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https://github.com/ggerganov/llama.cpp.git
synced 2024-11-11 21:39:52 +00:00
[SYCL] fix error when set main gpu to non-zero (#5901)
* fix error when set main gpu to non-zero * fix delete condition
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178
ggml-sycl.cpp
178
ggml-sycl.cpp
@ -3559,12 +3559,31 @@ class sycl_gpu_mgr {
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int work_group_size = 0;
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std::string gpus_list = "";
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/*
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Use all GPU with same top max compute units
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*/
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sycl_gpu_mgr() {
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detect_sycl_gpu_list_with_max_cu();
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get_allow_gpus();
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create_context_with_gpus();
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}
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/*
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Use the assigned GPU as only one
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*/
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sycl_gpu_mgr(int main_gpu_id) {
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sycl::device device = dpct::dev_mgr::instance().get_device(main_gpu_id);
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dpct::device_info prop;
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dpct::get_device_info(prop, device);
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gpus.push_back(main_gpu_id);
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devices.push_back(device);
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work_group_size = prop.get_max_work_group_size();
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max_compute_units = prop.get_max_compute_units();
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get_allow_gpus();
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create_context_with_gpus();
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}
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void create_context_with_gpus() {
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sycl::context ctx = sycl::context(devices);
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assert(gpus.size() > 0);
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@ -3580,7 +3599,7 @@ class sycl_gpu_mgr {
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gpus_list += std::to_string(gpus[i]);
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gpus_list += ",";
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}
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if (gpus_list.length() > 2) {
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if (gpus_list.length() > 1) {
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gpus_list.pop_back();
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}
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}
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@ -3629,8 +3648,8 @@ class sycl_gpu_mgr {
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if (gpus[i] == id)
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return i;
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}
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assert(false);
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return -1;
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printf("miss to get device index by id=%d\n", id);
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GGML_ASSERT(false);
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}
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int get_next_index(int id) {
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@ -3639,8 +3658,7 @@ class sycl_gpu_mgr {
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if (gpus[i] == id)
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return i;
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}
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assert(false);
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return -1;
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GGML_ASSERT(false);
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}
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};
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@ -3649,6 +3667,7 @@ static int g_device_count = -1;
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static int g_all_sycl_device_count = -1;
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static int g_main_device = -1;
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static int g_main_device_id = -1;
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static bool g_ggml_backend_sycl_buffer_type_initialized = false;
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static std::array<float, GGML_SYCL_MAX_DEVICES> g_default_tensor_split = {};
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@ -13225,7 +13244,7 @@ void ggml_backend_sycl_print_sycl_devices() {
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}
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void print_gpu_device_list() {
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fprintf(stderr, "detect %d SYCL GPUs: [%s] with Max compute units:%d\n",
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fprintf(stderr, "detect %d SYCL GPUs: [%s] with top Max compute units:%d\n",
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g_sycl_gpu_mgr->get_gpu_count(),
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g_sycl_gpu_mgr->gpus_list.c_str(),
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g_sycl_gpu_mgr->max_compute_units);
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@ -13264,23 +13283,6 @@ void ggml_init_sycl() try {
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#else
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fprintf(stderr, "%s: GGML_SYCL_F16: no\n", __func__);
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#endif
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if (CHECK_TRY_ERROR(g_all_sycl_device_count =
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dpct::dev_mgr::instance().device_count()) != 0) {
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initialized = true;
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g_sycl_loaded = false;
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return;
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}
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GGML_ASSERT(g_all_sycl_device_count <= GGML_SYCL_MAX_DEVICES);
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ggml_backend_sycl_print_sycl_devices();
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if (!g_sycl_gpu_mgr) g_sycl_gpu_mgr = new sycl_gpu_mgr();
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g_device_count = g_sycl_gpu_mgr->get_gpu_count();
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g_work_group_size = g_sycl_gpu_mgr->work_group_size;
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print_gpu_device_list();
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int64_t total_vram = 0;
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/* NOT REMOVE, keep it for next optimize for XMX.
