diff --git a/common/arg.cpp b/common/arg.cpp index cac8819956..b053a25a1e 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -3045,12 +3045,12 @@ common_params_context common_params_parser_init(common_params & params, llama_ex } ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_MODELS_MAX")); add_opt(common_arg( - {"--models-memory-max"}, "N", - string_format("for router server, maximum memory usage in MB (default: %d, 0 = unlimited)", params.models_memory_max), + {"--models-memory-margin"}, "N", + string_format("for router server, MB of memory to leave free, per device (default: %d, 0 = unlimited)", params.models_memory_margin), [](common_params & params, int value) { - params.models_memory_max = value; + params.models_memory_margin = value; } - ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_MODELS_MEMORY_MAX")); + ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_MODELS_MEMORY_MARGIN")); add_opt(common_arg( {"--models-autoload"}, {"--no-models-autoload"}, diff --git a/common/common.h b/common/common.h index 573a9bf4ef..879032977b 100644 --- a/common/common.h +++ b/common/common.h @@ -618,11 +618,11 @@ struct common_params { std::vector server_tools; // router server configs - std::string models_dir = ""; // directory containing models for the router server - std::string models_preset = ""; // directory containing model presets for the router server - int models_max = 4; // maximum number of models to load simultaneously - int models_memory_max = 0; // maximum memory usage in MB (0 = unlimited, estimated from model files) - bool models_autoload = true; // automatically load models when requested via the router server + std::string models_dir = ""; // directory containing models for the router server + std::string models_preset = ""; // directory containing model presets for the router server + int models_max = 4; // maximum number of models to load simultaneously + int models_memory_margin = 1024; // MB of free memory to preserve per device (0 = disabled) + bool models_autoload = true; // automatically load models when requested via the router server bool log_json = false; diff --git a/include/llama.h b/include/llama.h index a940f9d648..de7c0670f5 100644 --- a/include/llama.h +++ b/include/llama.h @@ -1547,6 +1547,12 @@ extern "C" { // print a breakdown of per-device memory use via LLAMA_LOG: LLAMA_API void llama_memory_breakdown_print(const struct llama_context * ctx); + // Returns the projected memory use (model + context + compute) in bytes + // for the given device within this context. Returns 0 if the device is not used. + LLAMA_API uint64_t llama_context_device_memory( + const struct llama_context * ctx, + ggml_backend_dev_t device); + // // training // diff --git a/src/llama-context.cpp b/src/llama-context.cpp index a808e3e454..a9b001bcbd 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -3610,6 +3610,19 @@ void llama_memory_breakdown_print(const struct llama_context * ctx) { } } +uint64_t llama_context_device_memory(const llama_context * ctx, ggml_backend_dev_t device) { + const bool is_host = ggml_backend_dev_type(device) == GGML_BACKEND_DEVICE_TYPE_CPU; + uint64_t total = 0; + for (const auto & [buft, mb] : ctx->memory_breakdown()) { + const bool matches = is_host ? ggml_backend_buft_is_host(buft) : + ggml_backend_buft_get_device(buft) == device; + if (matches) { + total += mb.total(); + } + } + return total; +} + // // training // diff --git a/tools/server/server-models.cpp b/tools/server/server-models.cpp index 943192a721..81b6d5b3e8 100644 --- a/tools/server/server-models.cpp +++ b/tools/server/server-models.cpp @@ -178,6 +178,21 @@ server_models::server_models( LOG_WRN("failed to get server executable path: %s\n", e.what()); LOG_WRN("using original argv[0] as fallback: %s\n", argv[0]); } + + const uint64_t memory_margin = base_params.models_memory_margin * 1024 * 1024; + + if (memory_margin > 0) { + const size_t n_devs = ggml_backend_dev_count(); + for (size_t i = 0; i < n_devs; i++) { + ggml_backend_dev_t dev = ggml_backend_dev_get(i); + size_t free, total; + ggml_backend_dev_memory(dev, &free, &total); + if (total > 0) { + memory_per_device[dev] = (free > memory_margin) ? free - memory_margin : 0; + } + } + } + load_models(); } @@ -293,17 +308,17 @@ void server_models::load_models() { // convert