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BARVINN

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BARVINN: A Barrel RISC-V Neural Network Accelerator: https://barvinn.readthedocs.io/en/latest/

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최종 버전 다운로드 (.zip)

- - common
  - Makefile
- - common
  - Makefile
- common
- apb
- common_cells
- FUSESOC_IGNORE
- MVU
- MVU_Code_Gen
- pito_riscv
- tech_cells_generic
- - BARVINN_LOGO.png
  - BARVINN_LOGO_BARREL.png
  - BARVINN_TOP.png
  - bn_bias_weights.png
  - classbased_verif.png
  - CMC_Logo.png
  - Data_transposer.png
  - feature_map_jump_schedule.png
  - FRQNT.png
  - IBM_logo_pos_blue60_RGB.png
  - input_feature_map_mem_layouts.png
  - jekyll-dark.png
  - jekyll.png
  - lsq.png
  - MILA.png
  - mitacs_transparent.png
  - MVU_ARCH.png
  - mvu_bitslice_ops.png
  - mvu_job_config.svg
  - NSERC_COHESA.png
  - pito_barreled.png
  - pito_code_run.png
  - pito_interrupt.png
  - polymtl.png
  - qn_bn_weights.png
  - resnet18_second_layer.png
  - slide_window_valid.png
  - sw_stack.png
  - temp_logo.webp
  - verif_env.png
  - weight_jump_schedule.png
  - weight_mem_layouts.png
- .gitignore
- acknowledgement.rst
- conf.py
- credits.rst
- design.rst
- examples.rst
- fpga_prototyping.rst
- index.rst
- intro.rst
- make.bat
- Makefile
- requirements.txt
- software.rst
- verification.rst
- core_wave.tcl
- debug.tcl
- mvu_data_mem_wave.tcl
- - csrfile.mem
  - decoderlut.mem
  - regfile.mem
- - code.bin
  - code.hex
  - riscv_hex_to_bin.py
  - run_docker.sh
  - set_env
  - str_transposed.py
  - utility.pyc
  - zephyr_sync.bin
  - zephyr_sync.hex
- barvinn.sv
- data_transposer.sv
.gitignore
.gitmodules
barvinn.core
LICENSE
README.md

// repository documentation

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# BARVINN: A Barrel RISC-V Neural Network Accelerator:

![alt text](https://github.com/hossein1387/BARVINN/blob/master/docs/_static/BARVINN_LOGO.png)

## How to Use:
    
You first need to clone the repository and update the submodules:

git clone https://github.com/hossein1387/BARVINN.git
    cd BARVINN
    git submodule update --init

Now that you cloned the BARVINN repository, you can run a sample code. First make sure the Vivado is sourced, example for Vivado 2023.1:

source /opt/Xilinx/Vivado/2023.1/settings64.sh

Then make sure you have fusesoc installed:

python3 -m pip install fusesoc

Then add `mvu`, `pito` and `barvinn` to your fusesoc libraries (NOTE: if you have used FuseSoC with any of the following projects, you can skip adding it to FuseSoC) :
    
    fusesoc library add barvinn .

Then run simulation (No GUI):
   
    fusesoc run --target=sim barvinn

For synthesis:
    
    fusesoc run --target=synth barvinn

To open sim in GUI mode:

cd build/pito_0/sim-vivado/ 
    make run-gui

And for synthesis:

cd build/pito_0/synth-vivado/ 
    make build-gui

This should open the project for you. Make sure you have run simulation or synthesis atleast once, otherwise fusesoc would not create a 
project file for you.

## Documentation:

BARVINN documentation is available in [docs/](https://github.com/hossein1387/BARVINN/tree/master/docs) folder. However, you can follow this url for an online version of documentation hosted on readthedocs. This url will ocassionally gets updated. You can build the lates docs using the following:

cd docs
    python pip -r install requirements
    make html

Then, you can open `./docs/_build/html/index.html` file.

## Publications

If you liked this project, please consider citing our paper:

```
@Article{barvinn_aspdac,
  author={AskariHemmat, MohammadHossein and Bilaniuk, Olexa and Wagner, Sean and Hariri, Yassine and Savaria, Yvon and David, Jean-Pierre},
  journal= {28th Asia and South Pacific Design Automation Conference ASP-DAC 2023},
  title  = {BARVINN: Arbitrary Precision DNN Accelerator Controlled by a RISC-V CPU},
  year   = {2023},
  doi    = {10.1145/3566097.3567872}
}
```

Link to our paper on [arXiv](https://arxiv.org/pdf/2301.00290.pdf).