mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-24 18:34:36 +00:00
6769e944c7
* k_quants: WIP super-blocks with 64 weights * k_quants: WIP super-blocks with 64 weights Q6_K scalar and AVX2 works * k_quants: WIP super-blocks with 64 weights Q4_K scalar and AVX2 works * k_quants: WIP super-blocks with 64 weights Q2_K scalar and AVX2 works. Q2_K is way too slow (it is actually slower than the scalar implementation) * k_quants: WIP super-blocks with 64 weights Q3_K scalar and AVX2 works. * k_quants: WIP super-blocks with 64 weights Q5_K scalar and AVX2 works, and with that all k_quants are done on AVX2 and scalar * k_quants: WIP super-blocks with 64 weights Q6_K working on CUDA. Cannot make it run quite as gast as with super-blocks with 256 weigths: 8% slower on 4080, 20% slower on the 1660 (but there we fit 1 less layer on the GPU because pf the larger model size), so some fraction of these 20% is due to that, * k_quants: WIP super-blocks with 64 weights Q4_K working on CUDA. ~10% slower on GTX-1660, 16% slower on 4080. * k_quants: WIP super-blocks with 64 weights Q2_K working on CUDA. ~3% slower on GTX-1660, 10% slower on 4080. * k_quants: WIP super-blocks with 64 weights Q3_K working on CUDA. * k_quants: WIP super-blocks with 64 weights Q5_K working on CUDA, and with this CUDA is done. * k_quants: WIP super-blocks with 64 weights Q6_K working on ARM_NEON * k_quants: WIP super-blocks with 64 weights Q4_K working on ARM_NEON, but quite a bit slower than 256 weights * k_quants: WIP super-blocks with 64 weights Q2_K working on ARM_NEON, but quite a bit slower than 256 weights * k_quants: WIP super-blocks with 64 weights Q3_K working on ARM_NEON, but quite a bit slower than 256 weights. * k_quants: WIP super-blocks with 64 weights Q5_K working on ARM_NEON, but quite a bit slower than 256 weights. With that, we have full support for ARM_NEON, although performance is not quite there. * k_quants: WIP super-blocks with 64 weights Slightly more efficient Q3_K and Q5_K * k_quants: WIP super-blocks with 64 weights Another small improvement for Q3_K and Q5_K on ARM_NEON * k_quants: WIP super-blocks with 64 weights Yet another speedup for Q5_K on ARM_NEON. We are now within 10% of the QK_K = 256 version. * k_quants: WIP super-blocks with 64 weights * We are able to pass preprocessor macros to the Metal compiler * Q6_K works and is actually slightly more efficient than the QK_K = 256 version (25.2 ms vs 25.8 ms) * k_quants: WIP super-blocks with 64 weights Q4_K works on Metal and is actually slightly faster than QK_K = 256 (21.95 ms vs 24.0 ms). * k_quants: WIP super-blocks with 64 weights Q2_K works on Metal and is very slightly faster than QK_K = 256 (23.8 ms vs 24.2 ms). * k_quants: WIP super-blocks with 64 weights Q3_K works on Metal and is slightly faster than QK_K = 256 (26.6 ms vs 28.3 ms). * k_quants: WIP super-blocks with 64 weights Q5_K works on Metal and is slightly faster than QK_K = 256 (23.7 ms vs 26.3 ms). * k_quants: call them _K, not _k, also on Metal * k_quants: correctly define QK_K in llama.cpp * Fixed bug in q4_K quantization added with the 64-block addition * Simplify via lambda * k_quants: swicth Q3_K to 4-bit scales when QK_K = 64 Otherwise there isn't much benefit from this quantization type. There is some very slight loss in accuracy, but we reduce size by ~7%. E.g., for OpenLLaMA-3B, Q3_K_S perplexity is 8.6131 with 8-bit scales and 8.6352 with 4-bit, while file size decreases from 1.53G to 1.44G. * k_quants: switch Q4_K to 4-bit scales when QK_K = 64 Here the loss in accuracy is greater than for Q3_K, but the Q4_K points still move further to the left on the perplexity vs size curve. * k_quants: forgot to add the Metal changes in last commit * k_quants: change Q5_K to be type 0 when QK_K = 64 Still needs AVX2 implementation * k_quants: AVX2 implementation for new 64-weight Q5_K * k_quants: 10% faster ARM_NEON Q5_K dot product * k_quants: fixed issue caused by merging with master --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
333 lines
9.4 KiB
Makefile
333 lines
9.4 KiB
Makefile
# Define the default target now so that it is always the first target
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BUILD_TARGETS = main quantize quantize-stats perplexity embedding vdot train-text-from-scratch simple
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ifdef LLAMA_BUILD_SERVER
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BUILD_TARGETS += server
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LLAMA_SERVER_VERBOSE ?= 1
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server: private CXXFLAGS += -DSERVER_VERBOSE=$(LLAMA_SERVER_VERBOSE)
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endif
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default: $(BUILD_TARGETS)
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ifndef UNAME_S
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UNAME_S := $(shell uname -s)
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endif
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ifndef UNAME_P
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UNAME_P := $(shell uname -p)
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endif
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ifndef UNAME_M
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UNAME_M := $(shell uname -m)
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endif
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CCV := $(shell $(CC) --version | head -n 1)
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CXXV := $(shell $(CXX) --version | head -n 1)
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# Mac OS + Arm can report x86_64
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# ref: https://github.com/ggerganov/whisper.cpp/issues/66#issuecomment-1282546789
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ifeq ($(UNAME_S),Darwin)
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ifneq ($(UNAME_P),arm)
