metal : add residency sets keep-alive heartbeat (#17766)
* examples : add idle * metal : attach residency sets to queue * idle : add link * idle : adjust intervals * metal : add residency sets keep-alive heartbeat * cont : adjust default keep-alive time
This commit is contained in:
Georgi Gerganov
GitHub
parent
6016d0bd41
commit
c41bde6fbd
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@ -20,6 +20,7 @@ else()
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add_subdirectory(gguf-hash)
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add_subdirectory(gguf)
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add_subdirectory(idle)
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add_subdirectory(lookahead)
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add_subdirectory(lookup)
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add_subdirectory(parallel)
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@ -0,0 +1,5 @@
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set(TARGET llama-idle)
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add_executable(${TARGET} idle.cpp)
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install(TARGETS ${TARGET} RUNTIME)
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target_link_libraries(${TARGET} PRIVATE llama common ${CMAKE_THREAD_LIBS_INIT})
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target_compile_features(${TARGET} PRIVATE cxx_std_11)
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@ -0,0 +1,3 @@
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# llama.cpp/example/idle
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https://github.com/ggml-org/llama.cpp/pull/17766
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@ -0,0 +1,110 @@
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#include "arg.h"
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#include "common.h"
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#include "log.h"
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#include "llama.h"
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#include <cmath>
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#include <cstdio>
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#include <cstring>
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#include <string>
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#include <thread>
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#include <vector>
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static void print_usage(int /*argc*/, char ** argv) {
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printf("\nexample usage:\n");
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printf("\n %s -m model.gguf [-ngl n_gpu_layers]\n", argv[0]);
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printf("\n");
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}
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int main(int argc, char ** argv) {
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common_params params;
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if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_COMMON, print_usage)) {
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return 1;
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}
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common_init();
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// init LLM
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llama_backend_init();
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llama_numa_init(params.numa);
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// initialize the model
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llama_model_params model_params = common_model_params_to_llama(params);
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llama_model * model = llama_model_load_from_file(params.model.path.c_str(), model_params);
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if (model == NULL) {
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LOG_ERR("%s: error: unable to load model\n" , __func__);
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return 1;
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}
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const llama_vocab * vocab = llama_model_get_vocab(model);
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// we need just a dummy token to evaluate
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std::vector<llama_token> prompt_tokens(1, llama_vocab_bos(vocab));
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llama_context_params ctx_params = llama_context_default_params();
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ctx_params.n_ctx = 512;
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ctx_params.n_batch = 512;
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ctx_params.no_perf = false;
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llama_context * ctx = llama_init_from_model(model, ctx_params);