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#if defined(SYCL_USE_XMX)
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@ -13289,52 +13291,71 @@ void ggml_init_sycl() try {
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fprintf(stderr, "%s: SYCL_USE_XMX: no\n", __func__);
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#endif
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*/
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for (int id = 0; id < GGML_SYCL_MAX_DEVICES; ++id) {
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g_device_caps[id].vmm = 0;
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g_device_caps[id].device_id = -1;
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g_device_caps[id].cc = 0;
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g_tensor_split[id] = 0;
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g_default_tensor_split[id] = 0;
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if (CHECK_TRY_ERROR(g_all_sycl_device_count =
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dpct::dev_mgr::instance().device_count()) != 0) {
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initialized = true;
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g_sycl_loaded = false;
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return;
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}
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for (int i = 0; i < g_device_count; ++i) {
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int device_id = g_sycl_gpu_mgr->gpus[i];
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g_device_caps[i].vmm = 0;
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dpct::device_info prop;
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SYCL_CHECK(CHECK_TRY_ERROR(dpct::get_device_info(
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prop, dpct::dev_mgr::instance().get_device(device_id))));
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g_default_tensor_split[i] = total_vram;
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total_vram += prop.get_global_mem_size();
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g_device_caps[i].cc =
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100 * prop.get_major_version() + 10 * prop.get_minor_version();
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}
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for (int i = 0; i < g_device_count; ++i) {
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g_default_tensor_split[i] /= total_vram;
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}
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for (int i = 0; i < g_device_count; ++i) {
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SYCL_CHECK(ggml_sycl_set_device(i));
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// create sycl streams
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for (int is = 0; is < MAX_STREAMS; ++is) {
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SYCL_CHECK(CHECK_TRY_ERROR(
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g_syclStreams[i][is] =
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dpct::get_current_device().create_queue(
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g_sycl_gpu_mgr->get_co_ctx(), dpct::get_current_device())));
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}
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const dpct::queue_ptr stream = g_syclStreams[i][0];
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// create sycl handle
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SYCL_CHECK(CHECK_TRY_ERROR(g_sycl_handles[i] = stream));
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}
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GGML_ASSERT(g_all_sycl_device_count <= GGML_SYCL_MAX_DEVICES);
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ggml_backend_sycl_print_sycl_devices();
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if (!g_sycl_gpu_mgr) g_sycl_gpu_mgr = new sycl_gpu_mgr();
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print_gpu_device_list();
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initialized = true;
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g_sycl_loaded = true;
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}
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g_device_count = g_sycl_gpu_mgr->get_gpu_count();
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g_work_group_size = g_sycl_gpu_mgr->work_group_size;
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int64_t total_vram = 0;
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for (int id = 0; id < GGML_SYCL_MAX_DEVICES; ++id) {
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g_device_caps[id].vmm = 0;
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g_device_caps[id].device_id = -1;
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g_device_caps[id].cc = 0;
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g_tensor_split[id] = 0;
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g_default_tensor_split[id] = 0;
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}
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for (int i = 0; i < g_device_count; ++i) {
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int device_id = g_sycl_gpu_mgr->gpus[i];
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g_device_caps[i].vmm = 0;
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dpct::device_info prop;
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SYCL_CHECK(CHECK_TRY_ERROR(dpct::get_device_info(
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prop, dpct::dev_mgr::instance().get_device(device_id))));
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g_default_tensor_split[i] = total_vram;
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total_vram += prop.get_global_mem_size();
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g_device_caps[i].cc =
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100 * prop.get_major_version() + 10 * prop.get_minor_version();
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}
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for (int i = 0; i < g_device_count; ++i) {
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g_default_tensor_split[i] /= total_vram;
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}
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for (int i = 0; i < g_device_count; ++i) {
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SYCL_CHECK(ggml_sycl_set_device(i));
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// create sycl streams
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for (int is = 0; is < MAX_STREAMS; ++is) {
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SYCL_CHECK(CHECK_TRY_ERROR(
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g_syclStreams[i][is] =
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dpct::get_current_device().create_queue(
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g_sycl_gpu_mgr->get_co_ctx(), dpct::get_current_device())));
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}
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const dpct::queue_ptr stream = g_syclStreams[i][0];
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// create sycl handle
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SYCL_CHECK(CHECK_TRY_ERROR(g_sycl_handles[i] = stream));
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}
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}
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catch (sycl::exception const &exc) {
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std::cerr << exc.what() << "Exception caught at file:" << __FILE__