presets to server_model_meta and add to mapping for (const auto & preset : final_presets) { server_model_meta meta{ - /* preset */ preset.second, - /* name */ preset.first, - /* aliases */ {}, - /* tags */ {}, - /* port */ 0, - /* status */ SERVER_MODEL_STATUS_UNLOADED, - /* last_used */ 0, - /* memory_mb */ 0, - /* args */ std::vector(), - /* exit_code */ 0, - /* stop_timeout */ DEFAULT_STOP_TIMEOUT, + /* preset */ preset.second, + /* name */ preset.first, + /* aliases */ {}, + /* tags */ {}, + /* port */ 0, + /* status */ SERVER_MODEL_STATUS_UNLOADED, + /* last_used */ 0, + /* memory_per_device */ {}, + /* args */ std::vector(), + /* exit_code */ 0, + /* stop_timeout */ DEFAULT_STOP_TIMEOUT, }; add_model(std::move(meta)); } @@ -494,36 +509,63 @@ std::vector server_models::get_all_meta() { return result; } -void server_models::unload_lru(uint64_t new_model_memory_mb) { - if (base_params.models_max <= 0 && base_params.models_memory_max <= 0) { +uint64_t server_models::get_memory_exceeded(const model_memory_map& new_model_memory_per_device) const { + model_memory_map total_memory_per_device; + for (const auto & m : mapping) { + if (m.second.meta.is_running()) { + for (const auto& [key, value] : m.second.meta.memory_per_device) { + total_memory_per_device[key] += value; + } + } + } + + auto get = [](const model_memory_map & m, ggml_backend_dev_t k) { + auto it = m.find(k); + return it != m.end() ? it->second : 0; + }; + + uint64_t memory_exceeded = 0; + + for (const auto& [key, limit] : memory_per_device) { + if (get(new_model_memory_per_device, key) + get(total_memory_per_device, key) > limit) { + memory_exceeded++; + } + } + + return memory_exceeded; +} + +void server_models::unload_lru(const model_memory_map& new_model_memory_per_device) { + const bool check_memory = base_params.models_memory_margin > 0 && !memory_per_device.empty(); + + if (base_params.models_max <= 0 && !check_memory) { return; // no limit } + while (true) { std::string lru_model_name = ""; int64_t lru_last_used = ggml_time_ms(); size_t count_active = 0; - uint64_t total_memory_mb = 0; + uint64_t memory_exceeded = 0; { std::unique_lock lk(mutex); for (const auto & m : mapping) { if (m.second.meta.is_running()) { count_active++; - total_memory_mb += m.second.meta.memory_mb; if (m.second.meta.last_used < lru_last_used) { lru_model_name = m.first; lru_last_used = m.second.meta.last_used; } } } + memory_exceeded = get_memory_exceeded(new_model_memory_per_device); } bool count_exceeded = base_params.models_max > 0 && (count_active + 1) >= (size_t)base_params.models_max; - uint64_t projected_memory = total_memory_mb + new_model_memory_mb; - bool memory_exceeded = base_params.models_memory_max > 0 && - projected_memory >= (uint64_t)base_params.models_memory_max; - if (!lru_model_name.empty() && (count_exceeded || memory_exceeded)) { - SRV_INF("limits reached (count=%zu, memory=%lu MB + %lu MB new), removing LRU name=%s\n", - count_active, (unsigned long)total_memory_mb, (unsigned long)new_model_memory_mb, lru_model_name.c_str()); + + if (!lru_model_name.empty() && (count_exceeded || memory_exceeded > 0)) { + SRV_INF("limits reached (count=%zu, memory margin exceeded on %zu device(s)), removing LRU name=%s\n", + count_active, memory_exceeded, lru_model_name.c_str()); unload(lru_model_name); // wait for unload to complete { @@ -538,12 +580,12 @@ void server_models::unload_lru(uint64_t new_model_memory_mb) { } } -static uint64_t get_model_memory_mb(const common_preset& preset) { +static model_memory_map get_model_memory_per_device(const common_preset& preset) { common_params params; preset.apply_to_params(params); if(params.model.path.empty()) { - return 0; + return {}; } struct log_ud_t { @@ -567,18 +609,32 @@ static uint64_t get_model_memory_mb(const common_preset& preset) { mparams.use_mmap = false; mparams.use_mlock = false; - llama_model * model = llama_model_load_from_file(params.model.path.c_str(), mparams); - - llama_log_set(log_ud.original.callback, log_ud.original.user_data); + llama_model_ptr model{llama_model_load_from_file(params.model.path.c_str(), mparams)}; if (!model) { - return 0; + llama_log_set(log_ud.original.callback, log_ud.original.user_data); + return {}; } - uint64_t size_bytes = llama_model_size(model); - llama_model_free(model); + llama_context_params