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if (ctx == NULL) {
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fprintf(stderr , "%s: error: failed to create the llama_context\n" , __func__);
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return 1;
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}
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llama_batch batch = llama_batch_get_one(prompt_tokens.data(), prompt_tokens.size());
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const int n_iters = 3;
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// warm-up
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llama_decode(ctx, batch);
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llama_memory_clear(llama_get_memory(ctx), true);
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llama_synchronize(ctx);
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for (int64_t t_pause_ms = 0; t_pause_ms <= 4000; t_pause_ms += 800) {
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double t_sum_us = 0.0;
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double t_sum2_us = 0.0;
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for (int i = 0; i < n_iters; i++) {
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// this pause is important - it simulates "idle GPU"
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std::this_thread::sleep_for(std::chrono::milliseconds(t_pause_ms));
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const int64_t t_start_us = llama_time_us();
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// this should take constant time
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llama_decode(ctx, batch);
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llama_synchronize(ctx);
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const int64_t t_end_us = llama_time_us();
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const double t_cur_us = t_end_us - t_start_us;
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#if 1
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// print individual decode times
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printf(" - decode time: %8.2f ms\n", t_cur_us / 1000);
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#endif
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t_sum_us += t_cur_us;
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t_sum2_us += t_cur_us * t_cur_us;
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llama_memory_clear(llama_get_memory(ctx), true);
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llama_synchronize(ctx); // just in case
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}
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const double t_avg_us = t_sum_us / n_iters;
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const double t_dev_us = sqrt((t_sum2_us / (n_iters - 1)) - (t_avg_us * t_avg_us * n_iters) / (n_iters - 1));
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printf("iters: %4d, pause: %5d ms, avg decode time: %8.2f +/- %4.2f ms\n", n_iters, (int) t_pause_ms, t_avg_us / 1000, t_dev_us / 1000);
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fflush(stdout);
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}
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llama_free(ctx);
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llama_model_free(model);
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return 0;
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}
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@ -24,9 +24,6 @@ struct ggml_metal_command_buffer {
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};
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struct ggml_metal {
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id<MTLDevice> device;
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id<MTLCommandQueue> queue; // currently a pointer to the device queue, but might become separate queue [TAG_QUEUE_PER_BACKEND]
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ggml_metal_device_t dev;
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ggml_metal_library_t lib;
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@ -91,15 +88,15 @@ ggml_metal_t ggml_metal_init(ggml_metal_device_t dev) {
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// init context
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ggml_metal_t res = calloc(1, sizeof(struct ggml_metal));
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res->device = ggml_metal_device_get_obj(dev);
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id<MTLDevice> device = ggml_metal_device_get_obj(dev);
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GGML_LOG_INFO("%s: picking default device: %s\n", __func__, [[res->device name] UTF8String]);
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GGML_LOG_INFO("%s: picking default device: %s\n", __func__, [[device name] UTF8String]);
