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cos/third_party/nvidia-container-toolkit/refs/tags/v1.19.0-rc.2
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7044c800572f24ddfa5f0c6f3ae664434e90abed
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Evan Lezar <elezar@nvidia.com>
Fri Jan 23 17:53:08 2026 +0100
object
5f72b2e1ac812607cdd1df16c64bf8b37f0fdca9
NVIDIA Container Toolkit v1.19.0-rc.2
commit
5f72b2e1ac812607cdd1df16c64bf8b37f0fdca9
[log]
author
Evan Lezar <elezar@nvidia.com>
Fri Jan 23 17:46:06 2026 +0100
committer
GitHub <noreply@github.com>
Fri Jan 23 17:46:06 2026 +0100
tree
4c4dd4c4e89dfc79701b8be9bb20fdd3f4f64f06
parent
e7f40796fabde0fe1fdda8a26b1b7ee4491669f5 [diff]
parent
526e500bfbe7c9a103f3b8083899c4c681ca3ca7 [diff]
Merge pull request #1610 from elezar/fix-verison-string

[no-relnote] Fix version bump
tree: 4c4dd4c4e89dfc79701b8be9bb20fdd3f4f64f06
  1. .github/
  2. cmd/
  3. deployments/
  4. docker/
  5. hack/
  6. internal/
  7. packaging/
  8. pkg/
  9. scripts/
  10. testdata/
  11. tests/
  12. third_party/
  13. vendor/
  14. .dockerignore
  15. .gitignore
  16. .gitmodules
  17. .golangci.yml
  18. .nvidia-ci.yml
  19. CHANGELOG.md
  20. CONTRIBUTING.md
  21. DEVELOPMENT.md
  22. go.mod
  23. go.sum
  24. LICENSE
  25. Makefile
  26. README.md
  27. RELEASE.md
  28. SECURITY.md
  29. 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!