A significant role in Artificial Intelligence (AI) and Machine Learning (ML) tools in the recent development of intelligent systems. AI solutions to the many other areas, such as a different field of health care, the regional aircraft and vehicles, security, marketing, customer analysis and other significant changes. One of the major challenges hindering the potential of AI is high-performance computing resources on demand. Recently, the hardware accelerator to provide the required computing power of AI and ML tool development. In the literature, a hardware accelerator to accelerate the computationally intensive tasks built using FPGA. The accelerator provides high-performance hardware, while maintaining the required accuracy. In this work, proposed that the focus of AI and ML exploration tools available hardware accelerator, a systematic review of the literature. The results showed that, compared to the proof hardware implementation based on software implemented significant performance improvements due to the parallel operation similar precision, and using an optimization technique designed to exploit the target system device mapping. In addition, to achieve our FPGA-based neural network system to support its future use for other applications.