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// TODO: would it be better to have one queue for the backend and one queue for the device?
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// the graph encoders and async ops would use the backend queue while the sync ops would use the device queue?
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//res->queue = [device newCommandQueue]; [TAG_QUEUE_PER_BACKEND]
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res->queue = ggml_metal_device_get_queue(dev);
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if (res->queue == nil) {
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id<MTLCommandQueue> queue = ggml_metal_device_get_queue(dev);
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if (queue == nil) {
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GGML_LOG_ERROR("%s: error: failed to create command queue\n", __func__);
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return NULL;
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}
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@ -274,7 +271,8 @@ static struct ggml_metal_buffer_id ggml_metal_get_buffer_id(const struct ggml_te
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void ggml_metal_set_tensor_async(ggml_metal_t ctx, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
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@autoreleasepool {
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// wrap the source data into a Metal buffer
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id<MTLBuffer> buf_src = [ctx->device newBufferWithBytes:data
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id<MTLDevice> device = ggml_metal_device_get_obj(ctx->dev);
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id<MTLBuffer> buf_src = [device newBufferWithBytes:data
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length:size
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options:MTLResourceStorageModeShared];
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@ -289,7 +287,8 @@ void ggml_metal_set_tensor_async(ggml_metal_t ctx, struct ggml_tensor * tensor,
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// queue the copy operation into the queue of the Metal context
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// this will be queued at the end, after any currently ongoing GPU operations
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id<MTLCommandBuffer> cmd_buf = [ctx->queue commandBuffer];
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id<MTLCommandQueue> queue = ggml_metal_device_get_queue(ctx->dev);
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id<MTLCommandBuffer> cmd_buf = [queue commandBuffer];
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id<MTLBlitCommandEncoder> encoder = [cmd_buf blitCommandEncoder];
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[encoder copyFromBuffer:buf_src
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@ -315,7 +314,8 @@ void ggml_metal_set_tensor_async(ggml_metal_t ctx, struct ggml_tensor * tensor,
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void ggml_metal_get_tensor_async(ggml_metal_t ctx, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size) {
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@autoreleasepool {
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id<MTLBuffer> buf_dst = [ctx->device newBufferWithBytesNoCopy:data
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id<MTLDevice> device = ggml_metal_device_get_obj(ctx->dev);
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id<MTLBuffer> buf_dst = [device newBufferWithBytesNoCopy:data
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length:size
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options:MTLResourceStorageModeShared
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deallocator:nil];
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@ -331,7 +331,8 @@ void ggml_metal_get_tensor_async(ggml_metal_t ctx, const struct ggml_tensor * te
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// queue the copy operation into the queue of the Metal context
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// this will be queued at the end, after any currently ongoing GPU operations
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id<MTLCommandBuffer> cmd_buf = [ctx->queue commandBuffer];
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id<MTLCommandQueue> queue = ggml_metal_device_get_queue(ctx->dev);
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id<MTLCommandBuffer> cmd_buf = [queue commandBuffer];
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id<MTLBlitCommandEncoder> encoder = [cmd_buf blitCommandEncoder];
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[encoder copyFromBuffer:bid_src.metal
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@ -362,6 +363,9 @@ enum ggml_status ggml_metal_graph_compute(ggml_metal_t ctx, struct ggml_cgraph *
