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cmake_minimum_required(VERSION 3.26)
# When building directly using CMake, make sure you run the install step
# (it places the .so files in the correct location).
#
# Example:
# mkdir build && cd build
# cmake -G Ninja -DVLLM_PYTHON_EXECUTABLE=`which python3` -DCMAKE_INSTALL_PREFIX=.. ..
# cmake --build . --target install
#
# If you want to only build one target, make sure to install it manually:
# cmake --build . --target _C
# cmake --install . --component _C
project(vllm_extensions LANGUAGES CXX)
# CUDA by default, can be overridden by using -DVLLM_TARGET_DEVICE=... (used by setup.py)
set(VLLM_TARGET_DEVICE "cuda" CACHE STRING "Target device backend for vLLM")
message(STATUS "Build type: ${CMAKE_BUILD_TYPE}")
message(STATUS "Target device: ${VLLM_TARGET_DEVICE}")
include(${CMAKE_CURRENT_LIST_DIR}/cmake/utils.cmake)
# Suppress potential warnings about unused manually-specified variables
set(ignoreMe "${VLLM_PYTHON_PATH}")
#
# Supported python versions. These versions will be searched in order, the
# first match will be selected. These should be kept in sync with setup.py.
#
set(PYTHON_SUPPORTED_VERSIONS "3.9" "3.10" "3.11" "3.12", "3.13")
# Supported NVIDIA architectures.
set(CUDA_SUPPORTED_ARCHS "7.0;7.2;7.5;8.0;8.6;8.7;8.9;9.0;10.0;10.1;12.0")
# Supported AMD GPU architectures.
set(HIP_SUPPORTED_ARCHS "gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101")
#
# Supported/expected torch versions for CUDA/ROCm.
#
# Currently, having an incorrect pytorch version results in a warning
# rather than an error.
#
# Note: the CUDA torch version is derived from pyproject.toml and various
# requirements.txt files and should be kept consistent. The ROCm torch
# versions are derived from Dockerfile.rocm
#
set(TORCH_SUPPORTED_VERSION_CUDA "2.6.0")
set(TORCH_SUPPORTED_VERSION_ROCM "2.6.0")
#
# Try to find python package with an executable that exactly matches
# `VLLM_PYTHON_EXECUTABLE` and is one of the supported versions.
#
if (VLLM_PYTHON_EXECUTABLE)
find_python_from_executable(${VLLM_PYTHON_EXECUTABLE} "${PYTHON_SUPPORTED_VERSIONS}")
else()
message(FATAL_ERROR
"Please set VLLM_PYTHON_EXECUTABLE to the path of the desired python version"
" before running cmake configure.")
endif()
#
# Update cmake's `CMAKE_PREFIX_PATH` with torch location.
#
append_cmake_prefix_path("torch" "torch.utils.cmake_prefix_path")
# Ensure the 'nvcc' command is in the PATH
find_program(NVCC_EXECUTABLE nvcc)
if (CUDA_FOUND AND NOT NVCC_EXECUTABLE)
message(FATAL_ERROR "nvcc not found")
endif()
#
# Import torch cmake configuration.
# Torch also imports CUDA (and partially HIP) languages with some customizations,
# so there is no need to do this explicitly with check_language/enable_language,
# etc.
#
find_package(Torch REQUIRED)
#
# Forward the non-CUDA device extensions to external CMake scripts.
#
if (NOT VLLM_TARGET_DEVICE STREQUAL "cuda" AND
NOT VLLM_TARGET_DEVICE STREQUAL "rocm")
if (VLLM_TARGET_DEVICE STREQUAL "cpu")
include(${CMAKE_CURRENT_LIST_DIR}/cmake/cpu_extension.cmake)
else()
return()
endif()
return()
endif()
#
# Set up GPU language and check the torch version and warn if it isn't
# what is expected.
#
if (NOT HIP_FOUND AND CUDA_FOUND)
set(VLLM_GPU_LANG "CUDA")
if (NOT Torch_VERSION VERSION_EQUAL ${TORCH_SUPPORTED_VERSION_CUDA})
message(WARNING "Pytorch version ${TORCH_SUPPORTED_VERSION_CUDA} "
"expected for CUDA build, saw ${Torch_VERSION} instead.")
