A python package to register on the bittensor network using a CUDA device.

• Ubuntu 20.04 or higher
• bittensor>=3.0.0
• sm_61, sm_70, sm_75, sm_80, or sm_86 enabled CUDA GPU (See here)

1. Change the base image to the target bittensor version
2. Build the image:
   1. sudo docker build -t opentensorfdn/bittensor:VERSION_BT-cubitVERSION_CUBIT -f ./docker/Dockerfile .
3. Push the image
   1. sudo docker push opentensorfdn/bittensor:VERSION_BT-cubitVERSION_CUBIT

Using the wheel for your version of python (3.8, etc.) from releases
For Python 3.8

pip install https://github.com/opentensor/cubit/releases/download/v1.1.2/cubit-1.1.2-cp38-cp38-linux_x86_64.whl

For Python 3.9

pip install https://github.com/opentensor/cubit/releases/download/v1.1.2/cubit-1.1.2-cp39-cp39-linux_x86_64.whl

For Python 3.10

pip install https://github.com/opentensor/cubit/releases/download/v1.1.2/cubit-1.1.2-cp310-cp310-linux_x86_64.whl

Install test extras from wheel For Python 3.8

pip install https://github.com/opentensor/cubit/releases/download/v1.1.2/cubit-1.1.2-cp38-cp38-linux_x86_64.whl[test]

For Python 3.9

pip install https://github.com/opentensor/cubit/releases/download/v1.1.2/cubit-1.1.2-cp39-cp39-linux_x86_64.whl[test]

For Python 3.10

pip install https://github.com/opentensor/cubit/releases/download/v1.1.2/cubit-1.1.2-cp310-cp310-linux_x86_64.whl[test]

• cuda-toolkit 11.3 or higher
  • nvcc
• gcc (9.3.1 or higher)
• python 3.8 or higher

You can check if you have cuda-toolkit with

nvcc --version

Clone repo

git clone https://github.com/opentensor/cubit.git

Enter dir

cd cubit/

Install as editable

pip install -e .

Install test extras as editable

pip install -e .[test]

Testing uses unittest as there is an issue with pytest and Cython compatability

python3 -m unittest test.py

https://github.com/rmcgibbo/npcuda-example/
https://github.com/mochimodev/cuda-hashing-algos/
https://github.com/camfairchild/bittensor_register_cuda/