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Author SHA1 Message Date
khluuandClaude Opus 4.6 5d236e5cf8 [Bugfix] Add MigCudaPlatform to avoid CUDA init before fork
NonNvmlCudaPlatform uses torch.cuda for get_device_capability(),
which initializes the CUDA context. When this runs at import time
(e.g. via requires_fp8 in test utils), it prevents fork-based tests
from working ("Cannot re-initialize CUDA in forked subprocess").

MigCudaPlatform inherits from NvmlCudaPlatform (NVML-based capability
queries don't init CUDA) and only overrides the memory methods that
fail on MIG partitions.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Signed-off-by: khluu <khluu000@gmail.com>
2026-04-16 11:49:08 -07:00
khluu f683266536 lint
Signed-off-by: khluu <khluu000@gmail.com>
2026-04-16 02:35:54 -07:00
khluuandClaude Opus 4.6 8dde2576c0 [Bugfix] Disable expandable_segments on MIG to fix PyTorch NVML assert
The previous commit added MIG detection to use NonNvmlCudaPlatform, which
fixes vllm's own NVML calls. However, PyTorch's CUDACachingAllocator has
a separate NVML code path via the expandable_segments feature that still
crashes with "NVML_SUCCESS == r INTERNAL ASSERT FAILED" on MIG devices.

This change automatically sets PYTORCH_CUDA_ALLOC_CONF=expandable_segments:False
when a MIG device is detected, so PyTorch's allocator falls back to non-NVML
memory management and real torch.cuda.OutOfMemoryError surfaces instead of
the misleading NVML assert.

Signed-off-by: khluu <khluu000@gmail.com>
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-15 16:09:29 -07:00
khluuandClaude Opus 4.6 ae60bf5ea7 [Bugfix] Use NonNvmlCudaPlatform on MIG devices to fix NVML masking OOM errors
On MIG partitions, NVML device-level queries fail with NVMLError_NoPermission.
This causes PyTorch's CUDACachingAllocator (via expandable_segments) to crash
with an internal assert before the real torch.cuda.OutOfMemoryError can surface,
and causes NVML memory queries to report the full GPU's memory (e.g. 141 GB for
H200) instead of the MIG partition's memory (e.g. 16 GB).

This change:
1. Adds MIG detection in vllm/platforms/cuda.py that checks CUDA_VISIBLE_DEVICES
   for MIG UUIDs and probes NVML for permission errors, then falls back to
   NonNvmlCudaPlatform which uses torch.cuda APIs that correctly report MIG
   partition memory.
2. Patches test utilities (wait_for_gpu_memory_to_clear, _get_gpu_memory_used)
   to fall back to torch.cuda.mem_get_info() when NVML fails with permission
   errors on MIG.

Signed-off-by: khluu <khluu000@gmail.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-14 23:44:59 -07:00
4 changed files with 474 additions and 359 deletions
+345 -348
View File
@@ -1,7 +1,9 @@
steps:
# =============================================================================
# Build Python Wheels (runs on every pipeline trigger)
# =============================================================================
- input: "Provide Release version here"
id: input-release-version
fields:
- text: "What is the release version?"
key: release-version
- group: "Build Python wheels"
key: "build-wheels"
@@ -96,257 +98,8 @@ steps:
commands:
- "bash .buildkite/scripts/generate-and-upload-nightly-index.sh"
# =============================================================================
# ROCm Wheel Pipeline (runs on every pipeline trigger)
# =============================================================================
# ROCm Job 1: Build ROCm Base Wheels (with S3 caching)
- label: ":rocm: Build ROCm Base Image & Wheels"
id: build-rocm-base-wheels
depends_on: ~
agents:
queue: cpu_queue_release
commands:
- |
set -euo pipefail
# Generate cache key
CACHE_KEY=$$(.buildkite/scripts/cache-rocm-base-wheels.sh key)
ECR_CACHE_TAG="public.ecr.aws/q9t5s3a7/vllm-release-repo:$${CACHE_KEY}-rocm-base"
echo "========================================"
echo "ROCm Base Build Configuration"
echo "========================================"
echo " CACHE_KEY: $${CACHE_KEY}"
echo " ECR_CACHE_TAG: $${ECR_CACHE_TAG}"
echo "========================================"
# Login to ECR
aws ecr-public get-login-password --region us-east-1 | \
docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7
IMAGE_EXISTS=false
WHEELS_EXIST=false
# Check ECR for Docker image
if docker manifest inspect "$${ECR_CACHE_TAG}" > /dev/null 2>&1; then
IMAGE_EXISTS=true
echo "ECR image cache HIT"
fi
# Check S3 for wheels
WHEEL_CACHE_STATUS=$(.buildkite/scripts/cache-rocm-base-wheels.sh check)
if [ "$${WHEEL_CACHE_STATUS}" = "hit" ]; then
WHEELS_EXIST=true
echo "S3 wheels cache HIT"
fi
# Scenario 1: Both cached (best case)
if [ "$${IMAGE_EXISTS}" = "true" ] && [ "$${WHEELS_EXIST}" = "true" ]; then
echo ""
echo "FULL CACHE HIT - Reusing both image and wheels"
echo ""
# Download wheels
.buildkite/scripts/cache-rocm-base-wheels.sh download
# Save ECR tag for downstream jobs
buildkite-agent meta-data set "rocm-base-image-tag" "$${ECR_CACHE_TAG}"
# Scenario 2: Full rebuild needed
else
echo ""
echo " CACHE MISS - Building from scratch..."