endif()
elseif(HIP_FOUND)
set(VLLM_GPU_LANG "HIP")
# Importing torch recognizes and sets up some HIP/ROCm configuration but does
# not let cmake recognize .hip files. In order to get cmake to understand the
# .hip extension automatically, HIP must be enabled explicitly.
enable_language(HIP)
# ROCm 5.X and 6.X
if (ROCM_VERSION_DEV_MAJOR GREATER_EQUAL 5 AND
NOT Torch_VERSION VERSION_EQUAL ${TORCH_SUPPORTED_VERSION_ROCM})
message(WARNING "Pytorch version >= ${TORCH_SUPPORTED_VERSION_ROCM} "
"expected for ROCm build, saw ${Torch_VERSION} instead.")
endif()
else()
message(FATAL_ERROR "Can't find CUDA or HIP installation.")
endif()
if(VLLM_GPU_LANG STREQUAL "CUDA")
#
# For cuda we want to be able to control which architectures we compile for on
# a per-file basis in order to cut down on compile time. So here we extract
# the set of architectures we want to compile for and remove the from the
# CMAKE_CUDA_FLAGS so that they are not applied globally.
#
clear_cuda_arches(CUDA_ARCH_FLAGS)
extract_unique_cuda_archs_ascending(CUDA_ARCHS "${CUDA_ARCH_FLAGS}")
message(STATUS "CUDA target architectures: ${CUDA_ARCHS}")
# Filter the target architectures by the supported supported archs
# since for some files we will build for all CUDA_ARCHS.
cuda_archs_loose_intersection(CUDA_ARCHS
"${CUDA_SUPPORTED_ARCHS}" "${CUDA_ARCHS}")
message(STATUS "CUDA supported target architectures: ${CUDA_ARCHS}")
else()
#
# For other GPU targets override the GPU architectures detected by cmake/torch
# and filter them by the supported versions for the current language.
# The final set of arches is stored in `VLLM_GPU_ARCHES`.
#
override_gpu_arches(VLLM_GPU_ARCHES
${VLLM_GPU_LANG}
"${${VLLM_GPU_LANG}_SUPPORTED_ARCHS}")
endif()
#
# Query torch for additional GPU compilation flags for the given
# `VLLM_GPU_LANG`.
# The final set of arches is stored in `VLLM_GPU_FLAGS`.
#
get_torch_gpu_compiler_flags(VLLM_GPU_FLAGS ${VLLM_GPU_LANG})
#
# Set nvcc parallelism.
#
if(NVCC_THREADS AND VLLM_GPU_LANG STREQUAL "CUDA")
list(APPEND VLLM_GPU_FLAGS "--threads=${NVCC_THREADS}")
endif()
#
# Use FetchContent for C++ dependencies that are compiled as part of vLLM's build process.
# setup.py will override FETCHCONTENT_BASE_DIR to play nicely with sccache.
# Each dependency that produces build artifacts should override its BINARY_DIR to avoid
# conflicts between build types. It should instead be set to ${CMAKE_BINARY_DIR}/<dependency>.
#
include(FetchContent)
file(MAKE_DIRECTORY ${FETCHCONTENT_BASE_DIR}) # Ensure the directory exists
message(STATUS "FetchContent base directory: ${FETCHCONTENT_BASE_DIR}")
#
# Set rocm version dev int.
#
if(VLLM_GPU_LANG STREQUAL "HIP")
#
# Overriding the default -O set up by cmake, adding ggdb3 for the most verbose devug info
#
set(CMAKE_${VLLM_GPU_LANG}_FLAGS_DEBUG "${CMAKE_${VLLM_GPU_LANG}_FLAGS_DEBUG} -O0 -ggdb3")
set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} -O0 -ggdb3")
