Application of Neuro-networks Algorithms for Solution of Complex Problems of Discrete Optimization

Student: Murzova Anastasiya

Faculty: Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod)

Educational Programme: Business Informatics (Bachelor)

Year of Graduation: 2016

The kernel of the work under consideration is maximum clique identification in cases of big graphs (including 4000 vertexes). Special attention is devoted to exploration of optimization tools, means and optimization possibility in relation to existing hybrid network-based MCP-algorithms: Hopfield neural network combination and genetic algorithm (HNN-GA), Tabu Machine (TM). Architecture peculiarities of the algorithms, optimization levels (compiler optimization, optimized libraries, parallel algorithm design) were analyzed. On the basis of the investigated articles it was decided to focus on GPU feature exploration and applicability to the MCP-algorithms. As a result a new disturbed TM-architecture on multi-GPU system and GPU realization of parallel time-consuming operations were provided.

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