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@ -16732,22 +16753,24 @@ static ggml_backend_buffer_type_i ggml_backend_sycl_buffer_type_interface = {
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/* .is_host = */ nullptr,
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};
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ggml_backend_buffer_type_t ggml_backend_sycl_buffer_type(int device) {
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ggml_backend_buffer_type_t ggml_backend_sycl_buffer_type(int device_index) {
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if (device_index>=g_device_count or device_index<0) {
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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",
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device_index, g_device_count-1);
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GGML_ASSERT(device_index<g_device_count);
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}
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static struct ggml_backend_buffer_type ggml_backend_sycl_buffer_types[GGML_SYCL_MAX_DEVICES];
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static bool ggml_backend_sycl_buffer_type_initialized = false;
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if (!ggml_backend_sycl_buffer_type_initialized) {
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if (!g_ggml_backend_sycl_buffer_type_initialized) {
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for (int i = 0; i < g_device_count; i++) {
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ggml_backend_sycl_buffer_types[i] = {
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/* .iface = */ ggml_backend_sycl_buffer_type_interface,
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/* .context = */ new ggml_backend_sycl_buffer_type_context{i, GGML_SYCL_NAME + std::to_string(g_sycl_gpu_mgr->gpus[i])},
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};
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}
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ggml_backend_sycl_buffer_type_initialized = true;
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g_ggml_backend_sycl_buffer_type_initialized = true;
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}
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return &ggml_backend_sycl_buffer_types[device];
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return &ggml_backend_sycl_buffer_types[device_index];
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}
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// sycl split buffer type
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@ -17496,6 +17519,17 @@ GGML_API GGML_CALL int ggml_backend_sycl_get_device_index(int device_id) {
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return g_sycl_gpu_mgr->get_index(device_id);
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}
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GGML_API GGML_CALL void ggml_backend_sycl_set_single_device(int main_gpu_id) {
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GGML_ASSERT(main_gpu_id<g_all_sycl_device_count);
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printf("ggml_backend_sycl_set_single_device: use single device: %d\n", main_gpu_id);
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if (g_sycl_gpu_mgr) {
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delete g_sycl_gpu_mgr;
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}
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g_sycl_gpu_mgr = new sycl_gpu_mgr(main_gpu_id);
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ggml_init_sycl();
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g_ggml_backend_sycl_buffer_type_initialized = false;
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}
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extern "C" int ggml_backend_sycl_reg_devices();
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int ggml_backend_sycl_reg_devices() {
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@ -28,6 +28,7 @@ GGML_API GGML_CALL int ggml_backend_sycl_get_device_count();
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GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_sycl_split_buffer_type(const float * tensor_split);
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GGML_API GGML_CALL void ggml_backend_sycl_get_device_memory(int device, size_t *free, size_t *total);
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GGML_API GGML_CALL int ggml_backend_sycl_get_device_index(int device_id);
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GGML_API GGML_CALL void ggml_backend_sycl_set_single_device(int main_gpu);
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#ifdef __cplusplus
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}
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16
llama.cpp
16
llama.cpp
@ -3750,6 +3750,14 @@ static bool llm_load_tensors(
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model.main_gpu = main_gpu;
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model.n_gpu_layers = n_gpu_layers;
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#ifdef GGML_USE_SYCL
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if (split_mode == LLAMA_SPLIT_MODE_NONE) {
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ggml_backend_sycl_set_single_device(main_gpu);
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//SYCL use device index (0, 1, 2), instead if device id.
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main_gpu = ggml_backend_sycl_get_device_index(main_gpu);
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}
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#endif
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const int64_t n_layer = hparams.n_layer;
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const int64_t i_gpu_start = std::max((int64_t) hparams.n_layer - n_gpu_layers, (int64_t) 0);
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@ -12260,13 +12268,13 @@ struct llama_context * llama_new_context_with_model(
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ctx->backends.push_back(backend);
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} else {
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// LLAMA_SPLIT_LAYER requires a backend for each GPU
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int id_list[GGML_SYCL_MAX_DEVICES];
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ggml_sycl_get_gpu_list(id_list, GGML_SYCL_MAX_DEVICES);
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for (int i = 0; i < ggml_backend_sycl_get_device_count(); ++i) {
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int device_id = id_list[i];
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ggml_backend_t backend = ggml_backend_sycl_init(i);
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if (backend == nullptr) {
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LLAMA_LOG_ERROR("%s: failed to initialize SYCL%d (index %d)backend\n", __func__, device_id, i);
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int id_list[GGML_SYCL_MAX_DEVICES];
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ggml_sycl_get_gpu_list(id_list, GGML_SYCL_MAX_DEVICES);
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LLAMA_LOG_ERROR("%s: failed to initialize SYCL%d (index %d)backend\n", __func__, id_list[i], i);
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llama_free(ctx);
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return nullptr;
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}
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