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cos/third_party/nvidia-container-toolkit/refs/tags/v1.19.0
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dfa3bb63319f986605272c96fa5901187da6daa5
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Evan Lezar <elezar@nvidia.com>
Tue Mar 10 16:17:41 2026 +0100
object
ec7b4e2fa2caecad6d89be4a26029b831fe7503a
NVIDIA Container Toolkit v1.19.0
commit
ec7b4e2fa2caecad6d89be4a26029b831fe7503a
[log]
author
Evan Lezar <elezar@nvidia.com>
Tue Mar 10 14:19:57 2026 +0100
committer
GitHub <noreply@github.com>
Tue Mar 10 14:19:57 2026 +0100
tree
09e4d76c0f37840a01bbc4326fce61b2023b8ba7
parent
b39720b9ed3102a59aa8033849fb08b08f96d8e1 [diff]
parent
2f6a6736065a60b1ed86d52bc6fd51c87ba01690 [diff]
Merge pull request #1722 from elezar/bump-release-v1.19.0

Bump version for v1.19.0 release
tree: 09e4d76c0f37840a01bbc4326fce61b2023b8ba7
  1. .github/
  2. api/
  3. cmd/
  4. deployments/
  5. docker/
  6. hack/
  7. internal/
  8. packaging/
  9. pkg/
  10. scripts/
  11. testdata/
  12. tests/
  13. third_party/
  14. vendor/
  15. .dockerignore
  16. .gitignore
  17. .gitmodules
  18. .golangci.yml
  19. .nvidia-ci.yml
  20. CHANGELOG.md
  21. CONTRIBUTING.md
  22. DEVELOPMENT.md
  23. go.mod
  24. go.sum
  25. LICENSE
  26. Makefile
  27. README.md
  28. RELEASE.md
  29. SECURITY.md
  30. versions.mk
README.md

NVIDIA Container Toolkit

GitHub license Documentation Package repository

nvidia-container-stack

Introduction

The NVIDIA Container Toolkit allows users to build and run GPU-accelerated containers. The toolkit includes a container runtime library and utilities to automatically configure containers to leverage NVIDIA GPUs.

Product documentation including an architecture overview, platform support, and installation and usage guides can be found in the documentation repository.

Getting Started

Make sure you have installed the NVIDIA driver for your Linux Distribution Note that you do not need to install the CUDA Toolkit on the host system, but the NVIDIA driver needs to be installed

For instructions on getting started with the NVIDIA Container Toolkit, refer to the installation guide.

Usage

The user guide provides information on the configuration and command line options available when running GPU containers with Docker.

Issues and Contributing

Checkout the Contributing document!