Remove support for Nvidia & AMD GPU, because the oneAPI plugin for Nvidia & AMD GPU is unavailable: download/installation channels are out of work. (#19246)
User can't build up the software for Nvidia & AMD GPU. rm the oneMath since it is only used in NV and AMD code path.
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@@ -1,7 +1,7 @@
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message(STATUS "GGML_SYCL_TARGET=${GGML_SYCL_TARGET}")
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if (NOT GGML_SYCL_TARGET MATCHES "^(INTEL|NVIDIA|AMD)$")
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message(FATAL_ERROR "Invalid backend chosen, supported options are INTEL, NVIDIA, or AMD")
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if (NOT GGML_SYCL_TARGET MATCHES "^(INTEL)$")
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message(FATAL_ERROR "GGML_SYCL_TARGET: Invalid target, the supported options are [INTEL]")
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endif()
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check_cxx_compiler_flag("-fsycl" SUPPORTS_SYCL)
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@@ -125,25 +125,22 @@ endif()
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target_compile_definitions(ggml-sycl PRIVATE GGML_SYCL_DNNL=${GGML_SYCL_DNNL})
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if (GGML_SYCL_F16)
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if (GGML_SYCL_TARGET STREQUAL "AMD")
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message(WARNING "AMD target does not entirely support FP16 in the SYCL backend.")
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endif()
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add_compile_definitions(GGML_SYCL_F16)
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endif()
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if (GGML_SYCL_TARGET STREQUAL "INTEL")
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add_compile_definitions(GGML_SYCL_WARP_SIZE=16)
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target_link_options(ggml-sycl PRIVATE -Xs -ze-intel-greater-than-4GB-buffer-required)
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elseif (GGML_SYCL_TARGET STREQUAL "NVIDIA")
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add_compile_definitions(GGML_SYCL_WARP_SIZE=32)
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elseif (GGML_SYCL_TARGET STREQUAL "AMD")
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# INFO: Allowed Sub_group_sizes are not consistent through all
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# hip targets. For example, 64 is used for certain models, but the backend
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# does not support it.
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# Target archs tested working: gfx1030, gfx1031, (Only tested sub_group_size = 32)
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add_compile_definitions(GGML_SYCL_WARP_SIZE=32)
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# Link against Intel oneMKL
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if (CMAKE_CXX_COMPILER_ID STREQUAL "Clang")
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set(SYCL_COMPILER ON)
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endif()
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find_package(MKL REQUIRED)
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target_link_libraries(ggml-sycl PRIVATE MKL::MKL_SYCL::BLAS)
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else()
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# default for other target
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message(FATAL_ERROR "GGML_SYCL_TARGET is not supported")
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add_compile_definitions(GGML_SYCL_WARP_SIZE=32)
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endif()
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@@ -151,82 +148,6 @@ if (GGML_SYCL_GRAPH)
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target_compile_definitions(ggml-sycl PRIVATE GGML_SYCL_GRAPH)
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endif()
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# Link against Intel oneMKL or oneMath
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if (GGML_SYCL_TARGET STREQUAL "INTEL")
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# Intel devices use Intel oneMKL directly instead of oneMath to avoid the limitation of linking Intel oneMKL statically
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# See https://github.com/uxlfoundation/oneMath/issues/654
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if (CMAKE_CXX_COMPILER_ID STREQUAL "Clang")
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set(SYCL_COMPILER ON)
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endif()
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find_package(MKL REQUIRED)
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target_link_libraries(ggml-sycl PRIVATE MKL::MKL_SYCL::BLAS)
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target_compile_definitions(ggml-sycl PRIVATE GGML_SYCL_USE_INTEL_ONEMKL)
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else()
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find_package(oneMath QUIET)
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if (NOT oneMath_FOUND)
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message(STATUS "oneMath not found: oneMath will be automatically downloaded")
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# Use FetchContent to automatically pull and build oneMath
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include(FetchContent)
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set(BUILD_FUNCTIONAL_TESTS False)
