镜像构建历史
# 2025-11-12 11:33:05 0.00B 配置容器启动时运行的命令
ENTRYPOINT ["tini" "--"]
# 2025-11-12 11:33:05 0.00B 设置工作目录为/
WORKDIR /
# 2025-11-12 11:33:05 0.00B 执行命令并创建新的镜像层
RUN |6 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 CMAKE_MAX_JOBS= SGLANG_VERSION=0.5.5 SGLANG_KERNEL_VERSION=0.3.16.post5 /bin/bash -eo pipefail -c # Postprocess
# Review
uv pip tree \
--package sglang \
--package sglang-router \
--package sgl-kernel \
--package flashinfer-python \
--package flash-attn \
--package triton \
--package vllm \
--package torch \
--package deep-ep \
--package diffusers \
--package opencv-python
# buildkit
# 2025-11-12 11:33:05 338.97MB 执行命令并创建新的镜像层
RUN |6 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 CMAKE_MAX_JOBS= SGLANG_VERSION=0.5.5 SGLANG_KERNEL_VERSION=0.3.16.post5 /bin/bash -eo pipefail -c # Dependencies
# Install Dependencies,
# see https://github.com/sgl-project/sglang/blob/41c10e67fcae6ac50dfe283655bdf545d224cba9/docker/Dockerfile#L181-L209.
cat <<EOT >/tmp/requirements.txt
nvidia-cutlass-dsl==4.3.0.dev0
datamodel_code_generator
mooncake-transfer-engine==0.3.7.post2
nixl
EOT
uv pip install \
-r /tmp/requirements.txt
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/*
# buildkit
# 2025-11-12 11:33:00 71.94MB 执行命令并创建新的镜像层
RUN |6 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 CMAKE_MAX_JOBS= SGLANG_VERSION=0.5.5 SGLANG_KERNEL_VERSION=0.3.16.post5 /bin/bash -eo pipefail -c # SGlang Router
# Install Rust
curl --retry 3 --retry-connrefused --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
export PATH="/root/.cargo/bin:${PATH}" \
&& rustc --version \
&& cargo --version
# Install build tools
uv pip install \
setuptools-rust maturin
# Install SGLang Router
git -C /tmp clone --recursive --shallow-submodules \
--depth 1 --branch v${SGLANG_VERSION} --single-branch \
https://github.com/sgl-project/sglang.git sglang
pushd /tmp/sglang/sgl-router \
&& ulimit -n 65536 && maturin build --release --features vendored-openssl --out dist \
&& tree -hs /tmp/sglang/sgl-router/dist \
&& uv pip install --force-reinstall /tmp/sglang/sgl-router/dist/*.whl
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/* \
&& rm -rf /root/.cargo \
&& rm -rf /root/.rustup \
&& sed -i '$d' /root/.profile \
&& sed -i '$d' /root/.bashrc \
&& ccache --clear --clean
# buildkit
# 2025-11-12 11:24:57 3.07GB 执行命令并创建新的镜像层
RUN |6 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 CMAKE_MAX_JOBS= SGLANG_VERSION=0.5.5 SGLANG_KERNEL_VERSION=0.3.16.post5 /bin/bash -eo pipefail -c # SGLang
IFS="." read -r CUDA_MAJOR CUDA_MINOR CUDA_PATCH <<< "${VLLM_TORCH_CUDA_VERSION}"
CMAKE_MAX_JOBS="${CMAKE_MAX_JOBS}"
if [[ -z "${CMAKE_MAX_JOBS}" ]]; then
CMAKE_MAX_JOBS="$(( $(nproc) / 2 ))"
fi
if (( $(echo "${CMAKE_MAX_JOBS} > 8" | bc -l) )); then
CMAKE_MAX_JOBS="8"
fi
SG_CUDA_ARCHS="${CUDA_ARCHS}"
if [[ -z "${SG_CUDA_ARCHS}" ]]; then
if (( $(echo "${CUDA_MAJOR} < 12" | bc -l) )); then
SG_CUDA_ARCHS="7.5 8.0+PTX 8.9"
elif (( $(echo "${CUDA_MAJOR}.${CUDA_MINOR} < 12.8" | bc -l) )); then
SG_CUDA_ARCHS="7.5 8.0+PTX 8.9 9.0"
else
SG_CUDA_ARCHS="7.5 8.0+PTX 8.9 9.0 10.0+PTX 12.0+PTX"
fi
fi
export MAX_JOBS="${CMAKE_MAX_JOBS}"
export TORCH_CUDA_ARCH_LIST="${SG_CUDA_ARCHS}"
export COMPILE_CUSTOM_KERNELS=1
export NVCC_THREADS=1
# Install SGLang
git -C /tmp clone --recursive --shallow-submodules \
--depth 1 --branch v${SGLANG_VERSION} --single-branch \
https://github.com/sgl-project/sglang.git sglang-${SGLANG_VERSION}
pushd /tmp/sglang-${SGLANG_VERSION}/python \
&& uv pip install --verbose .[all]
# Download FlashInfer pre-compiled cubins
export FLASHINFER_CUBIN_DOWNLOAD_THREADS="${CMAKE_MAX_JOBS}"
export FLASHINFER_LOGGING_LEVEL=warning
python -m flashinfer --download-cubin
# Install SGLang Diffusion Extension
if [[ "${TARGETARCH}" == "amd64" ]]; then
# Diffusion Extension
pushd /tmp/sglang-${SGLANG_VERSION}/python \
&& uv pip install --verbose .[diffusion]
fi
# Install pre-complied SGLang Kernel
if (( $(echo "${CUDA_MAJOR}.${CUDA_MINOR} < 12.7" | bc -l) )); then
IFS="." read -r KERNEL_MAJOR KERNEL_MINOR KERNEL_PATCH KERNEL_POST <<< "${SGLANG_KERNEL_VERSION}"
if [[ "${TARGETARCH}" == "arm64" ]] && [[ "${KERNEL_MAJOR}.${KERNEL_MINOR}" == "0.3" ]] && (( $(echo "${KERNEL_PATCH} < 15" | bc -l) )); then
uv pip install --force-reinstall --no-deps \
https://github.com/sgl-project/whl/releases/download/v${SGLANG_KERNEL_VERSION}/sgl_kernel-${SGLANG_KERNEL_VERSION}-cp310-abi3-manylinux2014_aarch64.whl
else
uv pip install --force-reinstall --no-deps \
https://github.com/sgl-project/whl/releases/download/v${SGLANG_KERNEL_VERSION}/sgl_kernel-${SGLANG_KERNEL_VERSION}+cu124-cp310-abi3-manylinux2014_$(uname -m).whl
fi
elif (( $(echo "${CUDA_MAJOR}.${CUDA_MINOR} < 12.9" | bc -l) )); then
uv pip install \
sgl-kernel==${SGLANG_KERNEL_VERSION}
else
uv pip install --force-reinstall --no-deps \
https://github.com/sgl-project/whl/releases/download/v${SGLANG_KERNEL_VERSION}/sgl_kernel-${SGLANG_KERNEL_VERSION}+cu130-cp310-abi3-manylinux2014_$(uname -m).whl
fi
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/* \
&& ccache --clear --clean
# buildkit
# 2025-11-12 11:24:57 0.00B 设置环境变量 SGLANG_VERSION SGLANG_KERNEL_VERSION
ENV SGLANG_VERSION=0.5.5 SGLANG_KERNEL_VERSION=0.3.16.post5
# 2025-11-12 11:24:57 0.00B 定义构建参数
ARG SGLANG_KERNEL_VERSION=0.3.16.post5
# 2025-11-12 11:24:57 0.00B 定义构建参数
ARG SGLANG_VERSION=0.5.5
# 2025-11-12 11:24:57 0.00B 定义构建参数
ARG CMAKE_MAX_JOBS
