Upstream merge 25 01 27

.buildkite/check-wheel-size.py

@@ -2,8 +2,11 @@
 import sys
 import zipfile
 
-# Read the VLLM_MAX_SIZE_MB environment variable, defaulting to 250 MB
-VLLM_MAX_SIZE_MB = int(os.environ.get('VLLM_MAX_SIZE_MB', 250))
+# Read the VLLM_MAX_SIZE_MB environment variable, defaulting to 300 MiB
+# Note that we have 400 MiB quota, please use it wisely.
+# See https://github.com/pypi/support/issues/3792 .
+# Please also sync the value with the one in Dockerfile.
+VLLM_MAX_SIZE_MB = int(os.environ.get('VLLM_MAX_SIZE_MB', 300))
 
 
 def print_top_10_largest_files(zip_file):

.buildkite/run-neuron-test.sh

@@ -25,8 +25,11 @@ if [ -f /tmp/neuron-docker-build-timestamp ]; then
     last_build=$(cat /tmp/neuron-docker-build-timestamp)
     current_time=$(date +%s)
     if [ $((current_time - last_build)) -gt 86400 ]; then
+        # Remove dangling images (those that are not tagged and not used by any container)
         docker image prune -f
-        docker system prune -f
+        # Remove unused volumes / force the system prune for old images as well.
+        docker volume prune -f && docker system prune -f
+        # Remove huggingface model artifacts and compiler cache
         rm -rf "${HF_MOUNT:?}/*"
         rm -rf "${NEURON_COMPILE_CACHE_MOUNT:?}/*"
         echo "$current_time" > /tmp/neuron-docker-build-timestamp

.buildkite/test-pipeline.yaml

@@ -76,7 +76,9 @@ steps:
   - tests/basic_correctness/test_basic_correctness
   - tests/basic_correctness/test_cpu_offload
   - tests/basic_correctness/test_preemption
+  - tests/basic_correctness/test_cumem.py
   commands:
+  - pytest -v -s basic_correctness/test_cumem.py
   - pytest -v -s basic_correctness/test_basic_correctness.py
   - pytest -v -s basic_correctness/test_cpu_offload.py
   - VLLM_TEST_ENABLE_ARTIFICIAL_PREEMPT=1 pytest -v -s basic_correctness/test_preemption.py
@@ -181,7 +183,16 @@ steps:
     - vllm/
     - tests/v1
   commands:
-    - VLLM_USE_V1=1 pytest -v -s v1
+    # split the test to avoid interference
+    - VLLM_USE_V1=1 pytest -v -s v1/core
+    - VLLM_USE_V1=1 pytest -v -s v1/engine
+    - VLLM_USE_V1=1 pytest -v -s v1/sample
+    - VLLM_USE_V1=1 pytest -v -s v1/worker
+    - VLLM_USE_V1=1 pytest -v -s v1/test_stats.py
+    - VLLM_USE_V1=1 pytest -v -s v1/test_utils.py
+    # TODO: accuracy does not match, whether setting
+    # VLLM_USE_FLASHINFER_SAMPLER or not on H100.
+    - VLLM_USE_V1=1 pytest -v -s v1/e2e
 
 - label: Examples Test # 25min
   working_dir: "/vllm-workspace/examples"
@@ -477,7 +488,9 @@ steps:
   - pytest models/encoder_decoder/language/test_bart.py -v -s -m 'distributed(num_gpus=2)'
   - pytest models/encoder_decoder/vision_language/test_broadcast.py -v -s -m 'distributed(num_gpus=2)'
   - pytest models/decoder_only/vision_language/test_models.py -v -s -m 'distributed(num_gpus=2)'
-  - pytest -v -s spec_decode/e2e/test_integration_dist_tp2.py
+  # this test fails consistently.
+  # TODO: investigate and fix
+  # - pytest -v -s spec_decode/e2e/test_integration_dist_tp2.py
   - CUDA_VISIBLE_DEVICES=0,1 pytest -v -s test_sharded_state_loader.py
   - CUDA_VISIBLE_DEVICES=0,1 pytest -v -s kv_transfer/disagg_test.py
 
@@ -515,7 +528,9 @@ steps:
   - vllm/engine
   - tests/multi_step
   commands:
-  - pytest -v -s multi_step/test_correctness_async_llm.py
+  # this test is quite flaky
+  # TODO: investigate and fix.
+  # - pytest -v -s multi_step/test_correctness_async_llm.py
   - pytest -v -s multi_step/test_correctness_llm.py
 
