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https://github.com/ikawrakow/ik_llama.cpp.git
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154e0d75fc
* Merging mainline - WIP * Merging mainline - WIP AVX2 and CUDA appear to work. CUDA performance seems slightly (~1-2%) lower as it is so often the case with llama.cpp/ggml after some "improvements" have been made. * Merging mainline - fix Metal * Remove check --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
30 lines
946 B
C
30 lines
946 B
C
#pragma once
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#include "ggml.h"
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#include "ggml-backend.h"
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#ifdef __cplusplus
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extern "C" {
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#endif
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#define GGML_VK_NAME "Vulkan"
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#define GGML_VK_MAX_DEVICES 16
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GGML_API void ggml_vk_instance_init(void);
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// backend API
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GGML_API GGML_CALL ggml_backend_t ggml_backend_vk_init(size_t dev_num);
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GGML_API GGML_CALL bool ggml_backend_is_vk(ggml_backend_t backend);
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GGML_API GGML_CALL int ggml_backend_vk_get_device_count(void);
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GGML_API GGML_CALL void ggml_backend_vk_get_device_description(int device, char * description, size_t description_size);
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GGML_API GGML_CALL void ggml_backend_vk_get_device_memory(int device, size_t * free, size_t * total);
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GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_vk_buffer_type(size_t dev_num);
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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_vk_host_buffer_type(void);
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#ifdef __cplusplus
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}
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#endif
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