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SYSCTL_M := $(shell sysctl -n hw.optional.arm64 2>/dev/null)
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ifeq ($(SYSCTL_M),1)
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# UNAME_P := arm
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# UNAME_M := arm64
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warn := $(warning Your arch is announced as x86_64, but it seems to actually be ARM64. Not fixing that can lead to bad performance. For more info see: https://github.com/ggerganov/whisper.cpp/issues/66\#issuecomment-1282546789)
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endif
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endif
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endif
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#
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# Compile flags
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#
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# keep standard at C11 and C++11
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# -Ofast tends to produce faster code, but may not be available for some compilers.
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ifdef LLAMA_FAST
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OPT = -Ofast
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else
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OPT = -O3
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endif
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CFLAGS = -I. $(OPT) -std=c11 -fPIC
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CXXFLAGS = -I. -I./examples $(OPT) -std=c++11 -fPIC
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LDFLAGS =
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ifdef LLAMA_DEBUG
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CFLAGS += -O0 -g
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CXXFLAGS += -O0 -g
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LDFLAGS += -g
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else
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CFLAGS += -DNDEBUG
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CXXFLAGS += -DNDEBUG
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endif
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# warnings
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CFLAGS += -Wall -Wextra -Wpedantic -Wcast-qual -Wdouble-promotion -Wshadow -Wstrict-prototypes -Wpointer-arith
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CXXFLAGS += -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar
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# OS specific
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# TODO: support Windows
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ifeq ($(UNAME_S),Linux)
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CFLAGS += -pthread
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CXXFLAGS += -pthread
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endif
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ifeq ($(UNAME_S),Darwin)
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CFLAGS += -pthread
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CXXFLAGS += -pthread
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endif
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ifeq ($(UNAME_S),FreeBSD)
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CFLAGS += -pthread
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CXXFLAGS += -pthread
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endif
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ifeq ($(UNAME_S),NetBSD)
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CFLAGS += -pthread
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CXXFLAGS += -pthread
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endif
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ifeq ($(UNAME_S),OpenBSD)
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CFLAGS += -pthread
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CXXFLAGS += -pthread
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endif
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ifeq ($(UNAME_S),Haiku)
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CFLAGS += -pthread
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CXXFLAGS += -pthread
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endif
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ifdef LLAMA_GPROF
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CFLAGS += -pg
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CXXFLAGS += -pg
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endif
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ifdef LLAMA_PERF
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CFLAGS += -DGGML_PERF
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CXXFLAGS += -DGGML_PERF
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endif
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# Architecture specific
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# TODO: probably these flags need to be tweaked on some architectures
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# feel free to update the Makefile for your architecture and send a pull request or issue
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ifeq ($(UNAME_M),$(filter $(UNAME_M),x86_64 i686))
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# Use all CPU extensions that are available:
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CFLAGS += -march=native -mtune=native
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CXXFLAGS += -march=native -mtune=native
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# Usage AVX-only
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#CFLAGS += -mfma -mf16c -mavx
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#CXXFLAGS += -mfma -mf16c -mavx
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# Usage SSSE3-only (Not is SSE3!)
