BARVINN

KO | EN

gitlite — search

#ai #golang #android #machine-learning #deep-learning #docker #nodejs #cli #kubernetes #awesome-list #pytorch #security #openai #open-source

(★ 99)

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

BARVINN 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# 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).

BARVINN

BARVINN 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

BARVINN

BARVINN 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README