The invention discloses a CNN (
Convolutional Neural Network)
data access method for an FPGA (
Field Programmable Gate Array), which belongs to the technical field of CNN
data access, and comprises the following steps: 1, inputting feature maps, and fragmenting the feature maps, each fragment comprising a plurality of feature maps, 2, determining the number of BRAMs (
Block Random Access Memory) in a CNN, and optimizing the BRAMs, 3, selecting a first feature map group, and 4, selecting a second feature map group, s3, splicing all the feature pixel data in the first feature image group, 4,
processing the feature image group by using the same method as S3 until the feature pixel data of all the feature image groups are spliced, and 5, interweaving all the spliced feature pixel data according to the sequence of fragmentation, the CNN
data access method for the FPGA platform is designed by adopting the method, the bandwidth can be utilized to the maximum when high
parallel processing is carried out, the problem of read address conflict is solved by using the optimized BRAM, and the read of interleaved data can be completed in one
clock period.