echo ""
# Build full base image and push to ECR
DOCKER_BUILDKIT=1 docker buildx build \
--file docker/Dockerfile.rocm_base \
--tag "$${ECR_CACHE_TAG}" \
--build-arg USE_SCCACHE=1 \
--build-arg SCCACHE_BUCKET_NAME=vllm-build-sccache \
--build-arg SCCACHE_REGION_NAME=us-west-2 \
--build-arg SCCACHE_S3_NO_CREDENTIALS=0 \
--push \
.
# Build wheel extraction stage
DOCKER_BUILDKIT=1 docker buildx build \
--file docker/Dockerfile.rocm_base \
--tag rocm-base-debs:$${BUILDKITE_BUILD_NUMBER} \
--target debs_wheel_release \
--build-arg USE_SCCACHE=1 \
--build-arg SCCACHE_BUCKET_NAME=vllm-build-sccache \
--build-arg SCCACHE_REGION_NAME=us-west-2 \
--build-arg SCCACHE_S3_NO_CREDENTIALS=0 \
--load \
.
# Extract and upload wheels
mkdir -p artifacts/rocm-base-wheels
cid=$(docker create rocm-base-debs:$${BUILDKITE_BUILD_NUMBER})
docker cp $${cid}:/app/debs/. artifacts/rocm-base-wheels/
docker rm $${cid}
.buildkite/scripts/cache-rocm-base-wheels.sh upload
# Cache base docker image to ECR
docker push "$${ECR_CACHE_TAG}"
buildkite-agent meta-data set "rocm-base-image-tag" "$${ECR_CACHE_TAG}"
echo ""
echo " Build complete - Image and wheels cached"
fi
artifact_paths:
- "artifacts/rocm-base-wheels/*.whl"
env:
DOCKER_BUILDKIT: "1"
S3_BUCKET: "vllm-wheels"
# ROCm Job 2: Build vLLM ROCm Wheel
- label: ":python: Build vLLM ROCm Wheel - x86_64"
id: build-rocm-vllm-wheel
depends_on:
- step: build-rocm-base-wheels
allow_failure: false
agents:
queue: cpu_queue_release
timeout_in_minutes: 180
commands:
# Download artifacts and prepare Docker image
- |
set -euo pipefail
# Ensure git tags are up-to-date (Buildkite's default fetch doesn't update tags)
# This fixes version detection when tags are moved/force-pushed
echo "Fetching latest tags from origin..."
git fetch --tags --force origin
# Log tag information for debugging version detection
echo "========================================"
echo "Git Tag Verification"
echo "========================================"
echo "Current HEAD: $(git rev-parse HEAD)"
echo "git describe --tags: $(git describe --tags 2>/dev/null || echo 'No tags found')"
echo ""
echo "Recent tags (pointing to commits near HEAD):"
git tag -l --sort=-creatordate | head -5
echo "setuptools_scm version detection:"
pip install -q setuptools_scm 2>/dev/null || true
python3 -c "import setuptools_scm; print(' Detected version:', setuptools_scm.get_version())" 2>/dev/null || echo " (setuptools_scm not available in this environment)"
echo "========================================"
# Download wheel artifacts from current build
echo "Downloading wheel artifacts from current build"
buildkite-agent artifact download "artifacts/rocm-base-wheels/*.whl" .