 - label: Pipeline Parallelism Test # 45min

.github/CODEOWNERS

@@ -2,32 +2,35 @@
 # for more info about CODEOWNERS file
 
 # This lists cover the "core" components of vLLM that require careful review
-/vllm/attention/backends/abstract.py @WoosukKwon @zhuohan123 @youkaichao @alexm-neuralmagic @comaniac @njhill
-/vllm/core @zhuohan123 @youkaichao @alexm-neuralmagic @comaniac @njhill
-/vllm/engine/llm_engine.py @zhuohan123 @youkaichao @alexm-neuralmagic @comaniac @njhill
-/vllm/executor/executor_base.py @zhuohan123 @youkaichao @alexm-neuralmagic @comaniac @njhill
-/vllm/worker/worker_base.py @zhuohan123 @youkaichao @alexm-neuralmagic @comaniac @njhill
-/vllm/worker/worker.py @zhuohan123 @youkaichao @alexm-neuralmagic @comaniac @njhill
-/vllm/model_executor/layers/sampler.py @zhuohan123 @youkaichao @alexm-neuralmagic @comaniac @njhill
+/vllm/attention/backends/abstract.py @WoosukKwon @zhuohan123 @youkaichao @alexm-redhat @comaniac @njhill
+/vllm/core @zhuohan123 @youkaichao @alexm-redhat @comaniac @njhill
+/vllm/engine/llm_engine.py @zhuohan123 @youkaichao @alexm-redhat @comaniac @njhill
+/vllm/executor/executor_base.py @zhuohan123 @youkaichao @alexm-redhat @comaniac @njhill
+/vllm/worker/worker_base.py @zhuohan123 @youkaichao @alexm-redhat @comaniac @njhill
+/vllm/worker/worker.py @zhuohan123 @youkaichao @alexm-redhat @comaniac @njhill
+/vllm/model_executor/layers/sampler.py @zhuohan123 @youkaichao @alexm-redhat @comaniac @njhill
+/vllm/model_executor/layers/quantization @mgoin @robertgshaw2-redhat @tlrmchlsmth
+/vllm/model_executor/guided_decoding @mgoin
+/vllm/multimodal @DarkLight1337 @ywang96
 CMakeLists.txt @tlrmchlsmth
 
 # vLLM V1
-/vllm/v1 @WoosukKwon @robertgshaw2-neuralmagic @njhill @ywang96 @comaniac @alexm-neuralmagic
+/vllm/v1 @WoosukKwon @robertgshaw2-redhat @njhill @ywang96 @comaniac @alexm-redhat
 
 # Test ownership
-/tests/async_engine @njhill @robertgshaw2-neuralmagic @simon-mo
+/tests/async_engine @njhill @robertgshaw2-redhat @simon-mo
 /tests/test_inputs.py @DarkLight1337 @ywang96
-/tests/entrypoints @DarkLight1337 @robertgshaw2-neuralmagic @simon-mo
+/tests/entrypoints @DarkLight1337 @robertgshaw2-redhat @simon-mo
 /tests/models @DarkLight1337 @ywang96
 /tests/multimodal @DarkLight1337 @ywang96
 /tests/prefix_caching @comaniac @KuntaiDu
 /tests/spec_decode @njhill @LiuXiaoxuanPKU
 /tests/kernels @tlrmchlsmth @WoosukKwon
-/tests/quantization @mgoin @robertgshaw2-neuralmagic
+/tests/quantization @mgoin @robertgshaw2-redhat
 /.buildkite/lm-eval-harness @mgoin @simon-mo
 /tests/distributed/test_multi_node_assignment.py @youkaichao
 /tests/distributed/test_pipeline_parallel.py @youkaichao
 /tests/distributed/test_same_node.py @youkaichao
-/tests/multi_step @alexm-neuralmagic @comaniac
+/tests/multi_step @alexm-redhat @comaniac
 /tests/weight_loading @mgoin @youkaichao
 /tests/basic_correctness/test_chunked_prefill @rkooo567 @comaniac

CMakeLists.txt

@@ -24,9 +24,6 @@ include(${CMAKE_CURRENT_LIST_DIR}/cmake/utils.cmake)
 # Suppress potential warnings about unused manually-specified variables
 set(ignoreMe "${VLLM_PYTHON_PATH}")
 
