72 lines
2.8 KiB
C
72 lines
2.8 KiB
C
// An interface allowing to compute ggml_cgraph with Metal
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//
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// This is a fully functional interface that extends ggml with GPU support for Apple devices.
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// A similar interface can be created for other GPU backends (e.g. Vulkan, CUDA, OpenCL, etc.)
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//
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// How it works?
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//
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// As long as your program can create and evaluate a ggml_cgraph on the CPU, you can use this
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// interface to evaluate the same graph on the GPU. Instead of using ggml_graph_compute(), you
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// use ggml_metal_graph_compute() (or ggml_vulkan_graph_compute(), etc.)
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//
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// You only need to make sure that all memory buffers that you used during the graph creation
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// are mapped to the device memory with the ggml_metal_add_buffer() function. This mapping is
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// used during the graph evaluation to determine the arguments of the compute kernels.
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//
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// Synchronization between device and host memory (for example for input and output tensors)
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// is done with the ggml_metal_set_tensor() and ggml_metal_get_tensor() functions.
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//
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#pragma once
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#include <stddef.h>
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#include <stdbool.h>
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//struct ggml_tensor;
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//struct ggml_cgraph;
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#ifdef __cplusplus
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extern "C" {
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#endif
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struct ggml_backend;
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struct ggml_backend * ggml_backend_metal_init(void);
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//struct ggml_metal_context;
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//
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//// number of command buffers to use
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//struct ggml_metal_context * ggml_metal_init(int n_cb);
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//void ggml_metal_free(struct ggml_metal_context * ctx);
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//
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//// set the number of command buffers to use
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//void ggml_metal_set_n_cb(struct ggml_metal_context * ctx, int n_cb);
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//
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//// creates a mapping between a host memory buffer and a device memory buffer
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//// - make sure to map all buffers used in the graph before calling ggml_metal_graph_compute
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//// - the mapping is used during computation to determine the arguments of the compute kernels
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//// - you don't need to keep the host memory buffer allocated as it is never accessed by Metal
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//// - max_size specifies the maximum size of a tensor and is used to create shared views such
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//// that it is guaranteed that the tensor will fit in at least one of the views
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////
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//bool ggml_metal_add_buffer(
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// struct ggml_metal_context * ctx,
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// const char * name,
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// void * data,
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// size_t size,
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// size_t max_size);
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//
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//// set data from host memory into the device
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//void ggml_metal_set_tensor(struct ggml_metal_context * ctx, struct ggml_tensor * t);
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//
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//// get data from the device into host memory
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//void ggml_metal_get_tensor(struct ggml_metal_context * ctx, struct ggml_tensor * t);
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//
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//// same as ggml_graph_compute but uses Metal
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//// creates gf->n_threads command buffers in parallel
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//void ggml_metal_graph_compute(struct ggml_metal_context * ctx, struct ggml_cgraph * gf);
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#ifdef __cplusplus
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}
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#endif
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