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Updated Frequently Asked Questions (markdown) authored by Jonathan Calmels's avatar Jonathan Calmels
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Frequently-Asked-Questions.md
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......@@ -40,7 +40,7 @@ For your host distribution, the list of supported platforms is available [here](
For your container images, both the [Docker Hub](https://github.com/NVIDIA/nvidia-docker/wiki/Docker-Hub) and [NGC registry](https://github.com/NVIDIA/nvidia-docker/wiki/NGC) images are officially supported.
#### Do you support PowerPC64 (ppc64)?
Not yet for 2.0 but are actively working with IBM on this.
Not yet for 2.0 but we are actively working with IBM on this.
#### How do I use this in on my Cloud service provider (e.g. AWS, Azure, GCP)?
We have a tutorial for [AWS](https://github.com/NVIDIA/nvidia-docker/wiki/Deploy-on-Amazon-EC2) and a tutorial for [Azure](https://github.com/NVIDIA/nvidia-docker/wiki/Deploy-on-Azure).
......@@ -104,7 +104,7 @@ You probably need to enable [persistence mode](http://docs.nvidia.com/deploy/dri
The recommended way is to start the `nvidia-persistenced` daemon on your host.
#### Can I use it with Docker-in-Docker (a.k.a. DinD)?
If you are running a Docker client inside a container: simply mount the Docker socket proceed as usual.\
If you are running a Docker client inside a container: simply mount the Docker socket and proceed as usual.\
If you are running a Docker daemon inside a container: this case is untested.
#### Why is my application inside the container slow to initialize?
......@@ -151,7 +151,7 @@ However, do not set `LD_LIBRARY_PATH` to this folder, the stubs must not be used
#### The official CUDA images are too big, what do I do?
The `devel` [image tags](https://hub.docker.com/r/nvidia/cuda/) are large since the CUDA toolkit ships with many libraries, a compiler and various command-line tools.\
As a general rule of thumb, you shouldn’t ship your application with its build-time dependencies. We recommend to use [multi-stage builds](https://docs.docker.com/engine/userguide/eng-image/multistage-build/) for this purpose. Your final container image should use our `runtime` or `base` images.\
Also, as of CUDA 9.0 we now ship a `base` [image tag](https://hub.docker.com/r/nvidia/cuda/) which bundles the strict minimum of dependencies.
As of CUDA 9.0 we now ship a `base` [image tag](https://hub.docker.com/r/nvidia/cuda/) which bundles the strict minimum of dependencies.
## Ecosystem enablement
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