#
# Certain HIP functions are marked as [[nodiscard]], yet vllm ignores the result which generates
# a lot of warnings that always mask real issues. Suppressing until this is properly addressed.
#
set(CMAKE_${VLLM_GPU_LANG}_FLAGS "${CMAKE_${VLLM_GPU_LANG}_FLAGS} -Wno-unused-result")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-unused-result")
endif()
#
# Define other extension targets
#
#
# cumem_allocator extension
#
set(VLLM_CUMEM_EXT_SRC
"csrc/cumem_allocator.cpp")
set_gencode_flags_for_srcs(
SRCS "${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::cuda_driver)
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
#
set(VLLM_EXT_SRC
"csrc/cache_kernels.cu"
"csrc/attention/paged_attention_v1.cu"
"csrc/attention/paged_attention_v2.cu"
"csrc/pos_encoding_kernels.cu"
"csrc/activation_kernels.cu"
"csrc/layernorm_kernels.cu"
"csrc/layernorm_quant_kernels.cu"
"csrc/quantization/gptq/q_gemm.cu"
"csrc/quantization/compressed_tensors/int8_quant_kernels.cu"
"csrc/quantization/fp8/common.cu"
"csrc/quantization/fused_kernels/fused_layernorm_dynamic_per_token_quant.cu"
"csrc/quantization/gguf/gguf_kernel.cu"
"csrc/cuda_utils_kernels.cu"
"csrc/prepare_inputs/advance_step.cu"
"csrc/torch_bindings.cpp")
if(VLLM_GPU_LANG STREQUAL "CUDA")
SET(CUTLASS_ENABLE_HEADERS_ONLY ON CACHE BOOL "Enable only the header library")
# Set CUTLASS_REVISION manually -- its revision detection doesn't work in this case.
# Please keep this in sync with FetchContent_Declare line below.
set(CUTLASS_REVISION "v3.8.0" CACHE STRING "CUTLASS revision to use")
# Use the specified CUTLASS source directory for compilation if VLLM_CUTLASS_SRC_DIR is provided
if (DEFINED ENV{VLLM_CUTLASS_SRC_DIR})
set(VLLM_CUTLASS_SRC_DIR $ENV{VLLM_CUTLASS_SRC_DIR})
endif()
if(VLLM_CUTLASS_SRC_DIR)
if(NOT IS_ABSOLUTE VLLM_CUTLASS_SRC_DIR)
get_filename_component(VLLM_CUTLASS_SRC_DIR "${VLLM_CUTLASS_SRC_DIR}" ABSOLUTE)
endif()
message(STATUS "The VLLM_CUTLASS_SRC_DIR is set, using ${VLLM_CUTLASS_SRC_DIR} for compilation")
FetchContent_Declare(cutlass SOURCE_DIR ${VLLM_CUTLASS_SRC_DIR})
else()
FetchContent_Declare(
cutlass
GIT_REPOSITORY https://github.com/nvidia/cutlass.git
# Please keep this in sync with CUTLASS_REVISION line above.
GIT_TAG v3.8.0
GIT_PROGRESS TRUE
# Speed up CUTLASS download by retrieving only the specified GIT_TAG instead of the history.
# Important: If GIT_SHALLOW is enabled then GIT_TAG works only with branch names and tags.
# So if the GIT_TAG above is updated to a commit hash, GIT_SHALLOW must be set to FALSE
GIT_SHALLOW TRUE
)
endif()
FetchContent_MakeAvailable(cutlass)
list(APPEND VLLM_EXT_SRC
"csrc/mamba/mamba_ssm/selective_scan_fwd.cu"
"csrc/mamba/causal_conv1d/causal_conv1d.cu"
"csrc/quantization/aqlm/gemm_kernels.cu"
"csrc/quantization/awq/gemm_kernels.cu"
"csrc/custom_all_reduce.cu"
"csrc/permute_cols.cu"
"csrc/quantization/cutlass_w8a8/scaled_mm_entry.cu"
"csrc/quantization/fp4/nvfp4_quant_entry.cu"
"csrc/quantization/fp4/nvfp4_scaled_mm_entry.cu"
"csrc/sparse/cutlass/sparse_scaled_mm_entry.cu"
"csrc/cutlass_extensions/common.cpp")
set_gencode_flags_for_srcs(
SRCS "${VLLM_EXT_SRC}"
CUDA_ARCHS "${CUDA_ARCHS}")