# Get ECR image tag from metadata (set by build-rocm-base-wheels)
ECR_IMAGE_TAG="$$(buildkite-agent meta-data get rocm-base-image-tag 2>/dev/null || echo '')"
if [ -z "$${ECR_IMAGE_TAG}" ]; then
echo "ERROR: rocm-base-image-tag metadata not found"
echo "This should have been set by the build-rocm-base-wheels job"
exit 1
fi
echo "Pulling base Docker image from ECR: $${ECR_IMAGE_TAG}"
# Login to ECR
aws ecr-public get-login-password --region us-east-1 | \
docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7
# Pull base Docker image from ECR
docker pull "$${ECR_IMAGE_TAG}"
echo "Loaded base image: $${ECR_IMAGE_TAG}"
# Prepare base wheels for Docker build context
mkdir -p docker/context/base-wheels
touch docker/context/base-wheels/.keep
cp artifacts/rocm-base-wheels/*.whl docker/context/base-wheels/
echo "Base wheels for vLLM build:"
ls -lh docker/context/base-wheels/
echo "========================================"
echo "Building vLLM wheel with:"
echo " BUILDKITE_COMMIT: $${BUILDKITE_COMMIT}"
echo " BUILDKITE_BRANCH: $${BUILDKITE_BRANCH}"
echo " BASE_IMAGE: $${ECR_IMAGE_TAG}"
echo "========================================"
# Build vLLM wheel using local checkout (REMOTE_VLLM=0)
DOCKER_BUILDKIT=1 docker build \
--file docker/Dockerfile.rocm \
--target export_vllm_wheel_release \
--output type=local,dest=rocm-dist \
--build-arg BASE_IMAGE="$${ECR_IMAGE_TAG}" \
--build-arg REMOTE_VLLM=0 \
--build-arg GIT_REPO_CHECK=1 \
--build-arg USE_SCCACHE=1 \
--build-arg SCCACHE_BUCKET_NAME=vllm-build-sccache \
--build-arg SCCACHE_REGION_NAME=us-west-2 \
--build-arg SCCACHE_S3_NO_CREDENTIALS=0 \
.
echo "Built vLLM wheel:"
ls -lh rocm-dist/*.whl
# Copy wheel to artifacts directory
mkdir -p artifacts/rocm-vllm-wheel
cp rocm-dist/*.whl artifacts/rocm-vllm-wheel/
echo "Final vLLM wheel:"
ls -lh artifacts/rocm-vllm-wheel/
artifact_paths:
- "artifacts/rocm-vllm-wheel/*.whl"
env:
DOCKER_BUILDKIT: "1"
S3_BUCKET: "vllm-wheels"
# ROCm Job 3: Upload Wheels to S3
- label: ":s3: Upload ROCm Wheels to S3"
id: upload-rocm-wheels
depends_on:
- step: build-rocm-vllm-wheel
allow_failure: false
agents:
queue: cpu_queue_release
timeout_in_minutes: 60
commands:
# Download all wheel artifacts and run upload
- |
set -euo pipefail
# Download artifacts from current build
echo "Downloading artifacts from current build"
buildkite-agent artifact download "artifacts/rocm-base-wheels/*.whl" .
buildkite-agent artifact download "artifacts/rocm-vllm-wheel/*.whl" .
# Run upload script
bash .buildkite/scripts/upload-rocm-wheels.sh
env:
DOCKER_BUILDKIT: "1"
S3_BUCKET: "vllm-wheels"
# ROCm Job 4: Annotate ROCm Wheel Release
- label: ":memo: Annotate ROCm wheel release"
id: annotate-rocm-release
depends_on:
- upload-rocm-wheels
agents:
queue: cpu_queue_release
commands:
- "bash .buildkite/scripts/annotate-rocm-release.sh"
env:
S3_BUCKET: "vllm-wheels"
# =============================================================================
# Nightly: Build & Publish Docker Images (NIGHTLY=1 only)
# =============================================================================
- group: "Build nightly Docker images"
- group: "Build release Docker images"
key: "build-release-images"
if: build.env("NIGHTLY") == "1"
steps:
- label: "Build release image - x86_64 - CUDA 12.9"
depends_on: ~
@@ -439,9 +192,44 @@ steps:
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=13.0.1 --build-arg UBUNTU_VERSION=24.04 --build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 --build-arg FLASHINFER_AOT_COMPILE=true --build-arg torch_cuda_arch_list='8.7 8.9 9.0 10.0+PTX 12.0 12.1' --build-arg INSTALL_KV_CONNECTORS=true --build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.1-devel-ubuntu24.04 --tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu130-ubuntu2404 --target vllm-openai --progress plain -f docker/Dockerfile ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu130-ubuntu2404"
- group: "Publish nightly images"
- block: "Build release image for x86_64 CPU"
key: block-cpu-release-image-build
depends_on: ~
- label: "Build release image - x86_64 - CPU"
depends_on:
- block-cpu-release-image-build
- input-release-version
agents:
queue: cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg GIT_REPO_CHECK=1 --build-arg VLLM_CPU_X86=true --tag public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:$(buildkite-agent meta-data get release-version) --tag public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:latest --progress plain --target vllm-openai -f docker/Dockerfile.cpu ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:latest"
