ollama/llm/generate/gen_linux.sh
Daniel Hiltgen cd5c8f6471
Optimize container images for startup (#6547)
* Optimize container images for startup

This change adjusts how to handle runner payloads to support
container builds where we keep them extracted in the filesystem.
This makes it easier to optimize the cpu/cuda vs cpu/rocm images for
size, and should result in faster startup times for container images.

* Refactor payload logic and add buildx support for faster builds

* Move payloads around

* Review comments

* Converge to buildx based helper scripts

* Use docker buildx action for release
2024-09-12 12:10:30 -07:00

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#!/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_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=on -DCMAKE_POSITION_INDEPENDENT_CODE=on ${CMAKE_DEFS}"
RUNNER="cpu"
BUILD_DIR="../build/linux/${ARCH}/${RUNNER}"
echo "Building custom CPU"
build
install
dist
compress
else
# Darwin Rosetta x86 emulation does NOT support AVX, AVX2, AVX512
# -DGGML_AVX -- 2011 Intel Sandy Bridge & AMD Bulldozer
# -DGGML_F16C -- 2012 Intel Ivy Bridge & AMD 2011 Bulldozer (No significant improvement over just AVX)
# -DGGML_AVX2 -- 2013 Intel Haswell & 2015 AMD Excavator / 2017 AMD Zen
# -DGGML_FMA (FMA3) -- 2013 Intel Haswell & 2012 AMD Piledriver
# Note: the following seem to yield slower results than AVX2 - ymmv
# -DGGML_AVX512 -- 2017 Intel Skylake and High End DeskTop (HEDT)
# -DGGML_AVX512_VBMI -- 2018 Intel Cannon Lake
# -DGGML_AVX512_VNNI -- 2021 Intel Alder Lake
COMMON_CPU_DEFS="-DBUILD_SHARED_LIBS=on -DCMAKE_POSITION_INDEPENDENT_CODE=on -DGGML_NATIVE=off -DGGML_OPENMP=off"
if [ -z "${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 ${CMAKE_DEFS}"
RUNNER=cpu
BUILD_DIR="../build/linux/${ARCH}/${RUNNER}"
echo "Building LCD CPU"
build
install
dist
compress
fi
if [ "${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 ${CMAKE_DEFS}"
RUNNER=cpu_avx
BUILD_DIR="../build/linux/${ARCH}/${RUNNER}"
echo "Building AVX CPU"
build
install
dist
compress
fi
if [ -z "${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 ${CMAKE_DEFS}"
RUNNER=cpu_avx2
BUILD_DIR="../build/linux/${ARCH}/${RUNNER}"
echo "Building AVX2 CPU"
build
install
dist
compress
fi
fi
fi
else
echo "Skipping CPU generation step as requested"
fi
# If needed, look for the default CUDA toolkit location
if [ -z "${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/${ARCH}/${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} ${CMAKE_DEFS} -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL=ON -DGGML_SYCL_F16=OFF"
RUNNER=oneapi
BUILD_DIR="../build/linux/${ARCH}/${RUNNER}"
ONEAPI_DIST_DIR="${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/${ARCH}/${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 "${ARCH}/rocm${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 *)"