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// number of threads in addition to the main thread
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const int n_cb = ctx->n_cb;
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// keep the memory wired
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ggml_metal_device_rsets_keep_alive(ctx->dev);
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// submit the ggml compute graph to the GPU by creating command buffers and encoding the ops in them
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// the first n_nodes_0 are encoded and submitted for processing directly by the calling thread
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// while these nodes are processing, we start n_cb threads to enqueue the rest of the nodes
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@ -389,7 +393,8 @@ enum ggml_status ggml_metal_graph_compute(ggml_metal_t ctx, struct ggml_cgraph *
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if (!ctx->capture_started) {
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// create capture scope
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ctx->capture_scope = [[MTLCaptureManager sharedCaptureManager] newCaptureScopeWithDevice:ctx->device];
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id<MTLDevice> device = ggml_metal_device_get_obj(ctx->dev);
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ctx->capture_scope = [[MTLCaptureManager sharedCaptureManager] newCaptureScopeWithDevice:device];
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MTLCaptureDescriptor * descriptor = [MTLCaptureDescriptor new];
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descriptor.captureObject = ctx->capture_scope;
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@ -406,10 +411,13 @@ enum ggml_status ggml_metal_graph_compute(ggml_metal_t ctx, struct ggml_cgraph *
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}
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}
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// short-hand
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id<MTLCommandQueue> queue = ggml_metal_device_get_queue(ctx->dev);
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// the main thread commits the first few commands immediately
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// cmd_buf[n_cb]
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{
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id<MTLCommandBuffer> cmd_buf = [ctx->queue commandBufferWithUnretainedReferences];
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id<MTLCommandBuffer> cmd_buf = [queue commandBufferWithUnretainedReferences];
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[cmd_buf retain];
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if (ctx->cmd_bufs[n_cb].obj) {
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@ -428,7 +436,7 @@ enum ggml_status ggml_metal_graph_compute(ggml_metal_t ctx, struct ggml_cgraph *
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// prepare the rest of the command buffers asynchronously (optional)
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// cmd_buf[0.. n_cb)
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for (int cb_idx = 0; cb_idx < n_cb; ++cb_idx) {
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id<MTLCommandBuffer> cmd_buf = [ctx->queue commandBufferWithUnretainedReferences];
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id<MTLCommandBuffer> cmd_buf = [queue commandBufferWithUnretainedReferences];
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[cmd_buf retain];
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if (ctx->cmd_bufs[cb_idx].obj) {
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@ -589,9 +597,11 @@ void ggml_metal_set_abort_callback(ggml_metal_t ctx, ggml_abort_callback abort_c
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}
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bool ggml_metal_supports_family(ggml_metal_t ctx, int family) {
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GGML_ASSERT(ctx->device != nil);
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GGML_ASSERT(ctx->dev != nil);
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return [ctx->device supportsFamily:(MTLGPUFamilyApple1 + family - 1)];
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id<MTLDevice> device = ggml_metal_device_get_obj(ctx->dev);
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return [device supportsFamily:(MTLGPUFamilyApple1 + family - 1)];
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}
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void ggml_metal_capture_next_compute(ggml_metal_t ctx) {
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@ -186,6 +186,16 @@ struct ggml_metal_pipeline_with_params ggml_metal_library_get_pipeline_flash_att
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int32_t dv,
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int32_t nwg);