# Only build Marlin kernels if we are building for at least some compatible archs.
# Keep building Marlin for 9.0 as there are some group sizes and shapes that
# are not supported by Machete yet.
cuda_archs_loose_intersection(MARLIN_ARCHS "8.0;8.6;8.7;8.9;9.0;10.0;10.1;12.0" "${CUDA_ARCHS}")
if (MARLIN_ARCHS)
set(MARLIN_SRCS
"csrc/quantization/fp8/fp8_marlin.cu"
"csrc/quantization/marlin/dense/marlin_cuda_kernel.cu"
"csrc/quantization/marlin/sparse/marlin_24_cuda_kernel.cu"
"csrc/quantization/marlin/qqq/marlin_qqq_gemm_kernel.cu"
"csrc/quantization/gptq_marlin/gptq_marlin.cu"
"csrc/quantization/gptq_marlin/gptq_marlin_repack.cu"
"csrc/quantization/gptq_marlin/awq_marlin_repack.cu")
set_gencode_flags_for_srcs(
SRCS "${MARLIN_SRCS}"
CUDA_ARCHS "${MARLIN_ARCHS}")
list(APPEND VLLM_EXT_SRC "${MARLIN_SRCS}")
message(STATUS "Building Marlin kernels for archs: ${MARLIN_ARCHS}")
else()
message(STATUS "Not building Marlin kernels as no compatible archs found"
" in CUDA target architectures")
endif()
# Only build AllSpark kernels if we are building for at least some compatible archs.
cuda_archs_loose_intersection(ALLSPARK_ARCHS "8.0;8.6;8.7;8.9" "${CUDA_ARCHS}")
if (ALLSPARK_ARCHS)
set(ALLSPARK_SRCS
"csrc/quantization/gptq_allspark/allspark_repack.cu"
"csrc/quantization/gptq_allspark/allspark_qgemm_w8a16.cu")
set_gencode_flags_for_srcs(
SRCS "${ALLSPARK_SRCS}"
CUDA_ARCHS "${ALLSPARK_ARCHS}")
list(APPEND VLLM_EXT_SRC "${ALLSPARK_SRCS}")
message(STATUS "Building AllSpark kernels for archs: ${ALLSPARK_ARCHS}")
else()
message(STATUS "Not building AllSpark kernels as no compatible archs found"
" in CUDA target architectures")
endif()
set(SCALED_MM_3X_ARCHS)
# The cutlass_scaled_mm kernels for Hopper (c3x, i.e. CUTLASS 3.x) require
# CUDA 12.0 or later
cuda_archs_loose_intersection(SCALED_MM_ARCHS "9.0a;" "${CUDA_ARCHS}")
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0 AND SCALED_MM_ARCHS)
set(SRCS
"csrc/quantization/cutlass_w8a8/scaled_mm_c3x_sm90.cu"
"csrc/quantization/cutlass_w8a8/c3x/scaled_mm_sm90_fp8.cu"
"csrc/quantization/cutlass_w8a8/c3x/scaled_mm_sm90_int8.cu"
"csrc/quantization/cutlass_w8a8/c3x/scaled_mm_azp_sm90_int8.cu"
"csrc/quantization/cutlass_w8a8/c3x/scaled_mm_blockwise_sm90_fp8.cu")
set_gencode_flags_for_srcs(
SRCS "${SRCS}"
CUDA_ARCHS "${SCALED_MM_ARCHS}")
list(APPEND VLLM_EXT_SRC "${SRCS}")
list(APPEND VLLM_GPU_FLAGS "-DENABLE_SCALED_MM_SM90=1")
# Let scaled_mm_c2x know it doesn't need to build these arches
list(APPEND SCALED_MM_3X_ARCHS "${SCALED_MM_ARCHS}")
message(STATUS "Building scaled_mm_c3x_sm90 for archs: ${SCALED_MM_ARCHS}")
else()
if (NOT ${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0 AND SCALED_MM_ARCHS)
message(STATUS "Not building scaled_mm_c3x_sm90 as CUDA Compiler version is "
"not >= 12.0, we recommend upgrading to CUDA 12.0 or "
"later if you intend on running FP8 quantized models on "
"Hopper.")
