diff --git a/website/_config.yml b/website/_config.yml index 4b6ffae8d..5679a5552 100644 --- a/website/_config.yml +++ b/website/_config.yml @@ -31,6 +31,10 @@ authors: bogomolov: name: Konstantin Bogomolov email: bogomolov@google.com + eperot: + name: Etienne Perot + email: eperot@google.com + url: https://perot.me lucasmanning: name: Lucas Manning email: lucasmanning@google.com diff --git a/website/_sass/style.scss b/website/_sass/style.scss index 4deb945d4..516181501 100644 --- a/website/_sass/style.scss +++ b/website/_sass/style.scss @@ -7,6 +7,7 @@ $link-hover-color: darken($link-color, 10%); $inverse-link-hover-color: darken($inverse-link-color, 10%); $text-color: #444; +$text-color-secondary: #666; $body-font-family: 'Roboto', 'Helvetica Neue', Helvetica, Arial, sans-serif; $code-font-family: 'Source Code Pro', monospace; @@ -152,3 +153,22 @@ table th { display: block; margin: 20px auto; } + +.blog-content .attribution { + /* Stay close to the image. */ + display: block; + margin-top: 6px; + padding-top: 0px; + + /* Italics, centered, lighter text. */ + text-align: center; + font-style: italic; + color: $text-color-secondary; +} + +.blog-content * img:has(+ .attribution) { + /* Remove bottom margins from images where there is an attribution line + * immediately following the image. + */ + margin-bottom: 0px; +} diff --git a/website/assets/images/2023-06-20-astronaut-thumbs-up.png b/website/assets/images/2023-06-20-astronaut-thumbs-up.png new file mode 100644 index 000000000..28e331cfd Binary files /dev/null and b/website/assets/images/2023-06-20-astronaut-thumbs-up.png differ diff --git a/website/assets/images/2023-06-20-sandboxed-gpu.png b/website/assets/images/2023-06-20-sandboxed-gpu.png new file mode 100644 index 000000000..304dbf328 Binary files /dev/null and b/website/assets/images/2023-06-20-sandboxed-gpu.png differ diff --git a/website/assets/images/2023-06-20-spacesuit-helmets.png b/website/assets/images/2023-06-20-spacesuit-helmets.png new file mode 100644 index 000000000..8dac4b9ad Binary files /dev/null and b/website/assets/images/2023-06-20-spacesuit-helmets.png differ diff --git a/website/assets/images/2023-06-20-stable-diffusion-web-ui.png b/website/assets/images/2023-06-20-stable-diffusion-web-ui.png new file mode 100644 index 000000000..1ccf870ee Binary files /dev/null and b/website/assets/images/2023-06-20-stable-diffusion-web-ui.png differ diff --git a/website/assets/images/2023-06-20-turbo.png b/website/assets/images/2023-06-20-turbo.png new file mode 100644 index 000000000..db2560c5d Binary files /dev/null and b/website/assets/images/2023-06-20-turbo.png differ diff --git a/website/blog/2023-06-20-gpu-pytorch-stable-diffusion.md b/website/blog/2023-06-20-gpu-pytorch-stable-diffusion.md new file mode 100644 index 000000000..b0da11f22 --- /dev/null +++ b/website/blog/2023-06-20-gpu-pytorch-stable-diffusion.md @@ -0,0 +1,261 @@ +# Running Stable Diffusion on GPU with gVisor + +gVisor is [starting to support GPU][gVisor GPU support] workloads. This post +showcases running the [Stable Diffusion] generative model from [Stability AI] to +generate images using a GPU from within gVisor. Both the +[Automatic1111 Stable Diffusion web UI][automatic1111/stable-diffusion-webui] +and the [PyTorch] code used by Stable Diffusion were run entirely within gVisor +while being able to leverage the NVIDIA GPU. + +![A sandboxed GPU](/assets/images/2023-06-20-sandboxed-gpu.png "A sandboxed GPU.") +**Sand**boxing a GPU. Generated with Stable Diffusion +v1.5.
