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https://github.com/ggerganov/llama.cpp.git
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master-b8e
| Author | SHA1 | Date | |
|---|---|---|---|
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b8ee340abe | ||
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9ecb30f959 | ||
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29cf5596fe |
2
.github/workflows/build.yml
vendored
2
.github/workflows/build.yml
vendored
@@ -165,7 +165,7 @@ jobs:
|
||||
- build: 'clblast'
|
||||
defines: '-DLLAMA_CLBLAST=ON -DCMAKE_PREFIX_PATH="$env:RUNNER_TEMP/clblast"'
|
||||
- build: 'openblas'
|
||||
defines: '-DLLAMA_OPENBLAS=ON -DBLAS_LIBRARIES="/LIBPATH:$env:RUNNER_TEMP/openblas/lib" -DOPENBLAS_INC="$env:RUNNER_TEMP/openblas/include"'
|
||||
defines: '-DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS -DBLAS_INCLUDE_DIRS="$env:RUNNER_TEMP/openblas/include"'
|
||||
|
||||
steps:
|
||||
- name: Clone
|
||||
|
||||
67
BLIS.md
Normal file
67
BLIS.md
Normal file
@@ -0,0 +1,67 @@
|
||||
BLIS Installation Manual
|
||||
------------------------
|
||||
|
||||
BLIS is a portable software framework for high-performance BLAS-like dense linear algebra libraries. It has received awards and recognition, including the 2023 James H. Wilkinson Prize for Numerical Software and the 2020 SIAM Activity Group on Supercomputing Best Paper Prize. BLIS provides a new BLAS-like API and a compatibility layer for traditional BLAS routine calls. It offers features such as object-based API, typed API, BLAS and CBLAS compatibility layers.
|
||||
|
||||
Project URL: https://github.com/flame/blis
|
||||
|
||||
### Prepare:
|
||||
|
||||
Compile BLIS:
|
||||
|
||||
```bash
|
||||
git clone https://github.com/flame/blis
|
||||
cd blis
|
||||
./configure --enable-cblas -t openmp,pthreads auto
|
||||
# will install to /usr/local/ by default.
|
||||
make -j
|
||||
```
|
||||
|
||||
Install BLIS:
|
||||
|
||||
```bash
|
||||
sudo make install
|
||||
```
|
||||
|
||||
We recommend using openmp since it's easier to modify the cores been used.
|
||||
|
||||
### llama.cpp compilation
|
||||
|
||||
Makefile:
|
||||
|
||||
```bash
|
||||
make LLAMA_BLIS=1 -j
|
||||
# make LLAMA_BLIS=1 benchmark-matmult
|
||||
```
|
||||
|
||||
CMake:
|
||||
|
||||
```bash
|
||||
mkdir build
|
||||
cd build
|
||||
cmake -DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=FLAME ..
|
||||
make -j
|
||||
```
|
||||
|
||||
### llama.cpp execution
|
||||
|
||||
According to the BLIS documentation, we could set the following
|
||||
environment variables to modify the behavior of openmp:
|
||||
|
||||
```
|
||||
export GOMP_GPU_AFFINITY="0-19"
|
||||
export BLIS_NUM_THREADS=14
|
||||
```
|
||||
|
||||
And then run the binaries as normal.
|
||||
|
||||
|
||||
### Intel specific issue
|
||||
|
||||
Some might get the error message saying that `libimf.so` cannot be found.
|
||||
Please follow this [stackoverflow page](https://stackoverflow.com/questions/70687930/intel-oneapi-2022-libimf-so-no-such-file-or-directory-during-openmpi-compila).
|
||||
|
||||
### Reference:
|
||||
|
||||
1. https://github.com/flame/blis#getting-started
|
||||
2. https://github.com/flame/blis/blob/master/docs/Multithreading.md
|
||||
@@ -65,7 +65,8 @@ endif()
|
||||
|
||||
# 3rd party libs
|
||||
option(LLAMA_ACCELERATE "llama: enable Accelerate framework" ON)
|
||||
option(LLAMA_OPENBLAS "llama: use OpenBLAS" OFF)
|
||||
option(LLAMA_BLAS "llama: use BLAS" OFF)
|
||||
option(LLAMA_BLAS_VENDOR "llama: BLA_VENDOR from https://cmake.org/cmake/help/latest/module/FindBLAS.html#blas-lapack-vendors" Generic)
|
||||
option(LLAMA_CUBLAS "llama: use cuBLAS" OFF)
|
||||
option(LLAMA_CLBLAST "llama: use CLBlast" OFF)
|
||||
|
||||
@@ -145,36 +146,28 @@ if (APPLE AND LLAMA_ACCELERATE)
|
||||
endif()
|
||||
endif()
|
||||
|
||||
if (LLAMA_OPENBLAS)
|
||||
if (LLAMA_BLAS)
|
||||
if (LLAMA_STATIC)
|
||||
set(BLA_STATIC ON)
|
||||
endif()
|
