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ECE-564-Convolutional-Neural-Network-Accelerator

A Verilog implementation of a CNN accelerator.

Abstract: This piece of hardware is a single stage binary convolution accelerator that can accept 3 different sized input matrixes. The input, output and weights are all stored in separate SRAMs and the outputs are left zero padded. Convolution is achieved by calculating the XNOR of the weight and input and bit counting the result to determine the sign of the desired output bit. Doing this in parallel allows the module to pipeline inputs and operate with a new memory input every clock cycle. A FSM controls the inputs and outputs and allows the module to process multiple input matrixes until it encounters a matrix terminated with 0x00FF. Each matrix is preempted with an xdim and ydim indicating how many columns and rows the matrix has respectively. The weights are stored in the second address of the weight SRAM and are a 3x3 matrix. Using this approach allowed memory bandwidth to be well utilized.

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