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e47c58656f
Replace the per-microarch avx/avx2/avx512/fallback multi-binary build on
x86 with a single grpc-server plus the dlopen-able libggml-cpu-*.so set
that ggml's backend registry selects at runtime by probing host CPU
features. One build instead of four, broader microarch coverage (adds
alderlake AVX-VNNI, zen4 AVX512-BF16, sapphirerapids AMX), and the
shell-side /proc/cpuinfo probing in run.sh goes away.
Build/link notes:
- CPU_ALL_VARIANTS requires GGML_BACKEND_DL + BUILD_SHARED_LIBS=ON, so
ggml/llama become shared objects. SHARED_LIBS is now a make variable
(default OFF) so the override survives the recursive sub-make into the
VARIANT build dir instead of being re-clobbered by the base flags.
- The cpu-all target also builds "--target ggml": the per-microarch
backends are runtime-dlopened, not link deps, so they only compile via
ggml's add_dependencies().
- hw_grpc_proto is pinned STATIC. Under BUILD_SHARED_LIBS=ON it would
otherwise become a DSO referencing hidden-visibility symbols in the
static libprotobuf.a, which fails to link ("hidden symbol ... is
referenced by DSO"). Keeping it static links gRPC/protobuf into the
executable while only ggml/llama stay shared, so no PIC or base-image
change is required.
- package.sh bundles the libggml-*.so set into package/lib; ggml finds
them by scanning the bundled ld.so directory (/proc/self/exe), which
run.sh launches from.
Scope: x86 only. arm64/darwin keep the single fallback build. The
ik-llama-cpp / turboquant forks and the other ggml C++ backends are
unchanged; the same recipe applies but is out of scope here.
Validated with a full docker build plus a live inference smoke test:
the model loads, ggml selects the AVX512_BF16 variant on a Zen-class
host, and tokens generate correctly.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
51 lines
1.5 KiB
Bash
Executable File
51 lines
1.5 KiB
Bash
Executable File
#!/bin/bash
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set -ex
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# Get the absolute current dir where the script is located
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CURDIR=$(dirname "$(realpath $0)")
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cd /
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echo "CPU info:"
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grep -e "model\sname" /proc/cpuinfo | head -1
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grep -e "flags" /proc/cpuinfo | head -1
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BINARY=llama-cpp-fallback
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# x86 ships a single llama-cpp-cpu-all built with ggml CPU_ALL_VARIANTS: ggml's backend
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# registry dlopens the best libggml-cpu-*.so for this host, so no shell-side AVX probing.
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# arm64/darwin builds ship only llama-cpp-fallback, so fall back to it when cpu-all absent.
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if [ -e $CURDIR/llama-cpp-cpu-all ]; then
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BINARY=llama-cpp-cpu-all
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fi
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if [ -n "$LLAMACPP_GRPC_SERVERS" ]; then
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if [ -e $CURDIR/llama-cpp-grpc ]; then
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BINARY=llama-cpp-grpc
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fi
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fi
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# Extend ld library path with the dir where this script is located/lib
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if [ "$(uname)" == "Darwin" ]; then
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export DYLD_LIBRARY_PATH=$CURDIR/lib:$DYLD_LIBRARY_PATH
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#export DYLD_FALLBACK_LIBRARY_PATH=$CURDIR/lib:$DYLD_FALLBACK_LIBRARY_PATH
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else
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export LD_LIBRARY_PATH=$CURDIR/lib:$LD_LIBRARY_PATH
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# Tell rocBLAS where to find TensileLibrary data (GPU kernel tuning files)
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if [ -d "$CURDIR/lib/rocblas/library" ]; then
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export ROCBLAS_TENSILE_LIBPATH=$CURDIR/lib/rocblas/library
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fi
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fi
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# If there is a lib/ld.so, use it
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if [ -f $CURDIR/lib/ld.so ]; then
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echo "Using lib/ld.so"
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echo "Using binary: $BINARY"
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exec $CURDIR/lib/ld.so $CURDIR/$BINARY "$@"
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fi
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echo "Using binary: $BINARY"
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exec $CURDIR/$BINARY "$@"
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# We should never reach this point, however just in case we do, run fallback
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exec $CURDIR/llama-cpp-fallback "$@" |