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Verilog implementation of a CNN Module in a Neural Network Chip; synthesized fully in Synopsys

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ASIC-Neural-Network

Verilog implementation of a CNN Module in a Neural Network Chip; synthesized fully in Synopsys

Overview

Contains the design and synthesized netlist for the Convolutional layer, a ReLu Activation Function, and a MaxPooling minimization layer. The project report details the design ideology, implementation challenges, and final design UML with the key registers named and described.

To Run

Copy into a fresh directory, and source your Synopsys setup files The following command executes the Synopsys synthesis - make-debug-564-base

Under the hood

The outputs of the design are verified against a golden model for each input configuration; then simulator as-is runs 2 sets of inputs matrices and kernels to determine functionality.

Result/Reports

The timing and total cell area reports provide insights into the performance metrics achieved by this implementation.

Improvements/Augmentations

The design, while completing with a small clock period, can be minimized by parallelizing operations with further utilization of continuous assignment statements. Further, the decision to clearly separate different aspect of the data path did not yield itself to minimize area; in this vein, further optimizations by reducing the number of Finite State Machines (FSMs) to 2 shall be pursued.

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Verilog implementation of a CNN Module in a Neural Network Chip; synthesized fully in Synopsys

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