||||
|
||||
set(BLA_VENDOR OpenBLAS)
|
||||
if ($(CMAKE_VERSION) VERSION_GREATER_EQUAL 3.22)
|
||||
set(BLA_SIZEOF_INTEGER 8)
|
||||
endif()
|
||||
set(BLA_VENDOR ${LLAMA_BLAS_VENDOR})
|
||||
find_package(BLAS)
|
||||
if (BLAS_FOUND)
|
||||
message(STATUS "OpenBLAS found")
|
||||
message(STATUS "BLAS found, Libraries: ${BLAS_LIBRARIES}")
|
||||
|
||||
add_compile_options(${BLAS_LINKER_FLAGS})
|
||||
add_compile_definitions(GGML_USE_OPENBLAS)
|
||||
add_link_options(${BLAS_LIBRARIES})
|
||||
set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} openblas)
|
||||
set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} ${BLAS_LIBRARIES})
|
||||
|
||||
# find header file
|
||||
set(OPENBLAS_INCLUDE_SEARCH_PATHS
|
||||
/usr/include
|
||||
/usr/include/openblas
|
||||
/usr/include/openblas-base
|
||||
/usr/local/include
|
||||
/usr/local/include/openblas
|
||||
/usr/local/include/openblas-base
|
||||
/opt/OpenBLAS/include
|
||||
$ENV{OpenBLAS_HOME}
|
||||
$ENV{OpenBLAS_HOME}/include
|
||||
)
|
||||
find_path(OPENBLAS_INC NAMES cblas.h PATHS ${OPENBLAS_INCLUDE_SEARCH_PATHS})
|
||||
add_compile_options(-I${OPENBLAS_INC})
|
||||
message("${BLAS_LIBRARIES} ${BLAS_INCLUDE_DIRS}")
|
||||
include_directories(${BLAS_INCLUDE_DIRS})
|
||||
else()
|
||||
message(WARNING "OpenBLAS not found")
|
||||
message(WARNING "BLAS not found, please refer to "
|
||||
"https://cmake.org/cmake/help/latest/module/FindBLAS.html#blas-lapack-vendors"
|
||||
" to set correct LLAMA_BLAS_VENDOR")
|
||||
endif()
|
||||
endif()
|
||||
|
||||
|
||||
4
Makefile
4
Makefile
@@ -122,6 +122,10 @@ ifdef LLAMA_OPENBLAS
|
||||
LDFLAGS += -lopenblas
|
||||
endif
|
||||
endif
|
||||
ifdef LLAMA_BLIS
|
||||
CFLAGS += -DGGML_USE_OPENBLAS -I/usr/local/include/blis -I/usr/include/blis
|
||||
LDFLAGS += -lblis -L/usr/local/lib
|
||||
endif
|
||||
ifdef LLAMA_CUBLAS
|
||||
CFLAGS += -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I$(CUDA_PATH)/targets/x86_64-linux/include
|
||||
CXXFLAGS += -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I$(CUDA_PATH)/targets/x86_64-linux/include
|
||||
|
||||
19
README.md
19
README.md
@@ -56,7 +56,7 @@ The main goal of `llama.cpp` is to run the LLaMA model using 4-bit integer quant
|
||||
- Mixed F16 / F32 precision
|
||||
- 4-bit, 5-bit and 8-bit integer quantization support
|
||||
- Runs on the CPU
|
||||
- OpenBLAS support
|
||||
- Supports OpenBLAS/Apple BLAS/ARM Performance Lib/ATLAS/BLIS/Intel MKL/NVHPC/ACML/SCSL/SGIMATH and [more](https://cmake.org/cmake/help/latest/module/FindBLAS.html#blas-lapack-vendors) in BLAS
|
||||
- cuBLAS and CLBlast support
|
||||
|
||||
The original implementation of `llama.cpp` was [hacked in an evening](https://github.com/ggerganov/llama.cpp/issues/33#issuecomment-1465108022).
|
||||
@@ -274,10 +274,25 @@ Building the program with BLAS support may lead to some performance improvements
|
||||
```bash
|
||||
mkdir build
|
||||
cd build
|
||||
cmake .. -DLLAMA_OPENBLAS=ON
|
||||
cmake .. -DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS
|
||||
cmake --build . --config Release
|
||||
```
|
||||
|
||||
- BLIS
|
||||
|
||||
Check [BLIS.md](BLIS.md) for more information.
|
||||
|
||||
- Intel MKL
|
||||
|
||||
By default, `LLAMA_BLAS_VENDOR` is set to `Generic`, so if you already sourced intel environment script and assign `-DLLAMA_BLAS=ON` in cmake, the mkl version of Blas will automatically been selected. You may also specify it by:
|
||||
|
||||
```bash
|
||||
mkdir build
|
||||
cd build
|
||||
cmake .. -DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=Intel10_64lp -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
|
||||
cmake --build . -config Release
|
||||
```
|
||||
|
||||
- cuBLAS
|
||||
|
||||
This provides BLAS acceleration using the CUDA cores of your Nvidia GPU. Make sure to have the CUDA toolkit installed. You can download it from your Linux distro's package manager or from here: [CUDA Toolkit](https://developer.nvidia.com/cuda-downloads).
