Decentralized compute layer
 
 
Go to file
Konstantine Tsafatinos 257e987fe2 edit discord init 2023-10-13 23:21:57 -04:00
docker Move docker related scripts to docker dir 2023-10-09 08:50:36 -03:00
skynet edit discord init 2023-10-13 23:21:57 -04:00
tests Add test for new ipfs async apis, fix cli entrypoints endpoint loading to new format 2023-09-24 15:23:25 -03:00
.dockerignore Add venv to dockerignore 2023-10-07 11:01:40 -03:00
.gitignore Add new config to .gitignore 2023-10-07 11:12:45 -03:00
LICENSE Update LICENSE 2023-04-09 19:50:08 -03:00
README.md Minor readme tweaks 2023-10-09 08:52:04 -03:00
launch_ipfs.sh Add venv to dockerignore 2023-10-07 11:01:40 -03:00
poetry.lock Fix missing quart dep 2023-10-09 07:50:39 -03:00
poetry.toml Switch to using poetry package manager 2023-10-07 11:01:40 -03:00
pyproject.toml Fix missing quart dep 2023-10-09 07:50:39 -03:00
pytest.ini Add test for new ipfs async apis, fix cli entrypoints endpoint loading to new format 2023-09-24 15:23:25 -03:00
skynet.toml.example Add worker benchmark api 2023-10-08 19:37:25 -03:00

README.md

skynet

<img src="https://explorer.skygpu.net/v2/explore/assets/logo.png" width=512 height=512>

decentralized compute platform

native install

system dependencies: - cuda 11.8 - llvm 10 - python 3.10+ - docker (for ipfs node)

# create and edit config from template
cp skynet.toml.example skynet.toml

# install poetry package manager
curl -sSL https://install.python-poetry.org | python3 -

# install
poetry install

# enable environment
poetry shell

# test you can run this command
skynet --help

# launch ipfs node
skynet run ipfs

# to launch worker
skynet run dgpu

dockerized install

frontend

system dependencies: - docker

# create and edit config from template
cp skynet.toml.example skynet.toml

# pull runtime container
docker pull guilledk/skynet:runtime-frontend

# run telegram bot
docker run \
    -it \
    --rm \
    --network host \
    --name skynet-telegram \
    --mount type=bind,source="$(pwd)",target=/root/target \
    guilledk/skynet:runtime-frontend \
    skynet run telegram --db-pass PASSWORD --db-user USER --db-host HOST

worker

system dependencies: - docker with gpu enabled

# create and edit config from template
cp skynet.toml.example skynet.toml

# pull runtime container
docker pull guilledk/skynet:runtime-cuda

# or build it (takes a bit of time)
./build_docker.sh

# launch simple ipfs node
./launch_ipfs.sh

# run worker with all gpus
docker run \
    -it \
    --rm \
    --gpus all \
    --network host \
    --name skynet-worker \
    --mount type=bind,source="$(pwd)",target=/root/target \
    guilledk/skynet:runtime-cuda \
    skynet run dgpu

# run worker with specific gpu
docker run \
    -it \
    --rm \
    --gpus '"device=1"' \
    --network host \
    --name skynet-worker-1 \
    --mount type=bind,source="$(pwd)",target=/root/target \
    guilledk/skynet:runtime-cuda \
    skynet run dgpu