#!/bin/bash # This script is intended to run inside the go generate # working directory must be llm/generate/ # First we build one or more CPU based LLM libraries # # Then if we detect CUDA, we build a CUDA dynamic library, and carry the required # library dependencies # # Then if we detect ROCm, we build a dynamically loaded ROCm lib. The ROCM # libraries are quite large, and also dynamically load data files at runtime # which in turn are large, so we don't attempt to cary them as payload set -ex set -o pipefail # See https://llvm.org/docs/AMDGPUUsage.html#processors for reference amdGPUs() { if [ -n "${AMDGPU_TARGETS}" ]; then echo "${AMDGPU_TARGETS}" return fi GPU_LIST=( "gfx900" "gfx906:xnack-" "gfx908:xnack-" "gfx90a:xnack+" "gfx90a:xnack-" "gfx940" "gfx941" "gfx942" "gfx1010" "gfx1012" "gfx1030" "gfx1100" "gfx1101" "gfx1102" ) ( IFS=$';' echo "'${GPU_LIST[*]}'" ) } echo "Starting linux generate script" if [ -z "${CUDACXX}" ]; then if [ -x /usr/local/cuda/bin/nvcc ]; then export CUDACXX=/usr/local/cuda/bin/nvcc else # Try the default location in case it exists export CUDACXX=$(command -v nvcc) fi fi COMMON_CMAKE_DEFS="-DBUILD_SHARED_LIBS=off -DCMAKE_POSITION_INDEPENDENT_CODE=on -DGGML_NATIVE=off -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_OPENMP=off" source $(dirname $0)/gen_common.sh init_vars git_module_setup apply_patches init_vars if [ -z "${OLLAMA_SKIP_STATIC_GENERATE}" -o "${OLLAMA_CPU_TARGET}" = "static" ]; then # Builds by default, allows skipping, forces build if OLLAMA_CPU_TARGET="static" # Enables optimized Dockerfile builds using a blanket skip and targeted overrides # Static build for linking into the Go binary init_vars CMAKE_TARGETS="--target llama --target ggml" CMAKE_DEFS="-DBUILD_SHARED_LIBS=off -DGGML_NATIVE=off -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_OPENMP=off ${CMAKE_DEFS}" BUILD_DIR="../build/linux/${ARCH}_static" echo "Building static library" build fi init_vars if [ -z "${OLLAMA_SKIP_CPU_GENERATE}" ]; then # Users building from source can tune the exact flags we pass to cmake for configuring # llama.cpp, and we'll build only 1 CPU variant in that case as the default. if [ -n "${OLLAMA_CUSTOM_CPU_DEFS}" ]; then init_vars echo "OLLAMA_CUSTOM_CPU_DEFS=\"${OLLAMA_CUSTOM_CPU_DEFS}\"" CMAKE_DEFS="${OLLAMA_CUSTOM_CPU_DEFS} -DBUILD_SHARED_LIBS=off -DCMAKE_POSITION_INDEPENDENT_CODE=on ${CMAKE_DEFS}" BUILD_DIR="../build/linux/${ARCH}/cpu" echo "Building custom CPU" build compress else # Darwin Rosetta x86 emulation does NOT support AVX, AVX2, AVX512 # -DGGML_AVX -- 2011 Intel Sandy Bridge & AMD Bulldozer # -DGGML_F16C -- 2012 Intel Ivy Bridge & AMD 2011 Bulldozer (No significant improvement over just AVX) # -DGGML_AVX2 -- 2013 Intel Haswell & 2015 AMD Excavator / 2017 AMD Zen # -DGGML_FMA (FMA3) -- 2013 Intel Haswell & 2012 AMD Piledriver # Note: the following seem to yield slower results than AVX2 - ymmv # -DGGML_AVX512 -- 2017 Intel Skylake and High End DeskTop (HEDT) # -DGGML_AVX512_VBMI -- 2018 Intel Cannon Lake # -DGGML_AVX512_VNNI -- 2021 Intel Alder Lake COMMON_CPU_DEFS="-DBUILD_SHARED_LIBS=off -DCMAKE_POSITION_INDEPENDENT_CODE=on -DGGML_NATIVE=off -DGGML_OPENMP=off" if [ -z "${OLLAMA_CPU_TARGET}" -o "${OLLAMA_CPU_TARGET}" = "cpu" ]; then # # CPU first for the default library, set up as lowest common denominator for maximum compatibility (including Rosetta) # init_vars CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}" BUILD_DIR="../build/linux/${ARCH}/cpu" echo "Building LCD CPU" build compress fi if [ "${ARCH}" == "x86_64" ]; then # # ARM chips in M1/M2/M3-based MACs and NVidia Tegra devices do not currently support avx extensions. # if [ -z "${OLLAMA_CPU_TARGET}" -o "${OLLAMA_CPU_TARGET}" = "cpu_avx" ]; then # # ~2011 CPU Dynamic library with more capabilities turned on to optimize performance # Approximately 400% faster than LCD on same CPU # init_vars CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}" BUILD_DIR="../build/linux/${ARCH}/cpu_avx" echo "Building AVX CPU" build compress fi if [ -z "${OLLAMA_CPU_TARGET}" -o "${OLLAMA_CPU_TARGET}" = "cpu_avx2" ]; then # # ~2013 CPU Dynamic library # Approximately 10% faster than AVX on same CPU # init_vars CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_AVX=on -DGGML_AVX2=on -DGGML_AVX512=off -DGGML_FMA=on -DGGML_F16C=on ${CMAKE_DEFS}" BUILD_DIR="../build/linux/${ARCH}/cpu_avx2" echo "Building AVX2 CPU" build compress fi fi fi else echo "Skipping CPU generation step as requested" fi # If needed, look for the default CUDA toolkit location if [ -z "${CUDA_LIB_DIR}" ] && [ -d /usr/local/cuda/lib64 ]; then CUDA_LIB_DIR=/usr/local/cuda/lib64 fi # If needed, look for CUDA on Arch Linux if [ -z "${CUDA_LIB_DIR}" ] && [ -d /opt/cuda/targets/x86_64-linux/lib ]; then CUDA_LIB_DIR=/opt/cuda/targets/x86_64-linux/lib fi # Allow override in case libcudart is in the wrong place if [ -z "${CUDART_LIB_DIR}" ]; then CUDART_LIB_DIR="${CUDA_LIB_DIR}" fi if [ -z "${OLLAMA_SKIP_CUDA_GENERATE}" -a -d "${CUDA_LIB_DIR}" ]; then echo "CUDA libraries detected - building dynamic CUDA library" init_vars CUDA_MAJOR=$(ls "${CUDA_LIB_DIR}"/libcudart.so.* | head -1 | cut -f3 -d. || true) if [ -n "${CUDA_MAJOR}" ]; then CUDA_VARIANT=_v${CUDA_MAJOR} fi if [ "${ARCH}" == "arm64" ]; then echo "ARM CPU detected - disabling unsupported AVX instructions" # ARM-based CPUs such as M1 and Tegra do not support AVX extensions. # # CUDA compute < 6.0 lacks proper FP16 support on ARM. # Disabling has minimal performance effect while maintaining compatibility. ARM64_DEFS="-DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_CUDA_F16=off" fi # Users building from source can tune the exact flags we pass to cmake for configuring llama.cpp if [ -n "${OLLAMA_CUSTOM_CUDA_DEFS}" ]; then echo "OLLAMA_CUSTOM_CUDA_DEFS=\"${OLLAMA_CUSTOM_CUDA_DEFS}\"" CMAKE_CUDA_DEFS="-DGGML_CUDA=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES} ${OLLAMA_CUSTOM_CUDA_DEFS}" echo "Building custom CUDA GPU" else CMAKE_CUDA_DEFS="-DGGML_CUDA=on -DCMAKE_CUDA_FLAGS=-t8 -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES} -DCMAKE_LIBRARY_PATH=/usr/local/cuda/compat" fi CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} ${ARM64_DEFS} ${CMAKE_CUDA_DEFS}" BUILD_DIR="../build/linux/${ARCH}/cuda${CUDA_VARIANT}" EXTRA_LIBS="-L${CUDA_LIB_DIR} -lcudart -lcublas -lcublasLt -lcuda" build # Carry the CUDA libs as payloads to help reduce dependency burden on users # # TODO - in the future we may shift to packaging these separately and conditionally # downloading them in the install script. DEPS="$(ldd ${BUILD_DIR}/bin/ollama_llama_server )" for lib in libcudart.so libcublas.so libcublasLt.so ; do DEP=$(echo "${DEPS}" | grep ${lib} | cut -f1 -d' ' | xargs || true) if [ -n "${DEP}" -a -e "${CUDA_LIB_DIR}/${DEP}" ]; then cp "${CUDA_LIB_DIR}/${DEP}" "${BUILD_DIR}/bin/" elif [ -e "${CUDA_LIB_DIR}/${lib}.${CUDA_MAJOR}" ]; then cp "${CUDA_LIB_DIR}/${lib}.