|
||||
|
||||
375
ggml-opencl.c
375
ggml-opencl.c
@@ -10,87 +10,77 @@
|
||||
#include "ggml.h"
|
||||
|
||||
#define MULTILINE_QUOTE(...) #__VA_ARGS__
|
||||
const char * clblast_dequant = MULTILINE_QUOTE(
|
||||
static const char * program_source = MULTILINE_QUOTE(
|
||||
|
||||
typedef char int8_t;
|
||||
typedef uchar uint8_t;
|
||||
typedef int int32_t;
|
||||
typedef uint uint32_t;
|
||||
|
||||
constant uint QK4_0 = 32;
|
||||
struct block_q4_0
|
||||
struct __attribute__ ((packed)) block_q4_0
|
||||
{
|
||||
float d;
|
||||
uint8_t qs[QK4_0 / 2];
|
||||
half d;
|
||||
uint8_t qs[16]; /* QK4_0 / 2 */
|
||||
};
|
||||
|
||||
constant uint QK4_1 = 32;
|
||||
struct block_q4_1
|
||||
struct __attribute__ ((packed)) block_q4_1
|
||||
{
|
||||
float d;
|
||||
float m;
|
||||
uint8_t qs[QK4_1 / 2];
|
||||
half d;
|
||||
half m;
|
||||
uint8_t qs[16]; /* QK4_1 / 2 */
|
||||
};
|
||||
|
||||
constant uint QK5_0 = 32;
|
||||
struct __attribute__ ((packed)) block_q5_0
|
||||
{
|
||||
half d;
|
||||
uint32_t qh;
|
||||
uint8_t qs[QK5_0 / 2];
|
||||
uint8_t qs[16]; /* QK5_0 / 2 */
|
||||
};
|
||||
|
||||
constant uint QK5_1 = 32;
|
||||
struct block_q5_1
|
||||
struct __attribute__ ((packed)) block_q5_1
|
||||
{
|
||||
half d;
|
||||
half m;
|
||||
uint32_t qh;
|
||||
uint8_t qs[QK5_1 / 2];
|
||||
uint8_t qs[16]; /* QK5_1 / 2 */
|
||||
};
|
||||
|
||||
constant uint QK8_0 = 32;
|
||||
struct block_q8_0
|
||||
struct __attribute__ ((packed)) block_q8_0
|
||||
{
|
||||
float d;
|
||||
uint8_t qs[QK8_0];
|
||||
half d;
|
||||
int8_t qs[32]; /* QK8_0 */
|
||||
};
|
||||
|
||||
|
||||
__kernel void dequantize_row_q4_0(__global struct block_q4_0* x, __global float* y) {
|
||||
constant uint qk = QK4_0;
|
||||
|
||||
const uint i = get_global_id(0) / qk;
|
||||
const uint i = get_global_id(0) / 32; /* QK4_0 */
|
||||
const uint j = get_local_id(0);
|
||||
|
||||
const float d = x[i].d;
|
||||
const float d = vload_half(0, (__global half*) &x[i].d);
|
||||
|
||||
const int x0 = (x[i].qs[j] & 0xf) - 8;
|
||||
const int x1 = (x[i].qs[j] >> 4) - 8;
|
||||
|
||||
y[i*qk + j + 0 ] = x0*d;
|
||||
y[i*qk + j + qk/2] = x1*d;
|
||||
y[i*32 + j + 0 ] = x0*d;
|
||||
y[i*32 + j + 16] = x1*d;
|
||||
}
|
||||
|
||||
__kernel void dequantize_row_q4_1(__global struct block_q4_1* x, __global float* y) {
|
||||
constant uint qk = QK4_1;
|
||||
|
||||
const uint i = get_global_id(0) / qk;
|
||||
const uint i = get_global_id(0) / 32; /* QK4_1 */
|
||||
const uint j = get_local_id(0);
|
||||
|
||||
const float d = x[i].d;
|
||||
const float m = x[i].m;
|
||||
const float d = vload_half(0, (__global half*) &x[i].d);
|
||||
const float m = vload_half(0, (__global half*) &x[i].m);
|
||||
|
||||
const int x0 = (x[i].qs[j] & 0xf);
|
||||
const int x1 = (x[i].qs[j] >> 4);
|
||||
|
||||
y[i*qk + j + 0 ] = x0*d + m;
|
||||
y[i*qk + j + qk/2] = x1*d + m;
|
||||
y[i*32 + j + 0 ] = x0*d + m;
|
||||
y[i*32 + j + 16] = x1*d + m;
|
||||
}
|
||||
|
||||
__kernel void dequantize_row_q5_0(__global struct block_q5_0* x, __global float* y) {
|
||||
constant uint qk = QK5_0;
|
||||
|
||||
const uint i = get_global_id(0) / qk;
|
||||
const uint i = get_global_id(0) / 32; /* QK5_0 */
|
||||
const uint j = get_local_id(0);
|
||||
|
||||
const float d = vload_half(0, (__global half*) &x[i].d);
|
||||
@@ -103,14 +93,12 @@ __kernel void dequantize_row_q5_0(__global struct block_q5_0* x, __global float*
|
||||
const int32_t x0 = ((x[i].qs[j] & 0xf) | xh_0) - 16;
|
||||
const int32_t x1 = ((x[i].qs[j] >> 4) | xh_1) - 16;
|
||||
|
||||
y[i*qk + j + 0 ] = x0*d;
|
||||
y[i*qk + j + qk/2] = x1*d;
|
||||
y[i*32 + j + 0 ] = x0*d;
|
||||
y[i*32 + j + 16] = x1*d;
|
||||
}
|
||||
|
||||
__kernel void dequantize_row_q5_1(__global struct block_q5_1* x, __global float* y) {
|