else()
message(STATUS "Not building scaled_mm_c3x_sm90 as no compatible archs found "
"in CUDA target architectures")
endif()
endif()
# The cutlass_scaled_mm kernels for Blackwell (c3x, i.e. CUTLASS 3.x) require
# CUDA 12.8 or later
cuda_archs_loose_intersection(SCALED_MM_ARCHS "10.0a;10.1a;12.0a" "${CUDA_ARCHS}")
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.8 AND SCALED_MM_ARCHS)
set(SRCS
"csrc/quantization/cutlass_w8a8/scaled_mm_c3x_sm100.cu"
"csrc/quantization/cutlass_w8a8/c3x/scaled_mm_sm100_fp8.cu"
)
set_gencode_flags_for_srcs(
SRCS "${SRCS}"
CUDA_ARCHS "${SCALED_MM_ARCHS}")
list(APPEND VLLM_EXT_SRC "${SRCS}")
list(APPEND VLLM_GPU_FLAGS "-DENABLE_SCALED_MM_SM100=1")
# Let scaled_mm_c2x know it doesn't need to build these arches
list(APPEND SCALED_MM_3X_ARCHS "${SCALED_MM_ARCHS}")
message(STATUS "Building scaled_mm_c3x_sm100 for archs: ${SCALED_MM_ARCHS}")
else()
if (NOT ${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.8 AND SCALED_MM_ARCHS)
message(STATUS "Not building scaled_mm_c3x_sm100 as CUDA Compiler version is "
"not >= 12.8, we recommend upgrading to CUDA 12.8 or "
"later if you intend on running FP8 quantized models on "
"Blackwell.")
else()
message(STATUS "Not building scaled_mm_c3x_100 as no compatible archs found "
"in CUDA target architectures")
endif()
endif()
#
# For the cutlass_scaled_mm kernels we want to build the c2x (CUTLASS 2.x)
# kernels for the remaining archs that are not already built for 3x.
cuda_archs_loose_intersection(SCALED_MM_2X_ARCHS
"7.5;8.0;8.6;8.7;8.9;9.0;10.0;10.1;12.0" "${CUDA_ARCHS}")
# subtract out the archs that are already built for 3x
list(REMOVE_ITEM SCALED_MM_2X_ARCHS ${SCALED_MM_3X_ARCHS})
if (SCALED_MM_2X_ARCHS)
set(SRCS "csrc/quantization/cutlass_w8a8/scaled_mm_c2x.cu")
set_gencode_flags_for_srcs(
SRCS "${SRCS}"
CUDA_ARCHS "${SCALED_MM_2X_ARCHS}")
list(APPEND VLLM_EXT_SRC "${SRCS}")
list(APPEND VLLM_GPU_FLAGS "-DENABLE_SCALED_MM_C2X=1")
message(STATUS "Building scaled_mm_c2x for archs: ${SCALED_MM_2X_ARCHS}")
else()
if (SCALED_MM_3X_ARCHS)
message(STATUS "Not building scaled_mm_c2x as all archs are already built"
" for and covered by scaled_mm_c3x")
else()
message(STATUS "Not building scaled_mm_c2x as no compatible archs found "
"in CUDA target architectures")
endif()
endif()
