Public welfare organization management system based on FPGA and deep learning

Public welfare organization system Promoting social support is one of the government's influence relieving benevolent associations. To qualify as exempt organizations, community or government support, the association exercises should simply replace the network edge, welfare organization is conducive to select another person, and every person should be registering for details. The social ground considered as network partner to the exercise of social, government support element in any case, despite all the affiliation, if the network is advantageous. Costs associated social modernization typically does not include support groups. Long-term support will be used to understand the impact of decisions and related efforts in the political mission exercises. So, the government's social support groups altruistic relationship. A Field-Programmable Gate Array (FPGA), and a Graphics Processing Unit (GPU) to improve the throughput of the cellular neural network. Rather, Field Programmable Gate Array (FPGA) accelerating the depth learning network is not just one reason, but also because of its ability in energy efficiency, the maximum parallelism. In this article, we review recent prior art deeply accelerated learning networks in the FPGA. We stress the importance of using a variety of techniques to improve the acceleration performance of important features. We also offer suggestions for improving the use of FPGA accelerated cellular neural networks. In this paper, research methods represent FPGA-based accelerator's recent trends in depth learning networks. Therefore, this review is expected to be useful in depth study researchers' direct and efficient hardware accelerator future development.