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CMakeLists.txt
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CMakeLists.txt
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cmake_minimum_required(VERSION 3.26)
project(aphrodite_extensions LANGUAGES CXX)
# CUDA by default, can be overridden by using -DAPHRODITE_TARGET_DEVICE=... (used by setup.py)
set(APHRODITE_TARGET_DEVICE "cuda" CACHE STRING "Target device backend for Aphrodite")
message(STATUS "Build type: ${CMAKE_BUILD_TYPE}")
message(STATUS "Target device: ${APHRODITE_TARGET_DEVICE}")
include(${CMAKE_CURRENT_LIST_DIR}/cmake/utils.cmake)
# Suppress potential warnings about unused manually-specified variables
set(ignoreMe "${APHRODITE_PYTHON_PATH}")
#
# Supported python versions. These versions will be searched in order, the
# first match will be selected. These should be kept in sync with setup.py.
#
set(PYTHON_SUPPORTED_VERSIONS "3.8" "3.9" "3.10" "3.11" "3.12")
# Supported NVIDIA architectures.
set(CUDA_SUPPORTED_ARCHS "6.0;6.1;7.0;7.5;8.0;8.6;8.9;9.0")
# Supported AMD GPU architectures.
set(HIP_SUPPORTED_ARCHS "gfx906;gfx908;gfx90a;gfx940;gfx941;gfx942;gfx1030;gfx1100;gfx1101")
#
# Supported/expected torch versions for CUDA/ROCm.
#
# Currently, having an incorrect pytorch version results in a warning
# rather than an error.
#
# Note: the CUDA torch version is derived from pyproject.toml and various
# requirements.txt files and should be kept consistent. The ROCm torch
# versions are derived from Dockerfile.rocm
#
set(TORCH_SUPPORTED_VERSION_CUDA "2.4.0")
set(TORCH_SUPPORTED_VERSION_ROCM "2.5.0")
#
# Try to find python package with an executable that exactly matches
# `APHRODITE_PYTHON_EXECUTABLE` and is one of the supported versions.
#
if (APHRODITE_PYTHON_EXECUTABLE)
find_python_from_executable(${APHRODITE_PYTHON_EXECUTABLE} "${PYTHON_SUPPORTED_VERSIONS}")
else()
message(FATAL_ERROR
"Please set APHRODITE_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)
if(MSVC)
find_package(CUDA REQUIRED)
find_package(CUDAToolkit REQUIRED)
# Add cuBLAS to the list of libraries to link against
list(APPEND LIBS CUDA::cublas)
set(CMAKE_CXX_STANDARD 17)
set(CMAKE_CXX_STANDARD_REQUIRED ON)
set(CMAKE_CUDA_STANDARD 17)
set(CMAKE_CUDA_STANDARD_REQUIRED ON)
# Replace -std=c++20 with -std=c++17 in APHRODITE_GPU_FLAGS
if(APHRODITE_GPU_LANG STREQUAL "CUDA")
list(APPEND APHRODITE_GPU_FLAGS "--std=c++17" "-Xcompiler -Wno-return-type")
endif()
endif()
#
# Add the `default` target which detects which extensions should be
# built based on platform/architecture. This is the same logic that
# setup.py uses to select which extensions should be built and should
# be kept in sync.
#
# The `default` target makes direct use of cmake easier since knowledge
# of which extensions are supported has been factored in, e.g.
#
# mkdir build && cd build
# cmake -G Ninja -DAPHRODITE_PYTHON_EXECUTABLE=`which python3` -DCMAKE_LIBRARY_OUTPUT_DIRECTORY=../aphrodite ..
# cmake --build . --target default
#
add_custom_target(default)
message(STATUS "Enabling core extension.")