||||
constant uint qk = QK5_1;
|
||||
|
||||
const uint i = get_global_id(0) / qk;
|
||||
const uint i = get_global_id(0) / 32; /* QK5_1 */
|
||||
const uint j = get_local_id(0);
|
||||
|
||||
const float d = vload_half(0, (__global half*) &x[i].d);
|
||||
@@ -124,28 +112,38 @@ __kernel void dequantize_row_q5_1(__global struct block_q5_1* x, __global float*
|
||||
const int x0 = (x[i].qs[j] & 0xf) | xh_0;
|
||||
const int x1 = (x[i].qs[j] >> 4) | xh_1;
|
||||
|
||||
y[i*qk + j + 0 ] = x0*d + m;
|
||||
y[i*qk + j + qk/2] = x1*d + m;
|
||||
y[i*32 + j + 0 ] = x0*d + m;
|
||||
y[i*32 + j + 16] = x1*d + m;
|
||||
}
|
||||
|
||||
__kernel void dequantize_row_q8_0(__global struct block_q8_0* x, __global float* y) {
|
||||
constant uint qk = QK8_0;
|
||||
const uint i = get_global_id(0) / qk;
|
||||
const uint i = get_global_id(0) / 32; /* QK8_0 */
|
||||
const uint j = get_local_id(0);
|
||||
|
||||
const float d = x[i].d;
|
||||
y[i*qk + j] = x[i].qs[j]*d;
|
||||
const float d = vload_half(0, (__global half*) &x[i].d);
|
||||
y[i*32 + j] = x[i].qs[j]*d;
|
||||
}
|
||||
|
||||
);
|
||||
|
||||
#define CL_CHECK(err, name) \
|
||||
do { \
|
||||
cl_int err_ = (err); \
|
||||
if (err_ != CL_SUCCESS) { \
|
||||
fprintf(stderr, "OpenCL %s error %d at %s:%d\n", name, err_, __FILE__, __LINE__); \
|
||||
exit(1); \
|
||||
} \
|
||||
#define CL_CHECK(err) \
|
||||
do { \
|
||||
cl_int err_ = (err); \
|
||||
if (err_ != CL_SUCCESS) { \
|
||||
fprintf(stderr, "ggml_opencl: %s error %d at %s:%d\n", \
|
||||
#err, err_, __FILE__, __LINE__); \
|
||||
exit(1); \
|
||||
} \
|
||||
} while (0)
|
||||
|
||||
#define CLBLAST_CHECK(err) \
|
||||
do { \
|
||||
CLBlastStatusCode err_ = (err); \
|
||||
if (err_ != CLBlastSuccess) { \
|
||||
fprintf(stderr, "ggml_opencl: %s error %d at %s:%d\n", \
|
||||
#err, err_, __FILE__, __LINE__); \
|
||||
exit(1); \
|
||||
} \
|
||||
} while (0)
|
||||
|
||||
static cl_platform_id platform;
|
||||
@@ -188,48 +186,174 @@ static cl_program build_program_from_source(cl_context ctx, cl_device_id dev, co
|
||||
|
||||
void ggml_cl_init(void) {
|
||||
cl_int err = 0;
|
||||
char * GGML_CLBLAST_PLATFORM = getenv("GGML_CLBLAST_PLATFORM");
|
||||
char * GGML_CLBLAST_DEVICE = getenv("GGML_CLBLAST_DEVICE");
|
||||
int plat_num = (GGML_CLBLAST_PLATFORM == NULL ? 0 : atoi(GGML_CLBLAST_PLATFORM));
|
||||
int dev_num = (GGML_CLBLAST_DEVICE == NULL ? 0 : atoi(GGML_CLBLAST_DEVICE));
|
||||
printf("\nInitializing CLBlast (First Run)...");
|
||||
printf("\nAttempting to use: Platform=%d, Device=%d (If invalid, program will crash)\n",plat_num,dev_num);
|
||||
cl_uint num_platforms;
|
||||
clGetPlatformIDs(0, NULL, &num_platforms);
|
||||
cl_platform_id* platforms = (cl_platform_id*)malloc(num_platforms*sizeof(cl_platform_id));
|
||||
clGetPlatformIDs(num_platforms, platforms, NULL);
|
||||
platform = platforms[plat_num];
|
||||
char platform_buffer[1024];
|
||||
clGetPlatformInfo(platform, CL_PLATFORM_NAME, sizeof(platform_buffer), &platform_buffer, NULL);
|
||||
cl_uint num_devices;
|
||||
clGetDeviceIDs(platform, CL_DEVICE_TYPE_ALL, 0, NULL, &num_devices);
|
||||
cl_device_id* devices = (cl_device_id*)malloc(num_devices*sizeof(cl_device_id));
|
||||
clGetDeviceIDs(platform, CL_DEVICE_TYPE_ALL, num_devices, devices, NULL);
|
||||
device = devices[dev_num];
|
||||
char device_buffer[1024];
|
||||
clGetDeviceInfo(device, CL_DEVICE_NAME, sizeof(device_buffer), &device_buffer, NULL);
|
||||
printf("Using Platform: %s Device: %s\n", platform_buffer, device_buffer);
|
||||
context = clCreateContext(NULL, 1, &device, NULL, NULL, &err);
|
||||
CL_CHECK(err, "clCreateContext");
|
||||
queue = clCreateCommandQueue(context, device, CL_QUEUE_OUT_OF_ORDER_EXEC_MODE_ENABLE, &err);
|
