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Revert "[SYCL] fix error when set main gpu to non-zero (#5901)" (#5918)

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This reverts commit ceca1aef07.
This commit is contained in:
Neo Zhang Jianyu 2024-03-07 19:14:49 +08:00 committed by GitHub
parent 55a2a900ff
commit 89fb735fcf
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GPG Key ID: B5690EEEBB952194
3 changed files with 73 additions and 116 deletions
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172
ggml-sycl.cpp
View File

@ -3559,31 +3559,12 @@ class sycl_gpu_mgr {
int work_group_size = 0;
std::string gpus_list = "";
/*
Use all GPU with same top max compute units
*/
sycl_gpu_mgr() {
detect_sycl_gpu_list_with_max_cu();
get_allow_gpus();
create_context_with_gpus();
}
/*
Use the assigned GPU as only one
*/
sycl_gpu_mgr(int main_gpu_id) {
sycl::device device = dpct::dev_mgr::instance().get_device(main_gpu_id);
dpct::device_info prop;
dpct::get_device_info(prop, device);
gpus.push_back(main_gpu_id);
devices.push_back(device);
work_group_size = prop.get_max_work_group_size();
max_compute_units = prop.get_max_compute_units();
get_allow_gpus();
create_context_with_gpus();
}
void create_context_with_gpus() {
sycl::context ctx = sycl::context(devices);
assert(gpus.size() > 0);
@ -3599,7 +3580,7 @@ class sycl_gpu_mgr {
gpus_list += std::to_string(gpus[i]);
gpus_list += ",";
}
if (gpus_list.length() > 1) {
if (gpus_list.length() > 2) {
gpus_list.pop_back();
}
}
@ -3648,8 +3629,8 @@ class sycl_gpu_mgr {
if (gpus[i] == id)
return i;
}
printf("miss to get device index by id=%d\n", id);
GGML_ASSERT(false);
assert(false);
return -1;
}
int get_next_index(int id) {
@ -3658,7 +3639,8 @@ class sycl_gpu_mgr {
if (gpus[i] == id)
return i;
}
GGML_ASSERT(false);
assert(false);
return -1;
}
};
@ -3667,7 +3649,6 @@ static int g_device_count = -1;
static int g_all_sycl_device_count = -1;
static int g_main_device = -1;
static int g_main_device_id = -1;
static bool g_ggml_backend_sycl_buffer_type_initialized = false;
static std::array<float, GGML_SYCL_MAX_DEVICES> g_default_tensor_split = {};
@ -13244,7 +13225,7 @@ void ggml_backend_sycl_print_sycl_devices() {
}
void print_gpu_device_list() {
fprintf(stderr, "detect %d SYCL GPUs: [%s] with top Max compute units:%d\n",
fprintf(stderr, "detect %d SYCL GPUs: [%s] with Max compute units:%d\n",
g_sycl_gpu_mgr->get_gpu_count(),
g_sycl_gpu_mgr->gpus_list.c_str(),
g_sycl_gpu_mgr->max_compute_units);
@ -13283,15 +13264,6 @@ void ggml_init_sycl() try {
#else
fprintf(stderr, "%s: GGML_SYCL_F16: no\n", __func__);
#endif
/* NOT REMOVE, keep it for next optimize for XMX.
#if defined(SYCL_USE_XMX)
fprintf(stderr, "%s: SYCL_USE_XMX: yes\n", __func__);
#else
fprintf(stderr, "%s: SYCL_USE_XMX: no\n", __func__);
#endif
*/
if (CHECK_TRY_ERROR(g_all_sycl_device_count =
dpct::dev_mgr::instance().device_count()) != 0) {
initialized = true;
@ -13300,61 +13272,68 @@ void ggml_init_sycl() try {
}
GGML_ASSERT(g_all_sycl_device_count <= GGML_SYCL_MAX_DEVICES);
ggml_backend_sycl_print_sycl_devices();
if (!g_sycl_gpu_mgr) g_sycl_gpu_mgr = new sycl_gpu_mgr();
g_device_count = g_sycl_gpu_mgr->get_gpu_count();
g_work_group_size = g_sycl_gpu_mgr->work_group_size;
print_gpu_device_list();
initialized = true;
g_sycl_loaded = true;
}
int64_t total_vram = 0;
g_device_count = g_sycl_gpu_mgr->get_gpu_count();
g_work_group_size = g_sycl_gpu_mgr->work_group_size;
int64_t total_vram = 0;
for (int id = 0; id < GGML_SYCL_MAX_DEVICES; ++id) {
g_device_caps[id].vmm = 0;
g_device_caps[id].device_id = -1;
g_device_caps[id].cc = 0;
g_tensor_split[id] = 0;
g_default_tensor_split[id] = 0;
}
for (int i = 0; i < g_device_count; ++i) {
int device_id = g_sycl_gpu_mgr->gpus[i];
g_device_caps[i].vmm = 0;
dpct::device_info prop;
SYCL_CHECK(CHECK_TRY_ERROR(dpct::get_device_info(
prop, dpct::dev_mgr::instance().get_device(device_id))));
g_default_tensor_split[i] = total_vram;
total_vram += prop.get_global_mem_size();
