of "finite size fibers" on computers of different architectures are given. In mathematical modeling of physical and technical processes in many cases there is a need to solve problems of algebraic problem of eigenvalues (APVZ) with sparse matrices of large volumes. In particular, such problems arise in the analysis of the strength of structures in civil and industrial construction, aircraft construction, electric welding, etc. The solving to these problems is to determine the eigenvalues and eigenvectors of sparse matrices of different structure. The efficiency of solving these problems largely depends on the effectiveness of mathematical modeling of the problem as a whole. Continuous growth of task parameters, calculation of more complete models of objects and processes on computers require an increase in computer productivity. High-performance computing requirements are far ahead of traditional parallel computing, even with multicore processors. High-performance computing requirements are far ahead of traditional parallel computing, even with multicore processors. Today, this problem is solved by using powerful supercomputers of hybrid architecture, such as computers with multicore processors (CPUs) and graphics processors (GPUs), which combine MIMD and SIMD architectures. But the potential of high-performance computers can be used to the fullest only with algorithmic software that takes into account both the properties of the task and the features of the hybrid architecture. Complicating the architecture of modern high-performance supercomputers of hybrid architecture, which are actively used for mathematical modeling (increasing the number of computer processors and cores, different types of computer memory, different programming technologies, etc.) means a significant complication of efficient use of these resources in creating parallel algorithms and programs. here are problems with the creation of algorithmic software with automatic execution of stages of work, which are associated with the efficient use of computing resources, ways to store and process sparse matrices, analysis of the reliability of computer results. This makes it possible to significantly increase the efficiency of mathematical modeling of practical problems on modern high-performance computers, as well as free users from the problems of parallelization of complex problems. he developed algorithmic software automatically implements all stages of parallel computing and processing of sparse matrices on a hybrid computer. It was used at the Institute of Mechanics named after S.P. Tymoshenko NAS of Ukraine in modeling the strength problems of composite material. A significant improvement in the time characteristics of mathematical modeling was obtained. Problems of mathematical modeling of the properties of composite materials has an important role in designing the processes of deformation and destruction of products in various subject areas. Algorithmic software for mathematical modeling of structural stability is considered, which is reduced to solving a partial generalized problem of eigen values of sparse matrices of different structure of large orders, with automatic parallelization of calculations on modern parallel computers with graphics processors. The main methodological principles and features of implementation of parallel algorithms for different structures of sparse matrices are presented, which ensure effective implementation of multilevel parallelism of a hybrid system and reduce data exchange time during the computational process. As an example of these approaches, a hybrid algorithm of the iteration method in subspace for tape and block-diagonal matrices with a frame for computers of hybrid architecture is given. Peculiarities of data decomposition for matrices of profile structure at realization of parallel algorithms are considered. The proposed approach provides automatic determination of the required topology of the hybrid computer and the optimal amount of resources for the organization of an efficient computational process. The results of testing the developed algorithmic software for problems from the collection of the University of Florida, as well as the times of solving the problem of stability of composite materials using a three-dimensional model of "finite size fibers" on computers of different architectures. The results show a significant improvement in the time characteristics of solving problems.

Viral Fictions: Navigating Time in Search of Memorial Markers for the Radio-Toxic Landscape of La Hague

Nuclear events have inscribed the 20th century into a new chemical temporality, that generally escapes our scrutiny due to radioactivity’s invisibility. Radioactive particles keep falling back to earth since nuclear tests peaked during the Cold War, they form an iterative invisible presence that is coated in political invisibility. Through films and fictions, the paper traces haunted images that keep coming back. Two distinct geographies are weaved together, that of West Coast American deserts, where numerous tests were conducted, and that of the nuclear peninsula of La Hague, in France. The recurring metaphors of dust and mist, not only characterise the two landscapes, but illustrate how radioactive particles literally journey and affect natural environments and activate the trope of contamination. Viral Fictions address the issue of creating a nuclear marker for La Hague’s burial site. Underlying the fragility of material cultures and the aporia of projecting knowledge through deep time, the article creates a possible im- material fictional nuclear marker for La Hague. Merging a set of references from local folk oral legends with the ability of fiction to transmit forms of knowledge and imaginary archetypes, Viral Fictions uses AI algorithmic software to generate speculative forms of fictions and visuals.

THREE-DIMENSIONAL FORWARD AND INVERSE MODELLING OF MULTI-HEIGHT MAGNETIC DATA USING THE RELIEF MAPS

We have developed the high-performance software and algorithmic software for solving the direct and inverse problems of modeling and inversion of spatially distributed magnetic, taking into account the relief. We show the results of solving the inverse problem of magnetic survey taking into account the relief for synthetic noisy data.