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Authors

Bobkov V.

Degree
Dr of Technique, Head of computer graphics laboratory of Institute of Automation and Control Processes of Far Eastern Branch of Russian Academy of Sciences
E-mail
bobkov@iacp.dvo.ru
Location
Vladivostok
Articles

Spatial data processing and visualization using hybrid computing cluster

The paper presents the analysis of features of programming graphical applications for processing and visualization of large amounts of data with high-performance hybrid computing cluster systems. Considered hybrid architecture of computing cluster, allow to implement of parallelism using CUDA and MPI at three levels: the cluster nodes, multicore and GPU video cards. The approach is proposed to organization of hybrid parallelism estimated its effectiveness by implementing of software complex of visualization synoptic data using hybrid cluster.
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Using population algorithms to optimize the temperature regime of roasting phosphorite pellets

The problem of rational energy resource use is especially acute for energy- intensive industries, which include high-temperature processing of mining chemical raw materials (for example, the production of phosphorite pellets from apatite-nepheline ore waste by drying and roasting). In this regard, the temperature modes of roasting conveyor machine should ensure not only the completion of the ongoing chemical-technological processes and the required product quality, but also energy and resource saving. Thus, there is an urgent scientific and practical task of optimizing charge heating modes based on the results of modeling heat and mass transfer processes occurring in various zones of the roasting conveyor machine. The impossibility of carrying out expensive full-scale experiments leads to the need to use computer simulation methods. Nonlinearity, large dimension of the search space, high computational complexity make it difficult to use traditional deterministic search methods. Under these conditions, the stochastic methods that deliberately introduce an element of randomness into the search algorithm show good results. Today, population algorithms based on modeling the collective behavior of living organisms and characterized by the ability to simultaneously process several options have become widespread. To solve the optimization problem, it is proposed to use a modified Cuckoo search algorithm (by introducing fuzzy elements), which provides a comprehensive account of a huge number of parameters set for each vacuum chamber of the roasting conveyor machine. The control of the chemical-energy-technological system for the processing of apatite-nepheline ores waste, taking into account the obtained data and based on the existing neural network model of the high-temperature process, will make it possible to minimize the amount of return and provide energy-saving conditions for the operation of roasting units. Read more...