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set(BUILD_EXAMPLES False)
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set(TARGET_DOMAINS blas)
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if (GGML_SYCL_TARGET STREQUAL "NVIDIA")
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set(ENABLE_MKLCPU_BACKEND False)
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set(ENABLE_MKLGPU_BACKEND False)
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set(ENABLE_CUBLAS_BACKEND True)
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elseif (GGML_SYCL_TARGET STREQUAL "AMD")
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set(ENABLE_MKLCPU_BACKEND False)
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set(ENABLE_MKLGPU_BACKEND False)
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set(ENABLE_ROCBLAS_BACKEND True)
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# Ensure setting a string variable here is not overriden by oneMath CACHE variables
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cmake_policy(SET CMP0126 NEW)
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# Setting the device architecture is only needed and useful for AMD devices in oneMath
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set(HIP_TARGETS ${GGML_SYCL_DEVICE_ARCH} CACHE STRING "oneMath HIP target" FORCE)
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endif()
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FetchContent_Declare(
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ONEMATH
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GIT_REPOSITORY https://github.com/uxlfoundation/oneMath.git
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GIT_TAG 8efe85f5aaebb37f1d8c503b7af66315feabf142
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)
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FetchContent_MakeAvailable(ONEMATH)
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# Create alias to match with find_package targets name
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function(onemath_alias target)
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if (TARGET ${target}_obj)
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# Silence verbose warnings from external libraries
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target_compile_options(${target}_obj PRIVATE -w)
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endif()
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if (TARGET ${target})
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add_library(ONEMATH::${target} ALIAS ${target})
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endif()
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endfunction()
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onemath_alias(onemath)
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onemath_alias(onemath_blas_mklcpu)
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onemath_alias(onemath_blas_mklgpu)
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onemath_alias(onemath_blas_cublas)
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onemath_alias(onemath_blas_rocblas)
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endif()
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# Below oneMath compile-time dispatching is used for better performance
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if (GGML_SYCL_TARGET STREQUAL "NVIDIA")
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target_link_libraries(ggml-sycl PRIVATE ONEMATH::onemath_blas_cublas)
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target_compile_options(ggml-sycl PRIVATE "-fsycl-targets=nvptx64-nvidia-cuda")
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target_link_options(ggml-sycl PRIVATE "-fsycl-targets=nvptx64-nvidia-cuda")
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target_compile_definitions(ggml-sycl PRIVATE GGML_SYCL_NVIDIA)
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elseif (GGML_SYCL_TARGET STREQUAL "AMD")
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if (NOT GGML_SYCL_DEVICE_ARCH)
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message(FATAL_ERROR "Can't enable SYCL hip backend, GGML_SYCL_DEVICE_ARCH has not been set.")
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endif()
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target_link_libraries(ggml-sycl PRIVATE ONEMATH::onemath_blas_rocblas)
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target_compile_options(ggml-sycl PRIVATE "-fsycl-targets=amdgcn-amd-amdhsa")
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target_link_options(ggml-sycl PRIVATE "-fsycl-targets=amdgcn-amd-amdhsa")
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target_compile_definitions(ggml-sycl PRIVATE GGML_SYCL_AMD)
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else()
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# Fallback to oneMath runtime dispatcher
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target_link_libraries(ggml-sycl PRIVATE ONEMATH::onemath)
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target_compile_definitions(ggml-sycl PRIVATE GGML_SYCL_GENERIC)
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endif()
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endif()
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if (GGML_SYCL_DEVICE_ARCH)
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target_compile_options(ggml-sycl PRIVATE -Xsycl-target-backend --offload-arch=${GGML_SYCL_DEVICE_ARCH})
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target_link_options(ggml-sycl PRIVATE -Xsycl-target-backend --offload-arch=${GGML_SYCL_DEVICE_ARCH})
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