# Define _core_C extension
# built for (almost) every target platform, (excludes TPU and Neuron)
set(APHRODITE_EXT_SRC
"kernels/core/torch_bindings.cpp")
define_gpu_extension_target(
_core_C
DESTINATION aphrodite
LANGUAGE CXX
SOURCES ${APHRODITE_EXT_SRC}
COMPILE_FLAGS ${CXX_COMPILE_FLAGS}
USE_SABI 3
WITH_SOABI)
add_dependencies(default _core_C)
#
# Forward the non-CUDA device extensions to external CMake scripts.
#
if (NOT APHRODITE_TARGET_DEVICE STREQUAL "cuda" AND
NOT APHRODITE_TARGET_DEVICE STREQUAL "rocm")
if (APHRODITE_TARGET_DEVICE STREQUAL "cpu")
include(${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(APHRODITE_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(APHRODITE_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()
#
# 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 `APHRODITE_GPU_ARCHES`.
#
override_gpu_arches(APHRODITE_GPU_ARCHES
${APHRODITE_GPU_LANG}
"${${APHRODITE_GPU_LANG}_SUPPORTED_ARCHS}")
#
# Query torch for additional GPU compilation flags for the given
# `APHRODITE_GPU_LANG`.
# The final set of arches is stored in `APHRODITE_GPU_FLAGS`.
#
get_torch_gpu_compiler_flags(APHRODITE_GPU_FLAGS ${APHRODITE_GPU_LANG})
#
# Set nvcc parallelism.
#
if(NVCC_THREADS AND APHRODITE_GPU_LANG STREQUAL "CUDA")
list(APPEND APHRODITE_GPU_FLAGS "--threads=${NVCC_THREADS}")
endif()
#
# Define other extension targets
#
#
# _C extension
#
set(APHRODITE_EXT_SRC
"kernels/cache_kernels.cu"
"kernels/attention/attention_kernels.cu"
"kernels/pos_encoding_kernels.cu"
"kernels/activation_kernels.cu"
"kernels/layernorm_kernels.cu"
"kernels/quantization/squeezellm/quant_cuda_kernel.cu"
"kernels/quantization/gptq/q_gemm.cu"
"kernels/quantization/compressed_tensors/int8_quant_kernels.cu"
"kernels/quantization/fp8/common.cu"
"kernels/cuda_utils_kernels.cu"
"kernels/moe/align_block_size_kernel.cu"
"kernels/prepare_inputs/advance_step.cu"
"kernels/torch_bindings.cpp")
if(APHRODITE_GPU_LANG STREQUAL "CUDA")
list(APPEND APHRODITE_EXT_SRC
"kernels/quantization/fp6/fp6_linear.cu"
"kernels/mamba/mamba_ssm/selective_scan_fwd.cu"
"kernels/mamba/causal_conv1d/causal_conv1d.cu"
"kernels/quantization/aqlm/gemm_kernels.cu"
"kernels/quantization/awq/gemm_kernels.cu"
"kernels/quantization/quip/origin_order.cu"
"kernels/quantization/gptq_marlin/gptq_marlin.cu"
"kernels/quantization/gptq_marlin/gptq_marlin_repack.cu"
"kernels/quantization/marlin/dense/marlin_cuda_kernel.cu"
"kernels/quantization/marlin/sparse/marlin_24_cuda_kernel.cu"
"kernels/quantization/marlin/qqq/marlin_qqq_gemm_kernel.cu"
"kernels/quantization/gguf/gguf_kernel.cu"
"kernels/quantization/gptq_marlin/awq_marlin_repack.cu"
"kernels/quantization/fp8/fp8_marlin.cu"
"kernels/all_reduce/custom_all_reduce.cu"
"kernels/permute_cols.cu"
"kernels/sampling/sampling.cu")
if(NOT MSVC)
# Include CUTLASS only when needed
include(FetchContent)
SET(CUTLASS_ENABLE_HEADERS_ONLY=ON)
FetchContent_Declare(
cutlass
GIT_REPOSITORY https://github.com/nvidia/cutlass.git
GIT_TAG v3.5.1
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
)
FetchContent_MakeAvailable(cutlass)
list(APPEND APHRODITE_EXT_SRC
"kernels/quantization/cutlass_w8a8/scaled_mm_entry.cu"
"kernels/quantization/cutlass_w8a8/scaled_mm_c2x.cu"
"kernels/quantization/cutlass_w8a8/scaled_mm_c3x.cu")
# Enable sm90a for Hopper CUTLASS kernels when using newer CUDA
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0)
set_source_files_properties(
"kernels/quantization/cutlass_w8a8/scaled_mm_c2x.cu"
"kernels/quantization/cutlass_w8a8/scaled_mm_c3x.cu"
PROPERTIES
COMPILE_FLAGS
"-gencode arch=compute_90a,code=sm_90a -Wno-psabi")
endif()
endif()
