Analysis of Nonlinear Dynamic System Based on Parallel Computing with Using Several Methods
Annotatsiya
While recent computing advances have come close to reaching the theoretical limits of performance, they are still unable to effectively handle the challenges of controlling nonlinear dynamic systems, continuously analyzing massive amounts of data, and putting complex artificial intelligence functions into practice. As a result, a fresh viewpoint on information processing has surfaced, influenced by the effective systems seen in nature. In particular, the brain is a paradigm for super-efficient biological neurocomputing because of its billions of neuron-processors that are globally networked while having slow individual processor speeds. This paradigm shift highlights the main path for technological advancement as incorporating ideas from natural information processing processes into technical systems. The development of parallel computing techniques in research computing is examined in this work, with an emphasis on how these techniques might be used to solve dynamic complex systems.