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ggml-backend : add device and backend reg interfaces (llama/9707)

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Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
This commit is contained in:
Diego Devesa 2024-10-03 01:49:47 +02:00 committed by Georgi Gerganov
parent ea642144d2
commit 1acfadb721
21 changed files with 3470 additions and 753 deletions
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203
ggml/include/ggml-backend.h
View File

@ -12,43 +12,52 @@ extern "C" {
typedef struct ggml_backend_event * ggml_backend_event_t;
typedef struct ggml_backend * ggml_backend_t;
typedef void * ggml_backend_graph_plan_t;
typedef struct ggml_backend_reg * ggml_backend_reg_t;
typedef struct ggml_backend_device * ggml_backend_dev_t;
//
// Backend buffer type
//
GGML_API const char * ggml_backend_buft_name (ggml_backend_buffer_type_t buft);
GGML_API ggml_backend_buffer_t ggml_backend_buft_alloc_buffer (ggml_backend_buffer_type_t buft, size_t size);
GGML_API size_t ggml_backend_buft_get_alignment (ggml_backend_buffer_type_t buft);
GGML_API size_t ggml_backend_buft_get_max_size (ggml_backend_buffer_type_t buft);
GGML_API size_t ggml_backend_buft_get_alloc_size(ggml_backend_buffer_type_t buft, struct ggml_tensor * tensor);
GGML_API bool ggml_backend_buft_is_host (ggml_backend_buffer_type_t buft);
GGML_API ggml_backend_dev_t ggml_backend_buft_get_device (ggml_backend_buffer_type_t buft);
//
// Backend buffer
//
// buffer type
GGML_API const char * ggml_backend_buft_name (ggml_backend_buffer_type_t buft);
GGML_API GGML_CALL ggml_backend_buffer_t ggml_backend_buft_alloc_buffer (ggml_backend_buffer_type_t buft, size_t size);
GGML_API size_t ggml_backend_buft_get_alignment (ggml_backend_buffer_type_t buft);
GGML_API size_t ggml_backend_buft_get_max_size (ggml_backend_buffer_type_t buft);
GGML_API GGML_CALL size_t ggml_backend_buft_get_alloc_size (ggml_backend_buffer_type_t buft, struct ggml_tensor * tensor);
GGML_API bool ggml_backend_buft_is_host (ggml_backend_buffer_type_t buft);
// buffer
enum ggml_backend_buffer_usage {
GGML_BACKEND_BUFFER_USAGE_ANY = 0,
GGML_BACKEND_BUFFER_USAGE_WEIGHTS = 1,
GGML_BACKEND_BUFFER_USAGE_COMPUTE = 2,
};
GGML_API const char * ggml_backend_buffer_name (ggml_backend_buffer_t buffer);
GGML_API void ggml_backend_buffer_free (ggml_backend_buffer_t buffer);
GGML_API void * ggml_backend_buffer_get_base (ggml_backend_buffer_t buffer);
GGML_API size_t ggml_backend_buffer_get_size (ggml_backend_buffer_t buffer);
GGML_API GGML_CALL void ggml_backend_buffer_init_tensor (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor);
GGML_API size_t ggml_backend_buffer_get_alignment (ggml_backend_buffer_t buffer);
GGML_API size_t ggml_backend_buffer_get_max_size (ggml_backend_buffer_t buffer);
GGML_API size_t ggml_backend_buffer_get_alloc_size(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor);
GGML_API void ggml_backend_buffer_clear (ggml_backend_buffer_t buffer, uint8_t value);
GGML_API bool ggml_backend_buffer_is_host (ggml_backend_buffer_t buffer);
GGML_API void ggml_backend_buffer_set_usage (ggml_backend_buffer_t buffer, enum ggml_backend_buffer_usage usage);
GGML_API enum ggml_backend_buffer_usage ggml_backend_buffer_get_usage (ggml_backend_buffer_t buffer);
GGML_API ggml_backend_buffer_type_t ggml_backend_buffer_get_type (ggml_backend_buffer_t buffer);
GGML_API void ggml_backend_buffer_reset (ggml_backend_buffer_t buffer);
GGML_API const char * ggml_backend_buffer_name (ggml_backend_buffer_t buffer);
GGML_API void ggml_backend_buffer_free (ggml_backend_buffer_t buffer);
GGML_API void * ggml_backend_buffer_get_base (ggml_backend_buffer_t buffer);
GGML_API size_t ggml_backend_buffer_get_size (ggml_backend_buffer_t buffer);
GGML_API void ggml_backend_buffer_init_tensor (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor);
GGML_API size_t ggml_backend_buffer_get_alignment (ggml_backend_buffer_t buffer);
GGML_API size_t ggml_backend_buffer_get_max_size (ggml_backend_buffer_t buffer);
GGML_API size_t ggml_backend_buffer_get_alloc_size(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor);
GGML_API void ggml_backend_buffer_clear (ggml_backend_buffer_t buffer, uint8_t value);
GGML_API bool ggml_backend_buffer_is_host (ggml_backend_buffer_t buffer);
GGML_API void ggml_backend_buffer_set_usage (ggml_backend_buffer_t buffer, enum ggml_backend_buffer_usage usage);
GGML_API enum ggml_backend_buffer_usage ggml_backend_buffer_get_usage (ggml_backend_buffer_t buffer);
GGML_API ggml_backend_buffer_type_t ggml_backend_buffer_get_type (ggml_backend_buffer_t buffer);
GGML_API void ggml_backend_buffer_reset (ggml_backend_buffer_t buffer);
// tensor copy between different backends
GGML_API void ggml_backend_tensor_copy(struct ggml_tensor * src, struct ggml_tensor * dst);
//
// Backend
// Backend (stream)
//
GGML_API ggml_guid_t ggml_backend_guid(ggml_backend_t backend);
@ -64,9 +73,9 @@ extern "C" {
GGML_API void ggml_backend_tensor_get_async(ggml_backend_t backend, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
// "offset" refers to the offset of the tensor data for setting/getting data
GGML_API GGML_CALL void ggml_backend_tensor_set( struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
GGML_API GGML_CALL void ggml_backend_tensor_get(const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
GGML_API GGML_CALL void ggml_backend_tensor_memset( struct ggml_tensor * tensor, uint8_t value, size_t offset, size_t size);
GGML_API void ggml_backend_tensor_set( struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
GGML_API void ggml_backend_tensor_get(const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
GGML_API void ggml_backend_tensor_memset( struct ggml_tensor * tensor, uint8_t value, size_t offset, size_t size);
GGML_API void ggml_backend_synchronize(ggml_backend_t backend);
@ -76,65 +85,121 @@ extern "C" {
GGML_API enum ggml_status ggml_backend_graph_plan_compute (ggml_backend_t backend, ggml_backend_graph_plan_t plan);
GGML_API enum ggml_status ggml_backend_graph_compute (ggml_backend_t backend, struct ggml_cgraph * cgraph);
GGML_API enum ggml_status ggml_backend_graph_compute_async(ggml_backend_t backend, struct ggml_cgraph * cgraph);
// NOTE: will be removed, use device version instead
GGML_API bool ggml_backend_supports_op(ggml_backend_t backend, const struct ggml_tensor * op);
GGML_API bool ggml_backend_supports_buft(ggml_backend_t backend, ggml_backend_buffer_type_t buft);
GGML_API bool ggml_backend_offload_op(ggml_backend_t backend, const struct ggml_tensor * op);
// tensor copy between different backends
GGML_API void ggml_backend_tensor_copy(struct ggml_tensor * src, struct ggml_tensor * dst);
// asynchronous copy
// the copy is performed after all the currently queued operations in backend_src
// backend_dst will wait for the copy to complete before performing other operations
// automatic fallback to sync copy if async is not supported
GGML_API void ggml_backend_tensor_copy_async(ggml_backend_t backend_src, ggml_backend_t backend_dst, struct ggml_tensor * src, struct ggml_tensor * dst);
// events
GGML_API ggml_backend_event_t ggml_backend_event_new (ggml_backend_t backend);
GGML_API void ggml_backend_event_free (ggml_backend_event_t event);
GGML_API void ggml_backend_event_record (ggml_backend_event_t event);
GGML_API void ggml_backend_event_synchronize(ggml_backend_event_t event);
GGML_API void ggml_backend_event_wait (ggml_backend_t backend, ggml_backend_event_t event);
GGML_API ggml_backend_dev_t ggml_backend_get_device(ggml_backend_t backend);
//
// CPU backend
// Events
//
GGML_API ggml_backend_t ggml_backend_cpu_init(void);
GGML_API ggml_backend_event_t ggml_backend_event_new(ggml_backend_dev_t device);
GGML_API void ggml_backend_event_free(ggml_backend_event_t event);
GGML_API void ggml_backend_event_record(ggml_backend_event_t event, ggml_backend_t backend);
GGML_API void ggml_backend_event_synchronize(ggml_backend_event_t event);
