mirror of https://github.com/skygpu/skynet.git
aeb595ce9a | ||
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docker | ||
skynet | ||
tests | ||
.dockerignore | ||
.gitignore | ||
LICENSE | ||
README.md | ||
launch_ipfs.sh | ||
poetry.lock | ||
poetry.toml | ||
pyproject.toml | ||
pytest.ini | ||
skynet.toml.example |
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