breaking: stop providing CUDA 11 pre-built wheels (#5080)

njzjz · web-flow · commit 09486c526b6c · 2025-12-12T13:49:52.000Z
CUDA 11 is very old. TensorFlow, PyTorch, and JAX stopped the support of
CUDA 11 very long ago.

&lt;!-- This is an auto-generated comment: release notes by coderabbit.ai
--&gt;

## Summary by CodeRabbit

* **Chores**
* Removed CUDA 11 support across build matrix; CUDA 12.8 is now the
minimum supported version.
* Dropped TensorFlow 2.14 support from C library builds; only TensorFlow
2.18 available.
  * Simplified build toolchain and updated base image specifications.

* **Documentation**
  * Removed CUDA 11.8 installation guides and references.
* Updated installation documentation to reflect current CUDA and
TensorFlow requirements.

&lt;sub&gt;✏️ Tip: You can customize this high-level summary in your review
settings.&lt;/sub&gt;

&lt;!-- end of auto-generated comment: release notes by coderabbit.ai --&gt;

---------

Signed-off-by: Jinzhe Zeng &lt;jinzhe.zeng@ustc.edu.cn&gt;
diff --git a/.github/workflows/build_cc.yml b/.github/workflows/build_cc.yml
@@ -20,8 +20,6 @@ jobs:
         include:
         - variant: cpu
           dp_variant: cpu
-        - variant: cuda
-          dp_variant: cuda
         - variant: cuda120
           dp_variant: cuda
         - variant: rocm
@@ -36,12 +34,6 @@ jobs:
     - uses: lukka/get-cmake@latest
     - run: python -m pip install uv
     - run: source/install/uv_with_retry.sh pip install --system --group pin_tensorflow_cpu --group pin_pytorch_cpu --torch-backend cpu
-    - run: |
-         wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.0-1_all.deb \
-         && sudo dpkg -i cuda-keyring_1.0-1_all.deb \
-         && sudo apt-get update \
-         && sudo apt-get -y install cuda-cudart-dev-11-8 cuda-nvcc-11-8
-      if: matrix.variant == 'cuda'
     - run: |
          wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.0-1_all.deb \
          && sudo dpkg -i cuda-keyring_1.0-1_all.deb \
diff --git a/.github/workflows/build_wheel.yml b/.github/workflows/build_wheel.yml
@@ -29,13 +29,7 @@ jobs:
             python: 311
             platform_id: manylinux_x86_64
             dp_variant: cuda
-            cuda_version: 12.2
-          - os: ubuntu-latest
-            python: 311
-            platform_id: manylinux_x86_64
-            dp_variant: cuda
-            cuda_version: 11.8
-            dp_pkg_name: deepmd-kit-cu11
+            cuda_version: 12.8
           # macos-x86-64
           - os: macos-15-intel
             python: 311
@@ -64,14 +58,6 @@ jobs:
       - name: Install uv
         run: curl --proto '=https' --tlsv1.2 -LsSf https://github.com/astral-sh/uv/releases/download/0.2.24/uv-installer.sh | sh
         if: runner.os != 'Linux'
-      - uses: docker/setup-qemu-action@v3
-        name: Setup QEMU
-        if: matrix.platform_id == 'manylinux_aarch64' && matrix.os == 'ubuntu-latest'
-      # detect version in advance. See #3168
-      - run: |
-          echo "SETUPTOOLS_SCM_PRETEND_VERSION=$(pipx run uv tool run --from setuptools_scm python -m setuptools_scm)" >> $GITHUB_ENV
-          rm -rf .git
-        if: matrix.dp_pkg_name == 'deepmd-kit-cu11'
       - name: Build wheels
         uses: pypa/cibuildwheel@v3.3
         env:
@@ -126,8 +112,6 @@ jobs:
         include:
           - variant: ""
             cuda_version: "12"
-          - variant: "_cu11"
-            cuda_version: "11"
     steps:
       - name: Delete huge unnecessary tools folder
         run: rm -rf /opt/hostedtoolcache
diff --git a/.github/workflows/package_c.yml b/.github/workflows/package_c.yml
@@ -24,9 +24,6 @@ jobs:
           - tensorflow_build_version: "2.18"
             tensorflow_version: ""
             filename: libdeepmd_c.tar.gz
-          - tensorflow_build_version: "2.14"
-            tensorflow_version: ">=2.5.0,<2.15"
-            filename: libdeepmd_c_cu11.tar.gz
     steps:
       - name: Free Disk Space (Ubuntu)
         uses: insightsengineering/disk-space-reclaimer@v1
diff --git a/backend/find_pytorch.py b/backend/find_pytorch.py
@@ -116,9 +116,6 @@ def get_pt_requirement(pt_version: str = "") -> dict:
             cibw_requirement = read_dependencies_from_dependency_group(
                 "pin_pytorch_cpu"
             )
-        elif cuda_version in SpecifierSet(">=11,<12"):
-            # CUDA 11.8, cudnn 8
-            pt_version = "2.3.1"
         else:
             raise RuntimeError("Unsupported CUDA version") from None
     if pt_version == "":
diff --git a/backend/find_tensorflow.py b/backend/find_tensorflow.py
@@ -95,14 +95,6 @@ def find_tensorflow() -> tuple[str | None, list[str]]:
                 requires.extend(
                     read_dependencies_from_dependency_group("pin_tensorflow_cpu")
                 )
-            elif cuda_version in SpecifierSet(">=11,<12"):
-                # CUDA 11.8, cudnn 8
-                requires.extend(
-                    [
-                        "tensorflow-cpu>=2.5.0,<2.15; platform_machine=='x86_64' and platform_system == 'Linux'",
-                    ]
-                )
-                tf_version = "2.14.1"
             else:
                 raise RuntimeError("Unsupported CUDA version") from None
         requires.extend(get_tf_requirement(tf_version)["cpu"])
diff --git a/doc/install/easy-install-dev.md b/doc/install/easy-install-dev.md
@@ -12,8 +12,6 @@ The [`devel` tag](https://github.com/deepmodeling/deepmd-kit/pkgs/container/deep
 docker pull ghcr.io/deepmodeling/deepmd-kit:devel
 ```
 
-For CUDA 11.8 support, use the `devel_cu11` tag.
-
 ## Install with pip
 
 Follow [the documentation for the stable version](easy-install.md#install-python-interface-with-pip), but add `--pre` and `--extra-index-url` options like below:
diff --git a/doc/install/easy-install.md b/doc/install/easy-install.md
@@ -96,14 +96,6 @@ pip install deepmd-kit[gpu,cu12]
 
 ::::
 
-::::{tab-item} CUDA 11
-
-```bash
-pip install deepmd-kit-cu11[gpu,cu11]
-```
-
-::::
-
 ::::{tab-item} CPU
 