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#CFLAGS += -mssse3
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#CXXFLAGS += -mssse3
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endif
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ifneq ($(filter ppc64%,$(UNAME_M)),)
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POWER9_M := $(shell grep "POWER9" /proc/cpuinfo)
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ifneq (,$(findstring POWER9,$(POWER9_M)))
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CFLAGS += -mcpu=power9
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CXXFLAGS += -mcpu=power9
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endif
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# Require c++23's std::byteswap for big-endian support.
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ifeq ($(UNAME_M),ppc64)
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CXXFLAGS += -std=c++23 -DGGML_BIG_ENDIAN
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endif
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endif
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ifndef LLAMA_NO_K_QUANTS
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CFLAGS += -DGGML_USE_K_QUANTS
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CXXFLAGS += -DGGML_USE_K_QUANTS
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OBJS += k_quants.o
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ifdef LLAMA_QKK_64
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CFLAGS += -DGGML_QKK_64
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CXXFLAGS += -DGGML_QKK_64
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endif
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endif
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ifndef LLAMA_NO_ACCELERATE
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# Mac M1 - include Accelerate framework.
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# `-framework Accelerate` works on Mac Intel as well, with negliable performance boost (as of the predict time).
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ifeq ($(UNAME_S),Darwin)
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CFLAGS += -DGGML_USE_ACCELERATE
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LDFLAGS += -framework Accelerate
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endif
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endif # LLAMA_NO_ACCELERATE
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ifdef LLAMA_OPENBLAS
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CFLAGS += -DGGML_USE_OPENBLAS -I/usr/local/include/openblas -I/usr/include/openblas
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LDFLAGS += -lopenblas
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endif # LLAMA_OPENBLAS
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ifdef LLAMA_BLIS
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CFLAGS += -DGGML_USE_OPENBLAS -I/usr/local/include/blis -I/usr/include/blis
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LDFLAGS += -lblis -L/usr/local/lib
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endif # LLAMA_BLIS
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ifdef LLAMA_CUBLAS
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CFLAGS += -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I$(CUDA_PATH)/targets/x86_64-linux/include
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CXXFLAGS += -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I$(CUDA_PATH)/targets/x86_64-linux/include
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LDFLAGS += -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L$(CUDA_PATH)/targets/x86_64-linux/lib
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OBJS += ggml-cuda.o
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NVCC = nvcc
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NVCCFLAGS = --forward-unknown-to-host-compiler -arch=native
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ifdef LLAMA_CUDA_DMMV_X
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NVCCFLAGS += -DGGML_CUDA_DMMV_X=$(LLAMA_CUDA_DMMV_X)
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else
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NVCCFLAGS += -DGGML_CUDA_DMMV_X=32
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endif # LLAMA_CUDA_DMMV_X
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ifdef LLAMA_CUDA_DMMV_Y
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NVCCFLAGS += -DGGML_CUDA_DMMV_Y=$(LLAMA_CUDA_DMMV_Y)
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else
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NVCCFLAGS += -DGGML_CUDA_DMMV_Y=1
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endif # LLAMA_CUDA_DMMV_Y
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ifdef LLAMA_CUDA_DMMV_F16
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NVCCFLAGS += -DGGML_CUDA_DMMV_F16
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endif # LLAMA_CUDA_DMMV_F16
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ifdef LLAMA_CUDA_KQUANTS_ITER
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NVCCFLAGS += -DK_QUANTS_PER_ITERATION=$(LLAMA_CUDA_KQUANTS_ITER)
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else
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NVCCFLAGS += -DK_QUANTS_PER_ITERATION=2
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endif
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ggml-cuda.o: ggml-cuda.cu ggml-cuda.h
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$(NVCC) $(NVCCFLAGS) $(CXXFLAGS) -Wno-pedantic -c $< -o $@
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endif # LLAMA_CUBLAS
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ifdef LLAMA_CLBLAST
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CFLAGS += -DGGML_USE_CLBLAST
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CXXFLAGS += -DGGML_USE_CLBLAST
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# Mac provides OpenCL as a framework
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ifeq ($(UNAME_S),Darwin)
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LDFLAGS += -lclblast -framework OpenCL
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else
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LDFLAGS += -lclblast -lOpenCL
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endif
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OBJS += ggml-opencl.o
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ggml-opencl.o: ggml-opencl.cpp ggml-opencl.h
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$(CXX) $(CXXFLAGS) -c $< -o $@
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endif # LLAMA_CLBLAST
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ifdef LLAMA_METAL
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CFLAGS += -DGGML_USE_METAL -DGGML_METAL_NDEBUG
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CXXFLAGS += -DGGML_USE_METAL
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LDFLAGS += -framework Foundation -framework Metal -framework MetalKit -framework MetalPerformanceShaders
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OBJS += ggml-metal.o
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ggml-metal.o: ggml-metal.m ggml-metal.h
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$(CC) $(CFLAGS) -c $< -o $@
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endif # LLAMA_METAL
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ifneq ($(filter aarch64%,$(UNAME_M)),)
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# Apple M1, M2, etc.