# 2025-11-12 11:24:57 0.00B 设置环境变量 UV_SYSTEM_PYTHON UV_PRERELEASE
ENV UV_SYSTEM_PYTHON=1 UV_PRERELEASE=allow
# 2025-11-12 11:24:57 0.00B 定义构建参数
ARG TARGETARCH=amd64
# 2025-11-12 11:24:57 0.00B 定义构建参数
ARG TARGETOS=linux
# 2025-11-12 11:24:57 0.00B 定义构建参数
ARG TARGETPLATFORM=linux/amd64
# 2025-11-12 11:24:57 0.00B
SHELL [/bin/bash -eo pipefail -c]
# 2025-11-12 01:36:05 0.00B 配置容器启动时运行的命令
ENTRYPOINT ["tini" "--"]
# 2025-11-12 01:36:05 0.00B 设置工作目录为/
WORKDIR /
# 2025-11-12 01:36:05 0.00B 设置环境变量 RAY_EXPERIMENTAL_NOSET_CUDA_VISIBLE_DEVICES
ENV RAY_EXPERIMENTAL_NOSET_CUDA_VISIBLE_DEVICES=1
# 2025-11-12 01:36:05 0.00B 执行命令并创建新的镜像层
RUN |11 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 VLLM_NVIDIA_HPCX_VERSION=2.22.1rc4 VLLM_AWS_EFA_VERSION=1.43.3 CMAKE_MAX_JOBS= VLLM_NVIDIA_NVSHMEM_VERSION=3.4.5 VLLM_TORCH_VERSION=2.8.0 VLLM_TORCH_CUDA_VERSION=12.8.1 VLLM_VERSION=0.11.0 VLLM_LMCACHE_VERSION=0.3.9post1 /bin/bash -eo pipefail -c # Postprocess
# Review
uv pip tree \
--package vllm \
--package flashinfer-python \
--package flash-attn \
--package torch \
--package triton \
--package pplx-kernels \
--package deep-gemm \
--package deep-ep \
--package lmcache
# buildkit
# 2025-11-12 01:36:04 274.38MB 执行命令并创建新的镜像层
RUN |11 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 VLLM_NVIDIA_HPCX_VERSION=2.22.1rc4 VLLM_AWS_EFA_VERSION=1.43.3 CMAKE_MAX_JOBS= VLLM_NVIDIA_NVSHMEM_VERSION=3.4.5 VLLM_TORCH_VERSION=2.8.0 VLLM_TORCH_CUDA_VERSION=12.8.1 VLLM_VERSION=0.11.0 VLLM_LMCACHE_VERSION=0.3.9post1 /bin/bash -eo pipefail -c # Dependencies
# Install
BITSANDBYTES_VERSION="0.46.1"
if [[ "${TARGETARCH}" == "arm64" ]]; then
BITSANDBYTES_VERSION="0.42.0"
fi
cat <<EOT >/tmp/requirements.txt
accelerate
hf_transfer
modelscope
bitsandbytes>=${BITSANDBYTES_VERSION}
timm>=1.0.17
boto3
EOT
uv pip install \
-r /tmp/requirements.txt
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/*
# buildkit
# 2025-11-12 01:36:03 37.37MB 执行命令并创建新的镜像层
RUN |11 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 VLLM_NVIDIA_HPCX_VERSION=2.22.1rc4 VLLM_AWS_EFA_VERSION=1.43.3 CMAKE_MAX_JOBS= VLLM_NVIDIA_NVSHMEM_VERSION=3.4.5 VLLM_TORCH_VERSION=2.8.0 VLLM_TORCH_CUDA_VERSION=12.8.1 VLLM_VERSION=0.11.0 VLLM_LMCACHE_VERSION=0.3.9post1 /bin/bash -eo pipefail -c # Ray
# Install Ray Client and Default
RAY_VERSION=$(pip show ray | grep Version: | cut -d' ' -f 2)
cat <<EOT >/tmp/requirements.txt
ray[client]==${RAY_VERSION}
ray[default]==${RAY_VERSION}
EOT
uv pip install \
-r /tmp/requirements.txt
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/*
# buildkit
# 2025-11-12 01:36:01 178.71MB 执行命令并创建新的镜像层
RUN |11 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 VLLM_NVIDIA_HPCX_VERSION=2.22.1rc4 VLLM_AWS_EFA_VERSION=1.43.3 CMAKE_MAX_JOBS= VLLM_NVIDIA_NVSHMEM_VERSION=3.4.5 VLLM_TORCH_VERSION=2.8.0 VLLM_TORCH_CUDA_VERSION=12.8.1 VLLM_VERSION=0.11.0 VLLM_LMCACHE_VERSION=0.3.9post1 /bin/bash -eo pipefail -c # LMCache
# Ref https://github.com/LMCache/LMCache/blob/5afe9688b3519074b9915e7b3acf871328250150/docs/source/getting_started/installation.rst?plain=1#L67-L129.
IFS="." read -r CUDA_MAJOR CUDA_MINOR CUDA_PATCH <<< "${VLLM_TORCH_CUDA_VERSION}"
if [[ "${TARGETARCH}" != "amd64" ]]; then
echo "Skipping LMCache building for ${TARGETARCH}..."
exit 0
fi
# Install LMCache
CMAKE_MAX_JOBS="${CMAKE_MAX_JOBS}"
if [[ -z "${CMAKE_MAX_JOBS}" ]]; then
CMAKE_MAX_JOBS="$(( $(nproc) / 2 ))"
fi
if (( $(echo "${CMAKE_MAX_JOBS} > 8" | bc -l) )); then
CMAKE_MAX_JOBS="8"
fi
LC_CUDA_ARCHS="${CUDA_ARCHS}"
if [[ -z "${LC_CUDA_ARCHS}" ]]; then
if (( $(echo "${CUDA_MAJOR} < 12" | bc -l) )); then
LC_CUDA_ARCHS="7.5 8.0+PTX 8.9"
elif (( $(echo "${CUDA_MAJOR}.${CUDA_MINOR} < 12.8" | bc -l) )); then
LC_CUDA_ARCHS="7.5 8.0+PTX 8.9 9.0"
else
LC_CUDA_ARCHS="7.5 8.0+PTX 8.9 9.0 10.0+PTX 12.0+PTX"
fi
fi
export MAX_JOBS="${CMAKE_MAX_JOBS}"
export TORCH_CUDA_ARCH_LIST="${LC_CUDA_ARCHS}"
export NVCC_THREADS=1
git -C /tmp clone --recursive --shallow-submodules \
--depth 1 --branch v${VLLM_LMCACHE_VERSION} --single-branch \
https://github.com/LMCache/LMCache.git lmcache
sed -i "s/^infinistore$/infinistore; platform_machine == 'x86_64'/" /tmp/lmcache/requirements/common.txt
uv pip install --no-build-isolation --verbose \
/tmp/lmcache
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/* \
&& ccache --clear --clean
# buildkit
# 2025-11-12 01:32:00 0.00B 设置环境变量 VLLM_LMCACHE_VERSION
ENV VLLM_LMCACHE_VERSION=0.3.9post1
# 2025-11-12 01:32:00 0.00B 定义构建参数
ARG VLLM_LMCACHE_VERSION=0.3.9post1
# 2025-11-12 01:32:00 998.76MB 执行命令并创建新的镜像层
RUN |10 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 VLLM_NVIDIA_HPCX_VERSION=2.22.1rc4 VLLM_AWS_EFA_VERSION=1.43.3 CMAKE_MAX_JOBS= VLLM_NVIDIA_NVSHMEM_VERSION=3.4.5 VLLM_TORCH_VERSION=2.8.0 VLLM_TORCH_CUDA_VERSION=12.8.1 VLLM_VERSION=0.11.0 /bin/bash -eo pipefail -c # FlashAttention
if [[ ! -d /flashattention/workspace ]]; then
echo "Skipping FlashAttention installation for ${TARGETARCH}..."
exit 0
fi
# Install
uv pip install --no-build-isolation \
/flashattention/workspace/*.whl
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/*
# buildkit
# 2025-11-11 13:44:41 53.90MB 执行命令并创建新的镜像层
RUN |10 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 VLLM_NVIDIA_HPCX_VERSION=2.22.1rc4 VLLM_AWS_EFA_VERSION=1.43.3 CMAKE_MAX_JOBS= VLLM_NVIDIA_NVSHMEM_VERSION=3.4.5 VLLM_TORCH_VERSION=2.8.0 VLLM_TORCH_CUDA_VERSION=12.8.1 VLLM_VERSION=0.11.0 /bin/bash -eo pipefail -c # DeepEP
if [[ ! -d /deepep/workspace ]]; then
echo "Skipping DeepEP installation for ${TARGETARCH}..."