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// MTLResidencySet wrapper
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typedef void * ggml_metal_rset_t;
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// a collection of residency sets (non-owning)
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typedef struct ggml_metal_rsets * ggml_metal_rsets_t;
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ggml_metal_rsets_t ggml_metal_rsets_init(void);
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void ggml_metal_rsets_free(ggml_metal_rsets_t rsets);
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//
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// device
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//
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@ -219,6 +229,11 @@ void * ggml_metal_device_get_queue(ggml_metal_device_t dev); // id<MTLCommandQue
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ggml_metal_library_t ggml_metal_device_get_library(ggml_metal_device_t dev);
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void ggml_metal_device_rsets_add(ggml_metal_device_t dev, ggml_metal_rset_t rset);
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void ggml_metal_device_rsets_rm (ggml_metal_device_t dev, ggml_metal_rset_t rset);
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void ggml_metal_device_rsets_keep_alive(ggml_metal_device_t dev);
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void ggml_metal_device_get_memory(ggml_metal_device_t dev, size_t * free, size_t * total);
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bool ggml_metal_device_supports_op(ggml_metal_device_t dev, const struct ggml_tensor * op);
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@ -1,7 +1,6 @@
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#import "ggml-metal-device.h"
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#import "ggml-impl.h"
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#import "ggml-threading.h"
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#include <Foundation/Foundation.h>
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@ -519,11 +518,101 @@ struct ggml_metal_device {
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// ref: https://github.com/ggml-org/llama.cpp/pull/15906
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id<MTLCommandQueue> mtl_queue;
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ggml_metal_rsets_t rsets;
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ggml_metal_library_t library;
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struct ggml_metal_device_props props;
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};
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//
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// MTLResidenceSet wrapper
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//
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struct ggml_metal_rsets {
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NSLock * lock;
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NSMutableArray * data;
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// number of seconds since the last graph computation
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// keep the residency sets wired for that amount of time to avoid being collected by the OS
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int keep_alive_s;
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// background heartbeat thread to keep the residency sets alive
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atomic_bool d_stop;
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atomic_int d_loop;
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dispatch_group_t d_group;
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};
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ggml_metal_rsets_t ggml_metal_rsets_init(void) {
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ggml_metal_rsets_t res = calloc(1, sizeof(struct ggml_metal_rsets));
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res->lock = [[NSLock alloc] init];
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res->data = [[NSMutableArray alloc] init];
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// by default keep the memory wired for 3 minutes
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res->keep_alive_s = 3*60;
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const char * GGML_METAL_RESIDENCY_KEEP_ALIVE_S = getenv("GGML_METAL_RESIDENCY_KEEP_ALIVE_S");
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if (GGML_METAL_RESIDENCY_KEEP_ALIVE_S) {
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res->keep_alive_s = atoi(GGML_METAL_RESIDENCY_KEEP_ALIVE_S);
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}
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if (res->keep_alive_s <= 0) {
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res->keep_alive_s = 3*60;
