mirror of https://github.com/ggerganov/llama.cpp
44 lines
1.4 KiB
C
44 lines
1.4 KiB
C
#pragma once
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#include "ggml.h"
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#include "ggml-backend.h"
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#ifdef GGML_USE_HIPBLAS
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#define GGML_CUDA_NAME "ROCm"
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#define GGML_CUBLAS_NAME "hipBLAS"
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#else
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#define GGML_CUDA_NAME "CUDA"
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#define GGML_CUBLAS_NAME "cuBLAS"
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#endif
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#ifdef __cplusplus
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extern "C" {
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#endif
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#define GGML_CUDA_MAX_DEVICES 16
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// backend API
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GGML_API GGML_CALL ggml_backend_t ggml_backend_cuda_init(int device);
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GGML_API GGML_CALL bool ggml_backend_is_cuda(ggml_backend_t backend);
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// device buffer
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GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_buffer_type(int device);
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// split tensor buffer that splits matrices by rows across multiple devices
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GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_split_buffer_type(const float * tensor_split);
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// pinned host buffer for use with the CPU backend for faster copies between CPU and GPU
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GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_host_buffer_type(void);
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GGML_API GGML_CALL int ggml_backend_cuda_get_device_count(void);
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GGML_API GGML_CALL void ggml_backend_cuda_get_device_description(int device, char * description, size_t description_size);
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GGML_API GGML_CALL void ggml_backend_cuda_get_device_memory(int device, size_t * free, size_t * total);
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GGML_API GGML_CALL bool ggml_backend_cuda_register_host_buffer(void * buffer, size_t size);
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GGML_API GGML_CALL void ggml_backend_cuda_unregister_host_buffer(void * buffer);
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#ifdef __cplusplus
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}
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#endif
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