Center for Teach-in Nanomaterials and Memristor Systems

Center for Teach-in Nanomaterials and Memristor Systems

Director: Vadim Filippov, PhD

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The staff of the center are working on a new class of strategic information technologies, exercising the development of artificial cognitive systems to meet the challenges of processing the semantics of texts, sounds, and images as well as knowledge synthesis. The center hopes to meet the challenges of creating technical objects, but also in the field of robotic management based on the already-formed universal corticomorphic neural network architectures (Universal artificial cortex). 


Areas of activity

  • Creation of a software for neurogenetic networks development, the dynamic models of complex objects and artificial cognitive systems

  • Creation of basic corticomorfic architectures, cortical columns, and the cerebral cortex models

  • Creation of management technologies for large and very large biomorphic artificial neural networks formation and development – cyber genomics  

  • Creation of artificial cognitive systems for functioning on the Internet

  • Creation of artificial cognitive decision supporting systems for complex technical systems managing

  • Creation of semantic neural network systems for machine translation

  • Creation of neural network systems for analyzing data sets, forecasting and stock exchange trading support

  • Creation of autonomous robots’ neuromorphic systems


Significant results

We have developed a software complex "TASO-NEUROKONSTRUKTOR" intended to develop architectures of artificial neural networks and the dynamic models of complex objects for artificial cognitive systems building. This solves the problem of data analysis, technical systems management, among others.


The software package provides:

  • Creation and support of artificial biomorphic neural networks operation with the number of elements (som, dendrites, axons ) more than 200 million units per reference 8-core processor-based node of Intel Xeon E5450 (Harpertown) 3.0 GHz type or the like;

  • Processing speed in the neural network with 5 million artificial synapses per second on[1] 1 GHz clock speed of available processors;

  • Creation and usage of complex biomorphic models of neurons with backward and forward linkages, including the phases of memory formation in neurons modeling necessary for an artificial neuron to perform its role of a basic element for the construction of cognitive systems;

  • Usage of cyber genomics technology to manage the artificial neural networks creation and development;

  • Fault-tolerant parallel development environment for neural networks and complex systems with the implementation of a distributed multiprocess system on a T-Blade cluster-type with MPI and hybrid system integrating MPI and OpenMP technologies;

  • Scalable software capacity by increasing the number of computing nodes.