- "docker push public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:$(buildkite-agent meta-data get release-version)"
env:
DOCKER_BUILDKIT: "1"
- block: "Build release image for arm64 CPU"
key: block-arm64-cpu-release-image-build
depends_on: ~
- label: "Build release image - arm64 - CPU"
depends_on:
- block-arm64-cpu-release-image-build
- input-release-version
agents:
queue: arm64_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg GIT_REPO_CHECK=1 --tag public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:$(buildkite-agent meta-data get release-version) --tag public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:latest --progress plain --target vllm-openai -f docker/Dockerfile.cpu ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:latest"
- "docker push public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:$(buildkite-agent meta-data get release-version)"
env:
DOCKER_BUILDKIT: "1"
- group: "Publish release images"
key: "publish-release-images"
if: build.env("NIGHTLY") == "1"
steps:
- label: "Create multi-arch manifest - CUDA 12.9"
depends_on:
@@ -503,6 +291,7 @@ steps:
- label: "Publish nightly multi-arch image to DockerHub"
depends_on:
- create-multi-arch-manifest
if: build.env("NIGHTLY") == "1"
agents:
queue: small_cpu_queue_release
commands:
@@ -520,6 +309,7 @@ steps:
- label: "Publish nightly multi-arch image to DockerHub - CUDA 13.0"
depends_on:
- create-multi-arch-manifest-cuda-13-0
if: build.env("NIGHTLY") == "1"
agents:
queue: small_cpu_queue_release
commands:
@@ -534,10 +324,298 @@ steps:
DOCKER_BUILDKIT: "1"
DOCKERHUB_USERNAME: "vllmbot"
# ROCm nightly Docker image
- group: "Publish wheels"
key: "publish-wheels"
steps:
- block: "Confirm update release wheels to PyPI (experimental, use with caution)?"
key: block-upload-release-wheels
depends_on:
- input-release-version
- build-wheels
- label: "Upload release wheels to PyPI"
depends_on:
- block-upload-release-wheels
id: upload-release-wheels
agents:
queue: small_cpu_queue_release
commands:
- "bash .buildkite/scripts/upload-release-wheels-pypi.sh"
# =============================================================================
# ROCm Release Pipeline (x86_64 only)
# =============================================================================
#
# vLLM version is determined by the Buildkite checkout (like CUDA pipeline).
# To build a specific version, trigger the build from that branch/tag.
#
# Environment variables for ROCm builds (set via Buildkite UI or schedule):
#
# Note: ROCm version is determined by BASE_IMAGE in docker/Dockerfile.rocm_base
#
# =============================================================================
# ROCm Job 1: Build ROCm Base Wheels (with S3 caching)
- label: ":rocm: Build ROCm Base Image & Wheels"
id: build-rocm-base-wheels
depends_on: ~
agents:
queue: cpu_queue_release
commands:
- |
set -euo pipefail
# Generate cache key
CACHE_KEY=$$(.buildkite/scripts/cache-rocm-base-wheels.sh key)
ECR_CACHE_TAG="public.ecr.aws/q9t5s3a7/vllm-release-repo:$${CACHE_KEY}-rocm-base"
echo "========================================"
echo "ROCm Base Build Configuration"
echo "========================================"
echo " CACHE_KEY: $${CACHE_KEY}"
echo " ECR_CACHE_TAG: $${ECR_CACHE_TAG}"
echo "========================================"
# Login to ECR
aws ecr-public get-login-password --region us-east-1 | \
docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7
IMAGE_EXISTS=false
WHEELS_EXIST=false
# Check ECR for Docker image
if docker manifest inspect "$${ECR_CACHE_TAG}" > /dev/null 2>&1; then
IMAGE_EXISTS=true
echo "ECR image cache HIT"
fi
# Check S3 for wheels
WHEEL_CACHE_STATUS=$(.buildkite/scripts/cache-rocm-base-wheels.sh check)
if [ "$${WHEEL_CACHE_STATUS}" = "hit" ]; then
WHEELS_EXIST=true
echo "S3 wheels cache HIT"
fi
# Scenario 1: Both cached (best case)
if [ "$${IMAGE_EXISTS}" = "true" ] && [ "$${WHEELS_EXIST}" = "true" ]; then
echo ""
echo "FULL CACHE HIT - Reusing both image and wheels"
echo ""
# Download wheels
.buildkite/scripts/cache-rocm-base-wheels.sh download
# Save ECR tag for downstream jobs
buildkite-agent meta-data set "rocm-base-image-tag" "$${ECR_CACHE_TAG}"
# Scenario 2: Full rebuild needed
else
echo ""
echo " CACHE MISS - Building from scratch..."
echo ""
# Build full base image and push to ECR
DOCKER_BUILDKIT=1 docker buildx build \
--file docker/Dockerfile.rocm_base \
--tag "$${ECR_CACHE_TAG}" \
--build-arg USE_SCCACHE=1 \
--build-arg SCCACHE_BUCKET_NAME=vllm-build-sccache \
--build-arg SCCACHE_REGION_NAME=us-west-2 \
--build-arg SCCACHE_S3_NO_CREDENTIALS=0 \
--push \
.
