mirror of
				https://github.com/ggml-org/llama.cpp.git
				synced 2025-10-28 08:31:25 +00:00 
			
		
		
		
	 d232aca5a7
			
		
	
	d232aca5a7
	
	
	
		
			
			* llama : initial ggml-backend integration * add ggml-metal * cuda backend can be used though ggml-backend with LLAMA_GGML_BACKEND_CUDA_TEST access all tensor data with ggml_backend_tensor_get/set * add ggml_backend_buffer_clear zero-init KV cache buffer * add ggml_backend_buffer_is_hos, used to avoid copies if possible when accesing tensor data * disable gpu backends with ngl 0 * more accurate mlock * unmap offloaded part of the model * use posix_fadvise64(.., POSIX_FADV_SEQUENTIAL) to improve performance with mmap * update quantize and lora * update session copy/set to use ggml-backend ggml-ci * use posix_fadvise instead of posix_fadvise64 * ggml_backend_alloc_ctx_tensors_from_buft : remove old print * llama_mmap::align_offset : use pointers instead of references for out parameters * restore progress_callback behavior * move final progress_callback call to load_all_data * cuda : fix fprintf format string (minor) * do not offload scales * llama_mmap : avoid unmapping the same fragments again in the destructor * remove unnecessary unmap * metal : add default log function that prints to stderr, cleanup code ggml-ci --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
		
			
				
	
	
		
			116 lines
		
	
	
		
			4.2 KiB
		
	
	
	
		
			C
		
	
	
	
	
	
			
		
		
	
	
			116 lines
		
	
	
		
			4.2 KiB
		
	
	
	
		
			C
		
	
	
	
	
	
| // An interface allowing to compute ggml_cgraph with Metal
 | |
| //
 | |
| // This is a fully functional interface that extends ggml with GPU support for Apple devices.
 | |
| // A similar interface can be created for other GPU backends (e.g. Vulkan, CUDA, OpenCL, etc.)
 | |
| //
 | |
| // How it works?
 | |
| //
 | |
| // As long as your program can create and evaluate a ggml_cgraph on the CPU, you can use this
 | |
| // interface to evaluate the same graph on the GPU. Instead of using ggml_graph_compute(), you
 | |
| // use ggml_metal_graph_compute() (or ggml_vulkan_graph_compute(), etc.)
 | |
| //
 | |
| // You only need to make sure that all memory buffers that you used during the graph creation
 | |
| // are mapped to the device memory with the ggml_metal_add_buffer() function. This mapping is
 | |
| // used during the graph evaluation to determine the arguments of the compute kernels.
 | |
| //
 | |
| // Synchronization between device and host memory (for example for input and output tensors)
 | |
| // is done with the ggml_metal_set_tensor() and ggml_metal_get_tensor() functions.
 | |
| //
 | |
| 
 | |
| #pragma once
 | |
| 
 | |
| #include "ggml.h"
 | |
| #include "ggml-backend.h"
 | |
| 
 | |
| #include <stddef.h>
 | |
| #include <stdbool.h>
 | |
| 
 | |
| // max memory buffers that can be mapped to the device
 | |
| #define GGML_METAL_MAX_BUFFERS 64
 | |
| #define GGML_METAL_MAX_COMMAND_BUFFERS 32
 | |
| 
 | |
| struct ggml_tensor;
 | |
| struct ggml_cgraph;
 | |
| 
 | |
| #ifdef __cplusplus
 | |
| extern "C" {
 | |
| #endif
 | |
| 
 | |
| //
 | |
| // internal API
 | |
| // temporary exposed to user-code
 | |
| //
 | |
| 
 | |
| struct ggml_metal_context;
 | |
| 
 | |
| void ggml_metal_log_set_callback(ggml_log_callback log_callback, void * user_data);
 | |
| 
 | |
| // number of command buffers to use
 | |
| struct ggml_metal_context * ggml_metal_init(int n_cb);
 | |
| void ggml_metal_free(struct ggml_metal_context * ctx);
 | |
| 
 | |
| void * ggml_metal_host_malloc(size_t n);
 | |
| void   ggml_metal_host_free  (void * data);
 | |
| 
 | |
| // set the number of command buffers to use
 | |
| void ggml_metal_set_n_cb(struct ggml_metal_context * ctx, int n_cb);
 | |
| 
 | |
| // creates a mapping between a host memory buffer and a device memory buffer
 | |
| // - make sure to map all buffers used in the graph before calling ggml_metal_graph_compute
 | |
| // - the mapping is used during computation to determine the arguments of the compute kernels
 | |
| // - you don't need to keep the host memory buffer allocated as it is never accessed by Metal
 | |
| // - max_size specifies the maximum size of a tensor and is used to create shared views such
 | |
| //   that it is guaranteed that the tensor will fit in at least one of the views
 | |
| //
 | |
| bool ggml_metal_add_buffer(
 | |
|         struct ggml_metal_context * ctx,
 | |
|                        const char * name,
 | |
|                              void * data,
 | |
|                            size_t   size,
 | |
|                            size_t   max_size);
 | |
| 
 | |
| // set data from host memory into the device
 | |
| void ggml_metal_set_tensor(struct ggml_metal_context * ctx, struct ggml_tensor * t);
 | |
| 
 | |
| // get data from the device into host memory
 | |
| void ggml_metal_get_tensor(struct ggml_metal_context * ctx, struct ggml_tensor * t);
 | |
| 
 | |
| // try to find operations that can be run concurrently in the graph
 | |
| // you should run it again if the topology of your graph changes
 | |
| void ggml_metal_graph_find_concurrency(struct ggml_metal_context * ctx, struct ggml_cgraph * gf, bool check_mem);
 | |
| 
 | |
| // if the graph has been optimized for concurrently dispatch, return length of the concur_list if optimized
 | |
| int ggml_metal_if_optimized(struct ggml_metal_context * ctx);
 | |
| 
 | |
| // output the concur_list for ggml_alloc
 | |
| int * ggml_metal_get_concur_list(struct ggml_metal_context * ctx);
 | |
| 
 | |
| // same as ggml_graph_compute but uses Metal
 | |
| // creates gf->n_threads command buffers in parallel
 | |
| void ggml_metal_graph_compute(struct ggml_metal_context * ctx, struct ggml_cgraph * gf);
 | |
| 
 | |
| //
 | |
| // backend API
 | |
| // user-code should use only these functions
 | |
| //
 | |
| 
 | |
| GGML_API ggml_backend_t ggml_backend_metal_init(void);
 | |
| 
 | |
| GGML_API bool ggml_backend_is_metal(ggml_backend_t backend);
 | |
| 
 | |
| GGML_API ggml_backend_buffer_t ggml_backend_metal_buffer_from_ptr(void * data, size_t size, size_t max_size);
 | |
| 
 | |
| GGML_API void ggml_backend_metal_set_n_cb(ggml_backend_t backend, int n_cb);
 | |
| 
 | |
| GGML_API ggml_backend_buffer_type_t ggml_backend_metal_buffer_type(void);
 | |
| 
 | |
| // helper to check if the device supports a specific family
 | |
| // ideally, the user code should be doing these checks
 | |
| // ref: https://developer.apple.com/metal/Metal-Feature-Set-Tables.pdf
 | |
| GGML_API bool ggml_backend_metal_supports_family(ggml_backend_t backend, int family);
 | |
| 
 | |
| #ifdef __cplusplus
 | |
| }
 | |
| #endif
 | |
| 
 |