exit 0
fi
# Install
uv pip install --no-build-isolation \
/deepep/workspace/*.whl
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/*
# buildkit
# 2025-11-11 13:44:41 119.84MB 执行命令并创建新的镜像层
RUN |10 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 VLLM_NVIDIA_HPCX_VERSION=2.22.1rc4 VLLM_AWS_EFA_VERSION=1.43.3 CMAKE_MAX_JOBS= VLLM_NVIDIA_NVSHMEM_VERSION=3.4.5 VLLM_TORCH_VERSION=2.8.0 VLLM_TORCH_CUDA_VERSION=12.8.1 VLLM_VERSION=0.11.0 /bin/bash -eo pipefail -c # PPLX Kernels
if [[ ! -d /pplx-kernels/workspace ]]; then
echo "Skipping PPLX Kernels installation for ${TARGETARCH}..."
exit 0
fi
# Install
uv pip install --no-build-isolation \
/pplx-kernels/workspace/*.whl
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/*
# buildkit
# 2025-11-11 13:44:40 43.15MB 执行命令并创建新的镜像层
RUN |10 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 VLLM_NVIDIA_HPCX_VERSION=2.22.1rc4 VLLM_AWS_EFA_VERSION=1.43.3 CMAKE_MAX_JOBS= VLLM_NVIDIA_NVSHMEM_VERSION=3.4.5 VLLM_TORCH_VERSION=2.8.0 VLLM_TORCH_CUDA_VERSION=12.8.1 VLLM_VERSION=0.11.0 /bin/bash -eo pipefail -c # DeepGEMM
if [[ ! -d /deepgemm/workspace ]]; then
echo "Skipping DeepGEMM installation for ${TARGETARCH}..."
exit 0
fi
# Install
uv pip install --no-build-isolation \
/deepgemm/workspace/*.whl
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/*
# buildkit
# 2025-11-11 13:44:40 4.15GB 执行命令并创建新的镜像层
RUN |10 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 VLLM_NVIDIA_HPCX_VERSION=2.22.1rc4 VLLM_AWS_EFA_VERSION=1.43.3 CMAKE_MAX_JOBS= VLLM_NVIDIA_NVSHMEM_VERSION=3.4.5 VLLM_TORCH_VERSION=2.8.0 VLLM_TORCH_CUDA_VERSION=12.8.1 VLLM_VERSION=0.11.0 /bin/bash -eo pipefail -c # FlashInfer
if [[ ! -d /flashinfer/workspace ]]; then
echo "Skipping FlashInfer installation for ${TARGETARCH}..."
exit 0
fi
# Install
uv pip install --no-build-isolation \
/flashinfer/workspace/*.whl
CMAKE_MAX_JOBS="${CMAKE_MAX_JOBS}"
if [[ -z "${CMAKE_MAX_JOBS}" ]]; then
CMAKE_MAX_JOBS="$(( $(nproc) / 2 ))"
fi
if (( $(echo "${CMAKE_MAX_JOBS} > 8" | bc -l) )); then
CMAKE_MAX_JOBS="8"
fi
# Download pre-compiled cubins
export FLASHINFER_CUBIN_DOWNLOAD_THREADS="${CMAKE_MAX_JOBS}"
export FLASHINFER_LOGGING_LEVEL=warning
python -m flashinfer --download-cubin
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/*
# buildkit
# 2025-11-11 09:23:48 2.82GB 执行命令并创建新的镜像层
RUN |10 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 VLLM_NVIDIA_HPCX_VERSION=2.22.1rc4 VLLM_AWS_EFA_VERSION=1.43.3 CMAKE_MAX_JOBS= VLLM_NVIDIA_NVSHMEM_VERSION=3.4.5 VLLM_TORCH_VERSION=2.8.0 VLLM_TORCH_CUDA_VERSION=12.8.1 VLLM_VERSION=0.11.0 /bin/bash -eo pipefail -c # vLLM
CMAKE_MAX_JOBS="${CMAKE_MAX_JOBS}"
if [[ -z "${CMAKE_MAX_JOBS}" ]]; then
CMAKE_MAX_JOBS="$(( $(nproc) / 2 ))"
fi
if (( $(echo "${CMAKE_MAX_JOBS} > 8" | bc -l) )); then
CMAKE_MAX_JOBS="8"
fi
VL_CUDA_ARCHS="${CUDA_ARCHS}"
if [[ -z "${VL_CUDA_ARCHS}" ]]; then
if (( $(echo "${CUDA_MAJOR} < 12" | bc -l) )); then
VL_CUDA_ARCHS="7.5 8.0+PTX 8.9"
elif (( $(echo "${CUDA_MAJOR}.${CUDA_MINOR} < 12.8" | bc -l) )); then
VL_CUDA_ARCHS="7.5 8.0+PTX 8.9 9.0"
else
VL_CUDA_ARCHS="7.5 8.0+PTX 8.9 9.0 10.0+PTX 12.0+PTX"
fi
fi
export MAX_JOBS="${CMAKE_MAX_JOBS}"
export TORCH_CUDA_ARCH_LIST="${VL_CUDA_ARCHS}"
export COMPILE_CUSTOM_KERNELS=1
export NVCC_THREADS=1
# Install
IFS="." read -r CUDA_MAJOR CUDA_MINOR CUDA_PATCH <<< "${VLLM_TORCH_CUDA_VERSION}"
if [[ "${TARGETARCH}" == "amd64" ]]; then
uv pip install --verbose --extra-index-url https://download.pytorch.org/whl/cu${CUDA_MAJOR}${CUDA_MINOR} \
vllm==${VLLM_VERSION}
else
uv pip install --verbose --extra-index-url https://download.pytorch.org/whl/cpu/ \
vllm==${VLLM_VERSION}
fi
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/* \
&& ccache --clear --clean
# buildkit
# 2025-11-11 09:23:29 0.00B 设置环境变量 VLLM_VERSION
ENV VLLM_VERSION=0.11.0
# 2025-11-11 09:23:29 0.00B 定义构建参数
ARG VLLM_VERSION=0.11.0
# 2025-11-11 09:23:29 0.00B 定义构建参数
ARG CMAKE_MAX_JOBS
# 2025-11-11 09:23:29 0.00B 定义构建参数
ARG TARGETARCH=amd64
# 2025-11-11 09:23:29 0.00B 定义构建参数
ARG TARGETOS=linux
# 2025-11-11 09:23:29 0.00B 定义构建参数
ARG TARGETPLATFORM=linux/amd64
# 2025-11-11 09:23:29 0.00B
SHELL [/bin/bash -eo pipefail -c]
# 2025-11-11 09:23:29 6.92GB 执行命令并创建新的镜像层
RUN |9 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 VLLM_NVIDIA_HPCX_VERSION=2.22.1rc4 VLLM_AWS_EFA_VERSION=1.43.3 CMAKE_MAX_JOBS= VLLM_NVIDIA_NVSHMEM_VERSION=3.4.5 VLLM_TORCH_VERSION=2.8.0 VLLM_TORCH_CUDA_VERSION=12.8.1 /bin/bash -eo pipefail -c # Torch
# Install
cat <<EOT >/tmp/requirements.txt
torch==${VLLM_TORCH_VERSION}
torchvision
torchaudio
EOT
IFS="." read -r CUDA_MAJOR CUDA_MINOR CUDA_PATCH <<< "${VLLM_TORCH_CUDA_VERSION}"
if [[ "${TARGETARCH}" == "amd64" ]]; then
uv pip install --index-url https://download.pytorch.org/whl/cu${CUDA_MAJOR}${CUDA_MINOR} \
-r /tmp/requirements.txt
else
uv pip install --extra-index-url https://download.pytorch.org/whl/cpu/ \
-r /tmp/requirements.txt
fi
uv pip install \
numpy scipy
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/*
# buildkit
# 2025-11-11 09:22:49 0.00B 设置环境变量 VLLM_TORCH_VERSION VLLM_TORCH_CUDA_VERSION
ENV VLLM_TORCH_VERSION=2.8.0 VLLM_TORCH_CUDA_VERSION=12.8.1
# 2025-11-11 09:22:49 0.00B 定义构建参数
ARG VLLM_TORCH_CUDA_VERSION=12.8.1
# 2025-11-11 09:22:49 0.00B 定义构建参数
ARG VLLM_TORCH_VERSION=2.8.0
# 2025-11-11 09:22:49 409.96MB 执行命令并创建新的镜像层
RUN |7 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 VLLM_NVIDIA_HPCX_VERSION=2.22.1rc4 VLLM_AWS_EFA_VERSION=1.43.3 CMAKE_MAX_JOBS= VLLM_NVIDIA_NVSHMEM_VERSION=3.4.5 /bin/bash -eo pipefail -c # NVIDIA NVSHMEM
IFS="." read -r CUDA_MAJOR CUDA_MINOR CUDA_PATCH <<< "${CUDA_VERSION}"
# Download
mkdir -p /tmp/nvshmem
if (( $(echo "${CUDA_MAJOR} > 12" | bc -l) )); then
curl --retry 3 --retry-connrefused -fL "https://github.com/NVIDIA/nvshmem/releases/download/v${VLLM_NVIDIA_NVSHMEM_VERSION}-0/nvshmem_src_cuda-all-all-${VLLM_NVIDIA_NVSHMEM_VERSION}.tar.gz" | tar -zxv -C /tmp
