Організація нечіткого логічного виведення на основі багаторівневого паралелізму

In this paper, a method for constructing hierarchical systems of fuzzy inference based on multilevel parallelism, in particular, second-level parallelism, is developed, theoretically substantiated and implemented. This approach is designed to accelerate the computation of hierarchical fuzzy systems...

Повний опис

Збережено в:
Бібліографічні деталі
Дата:2018
Автор: Ponomarenko, Roman M.
Формат: Стаття
Мова:rus
Опубліковано: The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 2018
Теми:
Онлайн доступ:http://journal.iasa.kpi.ua/article/view/150221
Теги: Додати тег
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Назва журналу:System research and information technologies

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System research and information technologies
Опис
Резюме:In this paper, a method for constructing hierarchical systems of fuzzy inference based on multilevel parallelism, in particular, second-level parallelism, is developed, theoretically substantiated and implemented. This approach is designed to accelerate the computation of hierarchical fuzzy systems having complex dependency graphs between blocks of fuzzy rules. The concept of multilevel parallelism is formulated and presented. The notion of the level of parallelism is introduced. The theorem is formulated and proved, and a method for theoretical estimation of the maximum possible acceleration for systems constructed on the basis of parallelism of the level n is developed. An approach to designing hierarchical fuzzy systems based on multilevel parallelism for NVIDIA graphics accelerators is developed. Using NVIDIA CUDA technology, an experimental software system was designed for hierarchical systems of fuzzy inference based on multilevel parallelism for systems having complex graphs of dependencies between blocks of fuzzy rules. Experimental estimates of the acceleration are obtained. Also, based on the developed method, theoretical estimates of the maximum possible acceleration are found. A comparative characteristic of the theoretical and experimental estimates of the acceleration of hierarchical fuzzy systems is given.