GGML_API void ggml_backend_event_wait(ggml_backend_t backend, ggml_backend_event_t event);
GGML_API GGML_CALL bool ggml_backend_is_cpu (ggml_backend_t backend);
GGML_API void ggml_backend_cpu_set_n_threads (ggml_backend_t backend_cpu, int n_threads);
GGML_API void ggml_backend_cpu_set_threadpool (ggml_backend_t backend_cpu, ggml_threadpool_t threadpool);
GGML_API void ggml_backend_cpu_set_abort_callback(ggml_backend_t backend_cpu, ggml_abort_callback abort_callback, void * abort_callback_data);
//
// Backend device
//
// Create a backend buffer from an existing pointer
GGML_API GGML_CALL ggml_backend_buffer_t ggml_backend_cpu_buffer_from_ptr(void * ptr, size_t size);
enum ggml_backend_dev_type {
GGML_BACKEND_DEVICE_TYPE_CPU,
GGML_BACKEND_DEVICE_TYPE_GPU,
// devices with full capabilities (excludes backends such as BLAS that only support matrix multiplication)
GGML_BACKEND_DEVICE_TYPE_CPU_FULL,
GGML_BACKEND_DEVICE_TYPE_GPU_FULL
};
GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_cpu_buffer_type(void);
// functionality supported by the device
struct ggml_backend_dev_caps {
// asynchronous operations
bool async;
// pinned host buffer
bool host_buffer;
// event synchronization
bool events;
};
#ifdef GGML_USE_CPU_HBM
GGML_API ggml_backend_buffer_type_t ggml_backend_cpu_hbm_buffer_type(void);
#endif
// all the device properties
struct ggml_backend_dev_props {
const char * name;
const char * description;
size_t memory_free;
size_t memory_total;
enum ggml_backend_dev_type type;
struct ggml_backend_dev_caps caps;
};
GGML_API const char * ggml_backend_dev_name(ggml_backend_dev_t device);
GGML_API const char * ggml_backend_dev_description(ggml_backend_dev_t device);
GGML_API void ggml_backend_dev_memory(ggml_backend_dev_t device, size_t * free, size_t * total);
GGML_API enum ggml_backend_dev_type ggml_backend_dev_type(ggml_backend_dev_t device);
GGML_API void ggml_backend_dev_get_props(ggml_backend_dev_t device, struct ggml_backend_dev_props * props);
GGML_API ggml_backend_reg_t ggml_backend_dev_backend_reg(ggml_backend_dev_t device);
GGML_API ggml_backend_t ggml_backend_dev_init(ggml_backend_dev_t device, const char * params);
GGML_API ggml_backend_buffer_type_t ggml_backend_dev_buffer_type(ggml_backend_dev_t device);
GGML_API ggml_backend_buffer_type_t ggml_backend_dev_host_buffer_type(ggml_backend_dev_t device);
GGML_API ggml_backend_buffer_t ggml_backend_dev_buffer_from_host_ptr(ggml_backend_dev_t device, void * ptr, size_t size, size_t max_tensor_size);
GGML_API bool ggml_backend_dev_supports_op(ggml_backend_dev_t device, const struct ggml_tensor * op);
GGML_API bool ggml_backend_dev_supports_buft(ggml_backend_dev_t device, ggml_backend_buffer_type_t buft);
GGML_API bool ggml_backend_dev_offload_op(ggml_backend_dev_t device, const struct ggml_tensor * op);
//
// Backend (reg)
//
GGML_API const char * ggml_backend_reg_name(ggml_backend_reg_t reg);
GGML_API size_t ggml_backend_reg_dev_count(ggml_backend_reg_t reg);
GGML_API ggml_backend_dev_t ggml_backend_reg_dev_get(ggml_backend_reg_t reg, size_t index);
GGML_API void * ggml_backend_reg_get_proc_address(ggml_backend_reg_t reg, const char * name);
GGML_API void ggml_backend_reg_set_log_callback(ggml_backend_reg_t reg, ggml_log_callback log_callback, void * user_data);
// Functions that may be obtained using ggml_backend_reg_get_proc_address
typedef ggml_backend_buffer_type_t (*ggml_backend_split_buffer_type_t)(const float *);
//
// Backend registry
//
// The backend registry is a registry of all the available backends, and allows initializing backends in a generic way
// Backend (reg) enumeration
GGML_API size_t ggml_backend_reg_count(void);
GGML_API ggml_backend_reg_t ggml_backend_reg_get(size_t index);
GGML_API ggml_backend_reg_t ggml_backend_reg_by_name(const char * name);
GGML_API size_t ggml_backend_reg_get_count(void);
GGML_API size_t ggml_backend_reg_find_by_name(const char * name); // returns index of backend with name, or SIZE_MAX if not found
GGML_API ggml_backend_t ggml_backend_reg_init_backend_from_str(const char * backend_str); // str is backend_name:params (params is optional)
GGML_API const char * ggml_backend_reg_get_name(size_t i);
GGML_API ggml_backend_t ggml_backend_reg_init_backend(size_t i, const char * params); // params is backend-specific
GGML_API ggml_backend_buffer_type_t ggml_backend_reg_get_default_buffer_type(size_t i);
GGML_API ggml_backend_buffer_t ggml_backend_reg_alloc_buffer(size_t i, size_t size);
// Device enumeration
GGML_API size_t ggml_backend_dev_count(void);
GGML_API ggml_backend_dev_t ggml_backend_dev_get(size_t index);
GGML_API ggml_backend_dev_t ggml_backend_dev_by_name(const char * name);
GGML_API ggml_backend_dev_t ggml_backend_dev_by_type(enum ggml_backend_dev_type type);
// Set the log callback for all registered backends
GGML_API void ggml_backend_set_log_callback(ggml_log_callback log_callback, void * user_data);
// Direct backend (stream) initialization
// = ggml_backend_dev_init(ggml_backend_dev_by_name(name), params)
GGML_API ggml_backend_t ggml_backend_init_by_name(const char * name, const char * params);
// = ggml_backend_dev_init(ggml_backend_dev_by_type(type), params)
GGML_API ggml_backend_t ggml_backend_init_by_type(enum ggml_backend_dev_type type, const char * params);
// = ggml_backend_dev_init(ggml_backend_dev_by_type(GPU_FULL) OR ggml_backend_dev_by_type(CPU_FULL), NULL)
GGML_API ggml_backend_t ggml_backend_init_best(void);
//
// Backend scheduler
//
// The backend scheduler allows for multiple backends to be used together
// The backend scheduler allows for multiple backend devices to be used together
// Handles compute buffer allocation, assignment of tensors to backends, and copying of tensors between backends
// The backends are selected based on:
// - the backend that supports the operation
@ -169,9 +234,9 @@ extern "C" {
}
*/
struct ggml_backend_sched;
typedef struct ggml_backend_sched * ggml_backend_sched_t;
// Evaluation callback for each node in the graph (set with ggml_backend_sched_set_eval_callback)
// when ask == true, the scheduler wants to know if the user wants to observe this node
// this allows the scheduler to batch nodes together in order to evaluate them in a single call
//
@ -226,7 +291,7 @@ extern "C" {
GGML_API struct ggml_backend_graph_copy ggml_backend_graph_copy(ggml_backend_t backend, struct ggml_cgraph * graph);
GGML_API void ggml_backend_graph_copy_free(struct ggml_backend_graph_copy copy);
typedef bool (*GGML_CALL ggml_backend_eval_callback)(int node_index, struct ggml_tensor * t1, struct ggml_tensor * t2, void * user_data);
typedef bool (*ggml_backend_eval_callback)(int node_index, struct ggml_tensor * t1, struct ggml_tensor * t2, void * user_data);
// Compare the output of two backends
GGML_API bool ggml_backend_compare_graph_backend(ggml_backend_t backend1, ggml_backend_t backend2, struct ggml_cgraph * graph, ggml_backend_eval_callback callback, void * user_data);
@ -235,6 +300,26 @@ extern "C" {
GGML_API void ggml_backend_tensor_alloc(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, void * addr);
GGML_API void ggml_backend_view_init(struct ggml_tensor * tensor);
//
// CPU backend
//
GGML_API ggml_backend_t ggml_backend_cpu_init(void);
GGML_API bool ggml_backend_is_cpu (ggml_backend_t backend);
GGML_API void ggml_backend_cpu_set_n_threads (ggml_backend_t backend_cpu, int n_threads);
GGML_API void ggml_backend_cpu_set_threadpool (ggml_backend_t backend_cpu, ggml_threadpool_t threadpool);
GGML_API void ggml_backend_cpu_set_abort_callback(ggml_backend_t backend_cpu, ggml_abort_callback abort_callback, void * abort_callback_data);
// Create a backend buffer from an existing pointer
GGML_API ggml_backend_buffer_t ggml_backend_cpu_buffer_from_ptr(void * ptr, size_t size);
GGML_API ggml_backend_buffer_type_t ggml_backend_cpu_buffer_type(void);
GGML_API ggml_backend_reg_t ggml_backend_cpu_reg(void);
#ifdef GGML_USE_CPU_HBM
GGML_API ggml_backend_buffer_type_t ggml_backend_cpu_hbm_buffer_type(void);
#endif
#ifdef __cplusplus
}

