vbatts/llama.cpp
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Merge branch 'master' into concedo_experimental

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# Conflicts:
#	CMakeLists.txt
#	Makefile
#	ggml-opencl.cpp
#	llama.cpp
This commit is contained in:
Concedo 2023-05-23 18:19:16 +08:00
commit 5bf9784381
2 changed files with 81 additions and 66 deletions
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41
ggml-opencl.cpp
View file

@ -302,7 +302,7 @@ static cl_program build_program_from_source(cl_context ctx, cl_device_id dev, co
program_log = (char*) malloc(log_size + 1);
program_log[log_size] = '\0';
clGetProgramBuildInfo(p, dev, CL_PROGRAM_BUILD_LOG, log_size + 1, program_log, NULL);
printf("%s\n", program_log);
fprintf(stderr, "ggml_opencl: kernel compile error:\n\n%s\n", program_log);
free(program_log);
exit(1);
}
@ -398,10 +398,17 @@ void ggml_cl_init(void) {
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;
}
if (user_platform_number != -1 && user_device_number != -1) {
cl_platform* platform = &platforms[user_platform_number];
if ((unsigned)user_device_number >= platform->n_devices) {
fprintf(stderr, "ggml_opencl: invalid device number %d\n", user_device_number);
exit(1);
}
default_device = &platform->devices[user_device_number];
} else {
struct cl_device * selected_devices = devices;
unsigned n_selected_devices = n_devices;
@ -455,14 +462,6 @@ void ggml_cl_init(void) {
if (default_device == NULL) {
default_device = &selected_devices[0];
}
//todo: fun hot fix
if (user_platform_number != -1 && user_device_number != -1)
{
cl_platform * myplat = &platforms[user_platform_number];
cl_device * mydev = &(myplat->devices[user_device_number]);
default_device = mydev;
default_device->platform = myplat;
}
fprintf(stderr, "ggml_opencl: selecting platform: '%s'\n", default_device->platform->name);
@ -679,14 +678,21 @@ static void ggml_cl_mul_mat_f32(const ggml_tensor * src0, const ggml_tensor * sr
size_t x_size;
size_t y_size;
size_t d_size;
cl_mem d_X = ggml_cl_pool_malloc(sizeof(float) * x_ne, &x_size, CL_MEM_READ_ONLY);
cl_mem d_X;
if (src0->backend == GGML_BACKEND_CL) {
d_X = *(cl_mem*) src0->data;
} else {
d_X = ggml_cl_pool_malloc(sizeof(ggml_fp16_t) * x_ne, &x_size, CL_MEM_READ_ONLY);
}
cl_mem d_Y = ggml_cl_pool_malloc(sizeof(float) * y_ne, &y_size, CL_MEM_READ_ONLY);
cl_mem d_D = ggml_cl_pool_malloc(sizeof(float) * d_ne, &d_size, CL_MEM_WRITE_ONLY);
for (int64_t i03 = 0; i03 < ne03; i03++) {
for (int64_t i02 = 0; i02 < ne02; i02++) {
// copy data to device
if (src0->backend != GGML_BACKEND_CL) {
CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_X, 0, src0, i03, i02, NULL));
}
CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_Y, 0, src1, i03, i02, NULL));
CL_CHECK(clFinish(queue));
@ -714,7 +720,9 @@ static void ggml_cl_mul_mat_f32(const ggml_tensor * src0, const ggml_tensor * sr
}
}
if (src0->backend != GGML_BACKEND_CL) {
ggml_cl_pool_free(d_X, x_size);
}
ggml_cl_pool_free(d_Y, y_size);
ggml_cl_pool_free(d_D, d_size);
}
@ -747,7 +755,12 @@ static void ggml_cl_mul_mat_f16(const ggml_tensor * src0, const ggml_tensor * sr
size_t x_size;
size_t y_size;
size_t d_size;
cl_mem d_X = ggml_cl_pool_malloc(sizeof(ggml_fp16_t) * x_ne, &x_size, CL_MEM_READ_ONLY);
cl_mem d_X;
if (src0->backend == GGML_BACKEND_CL) {
d_X = *(cl_mem*) src0->data;
} else {
d_X = ggml_cl_pool_malloc(sizeof(ggml_fp16_t) * x_ne, &x_size, CL_MEM_READ_ONLY);
}
cl_mem d_Y = ggml_cl_pool_malloc(sizeof(ggml_fp16_t) * y_ne, &y_size, CL_MEM_READ_ONLY);
cl_mem d_D = ggml_cl_pool_malloc(sizeof(ggml_fp16_t) * d_ne, &d_size, CL_MEM_WRITE_ONLY);
@ -757,7 +770,9 @@ static void ggml_cl_mul_mat_f16(const ggml_tensor * src0, const ggml_tensor * sr
for (int64_t i03 = 0; i03 < ne03; i03++) {
for (int64_t i02 = 0; i02 < ne02; i02++) {
// copy src0 to device
if (src0->backend != GGML_BACKEND_CL) {
CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_X, 0, src0, i03, i02, NULL));
}
// convert src1 to fp16
// TODO: use multiple threads
@ -813,7 +828,9 @@ static void ggml_cl_mul_mat_f16(const ggml_tensor * src0, const ggml_tensor * sr
}
}
if (src0->backend != GGML_BACKEND_CL) {
ggml_cl_pool_free(d_X, x_size);
}
ggml_cl_pool_free(d_Y, y_size);
ggml_cl_pool_free(d_D, d_size);
}

2
llama.cpp
View file

@ -1153,8 +1153,6 @@ static void llama_model_load_internal(
fprintf(stderr, "ggml_opencl: total VRAM used: %zu MB\n", vram_total / 1024 / 1024);
}
#else
(void) n_gpu_layers;
#endif
if (progress_callback) {