# Build wheel extraction stage
DOCKER_BUILDKIT=1 docker buildx build \
--file docker/Dockerfile.rocm_base \
--tag rocm-base-debs:$${BUILDKITE_BUILD_NUMBER} \
--target debs_wheel_release \
--build-arg USE_SCCACHE=1 \
--build-arg SCCACHE_BUCKET_NAME=vllm-build-sccache \
--build-arg SCCACHE_REGION_NAME=us-west-2 \
--build-arg SCCACHE_S3_NO_CREDENTIALS=0 \
--load \
.
# Extract and upload wheels
mkdir -p artifacts/rocm-base-wheels
cid=$(docker create rocm-base-debs:$${BUILDKITE_BUILD_NUMBER})
docker cp $${cid}:/app/debs/. artifacts/rocm-base-wheels/
docker rm $${cid}
.buildkite/scripts/cache-rocm-base-wheels.sh upload
# Cache base docker image to ECR
docker push "$${ECR_CACHE_TAG}"
buildkite-agent meta-data set "rocm-base-image-tag" "$${ECR_CACHE_TAG}"
echo ""
echo " Build complete - Image and wheels cached"
fi
artifact_paths:
- "artifacts/rocm-base-wheels/*.whl"
env:
DOCKER_BUILDKIT: "1"
S3_BUCKET: "vllm-wheels"
# ROCm Job 2: Build vLLM ROCm Wheel
- label: ":python: Build vLLM ROCm Wheel - x86_64"
id: build-rocm-vllm-wheel
depends_on:
- step: build-rocm-base-wheels
allow_failure: false
agents:
queue: cpu_queue_release
timeout_in_minutes: 180
commands:
# Download artifacts and prepare Docker image
- |
set -euo pipefail
# Ensure git tags are up-to-date (Buildkite's default fetch doesn't update tags)
# This fixes version detection when tags are moved/force-pushed
echo "Fetching latest tags from origin..."
git fetch --tags --force origin
# Log tag information for debugging version detection
echo "========================================"
echo "Git Tag Verification"
echo "========================================"
echo "Current HEAD: $(git rev-parse HEAD)"
echo "git describe --tags: $(git describe --tags 2>/dev/null || echo 'No tags found')"
echo ""
echo "Recent tags (pointing to commits near HEAD):"
git tag -l --sort=-creatordate | head -5
echo "setuptools_scm version detection:"
pip install -q setuptools_scm 2>/dev/null || true
python3 -c "import setuptools_scm; print(' Detected version:', setuptools_scm.get_version())" 2>/dev/null || echo " (setuptools_scm not available in this environment)"
echo "========================================"
# Download wheel artifacts from current build
echo "Downloading wheel artifacts from current build"
buildkite-agent artifact download "artifacts/rocm-base-wheels/*.whl" .
# Get ECR image tag from metadata (set by build-rocm-base-wheels)
ECR_IMAGE_TAG="$$(buildkite-agent meta-data get rocm-base-image-tag 2>/dev/null || echo '')"
if [ -z "$${ECR_IMAGE_TAG}" ]; then
echo "ERROR: rocm-base-image-tag metadata not found"
echo "This should have been set by the build-rocm-base-wheels job"
exit 1
fi
echo "Pulling base Docker image from ECR: $${ECR_IMAGE_TAG}"
# Login to ECR
aws ecr-public get-login-password --region us-east-1 | \
docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7
# Pull base Docker image from ECR
docker pull "$${ECR_IMAGE_TAG}"
echo "Loaded base image: $${ECR_IMAGE_TAG}"
# Prepare base wheels for Docker build context
mkdir -p docker/context/base-wheels
touch docker/context/base-wheels/.keep
cp artifacts/rocm-base-wheels/*.whl docker/context/base-wheels/
echo "Base wheels for vLLM build:"
ls -lh docker/context/base-wheels/
echo "========================================"
echo "Building vLLM wheel with:"
echo " BUILDKITE_COMMIT: $${BUILDKITE_COMMIT}"
echo " BUILDKITE_BRANCH: $${BUILDKITE_BRANCH}"
echo " BASE_IMAGE: $${ECR_IMAGE_TAG}"
echo "========================================"
# Build vLLM wheel using local checkout (REMOTE_VLLM=0)
DOCKER_BUILDKIT=1 docker build \
--file docker/Dockerfile.rocm \
--target export_vllm_wheel_release \
--output type=local,dest=rocm-dist \
--build-arg BASE_IMAGE="$${ECR_IMAGE_TAG}" \
--build-arg REMOTE_VLLM=0 \
--build-arg GIT_REPO_CHECK=1 \
--build-arg USE_SCCACHE=1 \
--build-arg SCCACHE_BUCKET_NAME=vllm-build-sccache \
--build-arg SCCACHE_REGION_NAME=us-west-2 \
--build-arg SCCACHE_S3_NO_CREDENTIALS=0 \
.
