ollama/llm/generate/gen_linux.sh
2024-01-12 21:59:19 +01:00

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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 our default built-in library which will be linked into the CGO
# binary as a normal dependency. This default build is CPU based.
#
# Then we build a CUDA dynamic library (although statically linked with the CUDA
# library dependencies for maximum portability)
#
# Then if we detect ROCm, we build a dynamically loaded ROCm lib. ROCm is particularly
# important to be a dynamic lib even if it's the only GPU library detected because
# we can't redistribute the objectfiles but must rely on dynamic libraries at
# runtime, which could lead the server not to start if not present.
set -ex
set -o pipefail
# See https://llvm.org/docs/AMDGPUUsage.html#processors for reference
amdGPUs() {
GPU_LIST=(
"gfx803"
"gfx900"
"gfx906:xnack-"
"gfx908:xnack-"
"gfx90a:xnack+"
"gfx90a:xnack-"
"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_POSITION_INDEPENDENT_CODE=on -DLLAMA_NATIVE=off -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off"
source $(dirname $0)/gen_common.sh
init_vars
git_module_setup
apply_patches
if [ -z "${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 "${OLLAMA_CUSTOM_CPU_DEFS}" ]; then
echo "OLLAMA_CUSTOM_CPU_DEFS=\"${OLLAMA_CUSTOM_CPU_DEFS}\""
CMAKE_DEFS="${OLLAMA_CUSTOM_CPU_DEFS} -DCMAKE_POSITION_INDEPENDENT_CODE=on ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/cpu"
echo "Building custom CPU"
build
install
link_server_lib
else
# Darwin Rosetta x86 emulation does NOT support AVX, AVX2, AVX512
# -DLLAMA_AVX -- 2011 Intel Sandy Bridge & AMD Bulldozer
# -DLLAMA_F16C -- 2012 Intel Ivy Bridge & AMD 2011 Bulldozer (No significant improvement over just AVX)
# -DLLAMA_AVX2 -- 2013 Intel Haswell & 2015 AMD Excavator / 2017 AMD Zen
# -DLLAMA_FMA (FMA3) -- 2013 Intel Haswell & 2012 AMD Piledriver
# Note: the following seem to yield slower results than AVX2 - ymmv
# -DLLAMA_AVX512 -- 2017 Intel Skylake and High End DeskTop (HEDT)
# -DLLAMA_AVX512_VBMI -- 2018 Intel Cannon Lake
# -DLLAMA_AVX512_VNNI -- 2021 Intel Alder Lake
COMMON_CPU_DEFS="-DCMAKE_POSITION_INDEPENDENT_CODE=on -DLLAMA_NATIVE=off"
#
# CPU first for the default library, set up as lowest common denominator for maximum compatibility (including Rosetta)
#
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/cpu"
echo "Building LCD CPU"
build
install
link_server_lib
#
# ~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} -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/cpu_avx"
echo "Building AVX CPU"
build
install
link_server_lib
#
# ~2013 CPU Dynamic library
# Approximately 10% faster than AVX on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_F16C=on ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/cpu_avx2"
echo "Building AVX2 CPU"
build
install
link_server_lib
fi
else
echo "Skipping CPU generation step as requested"
fi
if [ -z "${CUDA_LIB_DIR}" ]; then
# Try the default location in case it exists
CUDA_LIB_DIR=/usr/local/cuda/lib64
fi
if [ -d "${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
CMAKE_DEFS="-DLLAMA_CUBLAS=on ${COMMON_CMAKE_DEFS} ${CMAKE_DEFS}"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/cuda${CUDA_VARIANT}"
build
install
gcc -fPIC -g -shared -o ${BUILD_DIR}/lib/libext_server.so \
-Wl,--whole-archive \
${BUILD_DIR}/lib/libext_server.a \
${BUILD_DIR}/lib/libcommon.a \
${BUILD_DIR}/lib/libllama.a \
-Wl,--no-whole-archive \
${CUDA_LIB_DIR}/libcudart_static.a \
${CUDA_LIB_DIR}/libcublas_static.a \
${CUDA_LIB_DIR}/libcublasLt_static.a \
${CUDA_LIB_DIR}/libcudadevrt.a \
${CUDA_LIB_DIR}/libculibos.a \
-lrt -lpthread -ldl -lstdc++ -lm
fi
if [ -z "${ROCM_PATH}" ]; then
# Try the default location in case it exists
ROCM_PATH=/opt/rocm
fi
if [ -z "${CLBlast_DIR}" ]; then
# Try the default location in case it exists
if [ -d /usr/lib/cmake/CLBlast ]; then
export CLBlast_DIR=/usr/lib/cmake/CLBlast
fi
fi
if [ -d "${ROCM_PATH}" ]; then
echo "ROCm libraries detected - building dynamic ROCm library"
if [ -f ${ROCM_PATH}/lib/librocm_smi64.so.? ]; then
ROCM_VARIANT=_v$(ls ${ROCM_PATH}/lib/librocm_smi64.so.? | cut -f3 -d. || true)
fi
init_vars
CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} -DLLAMA_HIPBLAS=on -DCMAKE_C_COMPILER=$ROCM_PATH/llvm/bin/clang -DCMAKE_CXX_COMPILER=$ROCM_PATH/llvm/bin/clang++ -DAMDGPU_TARGETS=$(amdGPUs) -DGPU_TARGETS=$(amdGPUs)"
BUILD_DIR="${LLAMACPP_DIR}/build/linux/rocm${ROCM_VARIANT}"
build
install
gcc -fPIC -g -shared -o ${BUILD_DIR}/lib/libext_server.so \
-Wl,--whole-archive \
${BUILD_DIR}/lib/libext_server.a \
${BUILD_DIR}/lib/libcommon.a \
${BUILD_DIR}/lib/libllama.a \
-Wl,--no-whole-archive \
-lrt -lpthread -ldl -lstdc++ -lm \
-L/opt/rocm/lib -L/opt/amdgpu/lib/x86_64-linux-gnu/ \
-Wl,-rpath,/opt/rocm/lib,-rpath,/opt/amdgpu/lib/x86_64-linux-gnu/ \
-lhipblas -lrocblas -lamdhip64 -lrocsolver -lamd_comgr -lhsa-runtime64 -lrocsparse -ldrm -ldrm_amdgpu
fi
cleanup