g_device_caps[i].cc =
100 * prop.get_major_version() + 10 * prop.get_minor_version();
}
for (int i = 0; i < g_device_count; ++i) {
g_default_tensor_split[i] /= total_vram;
}
for (int i = 0; i < g_device_count; ++i) {
SYCL_CHECK(ggml_sycl_set_device(i));
// create sycl streams
for (int is = 0; is < MAX_STREAMS; ++is) {
SYCL_CHECK(CHECK_TRY_ERROR(
g_syclStreams[i][is] =
dpct::get_current_device().create_queue(
g_sycl_gpu_mgr->get_co_ctx(), dpct::get_current_device())));
/* NOT REMOVE, keep it for next optimize for XMX.
#if defined(SYCL_USE_XMX)
fprintf(stderr, "%s: SYCL_USE_XMX: yes\n", __func__);
#else
fprintf(stderr, "%s: SYCL_USE_XMX: no\n", __func__);
#endif
*/
for (int id = 0; id < GGML_SYCL_MAX_DEVICES; ++id) {
g_device_caps[id].vmm = 0;
g_device_caps[id].device_id = -1;
g_device_caps[id].cc = 0;
g_tensor_split[id] = 0;
g_default_tensor_split[id] = 0;
}
const dpct::queue_ptr stream = g_syclStreams[i][0];
// create sycl handle
SYCL_CHECK(CHECK_TRY_ERROR(g_sycl_handles[i] = stream));
for (int i = 0; i < g_device_count; ++i) {
int device_id = g_sycl_gpu_mgr->gpus[i];
g_device_caps[i].vmm = 0;
dpct::device_info prop;
SYCL_CHECK(CHECK_TRY_ERROR(dpct::get_device_info(
prop, dpct::dev_mgr::instance().get_device(device_id))));
g_default_tensor_split[i] = total_vram;
total_vram += prop.get_global_mem_size();
g_device_caps[i].cc =
100 * prop.get_major_version() + 10 * prop.get_minor_version();
}
for (int i = 0; i < g_device_count; ++i) {
g_default_tensor_split[i] /= total_vram;
}
for (int i = 0; i < g_device_count; ++i) {
SYCL_CHECK(ggml_sycl_set_device(i));
// create sycl streams
for (int is = 0; is < MAX_STREAMS; ++is) {
SYCL_CHECK(CHECK_TRY_ERROR(
g_syclStreams[i][is] =
dpct::get_current_device().create_queue(
g_sycl_gpu_mgr->get_co_ctx(), dpct::get_current_device())));
}
const dpct::queue_ptr stream = g_syclStreams[i][0];
// create sycl handle
SYCL_CHECK(CHECK_TRY_ERROR(g_sycl_handles[i] = stream));
}
initialized = true;
g_sycl_loaded = true;
}
}
catch (sycl::exception const &exc) {
@ -16753,24 +16732,22 @@ static ggml_backend_buffer_type_i ggml_backend_sycl_buffer_type_interface = {
/* .is_host = */ nullptr,
};
ggml_backend_buffer_type_t ggml_backend_sycl_buffer_type(int device_index) {
if (device_index>=g_device_count or device_index<0) {
printf("ggml_backend_sycl_buffer_type error: device_index:%d is out of range [0, %d], miss to call ggml_backend_sycl_set_single_device()\n",
device_index, g_device_count-1);
GGML_ASSERT(device_index<g_device_count);
}
ggml_backend_buffer_type_t ggml_backend_sycl_buffer_type(int device) {
static struct ggml_backend_buffer_type ggml_backend_sycl_buffer_types[GGML_SYCL_MAX_DEVICES];
if (!g_ggml_backend_sycl_buffer_type_initialized) {
static bool ggml_backend_sycl_buffer_type_initialized = false;
if (!ggml_backend_sycl_buffer_type_initialized) {
for (int i = 0; i < g_device_count; i++) {
ggml_backend_sycl_buffer_types[i] = {
/* .iface = */ ggml_backend_sycl_buffer_type_interface,
/* .context = */ new ggml_backend_sycl_buffer_type_context{i, GGML_SYCL_NAME + std::to_string(g_sycl_gpu_mgr->gpus[i])},
};
}
g_ggml_backend_sycl_buffer_type_initialized = true;
ggml_backend_sycl_buffer_type_initialized = true;
}
return &ggml_backend_sycl_buffer_types[device_index];
return &ggml_backend_sycl_buffer_types[device];
}
// sycl split buffer type
@ -17519,17 +17496,6 @@ GGML_API GGML_CALL int ggml_backend_sycl_get_device_index(int device_id) {
return g_sycl_gpu_mgr->get_index(device_id);
}
GGML_API GGML_CALL void ggml_backend_sycl_set_single_device(int main_gpu_id) {
GGML_ASSERT(main_gpu_id<g_all_sycl_device_count);
printf("ggml_backend_sycl_set_single_device: use single device: %d\n", main_gpu_id);
if (g_sycl_gpu_mgr) {
delete g_sycl_gpu_mgr;
}
g_sycl_gpu_mgr = new sycl_gpu_mgr(main_gpu_id);
ggml_init_sycl();
g_ggml_backend_sycl_buffer_type_initialized = false;
}
extern "C" int ggml_backend_sycl_reg_devices();
int ggml_backend_sycl_reg_devices() {