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# Raspberry Pi 3, 4, Zero 2 (64-bit)
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CFLAGS += -mcpu=native
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CXXFLAGS += -mcpu=native
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endif
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ifneq ($(filter armv6%,$(UNAME_M)),)
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# Raspberry Pi 1, Zero
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CFLAGS += -mfpu=neon-fp-armv8 -mfp16-format=ieee -mno-unaligned-access
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endif
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ifneq ($(filter armv7%,$(UNAME_M)),)
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# Raspberry Pi 2
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CFLAGS += -mfpu=neon-fp-armv8 -mfp16-format=ieee -mno-unaligned-access -funsafe-math-optimizations
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endif
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ifneq ($(filter armv8%,$(UNAME_M)),)
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# Raspberry Pi 3, 4, Zero 2 (32-bit)
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CFLAGS += -mfp16-format=ieee -mno-unaligned-access
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endif
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ifdef LLAMA_NO_K_QUANTS
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k_quants.o: k_quants.c k_quants.h
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$(CC) $(CFLAGS) -c $< -o $@
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endif # LLAMA_NO_K_QUANTS
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#
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# Print build information
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#
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$(info I llama.cpp build info: )
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$(info I UNAME_S: $(UNAME_S))
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$(info I UNAME_P: $(UNAME_P))
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$(info I UNAME_M: $(UNAME_M))
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$(info I CFLAGS: $(CFLAGS))
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$(info I CXXFLAGS: $(CXXFLAGS))
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$(info I LDFLAGS: $(LDFLAGS))
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$(info I CC: $(CCV))
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$(info I CXX: $(CXXV))
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$(info )
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#
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# Build library
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#
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ggml.o: ggml.c ggml.h ggml-cuda.h
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$(CC) $(CFLAGS) -c $< -o $@
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llama.o: llama.cpp ggml.h ggml-cuda.h ggml-metal.h llama.h llama-util.h
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$(CXX) $(CXXFLAGS) -c $< -o $@
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common.o: examples/common.cpp examples/common.h
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$(CXX) $(CXXFLAGS) -c $< -o $@
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libllama.so: llama.o ggml.o $(OBJS)
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$(CXX) $(CXXFLAGS) -shared -fPIC -o $@ $^ $(LDFLAGS)
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clean:
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rm -vf *.o *.so main quantize quantize-stats perplexity embedding benchmark-matmult save-load-state server vdot train-text-from-scratch build-info.h
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#
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# Examples
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#
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main: examples/main/main.cpp build-info.h ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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@echo
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@echo '==== Run ./main -h for help. ===='
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@echo
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simple: examples/simple/simple.cpp build-info.h ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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quantize: examples/quantize/quantize.cpp build-info.h ggml.o llama.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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quantize-stats: examples/quantize-stats/quantize-stats.cpp build-info.h ggml.o llama.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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perplexity: examples/perplexity/perplexity.cpp build-info.h ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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embedding: examples/embedding/embedding.cpp build-info.h ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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save-load-state: examples/save-load-state/save-load-state.cpp build-info.h ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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server: examples/server/server.cpp examples/server/httplib.h examples/server/json.hpp build-info.h ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) -Iexamples/server $(filter-out %.h,$(filter-out %.hpp,$^)) -o $@ $(LDFLAGS)
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train-text-from-scratch: examples/train-text-from-scratch/train-text-from-scratch.cpp build-info.h ggml.o llama.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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build-info.h: $(wildcard .git/index) scripts/build-info.sh
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@sh scripts/build-info.sh > $@.tmp
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@if ! cmp -s $@.tmp $@; then \
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mv $@.tmp $@; \
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else \
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rm $@.tmp; \
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fi
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#
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# Tests
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#
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benchmark-matmult: examples/benchmark/benchmark-matmult.cpp build-info.h ggml.o $(OBJS)
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$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
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./$@
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vdot: pocs/vdot/vdot.cpp ggml.o $(OBJS)
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$(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS)
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.PHONY: tests clean
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tests:
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bash ./tests/run-tests.sh
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