root/llama.cpp
1
0
Fork 0
mirror of https://github.com/ggerganov/llama.cpp.git synced 2024-12-24 18:34:36 +00:00
Code Issues Actions 7 Packages Projects Releases Wiki Activity

Improvements for Windows with Snapdragon X

Browse Source
This commit is contained in:
AndreasKunar 2024-07-17 08:59:21 +02:00
parent 5e116e8dd5
commit bf21397ae5
3 changed files with 16 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

3
cmake/arm64-windows-llvm.cmake
View File

@ -9,7 +9,8 @@ set( CMAKE_CXX_COMPILER clang++ )
set( CMAKE_C_COMPILER_TARGET ${target} )
set( CMAKE_CXX_COMPILER_TARGET ${target} )
set( arch_c_flags "-march=armv8.7-a -fvectorize -ffp-model=fast -fno-finite-math-only" )
# march for Snapdragon X should be 8.7-a, but this currently breaks Q_4_0_4_4 acceleration, 8.5 works
set( arch_c_flags "-march=armv8.5-a -fvectorize -ffp-model=fast -fno-finite-math-only" )
set( warn_c_flags "-Wno-format -Wno-unused-variable -Wno-unused-function -Wno-gnu-zero-variadic-macro-arguments" )
set( CMAKE_C_FLAGS_INIT "${arch_c_flags} ${warn_c_flags}" )

9
docs/build.md
View File

@ -16,7 +16,7 @@ In order to build llama.cpp you have four different options.
make
```
- On Windows:
- On Windows (x86/x64 only, arm64 requires cmake):
1. Download the latest fortran version of [w64devkit](https://github.com/skeeto/w64devkit/releases).
2. Extract `w64devkit` on your pc.
@ -45,6 +45,13 @@ In order to build llama.cpp you have four different options.
- For `Q4_0_4_4` quantization type build, add the `-DGGML_LLAMAFILE=OFF` cmake option. For example, use `cmake -B build -DGGML_LLAMAFILE=OFF`.
- For faster compilation, add the `-j` argument to run multiple jobs in parallel. For example, `cmake --build build --config Release -j 8` will run 8 jobs in parallel.
- For faster repeated compilation, install [ccache](https://ccache.dev/).
- For Windows:
- Install cmake e.g. via `winget install cmake`:
- As alternative to the w64devkit mentioned in "using make" above, install MSVC (e.g. via Visual Studio 2022 Community Edition).
- For Windows on ARM you need MSVC installed and _additonally_:
- Install [clang via LLVM for woa64](https://releases.llvm.org) to enable better ARM optimizations (clang needs the MSVC backend).
- For using clang, the first build step needs to be `cmake --preset arm64-windows-llvm-release` (instead of the `cmake -B ...` which defaults to MSVC).
- Note: Building for ARM can also just be done with MSVC (without installing clang or using the preset), but this e.g. does not support Q_4_0_4_4 acceleration, because the MSVC frontend cannot inline ARM assembly-code.
- For debug builds, there are two cases:
1. Single-config generators (e.g. default = `Unix Makefiles`; note that they just ignore the `--config` flag):

12
ggml/src/ggml-aarch64.c
View File

@ -392,7 +392,7 @@ void ggml_gemv_q4_0_4x4_q8_0(int n, float * restrict s, size_t bs, const void *
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_MATMUL_INT8)
GGML_ASSERT(!(ggml_cpu_has_neon() && ggml_cpu_has_matmul_int8()) &&
"__ARM_NEON and __ARM_FEATURE_MATMUL_INT8 defined, use the Q4_0_4_8 quantization format for optimal performance");
#elif defined(__ARM_NEON) && defined(__aarch64__)
#elif defined(__ARM_NEON) && defined(__aarch64__) && ! defined(_MSC_VER)
const void * b_ptr = vx;
const void * a_ptr = vy;
float * res_ptr = s;
@ -501,7 +501,7 @@ void ggml_gemv_q4_0_4x8_q8_0(int n, float * restrict s, size_t bs, const void *
"__ARM_FEATURE_SVE defined, use the Q4_0_8_8 quantization format for optimal performance");
}
#endif
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_MATMUL_INT8)
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_MATMUL_INT8) && ! defined(_MSC_VER)
const void * b_ptr = vx;
const void * a_ptr = vy;
float * res_ptr = s;
@ -613,7 +613,7 @@ void ggml_gemv_q4_0_8x8_q8_0(int n, float * restrict s, size_t bs, const void *
UNUSED(ncols_interleaved);
UNUSED(blocklen);
#if defined(__ARM_FEATURE_SVE)
#if defined(__ARM_FEATURE_SVE) && ! defined(_MSC_VER)
if (svcntw() == 8) {
const void * b_ptr = vx;
const void * a_ptr = vy;
@ -753,7 +753,7 @@ void ggml_gemm_q4_0_4x4_q8_0(int n, float * restrict s, size_t bs, const void *
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_MATMUL_INT8)
GGML_ASSERT(!(ggml_cpu_has_neon() && ggml_cpu_has_matmul_int8()) &&
"__ARM_NEON and __ARM_FEATURE_MATMUL_INT8 defined, use the Q4_0_4_8 quantization format for optimal performance");
#elif defined(__ARM_NEON) && defined(__aarch64__)
#elif defined(__ARM_NEON) && defined(__aarch64__) && ! defined(_MSC_VER)
const void * b_ptr = vx;
const void * a_ptr = vy;
float * res_ptr = s;
@ -1271,7 +1271,7 @@ void ggml_gemm_q4_0_4x8_q8_0(int n, float * restrict s, size_t bs, const void *
"__ARM_FEATURE_SVE defined, use the Q4_0_8_8 quantization format for optimal performance");
}
#endif
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_MATMUL_INT8)
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_MATMUL_INT8) && ! defined(_MSC_VER)
const void * b_ptr = vx;
const void * a_ptr = vy;
float * res_ptr = s;
@ -1727,7 +1727,7 @@ void ggml_gemm_q4_0_8x8_q8_0(int n, float * restrict s, size_t bs, const void *
UNUSED(ncols_interleaved);
UNUSED(blocklen);
#if defined(__ARM_FEATURE_SVE) && defined(__ARM_FEATURE_MATMUL_INT8)
#if defined(__ARM_FEATURE_SVE) && defined(__ARM_FEATURE_MATMUL_INT8) && ! defined(_MSC_VER)
if (svcntw() == 8) {
const void * b_ptr = vx;
const void * a_ptr = vy;