cparams = common_context_params_to_llama(params); + llama_context_ptr ctx{llama_init_from_model(model.get(), cparams)}; + llama_log_set(log_ud.original.callback, log_ud.original.user_data); - return size_bytes / (1024 * 1024); + if (!ctx) { + return {}; + } + + model_memory_map result; + const size_t n_devs = ggml_backend_dev_count(); + for (size_t i = 0; i < n_devs; i++) { + ggml_backend_dev_t dev = ggml_backend_dev_get(i); + uint64_t bytes = llama_context_device_memory(ctx.get(), dev); + if (bytes > 0) { + result[dev] = bytes; + } + } + + return result; } void server_models::load(const std::string & name) { @@ -586,23 +642,18 @@ void server_models::load(const std::string & name) { throw std::runtime_error("model name=" + name + " is not found"); } - uint64_t new_model_memory_mb = 0; - if (base_params.models_memory_max > 0) { + model_memory_map new_model_memory_per_device; + if (base_params.models_memory_margin > 0) { std::lock_guard lk(mutex); auto & meta = mapping[name].meta; - if (meta.memory_mb > 0) { - new_model_memory_mb = meta.memory_mb; - } else { - new_model_memory_mb = get_model_memory_mb(meta.preset); - meta.memory_mb = new_model_memory_mb; - } - if (new_model_memory_mb > 0) { - SRV_INF("model %s memory requirements: %lu MB\n", name.c_str(), - (unsigned long)new_model_memory_mb); + if (meta.memory_per_device.empty()) { + meta.memory_per_device = get_model_memory_per_device(meta.preset); } + + new_model_memory_per_device = meta.memory_per_device; } - unload_lru(new_model_memory_mb); + unload_lru(new_model_memory_per_device); std::lock_guard lk(mutex); @@ -616,17 +667,15 @@ void server_models::load(const std::string & name) { // exceeding models_max. Without this, the window between unload_lru() // releasing its lock and this lock_guard acquiring allows multiple // threads to each observe capacity and all proceed to load. - if (base_params.models_max > 0 || base_params.models_memory_max > 0) { + if (base_params.models_max > 0 || base_params.models_memory_margin > 0) { size_t count_active = 0; - uint64_t total_memory_mb = 0; for (const auto & m : mapping) { if (m.second.meta.is_running()) { count_active++; - total_memory_mb += m.second.meta.memory_mb; } } bool count_exceeded = base_params.models_max > 0 && count_active >= (size_t)base_params.models_max; - bool memory_exceeded = base_params.models_memory_max > 0 && total_memory_mb >= (uint64_t)base_params.models_memory_max; + bool memory_exceeded = get_memory_exceeded(new_model_memory_per_device) > 0; if (count_exceeded || memory_exceeded) { throw std::runtime_error("model limit reached, try again later"); } diff --git a/tools/server/server-models.h b/tools/server/server-models.h index 2cbdb35b32..38d6929a88 100644 --- a/tools/server/server-models.h +++ b/tools/server/server-models.h @@ -54,6 +54,8 @@ static std::string server_model_status_to_string(server_model_status status) { } } +using model_memory_map = std::map; + struct server_model_meta { common_preset preset; std::string name; @@ -62,7 +64,7 @@ struct server_model_meta { int port = 0; server_model_status status = SERVER_MODEL_STATUS_UNLOADED; int64_t last_used = 0; // for LRU unloading - uint64_t memory_mb = 0; // size in MB + model_memory_map memory_per_device; // projected bytes per device std::vector args; // args passed to the model instance, will be populated by render_args() int exit_code = 0; // exit code of the model instance process (only valid if status == FAILED) int stop_timeout = 0; // seconds to wait before force-killing the model instance during shutdown @@ -108,14 +110,20 @@ private: std::vector base_env; common_preset base_preset; // base preset from llama-server CLI args + // available memory per device + std::map memory_per_device; + void update_meta(const std::string & name, const server_model_meta & meta); // unload least recently used models if the limit is reached - void unload_lru(uint64_t new_model_memory_mb = 0); + void unload_lru(const model_memory_map& new_model_memory_per_device); // not thread-safe, caller must hold mutex void add_model(server_model_meta && meta); + // not thread-safe, caller must hold mutex + uint64_t get_memory_exceeded(const model_memory_map& new_model_memory_per_device) const; + public: server_models(const common_params & params, int argc, char ** argv);