 ```bash
@@ -128,15 +120,6 @@ pip install deepmd-kit[torch]
 
 ::::
 
-::::{tab-item} CUDA 11.8
-
-```bash
-pip install torch --index-url https://download.pytorch.org/whl/cu118
-pip install deepmd-kit-cu11
-```
-
-::::
-
 ::::{tab-item} CPU
 
 ```bash
@@ -194,18 +177,6 @@ pip install deepmd-kit
 
 ::::
 
-::::{tab-item} CUDA 11.8
-
-```bash
-# release version
-pip install paddlepaddle-gpu==3.1.1 -i https://www.paddlepaddle.org.cn/packages/stable/cu118/
-# nightly-build version
-# pip install --pre paddlepaddle-gpu -i https://www.paddlepaddle.org.cn/packages/nightly/cu118/
-pip install deepmd-kit
-```
-
-::::
-
 ::::{tab-item} CPU
 
 ```bash
diff --git a/doc/install/install-from-c-library.md b/doc/install/install-from-c-library.md
@@ -12,7 +12,7 @@ wget https://github.com/deepmodeling/deepmd-kit/releases/latest/download/libdeep
 tar xzf libdeepmd_c.tar.gz
 ```
 
-The library is built in Linux (GLIBC 2.17) with CUDA 12.2 (`libdeepmd_c.tar.gz`) or 11.8 (`libdeepmd_c_cu11.tar.gz`). It's noted that this package does not contain CUDA Toolkit and cuDNN, so one needs to download them from the NVIDIA website.
+The library is built in Linux (GLIBC 2.17) with CUDA 12.2 (`libdeepmd_c.tar.gz`). It's noted that this package does not contain CUDA Toolkit and cuDNN, so one needs to download them from the NVIDIA website.
 
 ## Use Pre-compiled C Library to build the LAMMPS plugin, i-PI driver, and GROMACS patch
 
diff --git a/doc/install/install-from-source.md b/doc/install/install-from-source.md
@@ -104,12 +104,6 @@ pip install paddlepaddle-gpu==3.1.1 -i https://www.paddlepaddle.org.cn/packages/
 # nightly-build version
 # pip install --pre paddlepaddle-gpu -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/
 
-# cu118
-# release version
-pip install paddlepaddle-gpu==3.1.1 -i https://www.paddlepaddle.org.cn/packages/stable/cu118/
-# nightly-build version
-# pip install --pre paddlepaddle-gpu -i https://www.paddlepaddle.org.cn/packages/nightly/cu118/
-
 # cpu
 # release version
 pip install paddlepaddle==3.1.1 -i https://www.paddlepaddle.org.cn/packages/stable/cpu/
@@ -361,9 +355,7 @@ download the TensorFlow C library from [this page](https://www.tensorflow.org/in
 
 If you want to use C++ interface of Paddle, you need to compile the Paddle inference library(C++ interface) manually from the [linux-compile-by-make](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/install/compile/linux-compile-by-make.html), then use the `.so` and `.a` files in `Paddle/build/paddle_inference_install_dir/`.
 
-We also provide a weekly-build Paddle C++ inference library for Linux x86_64 with CUDA 11.8/12.3/CPU below:
-
-CUDA 11.8: [Cuda118_cudnn860_Trt8531_D1/latest/paddle_inference.tgz](https://paddle-qa.bj.bcebos.com/paddle-pipeline/GITHUB_Docker_Compile_Test_Cuda118_cudnn860_Trt8531_D1/latest/paddle_inference.tgz)