echo "Built vLLM wheel:"
ls -lh rocm-dist/*.whl
# Copy wheel to artifacts directory
mkdir -p artifacts/rocm-vllm-wheel
cp rocm-dist/*.whl artifacts/rocm-vllm-wheel/
echo "Final vLLM wheel:"
ls -lh artifacts/rocm-vllm-wheel/
artifact_paths:
- "artifacts/rocm-vllm-wheel/*.whl"
env:
DOCKER_BUILDKIT: "1"
S3_BUCKET: "vllm-wheels"
# ROCm Job 3: Upload Wheels to S3
- label: ":s3: Upload ROCm Wheels to S3"
id: upload-rocm-wheels
depends_on:
- step: build-rocm-vllm-wheel
allow_failure: false
agents:
queue: cpu_queue_release
timeout_in_minutes: 60
commands:
# Download all wheel artifacts and run upload
- |
set -euo pipefail
# Download artifacts from current build
echo "Downloading artifacts from current build"
buildkite-agent artifact download "artifacts/rocm-base-wheels/*.whl" .
buildkite-agent artifact download "artifacts/rocm-vllm-wheel/*.whl" .
# Run upload script
bash .buildkite/scripts/upload-rocm-wheels.sh
env:
DOCKER_BUILDKIT: "1"
S3_BUCKET: "vllm-wheels"
# ROCm Job 4: Annotate ROCm Wheel Release
- label: ":memo: Annotate ROCm wheel release"
id: annotate-rocm-release
depends_on:
- upload-rocm-wheels
agents:
queue: cpu_queue_release
commands:
- "bash .buildkite/scripts/annotate-rocm-release.sh"
env:
S3_BUCKET: "vllm-wheels"
# ROCm Job 5: Generate Root Index for ROCm Wheels (for release only)
# This is the job to create https://wheels.vllm.ai/rocm/ index allowing
# users to install with `uv pip install vllm --extra-index-url https://wheels.vllm.ai/rocm/`
- block: "Generate Root Index for ROCm Wheels for Release"
key: block-generate-root-index-rocm-wheels
depends_on: upload-rocm-wheels
- label: ":package: Generate Root Index for ROCm Wheels for Release"
depends_on: block-generate-root-index-rocm-wheels
id: generate-root-index-rocm-wheels
agents:
queue: cpu_queue_release
commands:
- "bash tools/vllm-rocm/generate-rocm-wheels-root-index.sh"
env:
S3_BUCKET: "vllm-wheels"
VARIANT: "rocm721"
# ROCm Job 6: Build ROCm Release Docker Image
- label: ":docker: Build release image - x86_64 - ROCm"
id: build-rocm-release-image
if: build.env("NIGHTLY") == "1"
depends_on:
- step: build-rocm-base-wheels
allow_failure: false
@@ -547,11 +625,11 @@ steps:
commands:
- |
set -euo pipefail
# Login to ECR
aws ecr-public get-login-password --region us-east-1 | \
docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7
# Get ECR image tag from metadata (set by build-rocm-base-wheels)
ECR_IMAGE_TAG="$$(buildkite-agent meta-data get rocm-base-image-tag 2>/dev/null || echo '')"
if [ -z "$${ECR_IMAGE_TAG}" ]; then
@@ -559,23 +637,23 @@ steps:
echo "This should have been set by the build-rocm-base-wheels job"
exit 1
fi
echo "Pulling base Docker image from ECR: $${ECR_IMAGE_TAG}"
# Pull base Docker image from ECR
docker pull "$${ECR_IMAGE_TAG}"
echo "Loaded base image: $${ECR_IMAGE_TAG}"
# Pass the base image ECR tag to downstream steps (nightly publish)
buildkite-agent meta-data set "rocm-base-ecr-tag" "$${ECR_IMAGE_TAG}"
echo "========================================"
echo "Building vLLM ROCm release image with:"
echo " BASE_IMAGE: $${ECR_IMAGE_TAG}"
echo " BUILDKITE_COMMIT: $${BUILDKITE_COMMIT}"
echo "========================================"
# Build vLLM ROCm release image using cached base
DOCKER_BUILDKIT=1 docker build \
--build-arg max_jobs=16 \
@@ -588,10 +666,10 @@ steps:
--target vllm-openai \
--progress plain \
-f docker/Dockerfile.rocm .