6
ggml/include/ggml-blas.h
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@ -9,13 +9,13 @@ extern "C" {
#endif
// backend API
GGML_API GGML_CALL ggml_backend_t ggml_backend_blas_init(void);
GGML_API ggml_backend_t ggml_backend_blas_init(void);
GGML_API GGML_CALL bool ggml_backend_is_blas(ggml_backend_t backend);
GGML_API bool ggml_backend_is_blas(ggml_backend_t backend);
// number of threads used for conversion to float
// for openblas and blis, this will also set the number of threads used for blas operations
GGML_API GGML_CALL void ggml_backend_blas_set_n_threads(ggml_backend_t backend_blas, int n_threads);
GGML_API void ggml_backend_blas_set_n_threads(ggml_backend_t backend_blas, int n_threads);
#ifdef __cplusplus

18
ggml/include/ggml-cann.h
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@ -44,7 +44,7 @@ extern "C" {
* @param device The index of the device to initialize.
* @return A pointer to the initialized backend instance, or nullptr on failure.
*/
GGML_API GGML_CALL ggml_backend_t ggml_backend_cann_init(int32_t device);
GGML_API ggml_backend_t ggml_backend_cann_init(int32_t device);
/**
* @brief Checks if a given backend is a CANN backend.
@ -55,7 +55,7 @@ GGML_API GGML_CALL ggml_backend_t ggml_backend_cann_init(int32_t device);
* @param backend The backend instance to check.
* @return True if the backend is a CANN backend, false otherwise.
*/
GGML_API GGML_CALL bool ggml_backend_is_cann(ggml_backend_t backend);
GGML_API bool ggml_backend_is_cann(ggml_backend_t backend);
/**
* @brief Retrieves the CANN buffer type for a specified device.
@ -67,7 +67,7 @@ GGML_API GGML_CALL bool ggml_backend_is_cann(ggml_backend_t backend);
* @return A pointer to the buffer type interface for the specified device, or
* nullptr if the device index is out of range.
*/
GGML_API GGML_CALL ggml_backend_buffer_type_t
GGML_API ggml_backend_buffer_type_t
ggml_backend_cann_buffer_type(int32_t device);
/**
@ -78,14 +78,14 @@ ggml_backend_cann_buffer_type(int32_t device);
*
* @return The number of CANN devices available.
*/
GGML_API GGML_CALL int32_t ggml_backend_cann_get_device_count(void);
GGML_API int32_t ggml_backend_cann_get_device_count(void);
/**
* @brief pinned host buffer for use with the CPU backend for faster copies between CPU and NPU.
*
* @return A pointer to the host buffer type interface.
*/
GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_cann_host_buffer_type(void);
GGML_API ggml_backend_buffer_type_t ggml_backend_cann_host_buffer_type(void);
/**
* @brief Retrieves the description of a specific CANN device.
@ -97,7 +97,7 @@ GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_cann_host_buffer_type
* @param description Pointer to a buffer where the description will be written.
* @param description_size Size of the description buffer.
*/
GGML_API GGML_CALL void ggml_backend_cann_get_device_description(
GGML_API void ggml_backend_cann_get_device_description(
int32_t device, char* description, size_t description_size);
/**
@ -112,9 +112,9 @@ GGML_API GGML_CALL void ggml_backend_cann_get_device_description(
* @param total Pointer to a variable where the total memory size will be
* stored.
*/
GGML_API GGML_CALL void ggml_backend_cann_get_device_memory(int32_t device,
size_t* free,
size_t* total);
GGML_API void ggml_backend_cann_get_device_memory(int32_t device,
size_t* free,
size_t* total);
/**
* @brief Set the logging callback for GGML.

32
ggml/include/ggml-cuda.h
View File

@ -3,6 +3,10 @@
#include "ggml.h"
#include "ggml-backend.h"
#ifdef __cplusplus
extern "C" {
#endif
#ifdef GGML_USE_HIPBLAS
#define GGML_CUDA_NAME "ROCm"
#define GGML_CUBLAS_NAME "hipBLAS"
@ -13,35 +17,33 @@
#define GGML_CUDA_NAME "CUDA"
#define GGML_CUBLAS_NAME "cuBLAS"
#endif
#ifdef __cplusplus
extern "C" {
#endif
#define GGML_CUDA_MAX_DEVICES 16
// backend API
GGML_API GGML_CALL ggml_backend_t ggml_backend_cuda_init(int device);
GGML_API ggml_backend_t ggml_backend_cuda_init(int device);
GGML_API GGML_CALL bool ggml_backend_is_cuda(ggml_backend_t backend);
GGML_API bool ggml_backend_is_cuda(ggml_backend_t backend);
// device buffer
GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_buffer_type(int device);
GGML_API 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);
GGML_API 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_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);
GGML_API int ggml_backend_cuda_get_device_count(void);
GGML_API void ggml_backend_cuda_get_device_description(int device, char * description, size_t description_size);
GGML_API void ggml_backend_cuda_get_device_memory(int device, size_t * free, size_t * total);
GGML_API GGML_CALL bool ggml_backend_cuda_register_host_buffer(void * buffer, size_t size);
GGML_API GGML_CALL void ggml_backend_cuda_unregister_host_buffer(void * buffer);
GGML_API bool ggml_backend_cuda_register_host_buffer(void * buffer, size_t size);
GGML_API void ggml_backend_cuda_unregister_host_buffer(void * buffer);
GGML_API void ggml_backend_cuda_log_set_callback(ggml_log_callback log_callback, void * user_data);
GGML_API ggml_backend_reg_t ggml_backend_cuda_reg(void);
#ifdef __cplusplus
}
#endif

6
ggml/include/ggml-metal.h
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@ -1,3 +1,5 @@
// Note: this description is outdated
//
// An interface allowing to compute ggml_cgraph with Metal
//
// This is a fully functional interface that extends ggml with GPU support for Apple devices.
@ -43,11 +45,11 @@ GGML_API ggml_backend_t ggml_backend_metal_init(void);
GGML_API bool ggml_backend_is_metal(ggml_backend_t backend);
GGML_API GGML_CALL ggml_backend_buffer_t ggml_backend_metal_buffer_from_ptr(void * data, size_t size, size_t max_size);
GGML_API ggml_backend_buffer_t ggml_backend_metal_buffer_from_ptr(void * data, size_t size, size_t max_size);
GGML_API void ggml_backend_metal_set_abort_callback(ggml_backend_t backend, ggml_abort_callback abort_callback, void * user_data);
GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_metal_buffer_type(void);
GGML_API ggml_backend_buffer_type_t ggml_backend_metal_buffer_type(void);
// helper to check if the device supports a specific family
// ideally, the user code should be doing these checks

10
ggml/include/ggml-rpc.h
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@ -10,14 +10,14 @@ extern "C" {
#define GGML_RPC_MAX_SERVERS 16
// backend API
GGML_API GGML_CALL ggml_backend_t ggml_backend_rpc_init(const char * endpoint);
GGML_API GGML_CALL bool ggml_backend_is_rpc(ggml_backend_t backend);
GGML_API ggml_backend_t ggml_backend_rpc_init(const char * endpoint);
GGML_API bool ggml_backend_is_rpc(ggml_backend_t backend);
GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_rpc_buffer_type(const char * endpoint);
GGML_API ggml_backend_buffer_type_t ggml_backend_rpc_buffer_type(const char * endpoint);
GGML_API GGML_CALL void ggml_backend_rpc_get_device_memory(const char * endpoint, size_t * free, size_t * total);
GGML_API void ggml_backend_rpc_get_device_memory(const char * endpoint, size_t * free, size_t * total);
GGML_API GGML_CALL void start_rpc_server(ggml_backend_t backend, const char * endpoint, size_t free_mem, size_t total_mem);
GGML_API void start_rpc_server(ggml_backend_t backend, const char * endpoint, size_t free_mem, size_t total_mem);
#ifdef __cplusplus
}

16
ggml/include/ggml-sycl.h
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@ -23,20 +23,20 @@ GGML_API ggml_backend_t ggml_backend_sycl_init(int device);
GGML_API ggml_backend_buffer_type_t ggml_backend_sycl_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_sycl_split_buffer_type(const float * tensor_split);
GGML_API ggml_backend_buffer_type_t ggml_backend_sycl_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_backend_buffer_type_t ggml_backend_sycl_host_buffer_type(void);
GGML_API void ggml_backend_sycl_print_sycl_devices(void);
GGML_API GGML_CALL void ggml_sycl_get_gpu_list(int *id_list, int max_len);
GGML_API GGML_CALL void ggml_sycl_get_device_description(int device, char *description, size_t description_size);
GGML_API GGML_CALL int ggml_backend_sycl_get_device_count();
GGML_API GGML_CALL void ggml_backend_sycl_get_device_memory(int device, size_t *free, size_t *total);
GGML_API void ggml_backend_sycl_print_sycl_devices(void);
GGML_API void ggml_sycl_get_gpu_list(int *id_list, int max_len);
GGML_API void ggml_sycl_get_device_description(int device, char *description, size_t description_size);
GGML_API int ggml_backend_sycl_get_device_count();
GGML_API void ggml_backend_sycl_get_device_memory(int device, size_t *free, size_t *total);
// SYCL doesn't support registering host memory, keep here for reference
// GGML_API GGML_CALL bool ggml_backend_sycl_register_host_buffer(void * buffer, size_t size);
// GGML_API GGML_CALL void ggml_backend_sycl_unregister_host_buffer(void * buffer);
// GGML_API bool ggml_backend_sycl_register_host_buffer(void * buffer, size_t size);
// GGML_API void ggml_backend_sycl_unregister_host_buffer(void * buffer);
#ifdef __cplusplus
}
#endif