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}
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GGML_LOG_INFO("%s: creating a residency set collection (keep_alive = %d s)\n", __func__, res->keep_alive_s);
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atomic_store_explicit(&res->d_stop, false, memory_order_relaxed);
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atomic_store_explicit(&res->d_loop, 2*res->keep_alive_s, memory_order_relaxed);
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res->d_group = dispatch_group_create();
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// start a background thread that periodically requests residency for all the currently active sets in the collection
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// the requests stop after a certain amount of time (keep_alive_s) of inactivity
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dispatch_queue_t d_queue = dispatch_get_global_queue(QOS_CLASS_DEFAULT, 0);
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dispatch_group_async(res->d_group, d_queue, ^{
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while (!atomic_load_explicit(&res->d_stop, memory_order_relaxed)) {
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if (atomic_load_explicit(&res->d_loop, memory_order_relaxed) > 0) {
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[res->lock lock];
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for (int i = 0; i < (int) res->data.count; ++i) {
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[res->data[i] requestResidency];
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}
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atomic_fetch_sub_explicit(&res->d_loop, 1, memory_order_relaxed);
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[res->lock unlock];
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}
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// half a second
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usleep(500 * 1000);
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}
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});
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return res;
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}
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void ggml_metal_rsets_free(ggml_metal_rsets_t rsets) {
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if (rsets == NULL) {
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return;
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}
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GGML_ASSERT([rsets->data count] == 0);
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atomic_store_explicit(&rsets->d_stop, true, memory_order_relaxed);
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dispatch_group_wait(rsets->d_group, DISPATCH_TIME_FOREVER);
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dispatch_release(rsets->d_group);
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[rsets->data release];
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[rsets->lock release];
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free(rsets);
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}
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ggml_metal_device_t ggml_metal_device_init(void) {
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ggml_metal_device_t dev = calloc(1, sizeof(struct ggml_metal_device));
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@ -692,6 +781,13 @@ ggml_metal_device_t ggml_metal_device_init(void) {
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GGML_LOG_ERROR("%s: error: failed to create library\n", __func__);
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}
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if (dev->props.use_residency_sets) {
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dev->rsets = ggml_metal_rsets_init();
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} else {
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dev->rsets = nil;
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||||
}
|
||||
|
||||
|
||||
// --------------------------------------------------
|
||||
|
||||
// print MTL GPU family:
|
||||
|
|
@ -745,6 +841,8 @@ ggml_metal_device_t ggml_metal_device_init(void) {
|
|||
void ggml_metal_device_free(ggml_metal_device_t dev) {
|
||||
assert(dev != NULL);
|
||||
|
||||
ggml_metal_rsets_free(dev->rsets);
|
||||
|
||||
ggml_metal_library_free(dev->library);
|
||||
dev->library = NULL;
|
||||
|
||||
|
|
@ -773,6 +871,42 @@ ggml_metal_library_t ggml_metal_device_get_library(ggml_metal_device_t dev) {
|
|||
return dev->library;
|
||||
}
|
||||
|
||||
void ggml_metal_device_rsets_add(ggml_metal_device_t dev, ggml_metal_rset_t rset) {
|
||||
if (rset == nil) {
|
||||
return;
|
||||
}
|
||||
|
||||
GGML_ASSERT(dev->rsets);
|
||||
|
||||
[dev->rsets->lock lock];
|
||||
|
||||
[dev->rsets->data addObject:rset];
|
||||
|
||||
[dev->rsets->lock unlock];
|
||||
}
|