-# Prevent installation of dependencies (cutlass) by default.
-install(CODE "set(CMAKE_INSTALL_LOCAL_ONLY TRUE)" ALL_COMPONENTS)
-
 #
 # Supported python versions.  These versions will be searched in order, the
 # first match will be selected.  These should be kept in sync with setup.py.
@@ -215,6 +212,31 @@ endif()
 # Define extension targets
 #
 
+#
+# cumem_allocator extension
+#
+
+set(VLLM_CUMEM_EXT_SRC
+  "csrc/cumem_allocator.cpp")
+
+set_gencode_flags_for_srcs(
+  SRCS "${VLLM_CUMEM_EXT_SRC}"
+  CUDA_ARCHS "${CUDA_ARCHS}")
+
+if(VLLM_GPU_LANG STREQUAL "CUDA")
+  message(STATUS "Enabling cumem allocator extension.")
+  # link against cuda driver library
+  list(APPEND CUMEM_LIBS cuda)
+  define_gpu_extension_target(
+    cumem_allocator
+    DESTINATION vllm
+    LANGUAGE CXX
+    SOURCES ${VLLM_CUMEM_EXT_SRC}
+    LIBRARIES ${CUMEM_LIBS}
+    USE_SABI 3.8
+    WITH_SOABI)
+endif()
+
 #
 # _C extension
 #
@@ -287,7 +309,7 @@ if(VLLM_GPU_LANG STREQUAL "CUDA")
   # Only build Marlin kernels if we are building for at least some compatible archs.
   # Keep building Marlin for 9.0 as there are some group sizes and shapes that
   # are not supported by Machete yet.
-  cuda_archs_loose_intersection(MARLIN_ARCHS "8.0;8.6;8.7;8.9;9.0" ${CUDA_ARCHS})
+  cuda_archs_loose_intersection(MARLIN_ARCHS "8.0;8.6;8.7;8.9;9.0" "${CUDA_ARCHS}")
   if (MARLIN_ARCHS)
     set(MARLIN_SRCS
        "csrc/quantization/fp8/fp8_marlin.cu"
@@ -308,8 +330,8 @@ if(VLLM_GPU_LANG STREQUAL "CUDA")
   endif()
 
   # The cutlass_scaled_mm kernels for Hopper (c3x, i.e. CUTLASS 3.x) require
-  # CUDA 12.0 or later (and only work on Hopper, 9.0/9.0a for now).
-  cuda_archs_loose_intersection(SCALED_MM_3X_ARCHS "9.0;9.0a" "${CUDA_ARCHS}")
+  # CUDA 12.0 or later (and only work on Hopper, 9.0a for now).
+  cuda_archs_loose_intersection(SCALED_MM_3X_ARCHS "9.0a" "${CUDA_ARCHS}")
   if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0 AND SCALED_MM_3X_ARCHS)
     set(SRCS "csrc/quantization/cutlass_w8a8/scaled_mm_c3x.cu")
     set_gencode_flags_for_srcs(
@@ -363,7 +385,7 @@ if(VLLM_GPU_LANG STREQUAL "CUDA")
   # 2:4 Sparse Kernels
 
   # The 2:4 sparse kernels cutlass_scaled_sparse_mm and cutlass_compressor
-  # require CUDA 12.2 or later (and only work on Hopper, 9.0/9.0a for now).
+  # require CUDA 12.2 or later (and only work on Hopper, 9.0a for now).
   if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.2 AND SCALED_MM_3X_ARCHS)
     set(SRCS "csrc/sparse/cutlass/sparse_compressor_c3x.cu"
              "csrc/sparse/cutlass/sparse_scaled_mm_c3x.cu")
@@ -463,6 +485,9 @@ if(VLLM_GPU_LANG STREQUAL "HIP")
 endif()
 
 message(STATUS "Enabling C extension.")
+if(VLLM_GPU_LANG STREQUAL "CUDA")
+  list(APPEND VLLM_C_LIBS cuda)
+endif()
 define_gpu_extension_target(
   _C
   DESTINATION vllm
@@ -471,6 +496,7 @@ define_gpu_extension_target(
   COMPILE_FLAGS ${VLLM_GPU_FLAGS}
   ARCHITECTURES ${VLLM_GPU_ARCHES}
   INCLUDE_DIRECTORIES ${CUTLASS_INCLUDE_DIR};${CUTLASS_TOOLS_UTIL_INCLUDE_DIR}
+  LIBRARIES ${VLLM_C_LIBS}
   USE_SABI 3
   WITH_SOABI)
 