14
ggml/include/ggml-vulkan.h
View File

@ -13,16 +13,16 @@ extern "C" {
GGML_API void ggml_vk_instance_init(void);
// backend API
GGML_API GGML_CALL ggml_backend_t ggml_backend_vk_init(size_t dev_num);
GGML_API ggml_backend_t ggml_backend_vk_init(size_t dev_num);
GGML_API GGML_CALL bool ggml_backend_is_vk(ggml_backend_t backend);
GGML_API GGML_CALL int ggml_backend_vk_get_device_count(void);
GGML_API GGML_CALL void ggml_backend_vk_get_device_description(int device, char * description, size_t description_size);
GGML_API GGML_CALL void ggml_backend_vk_get_device_memory(int device, size_t * free, size_t * total);
GGML_API bool ggml_backend_is_vk(ggml_backend_t backend);
GGML_API int ggml_backend_vk_get_device_count(void);
GGML_API void ggml_backend_vk_get_device_description(int device, char * description, size_t description_size);
GGML_API void ggml_backend_vk_get_device_memory(int device, size_t * free, size_t * total);
GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_vk_buffer_type(size_t dev_num);
GGML_API ggml_backend_buffer_type_t ggml_backend_vk_buffer_type(size_t dev_num);
// 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_vk_host_buffer_type(void);
GGML_API ggml_backend_buffer_type_t ggml_backend_vk_host_buffer_type(void);
#ifdef __cplusplus
}

68
ggml/include/ggml.h
View File

@ -187,16 +187,6 @@
# define GGML_API
#endif
#ifdef GGML_MULTIPLATFORM
# if defined(_WIN32)
# define GGML_CALL
# else
# define GGML_CALL __attribute__((__ms_abi__))
# endif
#else
# define GGML_CALL
#endif
// TODO: support for clang
#ifdef __GNUC__
# define GGML_DEPRECATED(func, hint) func __attribute__((deprecated(hint)))
@ -340,7 +330,7 @@ extern "C" {
};
// get ggml_status name string
GGML_API GGML_CALL const char * ggml_status_to_string(enum ggml_status status);
GGML_API const char * ggml_status_to_string(enum ggml_status status);
// ieee 754-2008 half-precision float16
// todo: make this not an integral type
@ -717,46 +707,46 @@ extern "C" {
GGML_API void ggml_print_object (const struct ggml_object * obj);
GGML_API void ggml_print_objects(const struct ggml_context * ctx);
GGML_API GGML_CALL int64_t ggml_nelements (const struct ggml_tensor * tensor);
GGML_API GGML_CALL int64_t ggml_nrows (const struct ggml_tensor * tensor);
GGML_API GGML_CALL size_t ggml_nbytes (const struct ggml_tensor * tensor);
GGML_API size_t ggml_nbytes_pad (const struct ggml_tensor * tensor); // same as ggml_nbytes() but padded to GGML_MEM_ALIGN
GGML_API int64_t ggml_nelements (const struct ggml_tensor * tensor);
GGML_API int64_t ggml_nrows (const struct ggml_tensor * tensor);
GGML_API size_t ggml_nbytes (const struct ggml_tensor * tensor);
GGML_API size_t ggml_nbytes_pad(const struct ggml_tensor * tensor); // same as ggml_nbytes() but padded to GGML_MEM_ALIGN
GGML_API GGML_CALL int64_t ggml_blck_size(enum ggml_type type);
GGML_API GGML_CALL size_t ggml_type_size(enum ggml_type type); // size in bytes for all elements in a block
GGML_API GGML_CALL size_t ggml_row_size (enum ggml_type type, int64_t ne); // size in bytes for all elements in a row
GGML_API int64_t ggml_blck_size(enum ggml_type type);
GGML_API size_t ggml_type_size(enum ggml_type type); // size in bytes for all elements in a block
GGML_API size_t ggml_row_size (enum ggml_type type, int64_t ne); // size in bytes for all elements in a row
GGML_DEPRECATED(
GGML_API double ggml_type_sizef(enum ggml_type type), // ggml_type_size()/ggml_blck_size() as float
"use ggml_row_size() instead");
GGML_API GGML_CALL const char * ggml_type_name(enum ggml_type type);
GGML_API GGML_CALL const char * ggml_op_name (enum ggml_op op);
GGML_API const char * ggml_op_symbol(enum ggml_op op);
GGML_API const char * ggml_type_name(enum ggml_type type);
GGML_API const char * ggml_op_name (enum ggml_op op);
GGML_API const char * ggml_op_symbol(enum ggml_op op);
GGML_API const char * ggml_unary_op_name(enum ggml_unary_op op);
GGML_API GGML_CALL const char * ggml_op_desc(const struct ggml_tensor * t); // unary or op name
GGML_API const char * ggml_unary_op_name(enum ggml_unary_op op);
GGML_API const char * ggml_op_desc(const struct ggml_tensor * t); // unary or op name
GGML_API GGML_CALL size_t ggml_element_size(const struct ggml_tensor * tensor);
GGML_API size_t ggml_element_size(const struct ggml_tensor * tensor);
GGML_API GGML_CALL bool ggml_is_quantized(enum ggml_type type);
GGML_API bool ggml_is_quantized(enum ggml_type type);
// TODO: temporary until model loading of ggml examples is refactored
GGML_API enum ggml_type ggml_ftype_to_ggml_type(enum ggml_ftype ftype);
GGML_API GGML_CALL bool ggml_is_transposed(const struct ggml_tensor * tensor);
GGML_API GGML_CALL bool ggml_is_permuted (const struct ggml_tensor * tensor);
GGML_API GGML_CALL bool ggml_is_empty (const struct ggml_tensor * tensor);
GGML_API bool ggml_is_scalar (const struct ggml_tensor * tensor);
GGML_API bool ggml_is_vector (const struct ggml_tensor * tensor);
GGML_API bool ggml_is_matrix (const struct ggml_tensor * tensor);
GGML_API bool ggml_is_3d (const struct ggml_tensor * tensor);
GGML_API int ggml_n_dims (const struct ggml_tensor * tensor); // returns 1 for scalars
GGML_API bool ggml_is_transposed(const struct ggml_tensor * tensor);
GGML_API bool ggml_is_permuted (const struct ggml_tensor * tensor);
GGML_API bool ggml_is_empty (const struct ggml_tensor * tensor);
GGML_API bool ggml_is_scalar (const struct ggml_tensor * tensor);
GGML_API bool ggml_is_vector (const struct ggml_tensor * tensor);
GGML_API bool ggml_is_matrix (const struct ggml_tensor * tensor);
GGML_API bool ggml_is_3d (const struct ggml_tensor * tensor);
GGML_API int ggml_n_dims (const struct ggml_tensor * tensor); // returns 1 for scalars
GGML_API GGML_CALL bool ggml_is_contiguous (const struct ggml_tensor * tensor);
GGML_API GGML_CALL bool ggml_is_contiguous_0(const struct ggml_tensor * tensor); // same as ggml_is_contiguous()
GGML_API GGML_CALL bool ggml_is_contiguous_1(const struct ggml_tensor * tensor); // contiguous for dims >= 1
GGML_API GGML_CALL bool ggml_is_contiguous_2(const struct ggml_tensor * tensor); // contiguous for dims >= 2
GGML_API bool ggml_is_contiguous (const struct ggml_tensor * tensor);
GGML_API bool ggml_is_contiguous_0(const struct ggml_tensor * tensor); // same as ggml_is_contiguous()
GGML_API bool ggml_is_contiguous_1(const struct ggml_tensor * tensor); // contiguous for dims >= 1
GGML_API bool ggml_is_contiguous_2(const struct ggml_tensor * tensor); // contiguous for dims >= 2
GGML_API bool ggml_are_same_shape (const struct ggml_tensor * t0, const struct ggml_tensor * t1);
GGML_API bool ggml_are_same_stride(const struct ggml_tensor * t0, const struct ggml_tensor * t1);
@ -848,7 +838,7 @@ extern "C" {
GGML_API void * ggml_get_data (const struct ggml_tensor * tensor);
GGML_API float * ggml_get_data_f32(const struct ggml_tensor * tensor);
GGML_API GGML_CALL enum ggml_unary_op ggml_get_unary_op(const struct ggml_tensor * tensor);
GGML_API enum ggml_unary_op ggml_get_unary_op(const struct ggml_tensor * tensor);
GGML_API const char * ggml_get_name (const struct ggml_tensor * tensor);
GGML_API struct ggml_tensor * ggml_set_name ( struct ggml_tensor * tensor, const char * name);
@ -1568,7 +1558,7 @@ extern "C" {
"use ggml_rope_ext_inplace instead");
// compute correction dims for YaRN RoPE scaling
GGML_CALL void ggml_rope_yarn_corr_dims(
void ggml_rope_yarn_corr_dims(
int n_dims, int n_ctx_orig, float freq_base, float beta_fast, float beta_slow, float dims[2]);
// rotary position embedding backward, i.e compute dx from dy

2
ggml/src/CMakeLists.txt
View File

@ -1325,7 +1325,7 @@ add_library(ggml
../include/ggml-backend.h
ggml.c
ggml-alloc.c
ggml-backend.c
ggml-backend.cpp
ggml-quants.c
ggml-quants.h
${GGML_SOURCES_CUDA} ${GGML_HEADERS_CUDA}

