#!/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 compress_pids="" # 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="-DCMAKE_SKIP_RPATH=on -DBUILD_SHARED_LIBS=on -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_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=on -DCMAKE_POSITION_INDEPENDENT_CODE=on ${CMAKE_DEFS}" RUNNER="cpu" BUILD_DIR="../build/linux/${GOARCH}/${RUNNER}" echo "Building custom CPU" build install dist compress else # Darwin Rosetta x86 emulation does NOT support AVX, AVX2, AVX512 # -DGGML_AVX -- 2011 Intel Sandy Bridge & AMD Bulldozer # -DGGML_F16C -- 2012 Intel Ivy Bridge & AMD 2011 Bulldozer (No significant improvement over just AVX) # -DGGML_AVX2 -- 2013 Intel Haswell & 2015 AMD Excavator / 2017 AMD Zen # -DGGML_FMA (FMA3) -- 2013 Intel Haswell & 2012 AMD Piledriver # Note: the following seem to yield slower results than AVX2 - ymmv # -DGGML_AVX512 -- 2017 Intel Skylake and High End DeskTop (HEDT) # -DGGML_AVX512_VBMI -- 2018 Intel Cannon Lake # -DGGML_AVX512_VNNI -- 2021 Intel Alder Lake COMMON_CPU_DEFS="-DBUILD_SHARED_LIBS=on -DCMAKE_POSITION_INDEPENDENT_CODE=on -DGGML_NATIVE=off -DGGML_OPENMP=off" if [ -z "${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 ${CMAKE_DEFS}" RUNNER=cpu BUILD_DIR="../build/linux/${GOARCH}/${RUNNER}" echo "Building LCD CPU" build install dist compress fi if [ "${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 ${CMAKE_DEFS}" RUNNER=cpu_avx BUILD_DIR="../build/linux/${GOARCH}/${RUNNER}" echo "Building AVX CPU" build install dist compress fi if [ -z "${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 ${CMAKE_DEFS}" RUNNER=cpu_avx2 BUILD_DIR="../build/linux/${GOARCH}/${RUNNER}" echo "Building AVX2 CPU" build install dist compress fi fi fi else echo "Skipping CPU generation step as requested" fi # If needed, look for the default CUDA toolkit location if [ -z "${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}" -a -z "${CUDA_VARIANT}" ]; then CUDA_VARIANT=_v${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} ${OLLAMA_CUSTOM_CUDA_DEFS}" echo "Building custom CUDA GPU" else CMAKE_CUDA_DEFS="-DGGML_CUDA=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES}" fi export CUDAFLAGS="-t8" CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} ${ARM64_DEFS} ${CMAKE_CUDA_DEFS} -DGGML_STATIC=off" RUNNER=cuda${CUDA_VARIANT} BUILD_DIR="../build/linux/${GOARCH}/${RUNNER}" export LLAMA_SERVER_LDFLAGS="-L${CUDA_LIB_DIR} -lcudart -lcublas -lcublasLt -lcuda" CUDA_DIST_DIR="${CUDA_DIST_DIR:-${DIST_BASE}/lib/ollama}" build install dist echo "Installing CUDA dependencies in ${CUDA_DIST_DIR}" mkdir -p "${CUDA_DIST_DIR}" for lib in ${CUDA_LIB_DIR}/libcudart.so* ${CUDA_LIB_DIR}/libcublas.so* ${CUDA_LIB_DIR}/libcublasLt.so* ; do cp -a "${lib}" "${CUDA_DIST_DIR}" done compress fi if [ -z "${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} ${CMAKE_DEFS} -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL=ON -DGGML_SYCL_F16=OFF" RUNNER=oneapi BUILD_DIR="../build/linux/${GOARCH}/${RUNNER}" ONEAPI_DIST_DIR="${DIST_BASE}/lib/ollama" export LLAMA_SERVER_LDFLAGS="-fsycl -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 mkdir -p "${ONEAPI_DIST_DIR}" 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 -a "${dep}" "${ONEAPI_DIST_DIR}" done cp "${ONEAPI_ROOT}/compiler/latest/lib/libOpenCL.so" "${ONEAPI_DIST_DIR}" cp "${ONEAPI_ROOT}/compiler/latest/lib/libimf.so" "${ONEAPI_DIST_DIR}" cp "${ONEAPI_ROOT}/compiler/latest/lib/libintlc.so.5" "${ONEAPI_DIST_DIR}" cp "${ONEAPI_ROOT}/compiler/latest/lib/libirng.so" "${ONEAPI_DIST_DIR}" cp "${ONEAPI_ROOT}/compiler/latest/lib/libpi_level_zero.so" "${ONEAPI_DIST_DIR}" cp "${ONEAPI_ROOT}/compiler/latest/lib/libsvml.so" "${ONEAPI_DIST_DIR}" cp "${ONEAPI_ROOT}/compiler/latest/lib/libur_loader.so.0" "${ONEAPI_DIST_DIR}" install dist 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} ${CMAKE_DEFS} -DGGML_HIPBLAS=on -DGGML_CUDA_NO_PEER_COPY=on -DCMAKE_C_COMPILER=$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} ${OLLAMA_CUSTOM_ROCM_DEFS}" echo "Building custom ROCM GPU" fi RUNNER=rocm${ROCM_VARIANT} BUILD_DIR="../build/linux/${GOARCH}/${RUNNER}" # ROCm dependencies are too large to fit into a unified bundle ROCM_DIST_DIR="${DIST_BASE}/../linux-${GOARCH}-rocm/lib/ollama" # TODO figure out how to disable runpath (rpath) # export CMAKE_HIP_FLAGS="-fno-rtlib-add-rpath" # doesn't work export LLAMA_SERVER_LDFLAGS="-L${ROCM_PATH}/lib -L/opt/amdgpu/lib/x86_64-linux-gnu/ -lhipblas -lrocblas -lamdhip64 -lrocsolver -lamd_comgr -lhsa-runtime64 -lrocsparse -ldrm -ldrm_amdgpu" build # copy the ROCM dependencies mkdir -p "${ROCM_DIST_DIR}" for dep in $(ldd "${BUILD_DIR}/bin/ollama_llama_server" | grep "=>" | cut -f2 -d= | cut -f2 -d' ' | grep -v "${GOARCH}/rocm${ROCM_VARIANT}" | grep -e rocm -e amdgpu -e libtinfo -e libnuma -e libelf ); do cp -a "${dep}"* "${ROCM_DIST_DIR}" if [ $(readlink -f "${dep}") != "${dep}" ] ; then cp $(readlink -f "${dep}") "${ROCM_DIST_DIR}" fi done install dist compress fi cleanup wait_for_compress echo "go generate completed. LLM runners: $(cd ${PAYLOAD_BASE}; echo *)"