@@ -570,7 +596,7 @@ if(VLLM_GPU_LANG STREQUAL "HIP")
 endif()
 
 # vllm-flash-attn currently only supported on CUDA
-if (NOT VLLM_TARGET_DEVICE STREQUAL "cuda")
+if (NOT VLLM_GPU_LANG STREQUAL "CUDA")
   return()
 endif ()
 
@@ -593,7 +619,7 @@ endif()
 # They should be identical but if they aren't, this is a massive footgun.
 #
 # The vllm-flash-attn install rules are nested under vllm to make sure the library gets installed in the correct place.
-# To only install vllm-flash-attn, use --component vllm_flash_attn_c.
+# To only install vllm-flash-attn, use --component _vllm_fa2_C (for FA2) or --component _vllm_fa3_C (for FA3).
 # If no component is specified, vllm-flash-attn is still installed.
 
 # If VLLM_FLASH_ATTN_SRC_DIR is set, vllm-flash-attn is installed from that directory instead of downloading.
@@ -605,43 +631,41 @@ if (DEFINED ENV{VLLM_FLASH_ATTN_SRC_DIR})
 endif()
 
 if(VLLM_FLASH_ATTN_SRC_DIR)
-  FetchContent_Declare(vllm-flash-attn SOURCE_DIR ${VLLM_FLASH_ATTN_SRC_DIR})
+  FetchContent_Declare(
+          vllm-flash-attn SOURCE_DIR 
+          ${VLLM_FLASH_ATTN_SRC_DIR}
+          BINARY_DIR ${CMAKE_BINARY_DIR}/vllm-flash-attn
+  )
 else()
   FetchContent_Declare(
           vllm-flash-attn
           GIT_REPOSITORY https://github.com/vllm-project/flash-attention.git
-          GIT_TAG 96266b1111111f3d11aabefaf3bacbab6a89d03c
+          GIT_TAG d4e09037abf588af1ec47d0e966b237ee376876c
           GIT_PROGRESS TRUE
           # Don't share the vllm-flash-attn build between build types
           BINARY_DIR ${CMAKE_BINARY_DIR}/vllm-flash-attn
   )
 endif()
 
-# Set the parent build flag so that the vllm-flash-attn library does not redo compile flag and arch initialization.
-set(VLLM_PARENT_BUILD ON)
-
-# Ensure the vllm/vllm_flash_attn directory exists before installation
-install(CODE "file(MAKE_DIRECTORY \"\${CMAKE_INSTALL_PREFIX}/vllm/vllm_flash_attn\")" COMPONENT vllm_flash_attn_c)
-
-# Make sure vllm-flash-attn install rules are nested under vllm/
-install(CODE "set(CMAKE_INSTALL_LOCAL_ONLY FALSE)" COMPONENT vllm_flash_attn_c)
-install(CODE "set(OLD_CMAKE_INSTALL_PREFIX \"\${CMAKE_INSTALL_PREFIX}\")" COMPONENT vllm_flash_attn_c)
-install(CODE "set(CMAKE_INSTALL_PREFIX \"\${CMAKE_INSTALL_PREFIX}/vllm/\")" COMPONENT vllm_flash_attn_c)
 
 # Fetch the vllm-flash-attn library
 FetchContent_MakeAvailable(vllm-flash-attn)
 message(STATUS "vllm-flash-attn is available at ${vllm-flash-attn_SOURCE_DIR}")
 
-# Restore the install prefix
-install(CODE "set(CMAKE_INSTALL_PREFIX \"\${OLD_CMAKE_INSTALL_PREFIX}\")" COMPONENT vllm_flash_attn_c)
-install(CODE "set(CMAKE_INSTALL_LOCAL_ONLY TRUE)" COMPONENT vllm_flash_attn_c)
+# Copy over the vllm-flash-attn python files (duplicated for fa2 and fa3, in
+# case only one is built, in the case both are built redundant work is done)
+install(
+  DIRECTORY ${vllm-flash-attn_SOURCE_DIR}/vllm_flash_attn/
+  DESTINATION vllm_flash_attn
+  COMPONENT _vllm_fa2_C
+  FILES_MATCHING PATTERN "*.py"
+)
 
-# Copy over the vllm-flash-attn python files
 install(
-        DIRECTORY ${vllm-flash-attn_SOURCE_DIR}/vllm_flash_attn/
-        DESTINATION vllm/vllm_flash_attn
-        COMPONENT vllm_flash_attn_c
-        FILES_MATCHING PATTERN "*.py"
+  DIRECTORY ${vllm-flash-attn_SOURCE_DIR}/vllm_flash_attn/
+  DESTINATION vllm_flash_attn
+  COMPONENT _vllm_fa3_C
+  FILES_MATCHING PATTERN "*.py"
 )
 
