From 0af55cfcbe41750f7c821d5bfd7f54e1f20d94df Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Rafael=20Fern=C3=A1ndez=20L=C3=B3pez?= Date: Wed, 30 Oct 2024 13:43:30 +0100 Subject: [PATCH] docs: update docker and podman anchor on CUDA section --- doc/languages-frameworks/cuda.section.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/languages-frameworks/cuda.section.md b/doc/languages-frameworks/cuda.section.md index af52a3d31d05..bb394a243b79 100644 --- a/doc/languages-frameworks/cuda.section.md +++ b/doc/languages-frameworks/cuda.section.md @@ -150,7 +150,7 @@ All new projects should use the CUDA redistributables available in [`cudaPackage In the scenario you are unable to run the resulting binary: this is arguably the most complicated as it could be any combination of the previous reasons. This type of failure typically occurs when a library attempts to load or open a library it depends on that it does not declare in its `DT_NEEDED` section. As a first step, ensure that dependencies are patched with [`autoAddDriverRunpath`](https://search.nixos.org/packages?channel=unstable&type=packages&query=autoAddDriverRunpath). Failing that, try running the application with [`nixGL`](https://github.com/guibou/nixGL) or a similar wrapper tool. If that works, it likely means that the application is attempting to load a library that is not in the `RPATH` or `RUNPATH` of the binary. -## Running Docker or Podman containers with CUDA support {#running-docker-or-podman-containers-with-cuda-support} +## Running Docker or Podman containers with CUDA support {#cuda-docker-podman} It is possible to run Docker or Podman containers with CUDA support. The recommended mechanism to perform this task is to use the [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/index.html).