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https://github.com/ggerganov/llama.cpp.git
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17366df842
* CUDA multi GPU + scratch ggml_cuda_compute_forward Tensor parallelism ggml_cuda_add ggml_cuda_rms_norm ggml_cuda_silu CUDA scratch buffer --main-gpu CLI option
37 lines
1.4 KiB
C
37 lines
1.4 KiB
C
#pragma once
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#include "ggml.h"
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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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struct ggml_tensor_extra_gpu {
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void * data_device[GGML_CUDA_MAX_DEVICES]; // 1 pointer for each device for split tensors
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};
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void ggml_init_cublas(void);
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void ggml_cuda_set_tensor_split(const float * tensor_split);
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void ggml_cuda_mul(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst);
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bool ggml_cuda_can_mul_mat(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst);
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size_t ggml_cuda_mul_mat_get_wsize(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst);
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void ggml_cuda_mul_mat(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst, void * wdata, size_t wsize);
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// TODO: export these with GGML_API
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void * ggml_cuda_host_malloc(size_t size);
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void ggml_cuda_host_free(void * ptr);
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void ggml_cuda_load_data(const char * fname, struct ggml_tensor * tensors, size_t offset);
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void ggml_cuda_free_data(struct ggml_tensor * tensor);
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void ggml_cuda_assign_buffers(struct ggml_tensor * tensor);
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void ggml_cuda_set_main_device(int main_device);
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void ggml_cuda_set_scratch_size(size_t scratch_size);
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bool ggml_cuda_compute_forward(struct ggml_compute_params * params, struct ggml_tensor * tensor);
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#ifdef __cplusplus
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}
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#endif
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