llama : reorganize source code + improve CMake (#8006)

* scripts : update sync [no ci]

* files : relocate [no ci]

* ci : disable kompute build [no ci]

* cmake : fixes [no ci]

* server : fix mingw build

ggml-ci

* cmake : minor [no ci]

* cmake : link math library [no ci]

* cmake : build normal ggml library (not object library) [no ci]

* cmake : fix kompute build

ggml-ci

* make,cmake : fix LLAMA_CUDA + replace GGML_CDEF_PRIVATE

ggml-ci

* move public backend headers to the public include directory (#8122)

* move public backend headers to the public include directory

* nix test

* spm : fix metal header

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* scripts : fix sync paths [no ci]

* scripts : sync ggml-blas.h [no ci]

---------

Co-authored-by: slaren <slarengh@gmail.com>

examples/CMakeLists.txt

@@ -39,13 +39,13 @@ else()
     add_subdirectory(quantize-stats)
     add_subdirectory(quantize)
     add_subdirectory(retrieval)
-    if (LLAMA_RPC)
+    if (GGML_RPC)
         add_subdirectory(rpc)
     endif()
     if (LLAMA_BUILD_SERVER)
     add_subdirectory(server)
     endif()
-    if (LLAMA_SYCL)
+    if (GGML_SYCL)
         add_subdirectory(sycl)
     endif()
     add_subdirectory(save-load-state)

examples/imatrix/README.md

@@ -25,7 +25,7 @@ For faster computation, make sure to use GPU offloading via the `-ngl` argument
 ## Example
 
 ```bash
-LLAMA_CUDA=1 make -j
+GGML_CUDA=1 make -j
 
 # generate importance matrix (imatrix.dat)
 ./llama-imatrix -m ggml-model-f16.gguf -f train-data.txt -ngl 99

examples/llava/MobileVLM-README.md

@@ -194,7 +194,7 @@ llama_print_timings:       total time =   44411.01 ms /   377 tokens
 ## Orin compile and run
 ### compile
 ```sh
-make LLAMA_CUDA=1 CUDA_DOCKER_ARCH=sm_87 LLAMA_CUDA_F16=1 -j 32
+make GGML_CUDA=1 CUDA_DOCKER_ARCH=sm_87 GGML_CUDA_F16=1 -j 32
 ```
 ### run on Orin
 ### case 1

examples/rpc/README.md

@@ -29,13 +29,13 @@ You can also run multiple `rpc-server` instances on the same host, each with a d
 
 ## Usage
 
-On each host, build the corresponding backend with `cmake` and add `-DLLAMA_RPC=ON` to the build options.
+On each host, build the corresponding backend with `cmake` and add `-DGGML_RPC=ON` to the build options.
 For example, to build the CUDA backend with RPC support:
 
 ```bash
 mkdir build-rpc-cuda
 cd build-rpc-cuda
-cmake .. -DLLAMA_CUDA=ON -DLLAMA_RPC=ON
+cmake .. -DGGML_CUDA=ON -DGGML_RPC=ON
 cmake --build . --config Release
 ```
 
@@ -58,12 +58,12 @@ $ CUDA_VISIBLE_DEVICES=0 bin/rpc-server -p 50052
 This way you can run multiple `rpc-server` instances on the same host, each with a different CUDA device.
 
 
-On the main host build `llama.cpp` only with `-DLLAMA_RPC=ON`:
+On the main host build `llama.cpp` only with `-DGGML_RPC=ON`:
 
 ```bash
 mkdir build-rpc
 cd build-rpc
-cmake .. -DLLAMA_RPC=ON
+cmake .. -DGGML_RPC=ON
 cmake --build . --config Release
 ```
 

examples/server/CMakeLists.txt

@@ -1,7 +1,14 @@
 set(TARGET llama-server)
 option(LLAMA_SERVER_VERBOSE "Build verbose logging option for Server" ON)
-option(LLAMA_SERVER_SSL "Build SSL support for the server" OFF)
+option(LLAMA_SERVER_SSL     "Build SSL support for the server"        OFF)
+
 include_directories(${CMAKE_CURRENT_SOURCE_DIR} ${CMAKE_CURRENT_BINARY_DIR})
+
+if (MINGW)
+    # fix: https://github.com/ggerganov/llama.cpp/actions/runs/9651004652/job/26617901362?pr=8006
+    add_compile_definitions(_WIN32_WINNT=${GGML_WIN_VER})
+endif()
+
 set(TARGET_SRCS
     server.cpp
     utils.hpp
@@ -24,6 +31,7 @@ set(PUBLIC_ASSETS
     prompt-formats.js
     json-schema-to-grammar.mjs
 )
+
 foreach(asset ${PUBLIC_ASSETS})
     set(input "${CMAKE_CURRENT_SOURCE_DIR}/public/${asset}")
     set(output "${CMAKE_CURRENT_BINARY_DIR}/${asset}.hpp")
@@ -34,18 +42,23 @@ foreach(asset ${PUBLIC_ASSETS})
         COMMAND "${CMAKE_COMMAND}" "-DINPUT=${input}" "-DOUTPUT=${output}" -P "${PROJECT_SOURCE_DIR}/scripts/xxd.cmake"
     )
 endforeach()
+
 add_executable(${TARGET} ${TARGET_SRCS})
 install(TARGETS ${TARGET} RUNTIME)
 target_compile_definitions(${TARGET} PRIVATE
     SERVER_VERBOSE=$<BOOL:${LLAMA_SERVER_VERBOSE}>
 )
+
 target_link_libraries(${TARGET} PRIVATE common ${CMAKE_THREAD_LIBS_INIT})
+
 if (LLAMA_SERVER_SSL)
     find_package(OpenSSL REQUIRED)
     target_link_libraries(${TARGET} PRIVATE OpenSSL::SSL OpenSSL::Crypto)
     target_compile_definitions(${TARGET} PRIVATE CPPHTTPLIB_OPENSSL_SUPPORT)
 endif()
+
 if (WIN32)
     TARGET_LINK_LIBRARIES(${TARGET} PRIVATE ws2_32)
 endif()
+
 target_compile_features(${TARGET} PRIVATE cxx_std_11)

examples/sycl/build.sh

@@ -8,10 +8,10 @@ cd build
 source /opt/intel/oneapi/setvars.sh
 
 #for FP16
-#cmake .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL_F16=ON # faster for long-prompt inference
+#cmake .. -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL_F16=ON # faster for long-prompt inference
 
 #for FP32
-cmake .. -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
+cmake .. -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
 
 #build example/main
 #cmake --build . --config Release --target main

examples/sycl/win-build-sycl.bat

@@ -13,10 +13,10 @@ if %errorlevel% neq 0 goto ERROR
 
 ::  for FP16
 ::  faster for long-prompt inference
-::  cmake -G "MinGW Makefiles" ..  -DLLAMA_SYCL=ON -DCMAKE_CXX_COMPILER=icx -DBUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release -DLLAMA_SYCL_F16=ON
+::  cmake -G "MinGW Makefiles" ..  -DGGML_SYCL=ON -DCMAKE_CXX_COMPILER=icx -DBUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release -DGGML_SYCL_F16=ON
 
 ::  for FP32
-cmake -G "Ninja" ..  -DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=cl -DCMAKE_CXX_COMPILER=icx -DBUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release
+cmake -G "Ninja" ..  -DGGML_SYCL=ON -DCMAKE_C_COMPILER=cl -DCMAKE_CXX_COMPILER=icx -DBUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release
 if %errorlevel% neq 0 goto ERROR
 ::  build example/main only
 ::  make main