else
curl --retry 3 --retry-connrefused -fL "https://developer.download.nvidia.com/compute/redist/nvshmem/${VLLM_NVIDIA_NVSHMEM_VERSION}/source/nvshmem_src_cuda12-all-all-${VLLM_NVIDIA_NVSHMEM_VERSION}.tar.gz" | tar -zxv -C /tmp
fi
# Build
CMAKE_MAX_JOBS="${CMAKE_MAX_JOBS}"
if [[ -z "${CMAKE_MAX_JOBS}" ]]; then
CMAKE_MAX_JOBS="$(( $(nproc) / 2 ))"
fi
if (( $(echo "${CMAKE_MAX_JOBS} > 8" | bc -l) )); then
CMAKE_MAX_JOBS="8"
fi
NS_CUDA_ARCHS="${CUDA_ARCHS}"
if [[ -z "${NS_CUDA_ARCHS}" ]]; then
if (( $(echo "${CUDA_MAJOR} < 12" | bc -l) )); then
NS_CUDA_ARCHS="7.5 8.0 8.9"
elif (( $(echo "${CUDA_MAJOR}.${CUDA_MINOR} < 12.8" | bc -l) )); then
NS_CUDA_ARCHS="7.5 8.0 8.9 9.0"
else
NS_CUDA_ARCHS="7.5 8.0 8.9 9.0 10.0 10.3 12.0"
fi
fi
export MAX_JOBS="${CMAKE_MAX_JOBS}"
export CUDA_ARCH="${NS_CUDA_ARCHS}"
export NVSHMEM_IBGDA_SUPPORT=1
export NVSHMEM_USE_GDRCOPY=1
export NVSHMEM_SHMEM_SUPPORT=0
export NVSHMEM_UCX_SUPPORT=0
export NVSHMEM_USE_NCCL=0
export NVSHMEM_PMIX_SUPPORT=0
export NVSHMEM_TIMEOUT_DEVICE_POLLING=0
export NVSHMEM_IBRC_SUPPORT=0
export NVSHMEM_BUILD_TESTS=0
export NVSHMEM_BUILD_EXAMPLES=0
export NVSHMEM_MPI_SUPPORT=0
export NVSHMEM_BUILD_HYDRA_LAUNCHER=0
export NVSHMEM_BUILD_TXZ_PACKAGE=0
export NVSHMEM_TIMEOUT_DEVICE_POLLING=0
export NVCC_THREADS=1
echo "Building NVSHMEM with the following environment variables:"
env
# FIX: Hide Python3.10 to avoid issues with Python version mismatch.
PYTHON3_10_BIN=$(which python3.10 || true)
if [[ -n "${PYTHON3_10_BIN}" ]]; then
mv "${PYTHON3_10_BIN}" /tmp/python3.10
fi
pushd /tmp/nvshmem_src \
&& cmake -G Ninja -S . -B build -DCMAKE_INSTALL_PREFIX=${VLLM_NVIDIA_NVSHMEM_DIR} \
&& cmake --build build --target install -j${MAX_JOBS}
if [[ -n "${PYTHON3_10_BIN}" ]]; then
mv /tmp/python3.10 "${PYTHON3_10_BIN}"
fi
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/*
# buildkit
# 2025-11-11 08:53:39 0.00B 设置环境变量 VLLM_NVIDIA_NVSHMEM_VERSION VLLM_NVIDIA_NVSHMEM_DIR
ENV VLLM_NVIDIA_NVSHMEM_VERSION=3.4.5 VLLM_NVIDIA_NVSHMEM_DIR=/usr/local/nvshmem
# 2025-11-11 08:53:39 0.00B 定义构建参数
ARG VLLM_NVIDIA_NVSHMEM_VERSION=3.4.5
# 2025-11-11 08:53:39 0.00B 定义构建参数
ARG CMAKE_MAX_JOBS
# 2025-11-11 08:53:39 0.00B 设置环境变量 PATH
ENV PATH=/usr/local/mpi/bin:/usr/local/ucx/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/opt/amazon/efa/bin
# 2025-11-11 08:53:39 46.36MB 执行命令并创建新的镜像层
RUN |5 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 VLLM_NVIDIA_HPCX_VERSION=2.22.1rc4 VLLM_AWS_EFA_VERSION=1.43.3 /bin/bash -eo pipefail -c # AWS EFA
# Download
curl --retry 3 --retry-connrefused -fL "https://efa-installer.amazonaws.com/aws-efa-installer-${VLLM_AWS_EFA_VERSION}.tar.gz" | tar -zxv -C /tmp
# Install
pushd /tmp/aws-efa-installer && \
./efa_installer.sh -y --skip-kmod
# Prepare
rm /opt/amazon/efa/lib/libfabric.a || true
# Review
ldconfig -v
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/* \
&& rm -rf /var/cache/apt
# buildkit
# 2025-11-11 08:51:48 0.00B 设置环境变量 VLLM_AWS_EFA_VERSION
ENV VLLM_AWS_EFA_VERSION=1.43.3
# 2025-11-11 08:51:48 0.00B 定义构建参数
ARG VLLM_AWS_EFA_VERSION=1.43.3
# 2025-11-11 08:51:48 0.00B 设置环境变量 PATH OPAL_PREFIX OMPI_MCA_coll_hcoll_enable
ENV PATH=/usr/local/mpi/bin:/usr/local/ucx/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin OPAL_PREFIX=/opt/hpcx/ompi OMPI_MCA_coll_hcoll_enable=0
# 2025-11-11 08:51:48 1.44GB 执行命令并创建新的镜像层
RUN |4 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 VLLM_NVIDIA_HPCX_VERSION=2.22.1rc4 /bin/bash -eo pipefail -c # NVIDIA HPC-X
# Prepare
rm -f $(dpkg-query -L libibverbs-dev librdmacm-dev libibumad-dev | grep "\(\.so\|\.a\)$") || true
IFS="." read -r CUDA_MAJOR CUDA_MINOR CUDA_PATCH <<< "${CUDA_VERSION}"
source /etc/os-release
# Get Download Version
# If VLLM_NVIDIA_HPCX_VERSION=2.24.1_cuda13, VLLM_NVIDIA_HPCX_VERSION_DOWNLOAD=2.24.1
# If VLLM_NVIDIA_HPCX_VERSION=2.22.1rc4, VLLM_NVIDIA_HPCX_VERSION_DOWNLOAD=2.22.1
# If VLLM_NVIDIA_HPCX_VERSION=2.21.3, VLLM_NVIDIA_HPCX_VERSION_DOWNLOAD=2.21.3
if [[ "${VLLM_NVIDIA_HPCX_VERSION}" == *"_cuda"* ]]; then
VLLM_NVIDIA_HPCX_VERSION_DOWNLOAD=$(echo "${VLLM_NVIDIA_HPCX_VERSION}" | sed 's/_cuda.*//')
elif [[ "${VLLM_NVIDIA_HPCX_VERSION}" == *"rc"* ]]; then
VLLM_NVIDIA_HPCX_VERSION_DOWNLOAD=$(echo "${VLLM_NVIDIA_HPCX_VERSION}" | sed 's/rc.*//')
else
VLLM_NVIDIA_HPCX_VERSION_DOWNLOAD=${VLLM_NVIDIA_HPCX_VERSION}
fi
# Download
mkdir -p /opt/hpcx
curl --retry 3 --retry-connrefused -fL "https://content.mellanox.com/hpc/hpc-x/v${VLLM_NVIDIA_HPCX_VERSION}/hpcx-v${VLLM_NVIDIA_HPCX_VERSION_DOWNLOAD}-gcc-inbox-${ID}${VERSION_ID}-cuda${CUDA_MAJOR}-$(uname -m).tbz" | tar -jxv -C /opt/hpcx --strip-components 1
# Install
ln -sf /opt/hpcx/ompi /usr/local/mpi
ln -sf /opt/hpcx/ucx /usr/local/ucx
sed -i 's/^\(hwloc_base_binding_policy\) = core$/\1 = none/' /opt/hpcx/ompi/etc/openmpi-mca-params.conf
sed -i 's/^\(btl = self\)$/#\1/' /opt/hpcx/ompi/etc/openmpi-mca-params.conf
cat <<EOT > /etc/ld.so.conf.d/hpcx.conf
/opt/hpcx/clusterkit/lib
/opt/hpcx/hcoll/lib
/opt/hpcx/nccl_rdma_sharp_plugin/lib
/opt/hpcx/ncclnet_plugin/lib
/opt/hpcx/ompi/lib
/opt/hpcx/sharp/lib
/opt/hpcx/ucc/lib
/opt/hpcx/ucx/lib
EOT
# Fix DeepEP IBGDA symlink
ln -sf /usr/lib/$(uname -m)-linux-gnu/libmlx5.so.1 /usr/lib/$(uname -m)-linux-gnu/libmlx5.so || true
# Review
ldconfig -v
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/* \
&& rm -rf /var/cache/apt
# buildkit
# 2025-11-11 08:50:58 0.00B 设置环境变量 VLLM_NVIDIA_HPCX_VERSION
ENV VLLM_NVIDIA_HPCX_VERSION=2.22.1rc4
# 2025-11-11 08:50:58 0.00B 定义构建参数
ARG VLLM_NVIDIA_HPCX_VERSION=2.22.1rc4
# 2025-11-11 08:50:58 1.89MB 执行命令并创建新的镜像层
RUN |3 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 /bin/bash -eo pipefail -c # GDRCopy
if [[ ! -d /gdrcopy/workspace ]]; then
echo "Skipping GDRCopy installation for ${TARGETARCH}..."