1
ggml-sycl.h
View File

@ -28,7 +28,6 @@ GGML_API GGML_CALL int ggml_backend_sycl_get_device_count();
GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_sycl_split_buffer_type(const float * tensor_split);
GGML_API GGML_CALL void ggml_backend_sycl_get_device_memory(int device, size_t *free, size_t *total);
GGML_API GGML_CALL int ggml_backend_sycl_get_device_index(int device_id);
GGML_API GGML_CALL void ggml_backend_sycl_set_single_device(int main_gpu);
#ifdef __cplusplus
}

16
llama.cpp
View File

@ -3750,14 +3750,6 @@ static bool llm_load_tensors(
model.main_gpu = main_gpu;
model.n_gpu_layers = n_gpu_layers;
#ifdef GGML_USE_SYCL
if (split_mode == LLAMA_SPLIT_MODE_NONE) {
ggml_backend_sycl_set_single_device(main_gpu);
//SYCL use device index (0, 1, 2), instead if device id.
main_gpu = ggml_backend_sycl_get_device_index(main_gpu);
}
#endif
const int64_t n_layer = hparams.n_layer;
const int64_t i_gpu_start = std::max((int64_t) hparams.n_layer - n_gpu_layers, (int64_t) 0);
@ -12268,13 +12260,13 @@ struct llama_context * llama_new_context_with_model(
ctx->backends.push_back(backend);
} else {
// LLAMA_SPLIT_LAYER requires a backend for each GPU
int id_list[GGML_SYCL_MAX_DEVICES];
ggml_sycl_get_gpu_list(id_list, GGML_SYCL_MAX_DEVICES);
for (int i = 0; i < ggml_backend_sycl_get_device_count(); ++i) {
int device_id = id_list[i];
ggml_backend_t backend = ggml_backend_sycl_init(i);
if (backend == nullptr) {
int id_list[GGML_SYCL_MAX_DEVICES];
ggml_sycl_get_gpu_list(id_list, GGML_SYCL_MAX_DEVICES);
LLAMA_LOG_ERROR("%s: failed to initialize SYCL%d (index %d)backend\n", __func__, id_list[i], i);
LLAMA_LOG_ERROR("%s: failed to initialize SYCL%d (index %d)backend\n", __func__, device_id, i);
llama_free(ctx);
return nullptr;
}