#
# 2:4 Sparse Kernels
# The 2:4 sparse kernels cutlass_scaled_sparse_mm and cutlass_compressor
# require CUDA 12.2 or later (and only work on Hopper).
cuda_archs_loose_intersection(SCALED_MM_ARCHS "9.0a;" "${CUDA_ARCHS}")
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.2 AND SCALED_MM_ARCHS)
set(SRCS "csrc/sparse/cutlass/sparse_scaled_mm_c3x.cu")
set_gencode_flags_for_srcs(
SRCS "${SRCS}"
CUDA_ARCHS "${SCALED_MM_ARCHS}")
list(APPEND VLLM_EXT_SRC "${SRCS}")
list(APPEND VLLM_GPU_FLAGS "-DENABLE_SPARSE_SCALED_MM_C3X=1")
message(STATUS "Building sparse_scaled_mm_c3x for archs: ${SCALED_MM_ARCHS}")
else()
if (NOT ${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.2 AND SCALED_MM_ARCHS)
message(STATUS "Not building sparse_scaled_mm_c3x kernels as CUDA Compiler version is "
"not >= 12.2, we recommend upgrading to CUDA 12.2 or later "
"if you intend on running FP8 sparse quantized models on Hopper.")
else()
message(STATUS "Not building sparse_scaled_mm_c3x as no compatible archs found "
"in CUDA target architectures")
endif()
endif()
# FP4 Archs and flags
cuda_archs_loose_intersection(FP4_ARCHS "10.0a" "${CUDA_ARCHS}")
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.8 AND FP4_ARCHS)
set(SRCS
"csrc/quantization/fp4/nvfp4_quant_kernels.cu"
"csrc/quantization/fp4/nvfp4_scaled_mm_kernels.cu")
set_gencode_flags_for_srcs(
SRCS "${SRCS}"
CUDA_ARCHS "${FP4_ARCHS}")
list(APPEND VLLM_EXT_SRC "${SRCS}")
list(APPEND VLLM_GPU_FLAGS "-DENABLE_NVFP4=1")
message(STATUS "Building NVFP4 for archs: ${FP4_ARCHS}")
else()
message(STATUS "Not building NVFP4 as no compatible archs were found.")
# clear FP4_ARCHS
set(FP4_ARCHS)
endif()
#
# CUTLASS MoE kernels
# The MoE kernel cutlass_moe_mm requires CUDA 12.3 or later (and only works
# on Hopper). get_cutlass_moe_mm_data should only be compiled if it's possible
# to compile MoE kernels that use its output.
cuda_archs_loose_intersection(SCALED_MM_ARCHS "9.0a;" "${CUDA_ARCHS}")
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 12.3 AND SCALED_MM_ARCHS)
set(SRCS "csrc/quantization/cutlass_w8a8/moe/grouped_mm_c3x.cu"
"csrc/quantization/cutlass_w8a8/moe/moe_data.cu")
set_gencode_flags_for_srcs(
SRCS "${SRCS}"
CUDA_ARCHS "${SCALED_MM_ARCHS}")
list(APPEND VLLM_EXT_SRC "${SRCS}")
list(APPEND VLLM_GPU_FLAGS "-DENABLE_CUTLASS_MOE_SM90=1")
message(STATUS "Building grouped_mm_c3x for archs: ${SCALED_MM_ARCHS}")
else()
if (NOT ${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 12.3 AND SCALED_MM_ARCHS)
message(STATUS "Not building grouped_mm_c3x kernels as CUDA Compiler version is "
"not >= 12.3, we recommend upgrading to CUDA 12.3 or later "
"if you intend on running FP8 quantized MoE models on Hopper.")