||||
CL_CHECK(err, "clCreateCommandQueue");
|
||||
|
||||
free(platforms);
|
||||
free(devices);
|
||||
struct cl_device;
|
||||
struct cl_platform {
|
||||
cl_platform_id id;
|
||||
unsigned number;
|
||||
char name[128];
|
||||
char vendor[128];
|
||||
struct cl_device * devices;
|
||||
unsigned n_devices;
|
||||
struct cl_device * default_device;
|
||||
};
|
||||
|
||||
program = build_program_from_source(context, device, clblast_dequant);
|
||||
struct cl_device {
|
||||
struct cl_platform * platform;
|
||||
cl_device_id id;
|
||||
unsigned number;
|
||||
cl_device_type type;
|
||||
char name[128];
|
||||
};
|
||||
|
||||
enum { NPLAT = 16, NDEV = 16 };
|
||||
|
||||
struct cl_platform platforms[NPLAT];
|
||||
unsigned n_platforms = 0;
|
||||
struct cl_device devices[NDEV];
|
||||
unsigned n_devices = 0;
|
||||
struct cl_device * default_device = NULL;
|
||||
|
||||
platform = NULL;
|
||||
device = NULL;
|
||||
|
||||
cl_platform_id platform_ids[NPLAT];
|
||||
CL_CHECK(clGetPlatformIDs(NPLAT, platform_ids, &n_platforms));
|
||||
|
||||
for (unsigned i = 0; i < n_platforms; i++) {
|
||||
struct cl_platform * p = &platforms[i];
|
||||
p->number = i;
|
||||
p->id = platform_ids[i];
|
||||
CL_CHECK(clGetPlatformInfo(p->id, CL_PLATFORM_NAME, sizeof(p->name), &p->name, NULL));
|
||||
CL_CHECK(clGetPlatformInfo(p->id, CL_PLATFORM_VENDOR, sizeof(p->vendor), &p->vendor, NULL));
|
||||
|
||||
cl_device_id device_ids[NDEV];
|
||||
cl_int clGetDeviceIDsError = clGetDeviceIDs(p->id, CL_DEVICE_TYPE_ALL, NDEV, device_ids, &p->n_devices);
|
||||
if (clGetDeviceIDsError == CL_DEVICE_NOT_FOUND) {
|
||||
p->n_devices = 0;
|
||||
} else {
|
||||
CL_CHECK(clGetDeviceIDsError);
|
||||
}
|
||||
p->devices = p->n_devices > 0 ? &devices[n_devices] : NULL;
|
||||
p->default_device = NULL;
|
||||
|
||||
for (unsigned j = 0; j < p->n_devices; j++) {
|
||||
struct cl_device * d = &devices[n_devices];
|
||||
d->number = n_devices++;
|
||||
d->id = device_ids[j];
|
||||
d->platform = p;
|
||||
CL_CHECK(clGetDeviceInfo(d->id, CL_DEVICE_NAME, sizeof(d->name), &d->name, NULL));
|
||||
CL_CHECK(clGetDeviceInfo(d->id, CL_DEVICE_TYPE, sizeof(d->type), &d->type, NULL));
|
||||
|
||||
if (p->default_device == NULL && d->type == CL_DEVICE_TYPE_GPU) {
|
||||
p->default_device = d;
|
||||
}
|
||||
}
|
||||
|
||||
if (default_device == NULL && p->default_device != NULL) {
|
||||
default_device = p->default_device;
|
||||
}
|
||||
}
|
||||
|
||||
if (n_devices == 0) {
|
||||
fprintf(stderr, "ggml_opencl: could find any OpenCL devices.\n");
|
||||
exit(1);
|
||||
}
|
||||
|
||||
char * user_platform_string = getenv("GGML_OPENCL_PLATFORM");
|
||||
char * user_device_string = getenv("GGML_OPENCL_DEVICE");
|
||||
int user_platform_number = -1;
|
||||
int user_device_number = -1;
|
||||
|
||||
unsigned n;
|
||||
if (user_platform_string != NULL && sscanf(user_platform_string, " %u", &n) == 1 && n < n_platforms) {
|
||||
user_platform_number = (int)n;
|
||||
}
|
||||
if (user_device_string != NULL && sscanf(user_device_string, " %u", &n) == 1 && n < n_devices) {
|
||||
user_device_number = (int)n;
|
||||
}
|
||||
|
||||
struct cl_device * selected_devices = devices;
|
||||
unsigned n_selected_devices = n_devices;
|
||||
|
||||
if (user_platform_number == -1 && user_platform_string != NULL && user_platform_string[0] != 0) {
|
||||
for (unsigned i = 0; i < n_platforms; i++) {
|
||||
struct cl_platform * p = &platforms[i];
|
||||
if (strstr(p->name, user_platform_string) != NULL ||
|
||||
strstr(p->vendor, user_platform_string) != NULL) {
|
||||
user_platform_number = (int)i;
|
||||
break;
|
||||
}
|
||||
}
|
||||
if (user_platform_number == -1) {
|
||||
fprintf(stderr, "ggml_opencl: no platform matching '%s' was found.\n", user_platform_string);