exit 0
fi
# Install
dpkg -i /gdrcopy/workspace/libgdrapi_*.deb && \
ldconfig -v
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/* \
&& rm -rf /var/cache/apt
# buildkit
# 2025-11-11 08:50:58 0.00B 设置环境变量 UV_SYSTEM_PYTHON UV_PRERELEASE
ENV UV_SYSTEM_PYTHON=1 UV_PRERELEASE=allow
# 2025-11-11 08:50:58 0.00B 定义构建参数
ARG TARGETARCH=amd64
# 2025-11-11 08:50:58 0.00B 定义构建参数
ARG TARGETOS=linux
# 2025-11-11 08:50:58 0.00B 定义构建参数
ARG TARGETPLATFORM=linux/amd64
# 2025-11-11 08:50:58 0.00B
SHELL [/bin/bash -eo pipefail -c]
# 2025-11-10 12:18:57 0.00B 设置环境变量 CUDA_HOME CUDA_VERSION CUDA_ARCHS
ENV CUDA_HOME=/usr/local/cuda CUDA_VERSION=12.8.1 CUDA_ARCHS=
# 2025-11-10 12:18:57 0.00B 定义构建参数
ARG CUDA_ARCHS
# 2025-11-10 12:18:57 0.00B 定义构建参数
ARG CUDA_VERSION=12.8.1
# 2025-11-10 12:18:57 151.88MB 执行命令并创建新的镜像层
RUN |4 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 PYTHON_VERSION=3.12 /bin/bash -eo pipefail -c # Buildkit
cat <<EOT >/tmp/requirements.txt
build
cmake<4
ninja<1.11
setuptools<80
setuptools-scm
packaging<25
wheel==0.45.1
pybind11<3
Cython
psutil
pipx
uv
EOT
pip install -r /tmp/requirements.txt
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/*
# buildkit
# 2025-11-10 12:18:52 0.00B 设置环境变量 PIP_NO_CACHE_DIR PIP_DISABLE_PIP_VERSION_CHECK PIP_ROOT_USER_ACTION PIPX_HOME PIPX_LOCAL_VENVS UV_NO_CACHE UV_HTTP_TIMEOUT UV_INDEX_STRATEGY
ENV PIP_NO_CACHE_DIR=1 PIP_DISABLE_PIP_VERSION_CHECK=1 PIP_ROOT_USER_ACTION=ignore PIPX_HOME=/root/.local/share/pipx PIPX_LOCAL_VENVS=/root/.local/share/pipx/venvs UV_NO_CACHE=1 UV_HTTP_TIMEOUT=500 UV_INDEX_STRATEGY=unsafe-best-match
# 2025-11-10 12:18:52 90.36MB 执行命令并创建新的镜像层
RUN |4 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 PYTHON_VERSION=3.12 /bin/bash -eo pipefail -c # Python
if (( $(echo "$(python3 --version | cut -d' ' -f2 | cut -d'.' -f1,2) == ${PYTHON_VERSION}" | bc -l) )); then
echo "Skipping Python upgrade for ${PYTHON_VERSION}..."
if [[ -z "$(ldconfig -v 2>/dev/null | grep libpython${PYTHON_VERSION})" ]]; then
PYTHON_LIB_PREFIX=$(python3 -c "import sys; print(sys.base_prefix);")
echo "${PYTHON_LIB_PREFIX}/lib" >> /etc/ld.so.conf.d/python3.conf
echo "${PYTHON_LIB_PREFIX}/lib64" >> /etc/ld.so.conf.d/python3.conf
ldconfig -v
fi
exit 0
fi
# Add deadsnakes PPA for Python versions
for i in 1 2 3; do
add-apt-repository -y ppa:deadsnakes/ppa && break || { echo "Attempt $i failed, retrying in 5s..."; sleep 5; }
done
apt-get update -y
# Install
apt-get install -y --no-install-recommends \
python${PYTHON_VERSION} \
python${PYTHON_VERSION}-dev \
python${PYTHON_VERSION}-venv \
python${PYTHON_VERSION}-lib2to3 \
python${PYTHON_VERSION}-gdbm \
python${PYTHON_VERSION}-tk
if (( $(echo "${PYTHON_VERSION} <= 3.11" | bc -l) )); then
apt-get install -y --no-install-recommends \
python${PYTHON_VERSION}-distutils
fi
# Update alternatives
if [[ -f /etc/alternatives/python3 ]]; then update-alternatives --remove-all python3; fi; update-alternatives --install /usr/bin/python3 python3 /usr/bin/python${PYTHON_VERSION} 1
if [[ -f /etc/alternatives/python ]]; then update-alternatives --remove-all python; fi; update-alternatives --install /usr/bin/python python /usr/bin/python${PYTHON_VERSION} 1
curl -sS "https://bootstrap.pypa.io/get-pip.py" | python${PYTHON_VERSION}
if [[ -f /etc/alternatives/2to3 ]]; then update-alternatives --remove-all 2to3; fi; update-alternatives --install /usr/bin/2to3 2to3 /usr/bin/2to3${PYTHON_VERSION} 1 || true
if [[ -f /etc/alternatives/pydoc3 ]]; then update-alternatives --remove-all pydoc3; fi; update-alternatives --install /usr/bin/pydoc3 pydoc3 /usr/bin/pydoc${PYTHON_VERSION} 1 || true
if [[ -f /etc/alternatives/idle3 ]]; then update-alternatives --remove-all idle3; fi; update-alternatives --install /usr/bin/idle3 idle3 /usr/bin/idle${PYTHON_VERSION} 1 || true
if [[ -f /etc/alternatives/python3-config ]]; then update-alternatives --remove-all python3-config; fi; update-alternatives --install /usr/bin/python3-config python3-config /usr/bin/python${PYTHON_VERSION}-config 1 || true
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/* \
&& rm -rf /var/cache/apt
# buildkit
# 2025-11-10 12:17:13 0.00B 设置环境变量 PYTHON_VERSION
ENV PYTHON_VERSION=3.12
# 2025-11-10 12:17:13 0.00B 定义构建参数
ARG PYTHON_VERSION=3.12
# 2025-11-10 12:17:13 1.01GB 执行命令并创建新的镜像层
RUN |3 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 /bin/bash -eo pipefail -c # C buildkit
# Install
apt-get install -y --no-install-recommends \
make ninja-build pkg-config ccache
curl --retry 3 --retry-connrefused -fL "https://github.com/Kitware/CMake/releases/download/v3.31.7/cmake-3.31.7-linux-$(uname -m).tar.gz" | tar -zx -C /usr --strip-components 1
# Install dependencies
apt-get install -y --no-install-recommends \
perl-openssl-defaults perl yasm \
zlib1g zlib1g-dev libbz2-dev libffi-dev libgdbm-dev libgdbm-compat-dev \
openssl libssl-dev libsqlite3-dev lcov libomp-dev \
libblas-dev liblapack-dev libopenblas-dev libblas3 liblapack3 libhdf5-dev \
libxml2 libxslt1-dev libgl1-mesa-glx libgmpxx4ldbl \
libncurses5-dev libreadline6-dev libsqlite3-dev \
liblzma-dev lzma lzma-dev tk-dev uuid-dev libmpdec-dev \
ffmpeg libjpeg-dev libpng-dev libtiff-dev libwebp-dev \
libnuma1 libnuma-dev libjemalloc-dev \
libgrpc-dev libgrpc++-dev libprotobuf-dev protobuf-compiler protobuf-compiler-grpc \
libnl-route-3-200 libnl-3-200 libnl-3-dev libnl-route-3-dev \
libibverbs1 libibverbs-dev \
librdmacm1 librdmacm-dev \
libibumad3 libibumad-dev \
libtool \
ibverbs-utils ibverbs-providers libibverbs-dev
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/* \
&& rm -rf /var/cache/apt
# buildkit
# 2025-11-10 12:16:36 0.00B 执行命令并创建新的镜像层
RUN |3 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 /bin/bash -eo pipefail -c # GCC