${CUDA_MAJOR}" "${BUILD_DIR}/bin/" elif [ -e "${CUDART_LIB_DIR}/${lib}" ]; then cp -d ${CUDART_LIB_DIR}/${lib}* "${BUILD_DIR}/bin/" else cp -d "${CUDA_LIB_DIR}/${lib}*" "${BUILD_DIR}/bin/" fi done compress fi if [ -z "${ONEAPI_ROOT}" ]; then # Try the default location in case it exists ONEAPI_ROOT=/opt/intel/oneapi fi if [ -z "${OLLAMA_SKIP_ONEAPI_GENERATE}" -a -d "${ONEAPI_ROOT}" ]; then echo "OneAPI libraries detected - building dynamic OneAPI library" init_vars source ${ONEAPI_ROOT}/setvars.sh --force # set up environment variables for oneAPI CC=icx CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL=ON -DGGML_SYCL_F16=OFF" BUILD_DIR="../build/linux/${ARCH}/oneapi" EXTRA_LIBS="-fsycl -Wl,-rpath,${ONEAPI_ROOT}/compiler/latest/lib,-rpath,${ONEAPI_ROOT}/mkl/latest/lib,-rpath,${ONEAPI_ROOT}/tbb/latest/lib,-rpath,${ONEAPI_ROOT}/compiler/latest/opt/oclfpga/linux64/lib -lOpenCL -lmkl_core -lmkl_sycl_blas -lmkl_intel_ilp64 -lmkl_tbb_thread -ltbb" DEBUG_FLAGS="" # icx compiles with -O0 if we pass -g, so we must remove it build # copy oneAPI dependencies for dep in $(ldd "${BUILD_DIR}/bin/ollama_llama_server" | grep "=>" | cut -f2 -d= | cut -f2 -d' ' | grep -e sycl -e mkl -e tbb); do cp "${dep}" "${BUILD_DIR}/bin/" done cp "${ONEAPI_ROOT}/compiler/latest/lib/libOpenCL.so" "${BUILD_DIR}/bin/" cp "${ONEAPI_ROOT}/compiler/latest/lib/libimf.so" "${BUILD_DIR}/bin/" cp "${ONEAPI_ROOT}/compiler/latest/lib/libintlc.so.5" "${BUILD_DIR}/bin/" cp "${ONEAPI_ROOT}/compiler/latest/lib/libirng.so" "${BUILD_DIR}/bin/" cp "${ONEAPI_ROOT}/compiler/latest/lib/libpi_level_zero.so" "${BUILD_DIR}/bin/" cp "${ONEAPI_ROOT}/compiler/latest/lib/libsvml.so" "${BUILD_DIR}/bin/" cp "${ONEAPI_ROOT}/compiler/latest/lib/libur_loader.so.0" "${BUILD_DIR}/bin/" compress fi if [ -z "${ROCM_PATH}" ]; then # Try the default location in case it exists ROCM_PATH=/opt/rocm fi if [ -z "${CLBlast_DIR}" ]; then # Try the default location in case it exists if [ -d /usr/lib/cmake/CLBlast ]; then export CLBlast_DIR=/usr/lib/cmake/CLBlast fi fi if [ -z "${OLLAMA_SKIP_ROCM_GENERATE}" -a -d "${ROCM_PATH}" ]; then echo "ROCm libraries detected - building dynamic ROCm library" if [ -f ${ROCM_PATH}/lib/librocblas.so.*.*.????? ]; then ROCM_VARIANT=_v$(ls ${ROCM_PATH}/lib/librocblas.so.*.*.????? | cut -f5 -d. || true) fi init_vars CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} -DGGML_HIPBLAS=on -DLLAMA_CUDA_NO_PEER_COPY=on -DCMAKE_C_COMPILER=$ROCM_PATH/llvm/bin/clang -DCMAKE_CXX_COMPILER=$ROCM_PATH/llvm/bin/clang++ -DAMDGPU_TARGETS=$(amdGPUs) -DGPU_TARGETS=$(amdGPUs)" # Users building from source can tune the exact flags we pass to cmake for configuring llama.cpp if [ -n "${OLLAMA_CUSTOM_ROCM_DEFS}" ]; then echo "OLLAMA_CUSTOM_ROCM_DEFS=\"${OLLAMA_CUSTOM_ROCM_DEFS}\"" CMAKE_DEFS="${CMAKE_DEFS} ${OLLAMA_CUSTOM_ROCM_DEFS}" echo "Building custom ROCM GPU" fi BUILD_DIR="../build/linux/${ARCH}/rocm${ROCM_VARIANT}" EXTRA_LIBS="-L${ROCM_PATH}/lib -L/opt/amdgpu/lib/x86_64-linux-gnu/ -Wl,-rpath,\$ORIGIN/../../rocm/ -lhipblas -lrocblas -lamdhip64 -lrocsolver -lamd_comgr -lhsa-runtime64 -lrocsparse -ldrm -ldrm_amdgpu" build # Record the ROCM dependencies rm -f "${BUILD_DIR}/bin/deps.txt" touch "${BUILD_DIR}/bin/deps.txt" for dep in $(ldd "${BUILD_DIR}/bin/ollama_llama_server" | grep "=>" | cut -f2 -d= | cut -f2 -d' ' | grep -e rocm -e amdgpu -e libtinfo ); do echo "${dep}" >> "${BUILD_DIR}/bin/deps.txt" done # bomb out if for some reason we didn't get a few deps if [ $(cat "${BUILD_DIR}/bin/deps.txt" | wc -l ) -lt 8 ] ; then cat "${BUILD_DIR}/bin/deps.txt" echo "ERROR: deps file short" exit 1 fi compress fi cleanup echo "go generate completed. LLM runners: $(cd ${BUILD_DIR}/..; echo *)"