This picture gets a lot deeper once you realize that GPUs are made out +of sand. + +-------------------------------------------------------------------------------- + +## Disclaimer + +As of this writing (2023-06), [gVisor's GPU support][gVisor GPU support] is not +generalized. Only some PyTorch workloads have been tested on NVIDIA T4, L4, +A100, and H100 GPUs, using the specific driver versions `525.60.13` and +`525.105.17`. Contributions are welcome to expand this set to support other GPUs +and driver versions! + +Additionally, while gVisor does its best to sandbox the workload, interacting +with the GPU inherently requires running code on GPU hardware, where isolation +is enforced by the GPU driver and hardware itself rather than gVisor. More to +come soon on the value of the protection gVisor provides for GPU workloads. + +In a few months, gVisor's GPU support will have broadened and become +easier-to-use, such that it will not be constrained to the specific sets of +versions used here. In the meantime, this blog stands as an example of what's +possible today with gVisor's GPU support. + +![Various space suit helmets](/assets/images/2023-06-20-spacesuit-helmets.png "Various space suit helmets."){:width="100%"} +**A collection of astronaut helmets in various styles**.
Other than the helmet in the center, each helmet was generated using Stable Diffusion v1.5. + +## Why even do this? + +The recent explosion of machine learning models has led to a large number of new +open-source projects. Much like it is good practice to be careful about running +new software downloaded from the Internet, it is good practice to run new +open-source projects in a sandbox. For projects like the +[Automatic1111 Stable Diffusion web UI][automatic1111/stable-diffusion-webui], +which automatically download various models, components, and +[extensions][Stable Diffusion Web UI extensions] from external repositories as +the user enables them in the web UI, this principle applies all the more. + +Additionally, within the machine learning space, tooling for packaging and +distributing models are still nascent. While some models (including Stable +Diffusion) are packaged using the more secure [safetensors] format, **the +majority of models available online today are distributed using the +[Pickle format], which can execute arbitrary Python code** upon deserialization. +As such, even when using trustworthy software, using Pickle-formatted models may +still be risky. gVisor provides a layer of protection around this process which +helps protect the host machine. + +Third, **machine learning applications are typically not I/O heavy**, which +means they tend not to experience a significant performance overhead. The +process of uploading code to the GPU is not a significant number of system +calls, and most communication to/from the GPU happens over shared memory, where +gVisor imposes no overhead. Therefore, the question is not so much "why should I +run this GPU workload in gVisor?" but rather "why not?". + +![Cool astronauts don't look at explosions](/assets/images/2023-06-20-turbo.png "Cool astronauts don't look at explosions.") +**Cool astronauts don't look at explosions**. +Generated using Stable Diffusion v1.5. + +Lastly, running GPU workloads in gVisor is pretty cool. + +## Setup + +We use a Debian virtual machine on GCE. The machine needs to have a GPU and to +have sufficient RAM and disk space to handle Stable Diffusion and its large +model files. The following command creates a VM with 4 vCPUs, 15GiB of RAM, 64GB +of disk space, and an NVIDIA T4 GPU, running Debian 11 (bullseye). Since this is +just an experiment, the VM is set to self-destruct after 6 hours. + +```shell +$ gcloud compute instances create stable-diffusion-testing \ + --zone=us-central1-a \ + --machine-type=n1-standard-4 \ + --max-run-duration=6h \ + --instance-termination-action=DELETE \ + --maintenance-policy TERMINATE \ + --accelerator=count=1,type=nvidia-tesla-t4 \ + --create-disk=auto-delete=yes,boot=yes,device-name=stable-diffusion-testing,image=projects/debian-cloud/global/images/debian-11-bullseye-v20230509,mode=rw,size=64 +$ gcloud compute ssh --zone=us-central1-a stable-diffusion-testing +``` + +All further commands in this post are performed while SSH'd into the VM. We +first need to install the specific NVIDIA driver version that gVisor is +currently compatible with. + +```shell +$ sudo apt-get update && sudo apt-get -y upgrade +$ sudo apt-get install -y build-essential linux-headers-$(uname -r) +$ DRIVER_VERSION=525.60.13 +$ curl -fSsl -O "https://us.download.nvidia.com/tesla/$DRIVER_VERSION/NVIDIA-Linux-x86_64-$DRIVER_VERSION.run" +$ sudo sh NVIDIA-Linux-x86_64-$DRIVER_VERSION.run +``` + + + +Next, we install Docker, per [its instructions][Docker installation on Debian]. + +```shell +$ sudo apt-get install -y ca-certificates curl gnupg +$ sudo install -m 0755 -d /etc/apt/keyrings +$ curl -fsSL https://download.docker.com/linux/debian/gpg | sudo gpg --dearmor --batch --yes -o /etc/apt/keyrings/docker.gpg +$ sudo chmod a+r /etc/apt/keyrings/docker.gpg +$ echo "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/debian $(. /etc/os-release && echo "$VERSION_CODENAME") stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null +$ sudo apt-get update && sudo apt-get install -y docker-ce docker-ce-cli +``` + + + +We will also need the [NVIDIA container toolkit], which enables use of GPUs with +Docker. Per its +[installation instructions][NVIDIA container toolkit installation]: + +```shell +$ distribution=$(. /etc/os-release;echo $ID$VERSION_ID) && curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg && curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.list | sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list +$ sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit +``` + +Of course, we also need to [install gVisor][gVisor setup] itself. + +```shell +$ sudo apt-get install -y apt-transport-https ca-certificates curl gnupg +$ curl -fsSL https://gvisor.dev/archive.key | sudo gpg --dearmor -o /usr/share/keyrings/gvisor-archive-keyring.gpg +$ echo "deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/gvisor-archive-keyring.gpg] https://storage.googleapis.com/gvisor/releases release main" | sudo tee /etc/apt/sources.list.d/gvisor.list > /dev/null +$ sudo apt-get update && sudo apt-get install -y runsc + +＃ As gVisor does not yet enable GPU support by default, we need to set the flags +＃ that will enable it: +$ sudo runsc install -- --nvproxy=true --nvproxy-docker=true + +$ sudo systemctl restart docker +``` + +Now, let's make sure everything works by running commands that involve more and +more of what we just set up. + +```shell +＃ Check that the NVIDIA drivers are installed, with the right version, and with +＃ a supported GPU attached +$ sudo nvidia-smi -L +GPU 0: Tesla T4 (UUID: GPU-6a96a2af-2271-5627-34c5-91dcb4f408aa) +$ sudo cat /proc/driver/nvidia/version +NVRM version: NVIDIA UNIX x86_64 Kernel Module 525.60.13 Wed Nov 30 06:39:21 UTC 2022 + +＃ Check that Docker works. +$ sudo docker version +＃ [...] +Server: Docker Engine - Community + Engine: + Version: 24.0.2 +＃ [...] + +＃ Check that gVisor works. +$ sudo docker run --rm --runtime=runsc debian:latest dmesg | head -1 +[ 0.000000] Starting gVisor... + +＃ Check that Docker GPU support (without gVisor) works. +$ sudo docker run --rm --gpus=all nvidia/cuda:11.6.2-base-ubuntu20.04 nvidia-smi -L +GPU 0: Tesla T4 (UUID: GPU-6a96a2af-2271-5627-34c5-91dcb4f408aa) + +＃ Check that gVisor works with the GPU. +$ sudo docker run --rm --runtime=runsc --gpus=all nvidia/cuda:11.6.2-base-ubuntu20.04 nvidia-smi -L +GPU 0: Tesla T4 (UUID: GPU-6a96a2af-2271-5627-34c5-91dcb4f408aa) +``` + +We're all set! Now we can actually get Stable Diffusion running. + +We used the following `Dockerfile` to run Stable Diffusion and its web UI within +a GPU-enabled Docker container. + +```dockerfile +FROM python:3.10 + +＃ Set of dependencies that are needed to make this work. +RUN apt-get update && apt-get install -y git wget