226
ggml/src/ggml-backend-impl.h
View File

@ -9,145 +9,229 @@ extern "C" {
#endif
//
// Backend buffer
// Backend buffer type
//
// buffer type
typedef void * ggml_backend_buffer_type_context_t;
struct ggml_backend_buffer_type_i {
const char * (*GGML_CALL get_name) (ggml_backend_buffer_type_t buft);
const char * (*get_name) (ggml_backend_buffer_type_t buft);
// allocate a buffer of this type
ggml_backend_buffer_t (*GGML_CALL alloc_buffer) (ggml_backend_buffer_type_t buft, size_t size);
ggml_backend_buffer_t (*alloc_buffer) (ggml_backend_buffer_type_t buft, size_t size);
// tensor alignment
size_t (*GGML_CALL get_alignment) (ggml_backend_buffer_type_t buft);
// max buffer size that can be allocated
size_t (*GGML_CALL get_max_size) (ggml_backend_buffer_type_t buft);
// data size needed to allocate the tensor, including padding
size_t (*GGML_CALL get_alloc_size) (ggml_backend_buffer_type_t buft, const struct ggml_tensor * tensor);
// check if tensor data is in host memory
bool (*GGML_CALL is_host) (ggml_backend_buffer_type_t buft);
size_t (*get_alignment) (ggml_backend_buffer_type_t buft);
// (optional) max buffer size that can be allocated (defaults to SIZE_MAX)
size_t (*get_max_size) (ggml_backend_buffer_type_t buft);
// (optional) data size needed to allocate the tensor, including padding (defaults to ggml_nbytes)
size_t (*get_alloc_size)(ggml_backend_buffer_type_t buft, const struct ggml_tensor * tensor);
// (optional) check if tensor data is in host memory (defaults to false)
bool (*is_host) (ggml_backend_buffer_type_t buft);
};
struct ggml_backend_buffer_type {
struct ggml_backend_buffer_type_i iface;
ggml_backend_buffer_type_context_t context;
ggml_backend_dev_t device;
void * context;
};
// buffer
typedef void * ggml_backend_buffer_context_t;
//
// Backend buffer
//
struct ggml_backend_buffer_i {
const char * (*GGML_CALL get_name) (ggml_backend_buffer_t buffer);
void (*GGML_CALL free_buffer) (ggml_backend_buffer_t buffer);
void * (*GGML_CALL get_base) (ggml_backend_buffer_t buffer);
void (*GGML_CALL init_tensor) (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor);
void (*GGML_CALL memset_tensor) (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, uint8_t value, size_t offset, size_t size);
void (*GGML_CALL set_tensor) (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
void (*GGML_CALL get_tensor) (ggml_backend_buffer_t buffer, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
bool (*GGML_CALL cpy_tensor) (ggml_backend_buffer_t buffer, const struct ggml_tensor * src, struct ggml_tensor * dst); // dst is in the buffer, src may be in any buffer
void (*GGML_CALL clear) (ggml_backend_buffer_t buffer, uint8_t value);
void (*GGML_CALL reset) (ggml_backend_buffer_t buffer); // reset any internal state due to tensor initialization, such as tensor extras
const char * (*get_name) (ggml_backend_buffer_t buffer);
// (optional) free the buffer
void (*free_buffer) (ggml_backend_buffer_t buffer);
// base address of the buffer
void * (*get_base) (ggml_backend_buffer_t buffer);
// (optional) initialize a tensor in the buffer (eg. add tensor extras)
void (*init_tensor) (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor);
// tensor data access
void (*memset_tensor)(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, uint8_t value, size_t offset, size_t size);
void (*set_tensor) (ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
void (*get_tensor) (ggml_backend_buffer_t buffer, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
// (optional) tensor copy: dst is in the buffer, src may be in any buffer, including buffers from a different backend (return false if not supported)
bool (*cpy_tensor) (ggml_backend_buffer_t buffer, const struct ggml_tensor * src, struct ggml_tensor * dst);
// clear the entire buffer
void (*clear) (ggml_backend_buffer_t buffer, uint8_t value);
// (optional) reset any internal state due to tensor initialization, such as tensor extras
void (*reset) (ggml_backend_buffer_t buffer);
};
struct ggml_backend_buffer {
struct ggml_backend_buffer_i iface;
ggml_backend_buffer_type_t buft;
ggml_backend_buffer_context_t context;
void * context;
size_t size;
enum ggml_backend_buffer_usage usage;
};
GGML_CALL ggml_backend_buffer_t ggml_backend_buffer_init(
ggml_backend_buffer_type_t buft,
struct ggml_backend_buffer_i iface,
ggml_backend_buffer_context_t context,
size_t size);
ggml_backend_buffer_t ggml_backend_buffer_init(
ggml_backend_buffer_type_t buft,
struct ggml_backend_buffer_i iface,
void * context,
size_t size);
// do not use directly, use ggml_backend_tensor_copy instead
bool ggml_backend_buffer_copy_tensor(const struct ggml_tensor * src, struct ggml_tensor * dst);
// multi-buffer
// buffer that contains a collection of buffers
GGML_CALL ggml_backend_buffer_t ggml_backend_multi_buffer_alloc_buffer(ggml_backend_buffer_t * buffers, size_t n_buffers);
GGML_CALL bool ggml_backend_buffer_is_multi_buffer(ggml_backend_buffer_t buffer);
GGML_CALL void ggml_backend_multi_buffer_set_usage(ggml_backend_buffer_t buffer, enum ggml_backend_buffer_usage usage);
ggml_backend_buffer_t ggml_backend_multi_buffer_alloc_buffer(ggml_backend_buffer_t * buffers, size_t n_buffers);
bool ggml_backend_buffer_is_multi_buffer(ggml_backend_buffer_t buffer);
void ggml_backend_multi_buffer_set_usage(ggml_backend_buffer_t buffer, enum ggml_backend_buffer_usage usage);
//
// Backend
// Backend (stream)
//
typedef void * ggml_backend_context_t;
struct ggml_backend_i {
const char * (*GGML_CALL get_name)(ggml_backend_t backend);
const char * (*get_name)(ggml_backend_t backend);
void (*GGML_CALL free)(ggml_backend_t backend);
void (*free)(ggml_backend_t backend);
// buffer allocation
ggml_backend_buffer_type_t (*GGML_CALL get_default_buffer_type)(ggml_backend_t backend);
ggml_backend_buffer_type_t (*get_default_buffer_type)(ggml_backend_t backend);
// (optional) asynchronous tensor data access
void (*GGML_CALL set_tensor_async)(ggml_backend_t backend, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
void (*GGML_CALL get_tensor_async)(ggml_backend_t backend, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
bool (*GGML_CALL cpy_tensor_async)(ggml_backend_t backend_src, ggml_backend_t backend_dst, const struct ggml_tensor * src, struct ggml_tensor * dst);
void (*set_tensor_async)(ggml_backend_t backend, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size);
void (*get_tensor_async)(ggml_backend_t backend, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size);
bool (*cpy_tensor_async)(ggml_backend_t backend_src, ggml_backend_t backend_dst, const struct ggml_tensor * src, struct ggml_tensor * dst);
// (optional) complete all pending operations
void (*GGML_CALL synchronize)(ggml_backend_t backend);
void (*synchronize)(ggml_backend_t backend);
// compute graph with a plan (not used currently)
// create a new plan for a graph
ggml_backend_graph_plan_t (*GGML_CALL graph_plan_create) (ggml_backend_t backend, const struct ggml_cgraph * cgraph);
void (*GGML_CALL graph_plan_free) (ggml_backend_t backend, ggml_backend_graph_plan_t plan);
// (optional) compute graph with a plan (not used currently)
ggml_backend_graph_plan_t (*graph_plan_create) (ggml_backend_t backend, const struct ggml_cgraph * cgraph);
void (*graph_plan_free) (ggml_backend_t backend, ggml_backend_graph_plan_t plan);
// update the plan with a new graph - this should be faster than creating a new plan when the graph has the same topology
void (*GGML_CALL graph_plan_update) (ggml_backend_t backend, ggml_backend_graph_plan_t plan, const struct ggml_cgraph * cgraph);
void (*graph_plan_update) (ggml_backend_t backend, ggml_backend_graph_plan_t plan, const struct ggml_cgraph * cgraph);
// compute the graph with the plan
enum ggml_status (*GGML_CALL graph_plan_compute)(ggml_backend_t backend, ggml_backend_graph_plan_t plan);
enum ggml_status (*graph_plan_compute)(ggml_backend_t backend, ggml_backend_graph_plan_t plan);
// compute graph without a plan (async)
enum ggml_status (*GGML_CALL graph_compute) (ggml_backend_t backend, struct ggml_cgraph * cgraph);
// compute graph (always async if supported by the backend)
enum ggml_status (*graph_compute) (ggml_backend_t backend, struct ggml_cgraph * cgraph);
// IMPORTANT: these functions have been moved to the device interface and will be removed from the backend interface
// new backends should implement the device interface instead
// These functions are being moved to the device interface
// check if the backend can compute an operation
bool (*GGML_CALL supports_op)(ggml_backend_t backend, const struct ggml_tensor * op);
bool (*supports_op) (ggml_backend_t backend, const struct ggml_tensor * op);
// check if the backend can use tensors allocated in a buffer type
bool (*GGML_CALL supports_buft)(ggml_backend_t backend, ggml_backend_buffer_type_t buft);
bool (*supports_buft)(ggml_backend_t backend, ggml_backend_buffer_type_t buft);
// check if the backend wants to run an operation, even if the weights are allocated in a CPU buffer
// these should be expensive operations with large batch sizes that may benefit from running on this backend
// even if the weight has to be copied from the CPU temporarily
bool (*GGML_CALL offload_op)(ggml_backend_t backend, const struct ggml_tensor * op);
bool (*offload_op) (ggml_backend_t backend, const struct ggml_tensor * op);
// (optional) event synchronization
// create a new event that can record events on this backend instance
ggml_backend_event_t (*GGML_CALL event_new) (ggml_backend_t backend);
void (*GGML_CALL event_free) (ggml_backend_event_t event);
// record an event on the backend instance that created it
void (*GGML_CALL event_record) (ggml_backend_event_t event);
// wait for an event on on a different backend instance
void (*GGML_CALL event_wait) (ggml_backend_t backend, ggml_backend_event_t event);
// block until an event is recorded
void (*GGML_CALL event_synchronize) (ggml_backend_event_t event);
// record an event on this stream
void (*event_record)(ggml_backend_t backend, ggml_backend_event_t event);
// wait for an event on on a different stream
void (*event_wait) (ggml_backend_t backend, ggml_backend_event_t event);
};
struct ggml_backend {
ggml_guid_t guid;
struct ggml_backend_i iface;
ggml_backend_context_t context;
ggml_backend_dev_t device;
void * context;
};
struct ggml_backend_event {
ggml_backend_t backend;
struct ggml_backend_device * device;
void * context;
};
//
// Backend registry
// Backend device
//
typedef ggml_backend_t (*GGML_CALL ggml_backend_init_fn)(const char * params, void * user_data);
// Note: if additional properties are needed, we should add a struct with all of them
// the current functions to obtain the properties can remain, since they are more convenient for often used properties
struct ggml_backend_device_i {
// device name: short identifier for this device, such as "CPU" or "CUDA0"
const char * (*get_name)(ggml_backend_dev_t dev);
GGML_CALL void ggml_backend_register(const char * name, ggml_backend_init_fn init_fn, ggml_backend_buffer_type_t default_buffer_type, void * user_data);
// device description: short informative description of the device, could be the model name
const char * (*get_description)(ggml_backend_dev_t dev);
// device memory in bytes
void (*get_memory)(ggml_backend_dev_t dev, size_t * free, size_t * total);
// device type
enum ggml_backend_dev_type (*get_type)(ggml_backend_dev_t dev);
// device properties
void (*get_props)(ggml_backend_dev_t dev, struct ggml_backend_dev_props * props);
// backend (stream) initialization
ggml_backend_t (*init_backend)(ggml_backend_dev_t dev, const char * params);
// preferred buffer type
ggml_backend_buffer_type_t (*get_buffer_type)(ggml_backend_dev_t dev);
// (optional) host buffer type (in system memory, typically this is a pinned memory buffer for faster transfers between host and device)
ggml_backend_buffer_type_t (*get_host_buffer_type)(ggml_backend_dev_t dev);
// (optional) buffer from pointer: create a buffer from a host pointer (useful for memory mapped models and importing data from other libraries)
ggml_backend_buffer_t (*buffer_from_host_ptr)(ggml_backend_dev_t dev, void * ptr, size_t size, size_t max_tensor_size);
// check if the backend can compute an operation
bool (*supports_op)(ggml_backend_dev_t dev, const struct ggml_tensor * op);
// check if the backend can use tensors allocated in a buffer type
bool (*supports_buft)(ggml_backend_dev_t dev, ggml_backend_buffer_type_t buft);
// check if the backend wants to run an operation, even if the weights are allocated in a CPU buffer
// these should be expensive operations with large batch sizes that may benefit from running on this backend
// even if the weight has to be copied from the CPU temporarily
bool (*offload_op)(ggml_backend_dev_t dev, const struct ggml_tensor * op);
// (optional) event synchronization
ggml_backend_event_t (*event_new) (ggml_backend_dev_t dev);
void (*event_free) (ggml_backend_dev_t dev, ggml_backend_event_t event);
void (*event_synchronize) (ggml_backend_dev_t dev, ggml_backend_event_t event);
};
struct ggml_backend_device {
struct ggml_backend_device_i iface;
ggml_backend_reg_t reg;
void * context;
};
//
// Backend (reg)
//
struct ggml_backend_reg_i {
const char * (*get_name)(ggml_backend_reg_t reg);
// enumerate available devices
size_t (*get_device_count)(ggml_backend_reg_t reg);
ggml_backend_dev_t (*get_device)(ggml_backend_reg_t reg, size_t index);
// (optional) get a pointer to a function in the backend
// backends can add custom functions that are not part of the standard ggml-backend interface
void * (*get_proc_address)(ggml_backend_reg_t reg, const char * name);
// (optional) set the log callback for the backend
void (*set_log_callback)(ggml_backend_reg_t reg, ggml_log_callback log_callback, void * user_data);
};
struct ggml_backend_reg {
// int api_version; // TODO: for dynamic loading
struct ggml_backend_reg_i iface;
void * context;
};
// Internal backend registry API
void ggml_backend_register(ggml_backend_reg_t reg);
void ggml_backend_device_register(ggml_backend_dev_t device);
// TODO: backends can be loaded as a dynamic library, in which case it needs to export this function
// typedef ggml_backend_register_t * (*ggml_backend_init)(void);
#ifdef __cplusplus
}

