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| extern "C" { | |
| // Always success. To check if CUDA is actually loaded, use `ggml_cublas_loaded`. | |
| GGML_API GGML_CALL void ggml_init_cublas(void); | |
| // Returns `true` if there are available CUDA devices and cublas loads successfully; otherwise, it returns `false`. | |
| GGML_API GGML_CALL bool ggml_cublas_loaded(void); | |
| GGML_API GGML_CALL void * ggml_cuda_host_malloc(size_t size); | |
| GGML_API GGML_CALL void ggml_cuda_host_free(void * ptr); | |
| GGML_API GGML_CALL bool ggml_cuda_can_mul_mat(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst); | |
| GGML_API GGML_CALL bool ggml_cuda_compute_forward(struct ggml_compute_params * params, struct ggml_tensor * tensor); | |
| GGML_API GGML_CALL int ggml_cuda_get_device_count(void); | |
| GGML_API GGML_CALL void ggml_cuda_get_device_description(int device, char * description, size_t description_size); | |
| // backend API | |
| GGML_API GGML_CALL ggml_backend_t ggml_backend_cuda_init(int device); | |
| GGML_API GGML_CALL bool ggml_backend_is_cuda(ggml_backend_t backend); | |
| GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_buffer_type(int device); | |
| // split tensor buffer that splits matrices by rows across multiple devices | |
| GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_split_buffer_type(const float * tensor_split); | |
| // pinned host buffer for use with the CPU backend for faster copies between CPU and GPU | |
| GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_host_buffer_type(void); | |
| GGML_API GGML_CALL int ggml_backend_cuda_get_device_count(void); | |
| GGML_API GGML_CALL void ggml_backend_cuda_get_device_description(int device, char * description, size_t description_size); | |
| GGML_API GGML_CALL void ggml_backend_cuda_get_device_memory(int device, size_t * free, size_t * total); | |
| } | |