# Push to ECR
docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$${BUILDKITE_COMMIT}-rocm
echo ""
echo " Successfully built and pushed ROCm release image"
echo " Image: public.ecr.aws/q9t5s3a7/vllm-release-repo:$${BUILDKITE_COMMIT}-rocm"
@@ -618,84 +696,3 @@ steps:
env:
DOCKER_BUILDKIT: "1"
DOCKERHUB_USERNAME: "vllmbot"
# =============================================================================
# Release: Publish Wheels & Build CPU Images (manual, requires release version)
# =============================================================================
- input: "Provide Release version here"
id: input-release-version
fields:
- text: "What is the release version?"
key: release-version
- group: "Publish release wheels"
key: "publish-wheels"
steps:
- block: "Confirm update release wheels to PyPI (experimental, use with caution)?"
key: block-upload-release-wheels
depends_on:
- input-release-version
- build-wheels
- label: "Upload release wheels to PyPI"
depends_on:
- block-upload-release-wheels
id: upload-release-wheels
agents:
queue: small_cpu_queue_release
commands:
- "bash .buildkite/scripts/upload-release-wheels-pypi.sh"
- group: "Build release CPU Docker images"
steps:
- block: "Build release image for x86_64 CPU"
key: block-cpu-release-image-build
depends_on: ~
- label: "Build release image - x86_64 - CPU"
depends_on:
- block-cpu-release-image-build
- input-release-version
agents:
queue: cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg GIT_REPO_CHECK=1 --build-arg VLLM_CPU_X86=true --tag public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:$(buildkite-agent meta-data get release-version) --tag public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:latest --progress plain --target vllm-openai -f docker/Dockerfile.cpu ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:latest"
- "docker push public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:$(buildkite-agent meta-data get release-version)"
env:
DOCKER_BUILDKIT: "1"
- block: "Build release image for arm64 CPU"
key: block-arm64-cpu-release-image-build
depends_on: ~
- label: "Build release image - arm64 - CPU"
depends_on:
- block-arm64-cpu-release-image-build
- input-release-version
agents:
queue: arm64_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg GIT_REPO_CHECK=1 --tag public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:$(buildkite-agent meta-data get release-version) --tag public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:latest --progress plain --target vllm-openai -f docker/Dockerfile.cpu ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:latest"
- "docker push public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:$(buildkite-agent meta-data get release-version)"
env:
DOCKER_BUILDKIT: "1"
- block: "Generate Root Index for ROCm Wheels for Release"
key: block-generate-root-index-rocm-wheels
depends_on: upload-rocm-wheels
- label: ":package: Generate Root Index for ROCm Wheels for Release"
depends_on: block-generate-root-index-rocm-wheels
id: generate-root-index-rocm-wheels
agents:
queue: cpu_queue_release
commands:
- "bash tools/vllm-rocm/generate-rocm-wheels-root-index.sh"
env:
S3_BUCKET: "vllm-wheels"
VARIANT: "rocm721"
-2
View File
@@ -1,5 +1,3 @@
lmcache >= 0.3.9
nixl[cu13] >= 0.7.1, < 0.10.0 # Required for disaggregated prefill
nixl-cu12 >= 0.7.1, < 0.10.0
nixl-cu13 >= 0.7.1, < 0.10.0
mooncake-transfer-engine >= 0.3.8
+20 -8
View File
@@ -383,9 +383,14 @@ class RemoteVLLMServer:
total_used = 0
device_count = current_platform.device_count()
for i in range(device_count):
handle = nvmlDeviceGetHandleByIndex(i)
mem_info = nvmlDeviceGetMemoryInfo(handle)
total_used += mem_info.used
try:
handle = nvmlDeviceGetHandleByIndex(i)
mem_info = nvmlDeviceGetMemoryInfo(handle)
total_used += mem_info.used
except Exception:
# NVML fails on MIG — fall back to torch.cuda
free, total = torch.cuda.mem_get_info(i)
total_used += total - free
return total_used
except Exception as e:
print(f"[RemoteOpenAIServer] Could not query GPU memory: {e}")
@@ -1202,7 +1207,7 @@ def wait_for_gpu_memory_to_clear(
) -> None:
assert threshold_bytes is not None or threshold_ratio is not None
# Use nvml instead of pytorch to reduce measurement error from torch cuda
# context.
# context. Falls back to torch.cuda on MIG where NVML lacks permissions.
devices = get_physical_device_indices(devices)
start_time = time.time()
while True:
@@ -1215,10 +1220,17 @@ def wait_for_gpu_memory_to_clear(
gb_used = mem_info["vram_used"] / 2**10
gb_total = mem_info["vram_total"] / 2**10
else:
dev_handle = nvmlDeviceGetHandleByIndex(device)
mem_info = nvmlDeviceGetMemoryInfo(dev_handle)
gb_used = mem_info.used / 2**30
gb_total = mem_info.total / 2**30
try:
dev_handle = nvmlDeviceGetHandleByIndex(device)
mem_info = nvmlDeviceGetMemoryInfo(dev_handle)
gb_used = mem_info.used / 2**30
gb_total = mem_info.total / 2**30
except Exception:
# NVML fails on MIG with NoPermission — fall back to
# torch.cuda which correctly reports MIG partition memory.
free, total = torch.cuda.mem_get_info(device)
gb_total = total / 2**30
gb_used = (total - free) / 2**30
output_raw[device] = (gb_used, gb_total)
output[device] = f"{gb_used:.02f}/{gb_total:.02f}"
+109 -1
View File
@@ -844,6 +844,37 @@ class NonNvmlCudaPlatform(CudaPlatformBase):
return None
class MigCudaPlatform(NvmlCudaPlatform):
"""Platform for MIG (Multi-Instance GPU) devices.