2496
ggml/src/ggml-backend.cpp Normal file
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18
ggml/src/ggml-blas.cpp
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@ -235,25 +235,25 @@ static void ggml_backend_blas_out_prod(ggml_backend_blas_context * ctx, struct g
// backend interface
GGML_CALL static const char * ggml_backend_blas_name(ggml_backend_t backend) {
static const char * ggml_backend_blas_name(ggml_backend_t backend) {
return "BLAS";
GGML_UNUSED(backend);
}
GGML_CALL static void ggml_backend_blas_free(ggml_backend_t backend) {
static void ggml_backend_blas_free(ggml_backend_t backend) {
ggml_backend_blas_context * ctx = (ggml_backend_blas_context *)backend->context;
delete ctx;
delete backend;
}
GGML_CALL static ggml_backend_buffer_type_t ggml_backend_blas_get_default_buffer_type(ggml_backend_t backend) {
static ggml_backend_buffer_type_t ggml_backend_blas_get_default_buffer_type(ggml_backend_t backend) {
return ggml_backend_cpu_buffer_type();
GGML_UNUSED(backend);
}
GGML_CALL static enum ggml_status ggml_backend_blas_graph_compute(ggml_backend_t backend, struct ggml_cgraph * cgraph) {
static enum ggml_status ggml_backend_blas_graph_compute(ggml_backend_t backend, struct ggml_cgraph * cgraph) {
ggml_backend_blas_context * ctx = (ggml_backend_blas_context *)backend->context;
for (int i = 0; i < cgraph->n_nodes; i++) {
@ -285,7 +285,7 @@ GGML_CALL static enum ggml_status ggml_backend_blas_graph_compute(ggml_backend_t
GGML_UNUSED(backend);
}
GGML_CALL static bool ggml_backend_blas_supports_op(ggml_backend_t backend, const struct ggml_tensor * op) {
static bool ggml_backend_blas_supports_op(ggml_backend_t backend, const struct ggml_tensor * op) {
const struct ggml_tensor * src0 = op->src[0];
const struct ggml_tensor * src1 = op->src[1];
@ -300,7 +300,7 @@ GGML_CALL static bool ggml_backend_blas_supports_op(ggml_backend_t backend, cons
GGML_UNUSED(backend);
}
GGML_CALL static bool ggml_backend_blas_supports_buft(ggml_backend_t backend, ggml_backend_buffer_type_t buft) {
static bool ggml_backend_blas_supports_buft(ggml_backend_t backend, ggml_backend_buffer_type_t buft) {
return ggml_backend_buft_is_host(buft);
GGML_UNUSED(backend);
@ -322,11 +322,8 @@ static struct ggml_backend_i blas_backend_i = {
/* .supports_op = */ ggml_backend_blas_supports_op,
/* .supports_buft = */ ggml_backend_blas_supports_buft,
/* .offload_op = */ NULL,
/* .event_new = */ NULL,
/* .event_free = */ NULL,
/* .event_record = */ NULL,
/* .event_wait = */ NULL,
/* .event_synchronize = */ NULL,
};
static ggml_guid_t ggml_backend_blas_guid(void) {
@ -340,6 +337,7 @@ ggml_backend_t ggml_backend_blas_init(void) {
ggml_backend_t backend = new ggml_backend {
/* .guid = */ ggml_backend_blas_guid(),
/* .interface = */ blas_backend_i,
/* .device = */ nullptr,
/* .context = */ ctx,
};
@ -356,7 +354,7 @@ ggml_backend_t ggml_backend_blas_init(void) {
return backend;
}
GGML_CALL bool ggml_backend_is_blas(ggml_backend_t backend) {
bool ggml_backend_is_blas(ggml_backend_t backend) {
return backend != NULL && ggml_guid_matches(backend->guid, ggml_backend_blas_guid());
}