else()
message(STATUS "Not building grouped_mm_c3x as no compatible archs found "
"in CUDA target architectures")
endif()
endif()
#
# Machete kernels
# The machete kernels only work on hopper and require CUDA 12.0 or later.
# Only build Machete kernels if we are building for something compatible with sm90a
cuda_archs_loose_intersection(MACHETE_ARCHS "9.0a" "${CUDA_ARCHS}")
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0 AND MACHETE_ARCHS)
#
# For the Machete kernels we automatically generate sources for various
# preselected input type pairs and schedules.
# Generate sources:
set(MACHETE_GEN_SCRIPT
${CMAKE_CURRENT_SOURCE_DIR}/csrc/quantization/machete/generate.py)
file(MD5 ${MACHETE_GEN_SCRIPT} MACHETE_GEN_SCRIPT_HASH)
message(STATUS "Machete generation script hash: ${MACHETE_GEN_SCRIPT_HASH}")
message(STATUS "Last run machete generate script hash: $CACHE{MACHETE_GEN_SCRIPT_HASH}")
if (NOT DEFINED CACHE{MACHETE_GEN_SCRIPT_HASH}
OR NOT $CACHE{MACHETE_GEN_SCRIPT_HASH} STREQUAL ${MACHETE_GEN_SCRIPT_HASH})
execute_process(
COMMAND ${CMAKE_COMMAND} -E env
PYTHONPATH=${CMAKE_CURRENT_SOURCE_DIR}/csrc/cutlass_extensions/:${CUTLASS_DIR}/python/:${VLLM_PYTHON_PATH}:$PYTHONPATH
${Python_EXECUTABLE} ${MACHETE_GEN_SCRIPT}
RESULT_VARIABLE machete_generation_result
OUTPUT_VARIABLE machete_generation_output
OUTPUT_FILE ${CMAKE_CURRENT_BINARY_DIR}/machete_generation.log
ERROR_FILE ${CMAKE_CURRENT_BINARY_DIR}/machete_generation.log
)
if (NOT machete_generation_result EQUAL 0)
message(FATAL_ERROR "Machete generation failed."
" Result: \"${machete_generation_result}\""
"\nCheck the log for details: "
"${CMAKE_CURRENT_BINARY_DIR}/machete_generation.log")
else()
set(MACHETE_GEN_SCRIPT_HASH ${MACHETE_GEN_SCRIPT_HASH}
CACHE STRING "Last run machete generate script hash" FORCE)
message(STATUS "Machete generation completed successfully.")
endif()
else()
message(STATUS "Machete generation script has not changed, skipping generation.")
endif()
# Add machete generated sources
file(GLOB MACHETE_GEN_SOURCES "csrc/quantization/machete/generated/*.cu")
list(APPEND VLLM_EXT_SRC ${MACHETE_GEN_SOURCES})
# forward compatible
set_gencode_flags_for_srcs(
SRCS "${MACHETE_GEN_SOURCES}"
CUDA_ARCHS "${MACHETE_ARCHS}")
list(APPEND VLLM_EXT_SRC
csrc/quantization/machete/machete_pytorch.cu)
message(STATUS "Building Machete kernels for archs: ${MACHETE_ARCHS}")
else()
if (NOT ${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0
AND MACHETE_ARCHS)
message(STATUS "Not building Machete kernels as CUDA Compiler version is "
"not >= 12.0, we recommend upgrading to CUDA 12.0 or "
"later if you intend on running w4a16 quantized models on "
"Hopper.")
else()
message(STATUS "Not building Machete kernels as no compatible archs "
"found in CUDA target architectures")
endif()
endif()
# if CUDA endif
endif()
message(STATUS "Enabling C extension.")
define_gpu_extension_target(
_C
DESTINATION vllm
LANGUAGE ${VLLM_GPU_LANG}
SOURCES ${VLLM_EXT_SRC}
COMPILE_FLAGS ${VLLM_GPU_FLAGS}
ARCHITECTURES ${VLLM_GPU_ARCHES}
INCLUDE_DIRECTORIES ${CUTLASS_INCLUDE_DIR}
INCLUDE_DIRECTORIES ${CUTLASS_TOOLS_UTIL_INCLUDE_DIR}
USE_SABI 3
WITH_SOABI)