# Upgrade GCC if the Ubuntu version is lower than 21.04.
source /etc/os-release
if (( $(echo "${VERSION_ID} >= 21.04" | bc -l) )); then
echo "Skipping GCC upgrade for ${VERSION_ID}..."
exit 0
fi
# Install
apt-get install -y --no-install-recommends \
gcc-11 g++-11 gfortran-11 gfortran
# Update alternatives
if [[ -f /etc/alternatives/gcov-dump ]]; then update-alternatives --remove-all gcov-dump; fi; update-alternatives --install /usr/bin/gcov-dump gcov-dump /usr/bin/gcov-dump-11 10
if [[ -f /etc/alternatives/lto-dump ]]; then update-alternatives --remove-all lto-dump; fi; update-alternatives --install /usr/bin/lto-dump lto-dump /usr/bin/lto-dump-11 10
if [[ -f /etc/alternatives/gcov ]]; then update-alternatives --remove-all gcov; fi; update-alternatives --install /usr/bin/gcov gcov /usr/bin/gcov-11 10
if [[ -f /etc/alternatives/gcc ]]; then update-alternatives --remove-all gcc; fi; update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-11 10
if [[ -f /etc/alternatives/gcc-nm ]]; then update-alternatives --remove-all gcc-nm; fi; update-alternatives --install /usr/bin/gcc-nm gcc-nm /usr/bin/gcc-nm-11 10
if [[ -f /etc/alternatives/cpp ]]; then update-alternatives --remove-all cpp; fi; update-alternatives --install /usr/bin/cpp cpp /usr/bin/cpp-11 10
if [[ -f /etc/alternatives/g++ ]]; then update-alternatives --remove-all g++; fi; update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-11 10
if [[ -f /etc/alternatives/gcc-ar ]]; then update-alternatives --remove-all gcc-ar; fi; update-alternatives --install /usr/bin/gcc-ar gcc-ar /usr/bin/gcc-ar-11 10
if [[ -f /etc/alternatives/gcov-tool ]]; then update-alternatives --remove-all gcov-tool; fi; update-alternatives --install /usr/bin/gcov-tool gcov-tool /usr/bin/gcov-tool-11 10
if [[ -f /etc/alternatives/gcc-ranlib ]]; then update-alternatives --remove-all gcc-ranlib; fi; update-alternatives --install /usr/bin/gcc-ranlib gcc-ranlib /usr/bin/gcc-ranlib-11 10
if [[ -f /etc/alternatives/gfortran ]]; then update-alternatives --remove-all gfortran; fi; update-alternatives --install /usr/bin/gfortran gfortran /usr/bin/gfortran-11 10
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/* \
&& rm -rf /var/cache/apt
# buildkit
# 2025-11-10 12:16:36 353.40MB 执行命令并创建新的镜像层
RUN |3 TARGETPLATFORM=linux/amd64 TARGETOS=linux TARGETARCH=amd64 /bin/bash -eo pipefail -c # Tools
# Refresh
apt-get update -y && apt-get install -y --no-install-recommends \
software-properties-common apt-transport-https \
ca-certificates gnupg2 lsb-release gnupg-agent \
&& apt-get update -y \
&& add-apt-repository -y ppa:ubuntu-toolchain-r/test \
&& apt-get update -y
# Install
apt-get install -y --no-install-recommends \
ca-certificates build-essential binutils bash openssl \
curl wget aria2 \
git git-lfs \
unzip xz-utils \
tzdata locales \
iproute2 iputils-ping ifstat net-tools dnsutils pciutils ipmitool \
rdma-core rdmacm-utils infiniband-diags \
procps sysstat htop \
tini vim jq bc tree
# Update locale
localedef -i en_US -c -f UTF-8 -A /usr/share/locale/locale.alias en_US.UTF-8
# Update timezone
rm -f /etc/localtime \
&& ln -sf /usr/share/zoneinfo/Asia/Shanghai /etc/localtime \
&& echo "Asia/Shanghai" > /etc/timezone \
&& dpkg-reconfigure --frontend noninteractive tzdata
# Cleanup
rm -rf /var/tmp/* \
&& rm -rf /tmp/* \
&& rm -rf /var/cache/apt
# buildkit
# 2025-11-10 12:16:36 0.00B 设置环境变量 DEBIAN_FRONTEND LANG LANGUAGE LC_ALL
ENV DEBIAN_FRONTEND=noninteractive LANG=en_US.UTF-8 LANGUAGE=en_US:en LC_ALL=en_US.UTF-8
# 2025-11-10 12:16:36 0.00B 定义构建参数
ARG TARGETARCH=amd64
# 2025-11-10 12:16:36 0.00B 定义构建参数
ARG TARGETOS=linux
# 2025-11-10 12:16:36 0.00B 定义构建参数
ARG TARGETPLATFORM=linux/amd64
# 2025-11-10 12:16:36 0.00B
SHELL [/bin/bash -eo pipefail -c]
# 2025-03-11 07:14:56 1.05GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends ${NV_CUDNN_PACKAGE} ${NV_CUDNN_PACKAGE_DEV} && apt-mark hold ${NV_CUDNN_PACKAGE_NAME} && rm -rf /var/lib/apt/lists/* # buildkit
# 2025-03-11 07:14:56 0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=9.8.0.87-1
# 2025-03-11 07:14:56 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2025-03-11 07:14:56 0.00B 定义构建参数
ARG TARGETARCH
# 2025-03-11 07:14:56 0.00B 设置环境变量 NV_CUDNN_PACKAGE_DEV
ENV NV_CUDNN_PACKAGE_DEV=libcudnn9-dev-cuda-12=9.8.0.87-1
# 2025-03-11 07:14:56 0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn9-cuda-12=9.8.0.87-1
# 2025-03-11 07:14:56 0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn9-cuda-12
# 2025-03-11 07:14:56 0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=9.8.0.87-1
# 2025-03-11 06:36:52 0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
# 2025-03-11 06:36:52 389.48KB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_DEV_PACKAGE_NAME} ${NV_LIBNCCL_DEV_PACKAGE_NAME} # buildkit
# 2025-03-11 06:36:52 5.94GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-cudart-dev-12-8=${NV_CUDA_CUDART_DEV_VERSION} cuda-command-line-tools-12-8=${NV_CUDA_LIB_VERSION} cuda-minimal-build-12-8=${NV_CUDA_LIB_VERSION} cuda-libraries-dev-12-8=${NV_CUDA_LIB_VERSION} cuda-nvml-dev-12-8=${NV_NVML_DEV_VERSION} ${NV_NVPROF_DEV_PACKAGE} ${NV_LIBNPP_DEV_PACKAGE} libcusparse-dev-12-8=${NV_LIBCUSPARSE_DEV_VERSION} ${NV_LIBCUBLAS_DEV_PACKAGE} ${NV_LIBNCCL_DEV_PACKAGE} ${NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE} && rm -rf /var/lib/apt/lists/* # buildkit
# 2025-03-11 06:36:52 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2025-03-11 06:36:52 0.00B 定义构建参数
ARG TARGETARCH
# 2025-03-11 06:36:52 0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE
ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.25.1-1+cuda12.8
# 2025-03-11 06:36:52 0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.25.1-1
# 2025-03-11 06:36:52 0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.25.1-1
# 2025-03-11 06:36:52 0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
# 2025-03-11 06:36:52 0.00B 设置环境变量 NV_NVPROF_DEV_PACKAGE
ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-8=12.8.90-1
# 2025-03-11 06:36:52 0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=12.8.90-1
# 2025-03-11 06:36:52 0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE
ENV NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-8=12.8.1-1
# 2025-03-11 06:36:52 0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_VERSION
ENV NV_CUDA_NSIGHT_COMPUTE_VERSION=12.8.1-1
# 2025-03-11 06:36:52 0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-8=12.8.4.1-1
# 2025-03-11 06:36:52 0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-8
# 2025-03-11 06:36:52 0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=12.8.4.1-1
# 2025-03-11 06:36:52 0.00B 设置环境变量 NV_LIBNPP_DEV_PACKAGE
ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-8=12.3.3.100-1