build-essential \ + nghttp2 libnghttp2-dev libssl-dev ffmpeg libsm6 libxext6 +＃ Clone the project at the revision used for this test. +RUN git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git && \ + cd /stable-diffusion-webui && \ + git checkout baf6946e06249c5af9851c60171692c44ef633e0 +＃ We don't want the build step to start the server. +RUN sed -i '/start()/d' /stable-diffusion-webui/launch.py +＃ Install some pip packages. +＃ Note that this command will run as part of the Docker build process, +＃ which is *not* sandboxed by gVisor. +RUN cd /stable-diffusion-webui && COMMANDLINE_ARGS=--skip-torch-cuda-test python launch.py +WORKDIR /stable-diffusion-webui +＃ This causes the web UI to use the Gradio service to create a public URL. +＃ Do not use this if you plan on leaving the container running long-term. +ENV COMMANDLINE_ARGS=--share +＃ Start the webui app. +CMD ["python", "webui.py"] +``` + +We build the image and create a container with it using the `docker` +command-line. + +```shell +$ cat > Dockerfile +(... Paste the above contents...) +^D +$ sudo docker build --tag=sdui . +``` + +Finally, we can start the Stable Diffusion web UI. Note that it will take a long +time to start, as it has to download all the models from the Internet. To keep +this post simple, we didn't set up any kind of volume that would enable data +persistence, so it will do this every time the container starts. + +```shell +$ sudo docker run --runtime=runsc --gpus=all --name=sdui --detach sdui + +＃ Follow the logs: +$ sudo docker logs -f sdui +＃ [...] +Calculating sha256 for /stable-diffusion-webui/models/Stable-diffusion/v1-5-pruned-emaonly.safetensors: Running on local URL: http://127.0.0.1:7860 +Running on public URL: https://4446d982b4129a66d7.gradio.live + +This share link expires in 72 hours. +＃ [...] +``` + +We're all set! Now we can browse to the Gradio URL shown in the logs and start +generating pictures, all within the secure confines of gVisor. + +![Stable Diffusion Web UI](/assets/images/2023-06-20-stable-diffusion-web-ui.png "Stable Diffusion UI."){:width="100%"} +**Stable Diffusion Web UI screenshot.** Inner image +generated with Stable Diffusion v1.5. + +Happy sandboxing! + +![Astronaut showing thumbs up](/assets/images/2023-06-20-astronaut-thumbs-up.png "Astronaut showing thumbs up.") +**Happy sandboxing!** Generated with Stable Diffusion +v1.5. + +[gVisor GPU support]: https://github.com/google/gvisor/blob/master/g3doc/proposals/nvidia_driver_proxy.md +[Stable Diffusion]: https://stability.ai/blog/stable-diffusion-public-release +[Stability AI]: https://stability.ai/ +[automatic1111/stable-diffusion-webui]: https://github.com/AUTOMATIC1111/stable-diffusion-webui +[Stable Diffusion Web UI extensions]: https://github.com/AUTOMATIC1111/stable-diffusion-webui-extensions/blob/master/index.json +[PyTorch]: https://pytorch.org/ +[safetensors]: https://github.com/huggingface/safetensors +[Pickle format]: https://www.splunk.com/en_us/blog/security/paws-in-the-pickle-jar-risk-vulnerability-in-the-model-sharing-ecosystem.html +[Docker installation on Debian]: https://docs.docker.com/engine/install/debian/ +[NVIDIA container toolkit]: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/user-guide.html +[NVIDIA container toolkit installation]: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html +[gVisor setup]: https://gvisor.dev/docs/user_guide/install/ diff --git a/website/blog/BUILD b/website/blog/BUILD index 19bca6c55..e437a37fe 100644 --- a/website/blog/BUILD +++ b/website/blog/BUILD @@ -111,6 +111,16 @@ doc( permalink = "/blog/2023/05/08/rootfs-overlay/", ) +doc( + name = "gpu_pytorch_stable_diffusion", + src = "2023-06-20-gpu-pytorch-stable-diffusion.md", + authors = [ + "eperot", + ], + layout = "post", + permalink = "/blog/2023/06/20/gpu-pytorch-stable-diffusion/", +) + docs( name = "posts", deps = [