Inherits from NvmlCudaPlatform so that device queries like
get_device_capability() and get_device_name() use NVML instead of
torch.cuda, avoiding premature CUDA context initialization (which
would break fork-based test frameworks).
Overrides only the methods that fail on MIG partitions due to NVML
NoPermission errors (memory queries report full-GPU memory instead
of partition memory).
"""
@classmethod
def get_device_total_memory(cls, device_id: int = 0) -> int:
# NVML returns the *full* GPU's memory on MIG partitions, not the
# partition's memory. Use torch.cuda which reports correctly.
device_props = torch.cuda.get_device_properties(device_id)
return device_props.total_memory
@classmethod
def is_fully_connected(cls, physical_device_ids: list[int]) -> bool:
# P2P / NVLink queries are not meaningful on MIG partitions.
return False
@classmethod
def log_warnings(cls):
# Skip NVML-based heterogeneous-GPU warnings on MIG partitions.
pass
# Autodetect either NVML-enabled or non-NVML platform
# based on whether NVML is available.
nvml_available = False
@@ -858,6 +889,83 @@ finally:
if nvml_available:
pynvml.nvmlShutdown()
CudaPlatform = NvmlCudaPlatform if nvml_available else NonNvmlCudaPlatform
def _is_mig_device() -> bool:
"""Detect if the current CUDA device is a MIG (Multi-Instance GPU) partition.
On MIG partitions, most NVML device-level queries fail with
NVMLError_NoPermission. This causes PyTorch's CUDACachingAllocator to crash
with an internal assert (via expandable_segments) before the real OOM error
can surface. It also causes NVML memory queries to report the full GPU's
memory instead of the MIG partition's memory.
Detection methods:
1. CUDA_VISIBLE_DEVICES containing MIG UUIDs (MIG-GPU-...)
2. Probing NVML device queries for permission errors
"""
# Method 1: Check CUDA_VISIBLE_DEVICES for MIG UUID format
cuda_visible = os.environ.get("CUDA_VISIBLE_DEVICES", "")
if cuda_visible and any(
dev.strip().startswith("MIG-") for dev in cuda_visible.split(",")
):
logger.info(
"Detected MIG device from CUDA_VISIBLE_DEVICES=%s, "
"using MigCudaPlatform to avoid NVML memory errors.",
cuda_visible,
)
return True
# Method 2: Probe NVML for permission errors (catches MIG even when
# CUDA_VISIBLE_DEVICES uses numeric indices mapped by the container runtime)
if nvml_available:
try:
pynvml.nvmlInit()
try:
handle = pynvml.nvmlDeviceGetHandleByIndex(0)
pynvml.nvmlDeviceGetMemoryInfo(handle)
except pynvml.NVMLError as e:
if "NoPermission" in str(
type(e).__name__
) or "Insufficient Permissions" in str(e):
logger.info(
"Detected MIG device via NVML permission error: %s, "
"using MigCudaPlatform.",
e,
)
return True
finally:
pynvml.nvmlShutdown()
except Exception:
pass
return False
_mig_device = _is_mig_device()
CudaPlatform: type[NvmlCudaPlatform] | type[NonNvmlCudaPlatform] | type[MigCudaPlatform]
if _mig_device:
CudaPlatform = MigCudaPlatform
# Disable expandable_segments on MIG devices. PyTorch's
# CUDACachingAllocator internally calls NVML (for the
# expandable_segments feature) which fails on MIG with
# "NVML_SUCCESS == r INTERNAL ASSERT FAILED", crashing before
# a real torch.cuda.OutOfMemoryError can surface.
_alloc_conf = os.environ.get("PYTORCH_CUDA_ALLOC_CONF", "")
if "expandable_segments" not in _alloc_conf:
new_val = (
f"{_alloc_conf},expandable_segments:False"
if _alloc_conf
else "expandable_segments:False"
)
os.environ["PYTORCH_CUDA_ALLOC_CONF"] = new_val
logger.info(
"MIG device detected: set PYTORCH_CUDA_ALLOC_CONF=%s "
"to prevent NVML assert in CUDACachingAllocator.",
new_val,
)
else:
CudaPlatform = NvmlCudaPlatform if nvml_available else NonNvmlCudaPlatform
CudaPlatform.log_warnings()