# 2025-03-11 06:36:52 0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=12.3.3.100-1
# 2025-03-11 06:36:52 0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=12.5.8.93-1
# 2025-03-11 06:36:52 0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=12.8.90-1
# 2025-03-11 06:36:52 0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=12.8.90-1
# 2025-03-11 06:36:52 0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.8.1-1
# 2025-03-11 06:24:31 0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
# 2025-03-11 06:24:31 0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
# 2025-03-11 06:24:31 2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
# 2025-03-11 06:24:31 3.06KB 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
# 2025-03-11 06:24:31 263.00KB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_PACKAGE_NAME} ${NV_LIBNCCL_PACKAGE_NAME} # buildkit
# 2025-03-11 06:24:31 3.11GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-libraries-12-8=${NV_CUDA_LIB_VERSION} ${NV_LIBNPP_PACKAGE} cuda-nvtx-12-8=${NV_NVTX_VERSION} libcusparse-12-8=${NV_LIBCUSPARSE_VERSION} ${NV_LIBCUBLAS_PACKAGE} ${NV_LIBNCCL_PACKAGE} && rm -rf /var/lib/apt/lists/* # buildkit
# 2025-03-11 06:24:31 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2025-03-11 06:24:31 0.00B 定义构建参数
ARG TARGETARCH
# 2025-03-11 06:24:31 0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.25.1-1+cuda12.8
# 2025-03-11 06:24:31 0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.25.1-1
# 2025-03-11 06:24:31 0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.25.1-1
# 2025-03-11 06:24:31 0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
# 2025-03-11 06:24:31 0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-12-8=12.8.4.1-1
# 2025-03-11 06:24:31 0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=12.8.4.1-1
# 2025-03-11 06:24:31 0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-8
# 2025-03-11 06:24:31 0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=12.5.8.93-1
# 2025-03-11 06:24:31 0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-12-8=12.3.3.100-1
# 2025-03-11 06:24:31 0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=12.3.3.100-1
# 2025-03-11 06:24:31 0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=12.8.90-1
# 2025-03-11 06:24:31 0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=12.8.1-1
# 2025-03-11 06:19:20 0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
# 2025-03-11 06:19:20 0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
# 2025-03-11 06:19:20 17.29KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
# 2025-03-11 06:19:20 0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/cuda/lib64
# 2025-03-11 06:19:20 0.00B 设置环境变量 PATH
ENV PATH=/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
# 2025-03-11 06:19:20 22.00B 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c echo "/usr/local/cuda/lib64" >> /etc/ld.so.conf.d/nvidia.conf # buildkit
# 2025-03-11 06:19:20 203.35MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-cudart-12-8=${NV_CUDA_CUDART_VERSION} cuda-compat-12-8 && rm -rf /var/lib/apt/lists/* # buildkit
# 2025-03-11 06:19:05 0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=12.8.1
# 2025-03-11 06:19:05 10.60MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends gnupg2 curl ca-certificates && curl -fsSLO https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/${NVARCH}/cuda-keyring_1.1-1_all.deb && dpkg -i cuda-keyring_1.1-1_all.deb && apt-get purge --autoremove -y curl && rm -rf /var/lib/apt/lists/* # buildkit
# 2025-03-11 06:19:05 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2025-03-11 06:19:05 0.00B 定义构建参数
ARG TARGETARCH
# 2025-03-11 06:19:05 0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=12.8.90-1
# 2025-03-11 06:19:05 0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand
ENV NVIDIA_REQUIRE_CUDA=cuda>=12.8 brand=unknown,driver>=470,driver<471 brand=grid,driver>=470,driver<471 brand=tesla,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=vapps,driver>=470,driver<471 brand=vpc,driver>=470,driver<471 brand=vcs,driver>=470,driver<471 brand=vws,driver>=470,driver<471 brand=cloudgaming,driver>=470,driver<471 brand=unknown,driver>=535,driver<536 brand=grid,driver>=535,driver<536 brand=tesla,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=vapps,driver>=535,driver<536 brand=vpc,driver>=535,driver<536 brand=vcs,driver>=535,driver<536 brand=vws,driver>=535,driver<536 brand=cloudgaming,driver>=535,driver<536 brand=unknown,driver>=550,driver<551 brand=grid,driver>=550,driver<551 brand=tesla,driver>=550,driver<551 brand=nvidia,driver>=550,driver<551 brand=quadro,driver>=550,driver<551 brand=quadrortx,driver>=550,driver<551 brand=nvidiartx,driver>=550,driver<551 brand=vapps,driver>=550,driver<551 brand=vpc,driver>=550,driver<551 brand=vcs,driver>=550,driver<551 brand=vws,driver>=550,driver<551 brand=cloudgaming,driver>=550,driver<551 brand=unknown,driver>=560,driver<561 brand=grid,driver>=560,driver<561 brand=tesla,driver>=560,driver<561 brand=nvidia,driver>=560,driver<561 brand=quadro,driver>=560,driver<561 brand=quadrortx,driver>=560,driver<561 brand=nvidiartx,driver>=560,driver<561 brand=vapps,driver>=560,driver<561 brand=vpc,driver>=560,driver<561 brand=vcs,driver>=560,driver<561 brand=vws,driver>=560,driver<561 brand=cloudgaming,driver>=560,driver<561 brand=unknown,driver>=565,driver<566 brand=grid,driver>=565,driver<566 brand=tesla,driver>=565,driver<566 brand=nvidia,driver>=565,driver<566 brand=quadro,driver>=565,driver<566 brand=quadrortx,driver>=565,driver<566 brand=nvidiartx,driver>=565,driver<566 brand=vapps,driver>=565,driver<566 brand=vpc,driver>=565,driver<566 brand=vcs,driver>=565,driver<566 brand=vws,driver>=565,driver<566 brand=cloudgaming,driver>=565,driver<566
# 2025-03-11 06:19:05 0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
# 2025-01-26 13:31:11 0.00B
/bin/sh -c #(nop) CMD ["/bin/bash"]
# 2025-01-26 13:31:10 77.86MB
/bin/sh -c #(nop) ADD file:1b6c8c9518be42fa2afe5e241ca31677fce58d27cdfa88baa91a65a259be3637 in /
# 2025-01-26 13:31:07 0.00B
/bin/sh -c #(nop) LABEL org.opencontainers.image.version=22.04
# 2025-01-26 13:31:07 0.00B
/bin/sh -c #(nop) LABEL org.opencontainers.image.ref.name=ubuntu
# 2025-01-26 13:31:07 0.00B
/bin/sh -c #(nop) ARG LAUNCHPAD_BUILD_ARCH
# 2025-01-26 13:31:07 0.00B
/bin/sh -c #(nop) ARG RELEASE
镜像信息