155
ggml/src/ggml-cann.cpp
View File

@ -560,7 +560,7 @@ struct ggml_backend_cann_buffer_context {
* @return A pointer to a C-string containing the name of the buffer.
*/
GGML_CALL static const char* ggml_backend_cann_buffer_get_name(
static const char* ggml_backend_cann_buffer_get_name(
ggml_backend_buffer_t buffer) {
return "CANN";
@ -576,7 +576,7 @@ GGML_CALL static const char* ggml_backend_cann_buffer_get_name(
* @param buffer The buffer to check.
* @return true if the buffer is a CANN buffer, false otherwise.
*/
GGML_CALL static bool ggml_backend_buffer_is_cann(
static bool ggml_backend_buffer_is_cann(
ggml_backend_buffer_t buffer) {
return buffer->iface.get_name == ggml_backend_cann_buffer_get_name;
}
@ -589,7 +589,7 @@ GGML_CALL static bool ggml_backend_buffer_is_cann(
*
* @param buffer The CANN buffer to free.
*/
GGML_CALL static void ggml_backend_cann_buffer_free_buffer(
static void ggml_backend_cann_buffer_free_buffer(
ggml_backend_buffer_t buffer) {
ggml_backend_cann_buffer_context* ctx =
(ggml_backend_cann_buffer_context*)buffer->context;
@ -605,7 +605,7 @@ GGML_CALL static void ggml_backend_cann_buffer_free_buffer(
* @param buffer The CANN buffer whose base pointer is to be retrieved.
* @return A pointer to the base of the device memory allocated for the buffer.
*/
GGML_CALL static void* ggml_backend_cann_buffer_get_base(
static void* ggml_backend_cann_buffer_get_base(
ggml_backend_buffer_t buffer) {
ggml_backend_cann_buffer_context* ctx =
(ggml_backend_cann_buffer_context*)buffer->context;
@ -625,9 +625,9 @@ GGML_CALL static void* ggml_backend_cann_buffer_get_base(
* @param dst Pointer to the destination buffer where transformed data will be
* stored.
*/
GGML_CALL static void ggml_backend_cann_transform_q4_0(ggml_tensor* tensor,
const void* src,
void* dst) {
static void ggml_backend_cann_transform_q4_0(ggml_tensor* tensor,
const void* src,
void* dst) {
int64_t n_elems = ggml_nelements(tensor);
int64_t groups = n_elems / QK4_0;
@ -677,7 +677,7 @@ GGML_CALL static void ggml_backend_cann_transform_q4_0(ggml_tensor* tensor,
* @param dst Pointer to the destination buffer where the Q4.0 formatted data
* will be stored.
*/
GGML_CALL static void ggml_backend_cann_transform_back_q4_0(
static void ggml_backend_cann_transform_back_q4_0(
const ggml_tensor* tensor, void* src, void* dst) {
int64_t n_elems = ggml_nelements(tensor);
@ -726,9 +726,9 @@ GGML_CALL static void ggml_backend_cann_transform_back_q4_0(
* @param dst Pointer to the destination buffer where transformed data will be
* stored.
*/
GGML_CALL static void ggml_backend_cann_transform_q8_0(ggml_tensor* tensor,
const void* src,
void* dst) {
static void ggml_backend_cann_transform_q8_0(ggml_tensor* tensor,
const void* src,
void* dst) {
int64_t n_elems = ggml_nelements(tensor);
int64_t groups = n_elems / QK8_0;
size_t quant_bytes = n_elems * sizeof(uint8_t);
@ -760,7 +760,7 @@ GGML_CALL static void ggml_backend_cann_transform_q8_0(ggml_tensor* tensor,
* @param dst Pointer to the destination buffer where the Q8.0 formatted data
* will be stored.
*/
GGML_CALL static void ggml_backend_cann_transform_back_q8_0(
static void ggml_backend_cann_transform_back_q8_0(
const ggml_tensor* tensor, const void* src, void* dst) {
int64_t n_elems = ggml_nelements(tensor);
int64_t groups = n_elems / QK8_0;
@ -792,8 +792,8 @@ GGML_CALL static void ggml_backend_cann_transform_back_q8_0(
* @param dst Pointer to the destination buffer where transformed data will be
* stored.
*/
GGML_CALL static void ggml_backend_cann_transform(ggml_tensor* tensor,
const void* src, void* dst) {
static void ggml_backend_cann_transform(ggml_tensor* tensor,
const void* src, void* dst) {
switch (tensor->type) {
case GGML_TYPE_Q4_0:
ggml_backend_cann_transform_q4_0(tensor, src, dst);
@ -818,7 +818,7 @@ GGML_CALL static void ggml_backend_cann_transform(ggml_tensor* tensor,
* @param dst Pointer to the destination buffer where transformed tensor data
* will be stored.
*/
GGML_CALL static void ggml_backend_cann_transform_back(
static void ggml_backend_cann_transform_back(
const ggml_tensor* tensor, void* src, void* dst) {
switch (tensor->type) {
case GGML_TYPE_Q4_0:
@ -841,7 +841,7 @@ GGML_CALL static void ggml_backend_cann_transform_back(
* @param type The tensor type to check.
* @return true if transformation is needed, false otherwise.
*/
GGML_CALL static bool need_transform(ggml_type type) {
static bool need_transform(ggml_type type) {
switch (type) {
case GGML_TYPE_Q4_0:
case GGML_TYPE_Q8_0:
@ -860,7 +860,7 @@ GGML_CALL static bool need_transform(ggml_type type) {
* @param buffer The CANN buffer from which to initialize the tensor.
* @param tensor Pointer to the tensor to be initialized.
*/
GGML_CALL static void ggml_backend_cann_buffer_init_tensor(
static void ggml_backend_cann_buffer_init_tensor(
ggml_backend_buffer_t buffer, ggml_tensor* tensor) {
if (tensor->view_src != NULL && tensor->view_offs == 0) {
GGML_ASSERT(tensor->view_src->buffer->buft == buffer->buft);
@ -896,7 +896,7 @@ GGML_CALL static void ggml_backend_cann_buffer_init_tensor(
* @param offset Offset in the source data from where to start copying.
* @param size Size of the data to be copied, in bytes.
*/
GGML_CALL static void ggml_backend_cann_buffer_set_tensor(
static void ggml_backend_cann_buffer_set_tensor(
ggml_backend_buffer_t buffer, ggml_tensor *tensor, const void *data,
size_t offset, size_t size) {
ggml_backend_cann_buffer_context *ctx =
@ -941,7 +941,7 @@ GGML_CALL static void ggml_backend_cann_buffer_set_tensor(
* @param offset Offset in the destination buffer where to start copying.
* @param size Size of the data to be copied, in bytes.
*/
GGML_CALL static void ggml_backend_cann_buffer_get_tensor(
static void ggml_backend_cann_buffer_get_tensor(
ggml_backend_buffer_t buffer, const ggml_tensor* tensor, void* data,
size_t offset, size_t size) {
ggml_backend_cann_buffer_context* ctx =
@ -975,7 +975,7 @@ GGML_CALL static void ggml_backend_cann_buffer_get_tensor(
* @param dst Pointer to the destination tensor where the data will be copied.
* @return true if the copy operation succeeded, false otherwise.
*/
GGML_CALL static bool ggml_backend_cann_buffer_cpy_tensor(
static bool ggml_backend_cann_buffer_cpy_tensor(
ggml_backend_buffer_t buffer, const ggml_tensor* src, ggml_tensor* dst) {
if (ggml_backend_buffer_is_cann(src->buffer)) {
ggml_backend_cann_buffer_context* src_ctx =
@ -1017,7 +1017,7 @@ GGML_CALL static bool ggml_backend_cann_buffer_cpy_tensor(
* @param buffer The CANN buffer to be cleared.
* @param value The value to which each byte in the buffer will be set.
*/
GGML_CALL static void ggml_backend_cann_buffer_clear(
static void ggml_backend_cann_buffer_clear(
ggml_backend_buffer_t buffer, uint8_t value) {
ggml_backend_cann_buffer_context* ctx =
(ggml_backend_cann_buffer_context*)buffer->context;
@ -1065,7 +1065,7 @@ struct ggml_backend_cann_buffer_type_context {
* @param buft Pointer to the buffer type context.
* @return Const pointer to the C-style string containing the name.
*/
GGML_CALL static const char* ggml_backend_cann_buffer_type_name(
static const char* ggml_backend_cann_buffer_type_name(
ggml_backend_buffer_type_t buft) {
return "CANN";
@ -1082,7 +1082,7 @@ GGML_CALL static const char* ggml_backend_cann_buffer_type_name(
* @param size Size in bytes of the buffer to allocate.
* @return Pointer to the allocated buffer, or nullptr if allocation fails.
*/
GGML_CALL static ggml_backend_buffer_t
static ggml_backend_buffer_t
ggml_backend_cann_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft,
size_t size) {
ggml_backend_cann_buffer_type_context* buft_ctx =
@ -1121,7 +1121,7 @@ ggml_backend_cann_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft,
* @return The alignment requirement in bytes (fixed at 128 bytes for CANN
* buffers).
*/
GGML_CALL static size_t ggml_backend_cann_buffer_type_get_alignment(
static size_t ggml_backend_cann_buffer_type_get_alignment(
ggml_backend_buffer_type_t buft) {
return 128;
@ -1142,7 +1142,7 @@ GGML_CALL static size_t ggml_backend_cann_buffer_type_get_alignment(
* @return The total allocation size in bytes required for the tensor in the
* CANN buffer.
*/
GGML_CALL static size_t ggml_backend_cann_buffer_type_get_alloc_size(
static size_t ggml_backend_cann_buffer_type_get_alloc_size(
ggml_backend_buffer_type_t buft, const ggml_tensor* tensor) {
size_t size = ggml_nbytes(tensor);
int64_t ne0 = tensor->ne[0];
@ -1193,7 +1193,7 @@ static ggml_backend_buffer_type_i ggml_backend_cann_buffer_type_interface = {
* @return A pointer to the buffer type interface for the specified device, or
* nullptr if the device index is out of range.
