Economical and Technical FPGA Design Analysis Based on Machine Learning

FPGA device manufacturers offer a wide variety of choices oriented toward different kinds of applications. Diverse FPGA parts, grouped into several devices and families, offer a wide range of hardware resource combinations. Some FPGA parts were created by manufacturers with the need for unique customs in mind (automotive industry, military applications, communication applications, etc.). However, when a small or medium-sized business or designer needs an FPGA part, they must select one of the many options from the manufacturer's catalog. On top of that, the device has to be available on the market, and costs should be taken into account. In order to provide criterion analysis that simplifies the selection of FPGA devices, machine learning techniques are employed in this paper to determine correlations among the numerous technical and economical FPGA features.