+We also provide a weekly-build Paddle C++ inference library for Linux x86_64 with CUDA 12.3/CPU below:
 
 CUDA 12.3: [Cuda123_cudnn900_Trt8616_D1/latest/paddle_inference.tgz](https://paddle-qa.bj.bcebos.com/paddle-pipeline/GITHUB_Docker_Compile_Test_Cuda123_cudnn900_Trt8616_D1/latest/paddle_inference.tgz)
 
diff --git a/pyproject.toml b/pyproject.toml
@@ -116,16 +116,6 @@ ipi = [
 gui = [
     "dpgui",
 ]
-cu11 = [
-    "nvidia-cuda-runtime-cu11",
-    "nvidia-cublas-cu11",
-    "nvidia-cufft-cu11",
-    "nvidia-curand-cu11",
-    "nvidia-cusolver-cu11",
-    "nvidia-cusparse-cu11",
-    "nvidia-cudnn-cu11<9",
-    "nvidia-cuda-nvcc-cu11",
-]
 cu12 = [
     "nvidia-cuda-runtime-cu12",
     "nvidia-cublas-cu12",
@@ -254,9 +244,7 @@ test-command = [
 test-extras = ["cpu", "test", "lmp", "ipi", "torch", "paddle"]
 build = ["cp311-*"]
 skip = ["*-win32", "*-manylinux_i686", "*-musllinux*"]
-# TODO: uncomment to use the latest image when CUDA 11 is deprecated
-# manylinux-x86_64-image = "manylinux_2_28"
-manylinux-x86_64-image = "quay.io/pypa/manylinux_2_28_x86_64:2022-11-19-1b19e81"
+manylinux-x86_64-image = "manylinux_2_28"
 manylinux-aarch64-image = "manylinux_2_28"
 
 [tool.cibuildwheel.macos]
@@ -288,15 +276,9 @@ environment-pass = [
 ]
 before-all = [
     """if [ ! -z "${DP_PKG_NAME}" ]; then sed -i "s/name = \\"deepmd-kit\\"/name = \\"${DP_PKG_NAME}\\"/g" pyproject.toml; fi""",
-    # https://almalinux.org/blog/2023-12-20-almalinux-8-key-update/
-    """rpm --import https://repo.almalinux.org/almalinux/RPM-GPG-KEY-AlmaLinux""",
     """{ if [ "$(uname -m)" = "x86_64" ] ; then yum config-manager --add-repo http://developer.download.nvidia.com/compute/cuda/repos/rhel8/x86_64/cuda-rhel8.repo && yum install -y cuda-nvcc-${CUDA_VERSION/./-} cuda-cudart-devel-${CUDA_VERSION/./-}; fi }""",
-    # uv is not available in the old manylinux image
-    """{ if [ "$(uname -m)" = "x86_64" ] ; then pipx install uv; fi }""",
 ]
 before-build = [
-    # old build doesn't support uv
-    """{ if [ "$(uname -m)" = "x86_64" ] ; then uv pip install --system -U build; fi }""",
 ]
 [tool.cibuildwheel.linux.environment]
 PIP_PREFER_BINARY = "1"
diff --git a/source/install/docker/Dockerfile b/source/install/docker/Dockerfile
@@ -8,8 +8,7 @@ ENV PATH="/opt/deepmd-kit/bin:$PATH"
 ENV VIRTUAL_ENV="/opt/deepmd-kit"
 # Install package
 COPY dist /dist
-RUN if [ "${CUDA_VERSION}" = 11 ]; then export UV_TORCH_BACKEND=cu118; fi \
-    && uv pip install "$(ls /dist/deepmd_kit${VARIANT}-*manylinux*_x86_64.whl)[gpu,cu${CUDA_VERSION},lmp,ipi,torch]" \
+RUN uv pip install "$(ls /dist/deepmd_kit${VARIANT}-*manylinux*_x86_64.whl)[gpu,cu${CUDA_VERSION},lmp,ipi,torch]" \
     && dp -h \
     && lmp -h \
     && dp_ipi \
