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| // 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. | |
| // | |
| // max memory buffers that can be mapped to the device | |
| struct ggml_tensor; | |
| struct ggml_cgraph; | |
| extern "C" { | |
| 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); | |
| } | |