Analysis of the prospects of using the FPGA platform for the implementation of machine learning algorithms for the purpose of high-speed processing of information from the video stream

The article addresses the prospects of using the FPGA platform for the implementation of machine learning algorithms for the purpose of high-speed processing of information from a video stream. The authors substantiate the relevance and significance of the research topic. A brief justification of the role and significance of the development of the FPGA platform for the implementation of machine learning algorithms is given. It is stated that at present the FPGA is on average more productive in general tasks than a special-purpose processor. When the processor performance is insufficient and there are no ready-made circuits to solve the problem, FPGAs are used. Especially when it comes to 100-percent guaranteed processing and guaranteed latency. Unlike a powerful processor, a powerful FPGA does not require additional memory, consumes less energy and can be implemented in a compact device. FPGA is more productive, but less flexible in terms of implementing some tasks. At the same time, the scope of the technology is quite wide. The analysis of the scientific literature allowed us to conclude about its effectiveness in various fields