||||
|
||||
void ggml_metal_device_rsets_rm(ggml_metal_device_t dev, ggml_metal_rset_t rset) {
|
||||
if (rset == nil) {
|
||||
return;
|
||||
}
|
||||
|
||||
GGML_ASSERT(dev->rsets);
|
||||
|
||||
[dev->rsets->lock lock];
|
||||
|
||||
[dev->rsets->data removeObject:rset];
|
||||
|
||||
[dev->rsets->lock unlock];
|
||||
}
|
||||
|
||||
void ggml_metal_device_rsets_keep_alive(ggml_metal_device_t dev) {
|
||||
if (dev->rsets == NULL) {
|
||||
return;
|
||||
}
|
||||
|
||||
atomic_store_explicit(&dev->rsets->d_loop, 2*dev->rsets->keep_alive_s, memory_order_relaxed);
|
||||
}
|
||||
|
||||
void ggml_metal_device_get_memory(ggml_metal_device_t dev, size_t * free, size_t * total) {
|
||||
if (@available(macOS 10.12, iOS 16.0, *)) {
|
||||
*total = dev->mtl_device.recommendedMaxWorkingSetSize;
|
||||
|
|
@ -1066,9 +1200,8 @@ struct ggml_metal_buffer {
|
|||
// note: cannot use explicity "id<MTLResidencySet>" here because it is not available on certain OSes
|
||||
id rset;
|
||||
|
||||
// pointers to global device objects
|
||||
id<MTLDevice> device;
|
||||
id<MTLCommandQueue> queue;
|
||||
// pointers to global device
|
||||
ggml_metal_device_t dev;
|
||||
};
|
||||
|
||||
static void ggml_metal_log_allocated_size(id<MTLDevice> device, size_t size_aligned) {
|
||||
|
|
@ -1111,7 +1244,7 @@ static bool ggml_metal_buffer_rset_init(ggml_metal_buffer_t buf) {
|
|||
desc.initialCapacity = buf->n_buffers;
|
||||
|
||||
NSError * error;
|
||||
buf->rset = [buf->device newResidencySetWithDescriptor:desc error:&error];
|
||||
buf->rset = [buf->dev->mtl_device newResidencySetWithDescriptor:desc error:&error];
|
||||
if (error) {
|
||||
GGML_LOG_ERROR("%s: error: %s\n", __func__, [[error description] UTF8String]);
|
||||
[desc release];
|
||||
|
|
@ -1172,6 +1305,8 @@ static void * ggml_metal_host_malloc(size_t n) {
|
|||
ggml_metal_buffer_t ggml_metal_buffer_init(ggml_metal_device_t dev, size_t size, bool shared) {
|
||||
ggml_metal_buffer_t res = calloc(1, sizeof(struct ggml_metal_buffer));
|
||||
|
||||
res->dev = dev;
|
||||
|
||||
const size_t size_page = sysconf(_SC_PAGESIZE);
|
||||
|
||||
size_t size_aligned = size;
|
||||
|
|
@ -1196,9 +1331,6 @@ ggml_metal_buffer_t ggml_metal_buffer_init(ggml_metal_device_t dev, size_t size,
|
|||
|
||||
res->owned = true;
|
||||
|
||||
res->device = ggml_metal_device_get_obj(dev);
|
||||
res->queue = ggml_metal_device_get_queue(dev);
|
||||
|
||||
res->n_buffers = 1;
|
||||
|
||||
if (res->all_data != NULL) {
|
||||
|
|
@ -1207,12 +1339,12 @@ ggml_metal_buffer_t ggml_metal_buffer_init(ggml_metal_device_t dev, size_t size,
|
|||
|
||||
if (size_aligned > 0) {
|
||||
if (props_dev->use_shared_buffers && shared) {
|
||||
res->buffers[0].metal = [res->device newBufferWithBytesNoCopy:res->all_data
|
||||
res->buffers[0].metal = [res->dev->mtl_device newBufferWithBytesNoCopy:res->all_data
|
||||
length:size_aligned
|
||||
options:MTLResourceStorageModeShared
|
||||
deallocator:nil];
|
||||
} else {
|
||||
res->buffers[0].metal = [res->device newBufferWithLength:size_aligned options:MTLResourceStorageModePrivate];
|
||||
res->buffers[0].metal = [res->dev->mtl_device newBufferWithLength:size_aligned options:MTLResourceStorageModePrivate];
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -1233,6 +1365,8 @@ ggml_metal_buffer_t ggml_metal_buffer_init(ggml_metal_device_t dev, size_t size,
|
|||
return NULL;
|
||||
}
|
||||
|
||||
ggml_metal_device_rsets_add(dev, res->rset);
|
||||
|
||||
//ggml_metal_log_allocated_size(device, size_aligned);
|
||||
|
||||
return res;
|
||||
|
|
@ -1241,6 +1375,8 @@ ggml_metal_buffer_t ggml_metal_buffer_init(ggml_metal_device_t dev, size_t size,
|
|||
ggml_metal_buffer_t ggml_metal_buffer_map(ggml_metal_device_t dev, void * ptr, size_t size, size_t max_tensor_size) {
|
||||
ggml_metal_buffer_t res = calloc(1, sizeof(struct ggml_metal_buffer));
|
||||
|
||||
res->dev = dev;
|
||||
|
||||
res->all_data = ptr;
|
||||
res->all_size = size;
|
||||
|
||||
|
|
@ -1263,9 +1399,6 @@ ggml_metal_buffer_t ggml_metal_buffer_map(ggml_metal_device_t dev, void * ptr, s
|
|||
size_aligned += (size_page - (size_aligned % size_page));
|
||||
}
|
||||
|
||||
res->device = ggml_metal_device_get_obj(dev);
|
||||
res->queue = ggml_metal_device_get_queue(dev);
|
||||
|
||||
const struct ggml_metal_device_props * props_dev = ggml_metal_device_get_props(dev);
|
||||
|
||||
// the buffer fits into the max buffer size allowed by the device
|
||||
|
|
@ -1275,7 +1408,7 @@ ggml_metal_buffer_t ggml_metal_buffer_map(ggml_metal_device_t dev, void * ptr, s
|
|||
res->buffers[res->n_buffers].metal = nil;
|
||||
|
||||
if (size_aligned > 0) {
|
||||
res->buffers[res->n_buffers].metal = [res->device newBufferWithBytesNoCopy:ptr length:size_aligned options:MTLResourceStorageModeShared deallocator:nil];
|
||||
res->buffers[res->n_buffers].metal = [res->dev->mtl_device newBufferWithBytesNoCopy:ptr length:size_aligned options:MTLResourceStorageModeShared deallocator:nil];
|
||||
|
||||
if (res->buffers[res->n_buffers].metal == nil) {