|
||||
exit(1);
|
||||
}
|
||||
}
|
||||
if (user_platform_number != -1) {
|
||||
struct cl_platform * p = &platforms[user_platform_number];
|
||||
selected_devices = p->devices;
|
||||
n_selected_devices = p->n_devices;
|
||||
default_device = p->default_device;
|
||||
if (n_selected_devices == 0) {
|
||||
fprintf(stderr, "ggml_opencl: selected platform '%s' does not have any devices.\n", p->name);
|
||||
exit(1);
|
||||
}
|
||||
}
|
||||
|
||||
if (user_device_number == -1 && user_device_string != NULL && user_device_string[0] != 0) {
|
||||
for (unsigned i = 0; i < n_selected_devices; i++) {
|
||||
struct cl_device * d = &selected_devices[i];
|
||||
if (strstr(d->name, user_device_string) != NULL) {
|
||||
user_device_number = d->number;
|
||||
break;
|
||||
}
|
||||
}
|
||||
if (user_device_number == -1) {
|
||||
fprintf(stderr, "ggml_opencl: no device matching '%s' was found.\n", user_device_string);
|
||||
exit(1);
|
||||
}
|
||||
}
|
||||
if (user_device_number != -1) {
|
||||
selected_devices = &devices[user_device_number];
|
||||
n_selected_devices = 1;
|
||||
default_device = &selected_devices[0];
|
||||
}
|
||||
|
||||
GGML_ASSERT(n_selected_devices > 0);
|
||||
|
||||
if (default_device == NULL) {
|
||||
default_device = &selected_devices[0];
|
||||
}
|
||||
|
||||
fprintf(stderr, "ggml_opencl: selecting platform: '%s'\n", default_device->platform->name);
|
||||
fprintf(stderr, "ggml_opencl: selecting device: '%s'\n", default_device->name);
|
||||
if (default_device->type != CL_DEVICE_TYPE_GPU) {
|
||||
fprintf(stderr, "ggml_opencl: warning, not a GPU: '%s'.\n", default_device->name);
|
||||
}
|
||||
|
||||
platform = default_device->platform->id;
|
||||
device = default_device->id;
|
||||
|
||||
cl_context_properties properties[] = {
|
||||
(intptr_t)CL_CONTEXT_PLATFORM, (intptr_t)platform, 0
|
||||
};
|
||||
|
||||
CL_CHECK((context = clCreateContext(properties, 1, &device, NULL, NULL, &err), err));
|
||||
|
||||
CL_CHECK((queue = clCreateCommandQueue(context, device, CL_QUEUE_OUT_OF_ORDER_EXEC_MODE_ENABLE, &err),
|
||||
(err != CL_INVALID_PROPERTY && err != CL_INVALID_VALUE ? err :
|
||||
(queue = clCreateCommandQueue(context, device, 0, &err), err)
|
||||
)));
|
||||
|
||||
program = build_program_from_source(context, device, program_source);
|
||||
|
||||
// Prepare dequantize kernels
|
||||
kernel_q4_0 = clCreateKernel(program, "dequantize_row_q4_0", &err);
|
||||
CL_CHECK(err, "clCreateKernel");
|
||||
kernel_q4_1 = clCreateKernel(program, "dequantize_row_q4_1", &err);
|
||||
CL_CHECK(err, "clCreateKernel");
|
||||
kernel_q5_0 = clCreateKernel(program, "dequantize_row_q5_0", &err);
|
||||
CL_CHECK(err, "clCreateKernel");
|
||||
kernel_q5_1 = clCreateKernel(program, "dequantize_row_q5_1", &err);
|
||||
CL_CHECK(err, "clCreateKernel");
|
||||
kernel_q8_0 = clCreateKernel(program, "dequantize_row_q8_0", &err);
|
||||
CL_CHECK(err, "clCreateKernel");
|
||||
CL_CHECK((kernel_q4_0 = clCreateKernel(program, "dequantize_row_q4_0", &err), err));
|
||||
CL_CHECK((kernel_q4_1 = clCreateKernel(program, "dequantize_row_q4_1", &err), err));
|
||||
CL_CHECK((kernel_q5_0 = clCreateKernel(program, "dequantize_row_q5_0", &err), err));
|
||||
CL_CHECK((kernel_q5_1 = clCreateKernel(program, "dequantize_row_q5_1", &err), err));
|
||||
CL_CHECK((kernel_q8_0 = clCreateKernel(program, "dequantize_row_q8_0", &err), err));
|
||||
}
|
||||
|
||||
static void ggml_cl_malloc(size_t req_size, size_t* cur_size, cl_mem_flags flags, cl_mem* buf) {
|
||||
@@ -242,9 +366,8 @@ static void ggml_cl_malloc(size_t req_size, size_t* cur_size, cl_mem_flags flags
|
||||
clReleaseMemObject(*buf);
|
||||
}
|
||||
cl_int err;
|
||||
*buf = clCreateBuffer(context, flags, req_size, NULL, &err);