#
# Machete kernels
# The machete kernels only work on hopper and require CUDA 12.0 or later.
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0)
#
# For the Machete kernels we automatically generate sources for various
# preselected input type pairs and schedules.
# Generate sources:
execute_process(
COMMAND ${CMAKE_COMMAND} -E env
PYTHONPATH=${CMAKE_CURRENT_SOURCE_DIR}/kernels/cutlass_extensions/:${CUTLASS_DIR}/python/:${APHRODITE_PYTHON_PATH}:$PYTHONPATH
${Python_EXECUTABLE} ${CMAKE_CURRENT_SOURCE_DIR}/kernels/quantization/machete/generate.py
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()
message(STATUS "Machete generation completed successfully.")
endif()
# Add machete generated sources
file(GLOB MACHETE_GEN_SOURCES "kernels/quantization/machete/generated/*.cu")
list(APPEND APHRODITE_EXT_SRC ${MACHETE_GEN_SOURCES})
message(STATUS "Machete generated sources: ${MACHETE_GEN_SOURCES}")
set_source_files_properties(
${MACHETE_GEN_SOURCES}
PROPERTIES
COMPILE_FLAGS
"-gencode arch=compute_90a,code=sm_90a")
endif()
# Add pytorch binding for machete (add on even CUDA < 12.0 so that we can
# raise an error if the user that this was built with an incompatible
# CUDA version)
list(APPEND APHRODITE_EXT_SRC
kernels/quantization/machete/machete_pytorch.cu)
endif()
define_gpu_extension_target(
_C
DESTINATION aphrodite
LANGUAGE ${APHRODITE_GPU_LANG}
SOURCES ${APHRODITE_EXT_SRC}
COMPILE_FLAGS ${APHRODITE_GPU_FLAGS}
ARCHITECTURES ${APHRODITE_GPU_ARCHES}
INCLUDE_DIRECTORIES ${CUTLASS_INCLUDE_DIR}
LIBRARIES ${LIBS}
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(APHRODITE_MOE_EXT_SRC
"kernels/moe/torch_bindings.cpp"
"kernels/moe/softmax.cu")
if(APHRODITE_GPU_LANG STREQUAL "CUDA")
list(APPEND APHRODITE_MOE_EXT_SRC
"kernels/moe/marlin_moe_ops.cu")
endif()
define_gpu_extension_target(
_moe_C
DESTINATION aphrodite
LANGUAGE ${APHRODITE_GPU_LANG}
SOURCES ${APHRODITE_MOE_EXT_SRC}
COMPILE_FLAGS ${APHRODITE_GPU_FLAGS}
ARCHITECTURES ${APHRODITE_GPU_ARCHES}
USE_SABI 3
WITH_SOABI)
if(APHRODITE_GPU_LANG STREQUAL "HIP")
#
# _rocm_C extension
#
set(APHRODITE_ROCM_EXT_SRC
"kernels/rocm/torch_bindings.cpp"
"kernels/rocm/attention.cu")
define_gpu_extension_target(
_rocm_C
DESTINATION aphrodite
LANGUAGE ${APHRODITE_GPU_LANG}
SOURCES ${APHRODITE_ROCM_EXT_SRC}
COMPILE_FLAGS ${APHRODITE_GPU_FLAGS}
ARCHITECTURES ${APHRODITE_GPU_ARCHES}
USE_SABI 3
WITH_SOABI)
endif()
if(APHRODITE_GPU_LANG STREQUAL "CUDA" OR APHRODITE_GPU_LANG STREQUAL "HIP")
message(STATUS "Enabling C extension.")
add_dependencies(default _C)
message(STATUS "Enabling moe extension.")
add_dependencies(default _moe_C)
endif()
if(APHRODITE_GPU_LANG STREQUAL "HIP")
message(STATUS "Enabling rocm extension.")
add_dependencies(default _rocm_C)
endif()