FPGA CNN

FPGA implementation of Cellular Neural Network (CNN)

Initialization

CNN

CNN.v is Top-level design with initialization for A, B, I template
SixteenbySixteen.java generates Verilog code for 16x16 layer module sixteenbysixteen.v

Default

CornerDetection
Other available templates in here

Instruction

1. Change the size variable in SixteenbySixteen can generate different dimension module
2. Contain a 4x4 layer module fourbyfour.v
3. fourbyfour.v and sixteenbysixteen.v use one multiplier and two adders in calculation of equation 1
4. Any files ended with 18mul are associated with the version using 18 multipliers and finishing equation 1 calculation in one clock cycle
5. Top level design CNN.v and CNNfourbyfour.v is shared with both versions
6. Change the module link, for example, sixteenbysixteen u1 to sixteenbysixteen18mul u1
   will change to the version which does equation 1 calculation in one clock cycle
7. Eq1 Initial folder contains the work by Sangeetha J. who completes using one multiplier and one adder to calculate template A times output Y or template B times input U. The default version which using one multiplier and two adders in calcualtion of equation 1 is based on her contribution

Default

size = 16;
CNN.v is using sixteenbysixteen.v

Contributing

1. Fork
2. Create your feature branch: git checkout -b my-new-feature
3. Commit your changes: git commit -am 'Add some feature'
4. Push to the branch: git push origin my-new-feature
5. Submit a pull request

Source

SP-CNN: A Scalable and Programmable CNN-based Accelerator, Dilan Manatunga, Hyesoon Kim, Saibal Mukhopadhyay GOMACTech, Mar. 2015

Credits

Enmao Diao
Ria Gupte
Hyesoon Kim
Joshua Lee
Sangeetha J.