|
||||
CL_CHECK((*buf = clCreateBuffer(context, flags, req_size, NULL, &err), err));
|
||||
*cur_size = req_size;
|
||||
CL_CHECK(err, "clCreateBuffer");
|
||||
}
|
||||
|
||||
void ggml_cl_sgemm_wrapper(
|
||||
@@ -253,7 +376,6 @@ void ggml_cl_sgemm_wrapper(
|
||||
const float alpha, const void *host_a, const int lda,
|
||||
const float *host_b, const int ldb, const float beta,
|
||||
float *host_c, const int ldc, const int btype) {
|
||||
cl_int err = 0;
|
||||
|
||||
cl_kernel kernel;
|
||||
size_t global = n * k, local, size_qb;
|
||||
@@ -267,13 +389,13 @@ void ggml_cl_sgemm_wrapper(
|
||||
dequant = true;
|
||||
kernel = kernel_q4_0;
|
||||
local = 16;
|
||||
size_qb = global * (sizeof(float) + local) / 32;
|
||||
size_qb = global * (sizeof(ggml_fp16_t) + local) / 32;
|
||||
break;
|
||||
case GGML_TYPE_Q4_1:
|
||||
dequant = true;
|
||||
kernel = kernel_q4_1;
|
||||
local = 16;
|
||||
size_qb = global * (sizeof(float) * 2 + local) / 32;
|
||||
size_qb = global * (sizeof(ggml_fp16_t) * 2 + local) / 32;
|
||||
break;
|
||||
case GGML_TYPE_Q5_0:
|
||||
dequant = true;
|
||||
@@ -291,7 +413,7 @@ void ggml_cl_sgemm_wrapper(
|
||||
dequant = true;
|
||||
kernel = kernel_q8_0;
|
||||
local = 32;
|
||||
size_qb = global * (sizeof(float) + local) / 32;
|
||||
size_qb = global * (sizeof(ggml_fp16_t) + local) / 32;
|
||||
break;
|
||||
default:
|
||||
fprintf(stderr, "Error: Unsupported OpenCL btype %d\n", btype);
|
||||
@@ -313,49 +435,40 @@ void ggml_cl_sgemm_wrapper(
|
||||
cl_event ev_a, ev_qb, ev_b;
|
||||
|
||||
if (dequant) {
|
||||
err = clSetKernelArg(kernel, 0, sizeof(cl_mem), &cl_buffer_qb);
|
||||
err |= clSetKernelArg(kernel, 1, sizeof(cl_mem), &cl_buffer_b);
|
||||
CL_CHECK(err, "clSetKernelArg");
|
||||
err = clEnqueueWriteBuffer(queue, cl_buffer_qb, CL_FALSE, 0, size_qb, host_b, 0, NULL, &ev_qb);
|
||||
CL_CHECK(err, "clEnqueueWriteBuffer qb");
|
||||
CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &cl_buffer_qb));
|
||||
CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_mem), &cl_buffer_b));
|
||||
CL_CHECK(clEnqueueWriteBuffer(queue, cl_buffer_qb, CL_FALSE, 0, size_qb, host_b, 0, NULL, &ev_qb));
|
||||
} else {
|
||||
err = clEnqueueWriteBuffer(queue, cl_buffer_b, CL_FALSE, 0, size_b, host_b, 0, NULL, &ev_b);
|
||||
CL_CHECK(err, "clEnqueueWriteBuffer b");
|
||||
CL_CHECK(clEnqueueWriteBuffer(queue, cl_buffer_b, CL_FALSE, 0, size_b, host_b, 0, NULL, &ev_b));
|
||||
}
|
||||
|
||||
err = clEnqueueWriteBuffer(queue, cl_buffer_a, CL_FALSE, 0, size_a, host_a, 0, NULL, &ev_a);
|
||||
CL_CHECK(err, "clEnqueueWriteBuffer a");
|
||||
CL_CHECK(clEnqueueWriteBuffer(queue, cl_buffer_a, CL_FALSE, 0, size_a, host_a, 0, NULL, &ev_a));
|
||||
if (dequant) {
|
||||
err = clEnqueueNDRangeKernel(queue, kernel, 1, NULL, &global, &local, 1, &ev_qb, &ev_b);
|
||||
CL_CHECK(err, "clEnqueueNDRangeKernel");
|
||||
clReleaseEvent(ev_qb);
|
||||
CL_CHECK(clEnqueueNDRangeKernel(queue, kernel, 1, NULL, &global, &local, 1, &ev_qb, &ev_b));
|
||||
CL_CHECK(clReleaseEvent(ev_qb));
|
||||
}
|
||||
clWaitForEvents(1, &ev_a);
|
||||
clWaitForEvents(1, &ev_b);
|
||||
clReleaseEvent(ev_a);
|
||||
clReleaseEvent(ev_b);
|
||||
CL_CHECK(clWaitForEvents(1, &ev_a));
|
||||
CL_CHECK(clWaitForEvents(1, &ev_b));
|
||||
CL_CHECK(clReleaseEvent(ev_a));
|
||||
CL_CHECK(clReleaseEvent(ev_b));
|
||||
|
||||
cl_event ev_sgemm;
|
||||
CLBlastStatusCode status = CLBlastSgemm((CLBlastLayout)order,
|
||||
(CLBlastTranspose)trans_a, (CLBlastTranspose)trans_b,
|
||||
m, n, k,
|
||||
alpha,
|
||||
cl_buffer_a, 0, lda,
|
||||
cl_buffer_b, 0, ldb,
|
||||
beta,
|
||||
cl_buffer_c, 0, ldc,
|
||||
&queue, &ev_sgemm);
|
||||
|
||||
if (status != CLBlastSuccess) {
|
||||
fprintf(stderr, "Error: CLBlast SGEMM %d\n", status);