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],
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"Comment": "buildkit.dockerfile.v0",
"Created": "2025-11-12T03:33:05.478258465Z",
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"DockerVersion": "",
"Author": "",
"Config": {
"Hostname": "",
"Domainname": "",
"User": "",
"AttachStdin": false,
"AttachStdout": false,
"AttachStderr": false,
"Tty": false,
"OpenStdin": false,
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"Env": [
"PATH=/usr/local/mpi/bin:/usr/local/ucx/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/opt/amazon/efa/bin",
"NVARCH=x86_64",
"NVIDIA_REQUIRE_CUDA=cuda\u003e=12.8 brand=unknown,driver\u003e=470,driver\u003c471 brand=grid,driver\u003e=470,driver\u003c471 brand=tesla,driver\u003e=470,driver\u003c471 brand=nvidia,driver\u003e=470,driver\u003c471 brand=quadro,driver\u003e=470,driver\u003c471 brand=quadrortx,driver\u003e=470,driver\u003c471 brand=nvidiartx,driver\u003e=470,driver\u003c471 brand=vapps,driver\u003e=470,driver\u003c471 brand=vpc,driver\u003e=470,driver\u003c471 brand=vcs,driver\u003e=470,driver\u003c471 brand=vws,driver\u003e=470,driver\u003c471 brand=cloudgaming,driver\u003e=470,driver\u003c471 brand=unknown,driver\u003e=535,driver\u003c536 brand=grid,driver\u003e=535,driver\u003c536 brand=tesla,driver\u003e=535,driver\u003c536 brand=nvidia,driver\u003e=535,driver\u003c536 brand=quadro,driver\u003e=535,driver\u003c536 brand=quadrortx,driver\u003e=535,driver\u003c536 brand=nvidiartx,driver\u003e=535,driver\u003c536 brand=vapps,driver\u003e=535,driver\u003c536 brand=vpc,driver\u003e=535,driver\u003c536 brand=vcs,driver\u003e=535,driver\u003c536 brand=vws,driver\u003e=535,driver\u003c536 brand=cloudgaming,driver\u003e=535,driver\u003c536 brand=unknown,driver\u003e=550,driver\u003c551 brand=grid,driver\u003e=550,driver\u003c551 brand=tesla,driver\u003e=550,driver\u003c551 brand=nvidia,driver\u003e=550,driver\u003c551 brand=quadro,driver\u003e=550,driver\u003c551 brand=quadrortx,driver\u003e=550,driver\u003c551 brand=nvidiartx,driver\u003e=550,driver\u003c551 brand=vapps,driver\u003e=550,driver\u003c551 brand=vpc,driver\u003e=550,driver\u003c551 brand=vcs,driver\u003e=550,driver\u003c551 brand=vws,driver\u003e=550,driver\u003c551 brand=cloudgaming,driver\u003e=550,driver\u003c551 brand=unknown,driver\u003e=560,driver\u003c561 brand=grid,driver\u003e=560,driver\u003c561 brand=tesla,driver\u003e=560,driver\u003c561 brand=nvidia,driver\u003e=560,driver\u003c561 brand=quadro,driver\u003e=560,driver\u003c561 brand=quadrortx,driver\u003e=560,driver\u003c561 brand=nvidiartx,driver\u003e=560,driver\u003c561 brand=vapps,driver\u003e=560,driver\u003c561 brand=vpc,driver\u003e=560,driver\u003c561 brand=vcs,driver\u003e=560,driver\u003c561 brand=vws,driver\u003e=560,driver\u003c561 brand=cloudgaming,driver\u003e=560,driver\u003c561 brand=unknown,driver\u003e=565,driver\u003c566 brand=grid,driver\u003e=565,driver\u003c566 brand=tesla,driver\u003e=565,driver\u003c566 brand=nvidia,driver\u003e=565,driver\u003c566 brand=quadro,driver\u003e=565,driver\u003c566 brand=quadrortx,driver\u003e=565,driver\u003c566 brand=nvidiartx,driver\u003e=565,driver\u003c566 brand=vapps,driver\u003e=565,driver\u003c566 brand=vpc,driver\u003e=565,driver\u003c566 brand=vcs,driver\u003e=565,driver\u003c566 brand=vws,driver\u003e=565,driver\u003c566 brand=cloudgaming,driver\u003e=565,driver\u003c566",
"NV_CUDA_CUDART_VERSION=12.8.90-1",
"CUDA_VERSION=12.8.1",
"LD_LIBRARY_PATH=/usr/local/cuda/lib64",
"NVIDIA_VISIBLE_DEVICES=all",
"NVIDIA_DRIVER_CAPABILITIES=compute,utility",
"NV_CUDA_LIB_VERSION=12.8.1-1",
"NV_NVTX_VERSION=12.8.90-1",
"NV_LIBNPP_VERSION=12.3.3.100-1",
"NV_LIBNPP_PACKAGE=libnpp-12-8=12.3.3.100-1",
"NV_LIBCUSPARSE_VERSION=12.5.8.93-1",
"NV_LIBCUBLAS_PACKAGE_NAME=libcublas-12-8",
"NV_LIBCUBLAS_VERSION=12.8.4.1-1",
"NV_LIBCUBLAS_PACKAGE=libcublas-12-8=12.8.4.1-1",
"NV_LIBNCCL_PACKAGE_NAME=libnccl2",
"NV_LIBNCCL_PACKAGE_VERSION=2.25.1-1",
"NCCL_VERSION=2.25.1-1",
"NV_LIBNCCL_PACKAGE=libnccl2=2.25.1-1+cuda12.8",
"NVIDIA_PRODUCT_NAME=CUDA",
"NV_CUDA_CUDART_DEV_VERSION=12.8.90-1",
"NV_NVML_DEV_VERSION=12.8.90-1",
"NV_LIBCUSPARSE_DEV_VERSION=12.5.8.93-1",
"NV_LIBNPP_DEV_VERSION=12.3.3.100-1",
"NV_LIBNPP_DEV_PACKAGE=libnpp-dev-12-8=12.3.3.100-1",
"NV_LIBCUBLAS_DEV_VERSION=12.8.4.1-1",
"NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-12-8",
"NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-12-8=12.8.4.1-1",
"NV_CUDA_NSIGHT_COMPUTE_VERSION=12.8.1-1",
"NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-12-8=12.8.1-1",
"NV_NVPROF_VERSION=12.8.90-1",
"NV_NVPROF_DEV_PACKAGE=cuda-nvprof-12-8=12.8.90-1",
"NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev",
"NV_LIBNCCL_DEV_PACKAGE_VERSION=2.25.1-1",
"NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.25.1-1+cuda12.8",
"LIBRARY_PATH=/usr/local/cuda/lib64/stubs",
"NV_CUDNN_VERSION=9.8.0.87-1",
"NV_CUDNN_PACKAGE_NAME=libcudnn9-cuda-12",
"NV_CUDNN_PACKAGE=libcudnn9-cuda-12=9.8.0.87-1",
"NV_CUDNN_PACKAGE_DEV=libcudnn9-dev-cuda-12=9.8.0.87-1",
"DEBIAN_FRONTEND=noninteractive",
"LANG=en_US.UTF-8",
"LANGUAGE=en_US:en",
"LC_ALL=en_US.UTF-8",
"PYTHON_VERSION=3.12",
"PIP_NO_CACHE_DIR=1",
"PIP_DISABLE_PIP_VERSION_CHECK=1",
"PIP_ROOT_USER_ACTION=ignore",
"PIPX_HOME=/root/.local/share/pipx",
"PIPX_LOCAL_VENVS=/root/.local/share/pipx/venvs",
"UV_NO_CACHE=1",
"UV_HTTP_TIMEOUT=500",
"UV_INDEX_STRATEGY=unsafe-best-match",
"CUDA_HOME=/usr/local/cuda",
"CUDA_ARCHS=",
"UV_SYSTEM_PYTHON=1",
"UV_PRERELEASE=allow",
"VLLM_NVIDIA_HPCX_VERSION=2.22.1rc4",
"OPAL_PREFIX=/opt/hpcx/ompi",
"OMPI_MCA_coll_hcoll_enable=0",
"VLLM_AWS_EFA_VERSION=1.43.3",
"VLLM_NVIDIA_NVSHMEM_VERSION=3.4.5",
"VLLM_NVIDIA_NVSHMEM_DIR=/usr/local/nvshmem",
"VLLM_TORCH_VERSION=2.8.0",
"VLLM_TORCH_CUDA_VERSION=12.8.1",
"VLLM_VERSION=0.11.0",
"VLLM_LMCACHE_VERSION=0.3.9post1",
"RAY_EXPERIMENTAL_NOSET_CUDA_VISIBLE_DEVICES=1",
"SGLANG_VERSION=0.5.5",
"SGLANG_KERNEL_VERSION=0.3.16.post5"
],
"Cmd": null,
"Image": "",
"Volumes": null,
"WorkingDir": "/",
"Entrypoint": [
"tini",
"--"
],
"OnBuild": null,
"Labels": {
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"maintainer": "NVIDIA CORPORATION \u003ccudatools@nvidia.com\u003e",
"org.opencontainers.image.ref.name": "ubuntu",
"org.opencontainers.image.version": "22.04"
},
"Shell": [
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"-eo",
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"-c"
]
},
"Architecture": "amd64",
"Os": "linux",
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