llama.cpp/ggml-metal.h

72 lines
2.8 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 <stddef.h>
#include <stdbool.h>
//struct ggml_tensor;
//struct ggml_cgraph;
#ifdef __cplusplus
extern "C" {
#endif
struct ggml_backend;
struct ggml_backend * ggml_backend_metal_init(void);
//struct ggml_metal_context;
//
//// 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);
//
//// 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);
//
//// 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);
#ifdef __cplusplus
}
#endif