|
||||
abort();
|
||||
}
|
||||
CLBLAST_CHECK(CLBlastSgemm(
|
||||
(CLBlastLayout)order,
|
||||
(CLBlastTranspose)trans_a, (CLBlastTranspose)trans_b,
|
||||
m, n, k,
|
||||
alpha,
|
||||
cl_buffer_a, 0, lda,
|
||||
cl_buffer_b, 0, ldb,
|
||||
beta,
|
||||
cl_buffer_c, 0, ldc,
|
||||
&queue, &ev_sgemm));
|
||||
|
||||
cl_event ev_c;
|
||||
clEnqueueReadBuffer(queue, cl_buffer_c, CL_TRUE, 0, size_c, host_c, 1, &ev_sgemm, &ev_c);
|
||||
CL_CHECK(clEnqueueReadBuffer(queue, cl_buffer_c, CL_TRUE, 0, size_c, host_c, 1, &ev_sgemm, &ev_c));
|
||||
|
||||
// Wait for completion
|
||||
clWaitForEvents(1, &ev_c);
|
||||
clReleaseEvent(ev_sgemm);
|
||||
clReleaseEvent(ev_c);
|
||||
CL_CHECK(clWaitForEvents(1, &ev_c));
|
||||
CL_CHECK(clReleaseEvent(ev_sgemm));
|
||||
CL_CHECK(clReleaseEvent(ev_c));
|
||||
}
|
||||
|
||||
40
llama.cpp
40
llama.cpp
@@ -427,26 +427,30 @@ struct llama_file_loader {
|
||||
}
|
||||
void read_magic() {
|
||||
uint32_t magic = file.read_u32();
|
||||
uint32_t version = 0;
|
||||
|
||||
if (magic != 'ggml') {
|
||||
version = file.read_u32();
|
||||
}
|
||||
|
||||
if (magic == 'ggml' && version == 0) {
|
||||
if (magic == LLAMA_FILE_MAGIC_GGML) {
|
||||
file_version = LLAMA_FILE_VERSION_GGML;
|
||||
} else if (magic == 'ggmf' && version == 1) {
|
||||
file_version = LLAMA_FILE_VERSION_GGMF_V1;
|
||||
} else if (magic == 'ggjt' && version == 1) {
|
||||
file_version = LLAMA_FILE_VERSION_GGJT_V1;
|
||||
} else if (magic == 'ggjt' && version == 2) {
|
||||
file_version = LLAMA_FILE_VERSION_GGJT_V2;
|
||||
} else if (magic == 'ggjt' && version == 3) {
|
||||
file_version = LLAMA_FILE_VERSION_GGJT_V3;
|
||||
} else {
|
||||
throw format("unknown (magic, version) combination: %08x, %08x; is this really a GGML file?",
|
||||
magic, version);
|
||||
return;
|
||||
}
|
||||
|
||||
uint32_t version = file.read_u32();
|
||||
|
||||
switch (magic) {
|
||||
case LLAMA_FILE_MAGIC_GGMF:
|
||||
switch (version) {
|
||||
case 1: file_version = LLAMA_FILE_VERSION_GGMF_V1; return;
|
||||
}
|
||||
break;
|
||||
case LLAMA_FILE_MAGIC_GGJT:
|
||||
switch (version) {
|
||||
case 1: file_version = LLAMA_FILE_VERSION_GGJT_V1; return;
|
||||
case 2: file_version = LLAMA_FILE_VERSION_GGJT_V2; return;
|
||||
case 3: file_version = LLAMA_FILE_VERSION_GGJT_V3; return;
|
||||
}
|
||||
}
|
||||
|
||||
throw format("unknown (magic, version) combination: %08x, %08x; is this really a GGML file?",
|
||||
magic, version);
|
||||
}
|
||||
void read_hparams() {
|
||||
hparams.n_vocab = file.read_u32();
|
||||
@@ -2290,7 +2294,7 @@ int llama_apply_lora_from_file_internal(struct llama_context * ctx, const char *
|
||||
{
|
||||
uint32_t magic;
|
||||
fin.read((char *) &magic, sizeof(magic));
|
||||
if (magic != 'ggla') {
|
||||
if (magic != LLAMA_FILE_MAGIC_GGLA) {
|
||||
fprintf(stderr, "%s: bad file magic\n", __func__);
|
||||
return 1;
|
||||
}
|
||||
|
||||
12
llama.h
12
llama.h
@@ -19,10 +19,16 @@
|
||||
# define LLAMA_API
|
||||
#endif
|
||||
|
||||
#define LLAMA_FILE_MAGIC_GGJT 0x67676a74u // 'ggjt'
|
||||
#define LLAMA_FILE_MAGIC_GGLA 0x67676c61u // 'ggla'
|
||||
#define LLAMA_FILE_MAGIC_GGMF 0x67676d66u // 'ggmf'
|
||||
#define LLAMA_FILE_MAGIC_GGML 0x67676d6cu // 'ggml'
|
||||
#define LLAMA_FILE_MAGIC_GGSN 0x6767736eu // 'ggsn'
|
||||
|
||||
#define LLAMA_FILE_VERSION 3
|
||||
#define LLAMA_FILE_MAGIC 'ggjt'
|
||||
#define LLAMA_FILE_MAGIC_UNVERSIONED 'ggml'
|
||||
#define LLAMA_SESSION_MAGIC 'ggsn'
|
||||
#define LLAMA_FILE_MAGIC LLAMA_FILE_MAGIC_GGJT
|
||||
#define LLAMA_FILE_MAGIC_UNVERSIONED LLAMA_FILE_MAGIC_GGML
|
||||
#define LLAMA_SESSION_MAGIC LLAMA_FILE_MAGIC_GGSN
|
||||
#define LLAMA_SESSION_VERSION 1
|
||||
|
||||
#ifdef __cplusplus
|
||||
|
||||
Reference in New Issue
Block a user