An FPGA implementation for neural networks with the FDFM processor core approach

Abstract

This paper presents a field programmable gate array (FPGA) implementation of a three-layer perceptron using the few DSP blocks and few block RAMs (FDFM) approach implemented in the Xilinx Virtex-6 family FPGA. In the FDFM approach, multiple processor cores with few DSP slices and few block RAMs are used. We have implemented 150 processor cores for perceptrons in a Xilinx Virtex-6 family FPGA XC6VLX240T-FF1156. The implementation results show that the 150 processor cores for 32-32-32 input–hidden–output layer perceptrons can be implemented in the FPGA using 150 DSP48 slices, 185 block RAMs and 9676 slices. It runs in 242.89 MHz clock frequency, and a single evaluation of 150 nodes perceptron can be performed 1.65 × 107 times per second.