|
||||
GGML_LOG_ERROR("%s: error: failed to allocate buffer, size = %8.2f MiB\n", __func__, size_aligned / 1024.0 / 1024.0);
|
||||
|
|
@ -1284,7 +1417,7 @@ ggml_metal_buffer_t ggml_metal_buffer_map(ggml_metal_device_t dev, void * ptr, s
|
|||
}
|
||||
}
|
||||
|
||||
ggml_metal_log_allocated_size(res->device, size_aligned);
|
||||
ggml_metal_log_allocated_size(res->dev->mtl_device, size_aligned);
|
||||
|
||||
++res->n_buffers;
|
||||
} else {
|
||||
|
|
@ -1302,7 +1435,7 @@ ggml_metal_buffer_t ggml_metal_buffer_map(ggml_metal_device_t dev, void * ptr, s
|
|||
res->buffers[res->n_buffers].metal = nil;
|
||||
|
||||
if (size_step_aligned > 0) {
|
||||
res->buffers[res->n_buffers].metal = [res->device newBufferWithBytesNoCopy:(void *) ((uint8_t *) ptr + i) length:size_step_aligned options:MTLResourceStorageModeShared deallocator:nil];
|
||||
res->buffers[res->n_buffers].metal = [res->dev->mtl_device newBufferWithBytesNoCopy:(void *) ((uint8_t *) ptr + i) length:size_step_aligned options:MTLResourceStorageModeShared deallocator:nil];
|
||||
|
||||
if (res->buffers[res->n_buffers].metal == nil) {
|
||||
GGML_LOG_ERROR("%s: error: failed to allocate buffer, size = %8.2f MiB\n", __func__, size_step_aligned / 1024.0 / 1024.0);
|
||||
|
|
@ -1311,7 +1444,7 @@ ggml_metal_buffer_t ggml_metal_buffer_map(ggml_metal_device_t dev, void * ptr, s
|
|||
}
|
||||
}
|
||||
|
||||
ggml_metal_log_allocated_size(res->device, size_step_aligned);
|
||||
ggml_metal_log_allocated_size(res->dev->mtl_device, size_step_aligned);
|
||||
|
||||
if (i + size_step < size) {
|
||||
GGML_LOG_INFO("\n");
|
||||
|
|
@ -1329,10 +1462,14 @@ ggml_metal_buffer_t ggml_metal_buffer_map(ggml_metal_device_t dev, void * ptr, s
|
|||
return NULL;
|
||||
}
|
||||
|
||||
ggml_metal_device_rsets_add(dev, res->rset);
|
||||
|
||||
return res;
|
||||
}
|
||||
|
||||
void ggml_metal_buffer_free(ggml_metal_buffer_t buf) {
|
||||
ggml_metal_device_rsets_rm(buf->dev, buf->rset);
|
||||
|
||||
for (int i = 0; i < buf->n_buffers; i++) {
|
||||
[buf->buffers[i].metal release];
|
||||
}
|
||||
|
|
@ -1369,8 +1506,7 @@ void ggml_metal_buffer_memset_tensor(ggml_metal_buffer_t buf, struct ggml_tensor
|
|||
struct ggml_metal_buffer_id bid_dst = ggml_metal_buffer_get_id(buf, tensor);
|
||||
bid_dst.offs += offset;
|
||||
|
||||
id<MTLCommandQueue> queue = buf->queue;
|
||||
id<MTLCommandBuffer> cmd_buf = [queue commandBufferWithUnretainedReferences];
|
||||
id<MTLCommandBuffer> cmd_buf = [buf->dev->mtl_queue commandBufferWithUnretainedReferences];
|
||||
|
||||
{
|
||||
id<MTLBlitCommandEncoder> encoder = [cmd_buf blitCommandEncoder];
|
||||
|
|
@ -1396,7 +1532,7 @@ void ggml_metal_buffer_set_tensor(ggml_metal_buffer_t buf, struct ggml_tensor *
|
|||
@autoreleasepool {
|
||||
// src
|
||||
void * data_ptr = (void *)(uintptr_t) data; // "const cast" the src data
|
||||
id<MTLBuffer> buf_src = [buf->device newBufferWithBytesNoCopy:data_ptr
|
||||
id<MTLBuffer> buf_src = [buf->dev->mtl_device newBufferWithBytesNoCopy:data_ptr
|
||||
length:size
|
||||
options:MTLResourceStorageModeShared
|
||||
deallocator:nil];
|
||||
|
|
@ -1411,8 +1547,7 @@ void ggml_metal_buffer_set_tensor(ggml_metal_buffer_t buf, struct ggml_tensor *
|
|||
// this is alternative to waitUntilCompleted, which should be faster, but don't seem to make much difference
|
||||
dispatch_semaphore_t completion_semaphore = dispatch_semaphore_create(0);
|
||||
|
||||
id<MTLCommandQueue> queue = buf->queue;
|
||||
id<MTLCommandBuffer> cmd_buf = [queue commandBufferWithUnretainedReferences];
|
||||
id<MTLCommandBuffer> cmd_buf = [buf->dev->mtl_queue commandBufferWithUnretainedReferences];
|
||||
|
||||
{
|
||||
id<MTLBlitCommandEncoder> encoder = [cmd_buf blitCommandEncoder];
|
||||
|
|
@ -1454,15 +1589,14 @@ void ggml_metal_buffer_get_tensor(ggml_metal_buffer_t buf, const struct ggml_ten
|
|||
bid_src.offs += offset;
|
||||
|
||||
// dst
|
||||
id<MTLBuffer> buf_dst = [buf->device newBufferWithBytesNoCopy:data
|
||||
id<MTLBuffer> buf_dst = [buf->dev->mtl_device newBufferWithBytesNoCopy:data
|
||||
length:size
|
||||
options:MTLResourceStorageModeShared
|
||||
deallocator:nil];
|
||||
|
||||
GGML_ASSERT(buf_dst);
|
||||
|
||||
id<MTLCommandQueue> queue = buf->queue;
|
||||
id<MTLCommandBuffer> cmd_buf = [queue commandBufferWithUnretainedReferences];
|
||||
id<MTLCommandBuffer> cmd_buf = [buf->dev->mtl_queue commandBufferWithUnretainedReferences];
|
||||
|
||||
{
|
||||
id<MTLBlitCommandEncoder> encoder = [cmd_buf blitCommandEncoder];
|
||||
|
|
@ -1488,8 +1622,7 @@ void ggml_metal_buffer_clear(ggml_metal_buffer_t buf, uint8_t value) {
|
|||
}
|
||||
|
||||
@autoreleasepool {
|
||||
id<MTLCommandQueue> queue = buf->queue;
|
||||
id<MTLCommandBuffer> cmd_buf = [queue commandBufferWithUnretainedReferences];
|
||||
id<MTLCommandBuffer> cmd_buf = [buf->dev->mtl_queue commandBufferWithUnretainedReferences];
|
||||
|
||||
{
|
||||
id<MTLBlitCommandEncoder> encoder = [cmd_buf blitCommandEncoder];
|
||||
|
|
|
|||
Loading…
Reference in New Issue