 # Nothing after vllm-flash-attn, see comment about macros above

Dockerfile

@@ -52,7 +52,7 @@ WORKDIR /workspace
 # after this step
 RUN --mount=type=cache,target=/root/.cache/pip \
     if [ "$TARGETPLATFORM" = "linux/arm64" ]; then \
-        python3 -m pip install --index-url https://download.pytorch.org/whl/nightly/cu124 "torch==2.6.0.dev20241210+cu124" "torchvision==0.22.0.dev20241215";  \
+        python3 -m pip install --index-url https://download.pytorch.org/whl/nightly/cu126 "torch==2.7.0.dev20250121+cu126" "torchvision==0.22.0.dev20250121";  \
     fi
 
 COPY requirements-common.txt requirements-common.txt
@@ -126,8 +126,8 @@ RUN --mount=type=cache,target=/root/.cache/ccache \
 
 # Check the size of the wheel if RUN_WHEEL_CHECK is true
 COPY .buildkite/check-wheel-size.py check-wheel-size.py
-# Default max size of the wheel is 250MB
-ARG VLLM_MAX_SIZE_MB=250
+# sync the default value with .buildkite/check-wheel-size.py
+ARG VLLM_MAX_SIZE_MB=300
 ENV VLLM_MAX_SIZE_MB=$VLLM_MAX_SIZE_MB
 ARG RUN_WHEEL_CHECK=true
 RUN if [ "$RUN_WHEEL_CHECK" = "true" ]; then \
@@ -149,7 +149,8 @@ RUN --mount=type=cache,target=/root/.cache/pip \
 
 #################### vLLM installation IMAGE ####################
 # image with vLLM installed
-FROM nvidia/cuda:${CUDA_VERSION}-base-ubuntu22.04 AS vllm-base
+# TODO: Restore to base image after FlashInfer AOT wheel fixed
+FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu22.04 AS vllm-base
 ARG CUDA_VERSION=12.4.1
 ARG PYTHON_VERSION=3.12
 WORKDIR /vllm-workspace
@@ -194,12 +195,30 @@ RUN --mount=type=bind,from=build,src=/workspace/dist,target=/vllm-workspace/dist
     --mount=type=cache,target=/root/.cache/pip \
     python3 -m pip install dist/*.whl --verbose
 
+# How to build this FlashInfer wheel:
+# $ export FLASHINFER_ENABLE_AOT=1
+# $ # Note we remove 7.0 from the arch list compared to the list below, since FlashInfer only supports sm75+
+# $ export TORCH_CUDA_ARCH_LIST='7.5 8.0 8.6 8.9 9.0+PTX'
+# $ git clone https://github.com/flashinfer-ai/flashinfer.git --recursive
+# $ cd flashinfer
+# $ git checkout 524304395bd1d8cd7d07db083859523fcaa246a4
+# $ python3 setup.py bdist_wheel --dist-dir=dist --verbose
+
 RUN --mount=type=cache,target=/root/.cache/pip \
 . /etc/environment && \
 if [ "$TARGETPLATFORM" != "linux/arm64" ]; then \
-    python3 -m pip install https://github.com/flashinfer-ai/flashinfer/releases/download/v0.1.6/flashinfer-0.1.6+cu121torch2.4-cp${PYTHON_VERSION_STR}-cp${PYTHON_VERSION_STR}-linux_x86_64.whl; \
+    python3 -m pip install https://wheels.vllm.ai/flashinfer/524304395bd1d8cd7d07db083859523fcaa246a4/flashinfer_python-0.2.0.post1-cp${PYTHON_VERSION_STR}-cp${PYTHON_VERSION_STR}-linux_x86_64.whl; \
 fi
 COPY examples examples
+
+# Although we build Flashinfer with AOT mode, there's still
+# some issues w.r.t. JIT compilation. Therefore we need to
+# install build dependencies for JIT compilation.
+# TODO: Remove this once FlashInfer AOT wheel is fixed
+COPY requirements-build.txt requirements-build.txt
+RUN --mount=type=cache,target=/root/.cache/pip \
+    python3 -m pip install -r requirements-build.txt
+
 #################### vLLM installation IMAGE ####################
 
 #################### TEST IMAGE ####################