# If CUTLASS is compiled on NVCC >= 12.5, it by default uses
# cudaGetDriverEntryPointByVersion as a wrapper to avoid directly calling the
# driver API. This causes problems when linking with earlier versions of CUDA.
# Setting this variable sidesteps the issue by calling the driver directly.
target_compile_definitions(_C PRIVATE CUTLASS_ENABLE_DIRECT_CUDA_DRIVER_CALL=1)
#
# _moe_C extension
#
set(VLLM_MOE_EXT_SRC
"csrc/moe/torch_bindings.cpp"
"csrc/moe/moe_align_sum_kernels.cu"
"csrc/moe/topk_softmax_kernels.cu")
if(VLLM_GPU_LANG STREQUAL "CUDA")
list(APPEND VLLM_MOE_EXT_SRC "csrc/moe/moe_wna16.cu")
endif()
set_gencode_flags_for_srcs(
SRCS "${VLLM_MOE_EXT_SRC}"
CUDA_ARCHS "${CUDA_ARCHS}")
if(VLLM_GPU_LANG STREQUAL "CUDA")
set(VLLM_MOE_WNA16_SRC
"csrc/moe/moe_wna16.cu")
set_gencode_flags_for_srcs(
SRCS "${VLLM_MOE_WNA16_SRC}"
CUDA_ARCHS "${CUDA_ARCHS}")
list(APPEND VLLM_MOE_EXT_SRC "${VLLM_MOE_WNA16_SRC}")
cuda_archs_loose_intersection(MARLIN_MOE_ARCHS "8.0;8.6;8.7;8.9;9.0;10.0;10.1;12.0" "${CUDA_ARCHS}")
if (MARLIN_MOE_ARCHS)
set(MARLIN_MOE_SRC
"csrc/moe/marlin_kernels/marlin_moe_kernel.h"
"csrc/moe/marlin_kernels/marlin_moe_kernel_ku4b8.h"
"csrc/moe/marlin_kernels/marlin_moe_kernel_ku4b8.cu"
"csrc/moe/marlin_kernels/marlin_moe_kernel_ku8b128.h"
"csrc/moe/marlin_kernels/marlin_moe_kernel_ku8b128.cu"
"csrc/moe/marlin_kernels/marlin_moe_kernel_ku4.h"
"csrc/moe/marlin_kernels/marlin_moe_kernel_ku4.cu"
"csrc/moe/marlin_moe_ops.cu")
set_gencode_flags_for_srcs(
SRCS "${MARLIN_MOE_SRC}"
CUDA_ARCHS "${MARLIN_MOE_ARCHS}")
list(APPEND VLLM_MOE_EXT_SRC "${MARLIN_MOE_SRC}")
message(STATUS "Building Marlin MOE kernels for archs: ${MARLIN_MOE_ARCHS}")
else()
message(STATUS "Not building Marlin MOE kernels as no compatible archs found"
" in CUDA target architectures")
endif()
endif()
message(STATUS "Enabling moe extension.")
define_gpu_extension_target(
_moe_C
DESTINATION vllm
LANGUAGE ${VLLM_GPU_LANG}
SOURCES ${VLLM_MOE_EXT_SRC}
COMPILE_FLAGS ${VLLM_GPU_FLAGS}
ARCHITECTURES ${VLLM_GPU_ARCHES}
USE_SABI 3
WITH_SOABI)
if(VLLM_GPU_LANG STREQUAL "HIP")
#
# _rocm_C extension
#
set(VLLM_ROCM_EXT_SRC
"csrc/rocm/torch_bindings.cpp"
"csrc/rocm/attention.cu")
define_gpu_extension_target(
_rocm_C
DESTINATION vllm
LANGUAGE ${VLLM_GPU_LANG}
SOURCES ${VLLM_ROCM_EXT_SRC}
COMPILE_FLAGS ${VLLM_GPU_FLAGS}
ARCHITECTURES ${VLLM_GPU_ARCHES}
USE_SABI 3
WITH_SOABI)
endif()
# For CUDA we also build and ship some external projects.
if (VLLM_GPU_LANG STREQUAL "CUDA")
include(cmake/external_projects/flashmla.cmake)
include(cmake/external_projects/vllm_flash_attn.cmake)
endif ()
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