Skip to main content

A package to generate verilog for TNNs

Project description

Twn_Generator v0.1.5

This package generates c or verilog code for convolutions in Ternary Neural Networks

Installation

To install run

  pip3 install twn_generator

Example Usage

There are two example verilog use cases for computing the convolution

The first uses 16 bit adders to compute the convolution quickly. The second computes the same result but computes the convolution using 4 bit serial adders. This only has a quarter of the throughput but also a quarter of the area in adders.

To run the CSE and generate the adders, run:

   python3 run_cse_and_generate_example.py --matrix_fname data/conv1_weights.csv --cse_fname data/conv1_tern_op_list.csv --module_name lyr1 --BW_in 16
   python3 run_cse_and_generate_example.py --matrix_fname data/conv1_weights.csv --cse_fname data/conv1_tern_op_list.csv --module_name lyr1_serial --BW_in 4 --serial

This will generate 3 files:

  • lyr1.sv => the 16 bit adder version
  • lyr1_serial.sv => the 4 bit serial adder version
  • serial_adder.sv => a helper module implementing the serial adder

In the verilog/ directory the following can be used to verify the 16 bit adder example:

  • conv_windower.sv
  • windower_3x3_pad.sv
  • conv_windower_test.sv

For the 4 bit serial adder example:

  • conv_windower_serial.sv
  • from_serial.v
  • to_serial.v
  • windower_3x3_pad_serial_4.sv
  • conv_windower_serial_test.sv

The top level design modules are conv_windower.sv and conv_windower_serial.sv respectively. The simulation test sources are conv_windower_test.sv and conv_windower_serial.sv

For more details on CSE

For more details on SMM

Copyleft

The output of the generator ( the verilog or c in this case ) is not under GPL

See: In what cases is the output of a GPL program covered by the GPL too?

Citation

Please cite:

@article{tridgell2019unrolling,
  title={Unrolling Ternary Neural Networks},
  author={Tridgell, Stephen and Kumm, Martin and Hardieck, Martin and Boland, David and Moss, Duncan and Zipf, Peter and Leong, Philip HW},
  journal={ACM Transactions on Reconfigurable Technology and Systems (TRETS)},
  volume={12},
  number={4},
  pages={22},
  year={2019},
  publisher={ACM}
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for twn-generator, version 0.1.5
Filename, size File type Python version Upload date Hashes
Filename, size twn_generator-0.1.5-py3-none-any.whl (29.1 kB) File type Wheel Python version py3 Upload date Hashes View
Filename, size twn_generator-0.1.5.tar.gz (14.9 kB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page