*/
GGML_CALL ggml_backend_buffer_type_t
ggml_backend_buffer_type_t
ggml_backend_cann_buffer_type(int32_t device) {
static std::mutex mutex;
std::lock_guard<std::mutex> lock(mutex);
@ -1231,7 +1231,7 @@ ggml_backend_cann_buffer_type(int32_t device) {
* @param buft Pointer to the host buffer type context.
* @return Const pointer to the C-style string containing the name.
*/
GGML_CALL static const char * ggml_backend_cann_host_buffer_type_name(ggml_backend_buffer_type_t buft) {
static const char * ggml_backend_cann_host_buffer_type_name(ggml_backend_buffer_type_t buft) {
return "CANN_Host";
GGML_UNUSED(buft);
@ -1246,7 +1246,7 @@ GGML_CALL static const char * ggml_backend_cann_host_buffer_type_name(ggml_backe
* @param buft Pointer to the host buffer context.
* @return Const pointer to the C-style string containing the name.
*/
GGML_CALL static const char * ggml_backend_cann_host_buffer_name(ggml_backend_buffer_t buffer) {
static const char * ggml_backend_cann_host_buffer_name(ggml_backend_buffer_t buffer) {
return "CANN_Host";
GGML_UNUSED(buffer);
@ -1260,7 +1260,7 @@ GGML_CALL static const char * ggml_backend_cann_host_buffer_name(ggml_backend_bu
*
* @param buffer The CANN host buffer to free.
*/
GGML_CALL static void ggml_backend_cann_host_buffer_free(ggml_backend_buffer_t buffer) {
static void ggml_backend_cann_host_buffer_free(ggml_backend_buffer_t buffer) {
ACL_CHECK(aclrtFreeHost(buffer->context));
}
@ -1294,7 +1294,7 @@ static void * ggml_cann_host_malloc(size_t size) {
* @param size Size in bytes of the host buffer to allocate.
* @return Pointer to the allocated host buffer, or CPU buffer pointer if allocation fails.
*/
GGML_CALL static ggml_backend_buffer_t ggml_backend_cann_host_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
static ggml_backend_buffer_t ggml_backend_cann_host_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
void * hostPtr = ggml_cann_host_malloc(size);
if (hostPtr == nullptr) {
@ -1316,7 +1316,7 @@ GGML_CALL static ggml_backend_buffer_t ggml_backend_cann_host_buffer_type_alloc_
* Provides function pointers for allocating, querying properties, and managing
* memory for CANN buffer types in the GGML backend.
*/
GGML_CALL ggml_backend_buffer_type_t ggml_backend_cann_host_buffer_type() {
ggml_backend_buffer_type_t ggml_backend_cann_host_buffer_type() {
static struct ggml_backend_buffer_type ggml_backend_cann_buffer_type_host = {
/* .iface = */ {
/* .get_name = */ ggml_backend_cann_host_buffer_type_name,
@ -1326,6 +1326,7 @@ GGML_CALL ggml_backend_buffer_type_t ggml_backend_cann_host_buffer_type() {
/* .get_alloc_size = */ ggml_backend_cpu_buffer_type()->iface.get_alloc_size,
/* .is_host = */ ggml_backend_cpu_buffer_type()->iface.is_host,
},
/* .device = */ nullptr,
/* .context = */ nullptr,
};
@ -1495,7 +1496,7 @@ static bool ggml_cann_compute_forward(ggml_backend_cann_context& ctx,
* @param backend Pointer to the CANN backend structure.
* @return A pointer to a constant string representing the backend name.
*/
GGML_CALL static const char* ggml_backend_cann_name(ggml_backend_t backend) {
static const char* ggml_backend_cann_name(ggml_backend_t backend) {
ggml_backend_cann_context* cann_ctx =
(ggml_backend_cann_context*)backend->context;
@ -1510,7 +1511,7 @@ GGML_CALL static const char* ggml_backend_cann_name(ggml_backend_t backend) {
*
* @param backend Pointer to the CANN backend structure to be freed.
*/
GGML_CALL static void ggml_backend_cann_free(ggml_backend_t backend) {
static void ggml_backend_cann_free(ggml_backend_t backend) {
ggml_backend_cann_context* cann_ctx =
(ggml_backend_cann_context*)backend->context;
ACL_CHECK(aclrtSynchronizeDevice());
@ -1535,7 +1536,7 @@ GGML_CALL static void ggml_backend_cann_free(ggml_backend_t backend) {
* @param backend Pointer to the CANN backend structure.
* @return Pointer to the buffer type structure for the CANN backend.
*/
GGML_CALL static ggml_backend_buffer_type_t
static ggml_backend_buffer_type_t
ggml_backend_cann_get_default_buffer_type(ggml_backend_t backend) {
ggml_backend_cann_context* cann_ctx =
(ggml_backend_cann_context*)backend->context;
@ -1556,11 +1557,11 @@ ggml_backend_cann_get_default_buffer_type(ggml_backend_t backend) {
* @param offset Offset in bytes within the host data.
* @param size Size of the data to copy in bytes.
*/
GGML_CALL static void ggml_backend_cann_set_tensor_async(ggml_backend_t backend,
ggml_tensor *tensor,
const void *data,
size_t offset,
size_t size) {
static void ggml_backend_cann_set_tensor_async(ggml_backend_t backend,
ggml_tensor *tensor,
const void *data,
size_t offset,
size_t size) {
ggml_backend_cann_context *cann_ctx =
(ggml_backend_cann_context *)backend->context;
@ -1587,7 +1588,7 @@ GGML_CALL static void ggml_backend_cann_set_tensor_async(ggml_backend_t backend,
}
}
GGML_CALL static void ggml_backend_cann_get_tensor_async(
static void ggml_backend_cann_get_tensor_async(
ggml_backend_t backend, const ggml_tensor *tensor, void *data,
size_t offset, size_t size) {
ggml_backend_cann_context *cann_ctx =
@ -1626,7 +1627,7 @@ GGML_CALL static void ggml_backend_cann_get_tensor_async(
* @param dst Pointer to the destination tensor to copy data to.
* @return true if the copy operation succeeds, false otherwise.
*/
GGML_CALL static bool ggml_backend_cann_cpy_tensor_async(
static bool ggml_backend_cann_cpy_tensor_async(
ggml_backend_t backend_src, ggml_backend_t backend_dst,
const ggml_tensor* src, ggml_tensor* dst) {
GGML_ASSERT(ggml_backend_is_cann(backend_src) ||
@ -1694,7 +1695,7 @@ GGML_CALL static bool ggml_backend_cann_cpy_tensor_async(
*
* @param backend Pointer to the CANN backend structure to synchronize.
*/
GGML_CALL static void ggml_backend_cann_synchronize(ggml_backend_t backend) {
static void ggml_backend_cann_synchronize(ggml_backend_t backend) {
ggml_backend_cann_context* cann_ctx =
(ggml_backend_cann_context*)backend->context;
@ -1715,7 +1716,7 @@ GGML_CALL static void ggml_backend_cann_synchronize(ggml_backend_t backend) {
* @return enum ggml_status Returns GGML_STATUS_SUCCESS if computation
* completes successfully, otherwise an appropriate error status.
*/
GGML_CALL static enum ggml_status ggml_backend_cann_graph_compute(
static enum ggml_status ggml_backend_cann_graph_compute(
ggml_backend_t backend, ggml_cgraph* cgraph) {
ggml_backend_cann_context* cann_ctx =
(ggml_backend_cann_context*)backend->context;
@ -1753,7 +1754,7 @@ GGML_CALL static enum ggml_status ggml_backend_cann_graph_compute(
* @return bool Returns true if the operation is supported by the backend,
* otherwise false.
*/
GGML_CALL static bool ggml_backend_cann_supports_op(ggml_backend_t backend,
static bool ggml_backend_cann_supports_op(ggml_backend_t backend,
const ggml_tensor* op) {
switch (op->op) {
case GGML_OP_UNARY:
@ -1875,7 +1876,7 @@ static bool ggml_backend_buft_is_cann(ggml_backend_buffer_type_t buft) {
* @return bool Returns true if the CANN backend supports the buffer type,
* otherwise false.
*/
GGML_CALL static bool ggml_backend_cann_supports_buft(
static bool ggml_backend_cann_supports_buft(
ggml_backend_t backend, ggml_backend_buffer_type_t buft) {
if (ggml_backend_buft_is_cann(buft)) {
ggml_backend_cann_context * cann_ctx =
@ -1901,7 +1902,7 @@ GGML_CALL static bool ggml_backend_cann_supports_buft(
* @return bool Returns true if the operation should be offloaded, otherwise
* false.
*/
GGML_CALL static bool ggml_backend_cann_offload_op(ggml_backend_t backend,
static bool ggml_backend_cann_offload_op(ggml_backend_t backend,
const ggml_tensor* op) {
const int min_batch_size = 32;
GGML_UNUSED(backend);
@ -2021,11 +2022,8 @@ static ggml_backend_i ggml_backend_cann_interface = {
/* .supports_op = */ ggml_backend_cann_supports_op,
/* .supports_buft = */ ggml_backend_cann_supports_buft,
/* .offload_op = */ ggml_backend_cann_offload_op,
/* .event_new = */ ggml_backend_cann_event_new,
/* .event_free = */ ggml_backend_cann_event_free,
/* .event_record = */ ggml_backend_cann_event_record,
/* .event_wait = */ ggml_backend_cann_event_wait,
/* .event_synchronize = */ ggml_backend_cann_event_synchronize,
};
/**
@ -2042,7 +2040,7 @@ static ggml_guid_t ggml_backend_cann_guid() {
return &guid;
}
GGML_CALL ggml_backend_t ggml_backend_cann_init(int32_t device) {
ggml_backend_t ggml_backend_cann_init(int32_t device) {
aclInit(nullptr);
if (device < 0 || device >= ggml_backend_cann_get_device_count()) {
GGML_CANN_LOG_ERROR("%s: error: invalid device %d\n", __func__, device);
@ -2058,75 +2056,30 @@ GGML_CALL ggml_backend_t ggml_backend_cann_init(int32_t device) {
ggml_backend_t cann_backend =
new ggml_backend{/* .guid = */ ggml_backend_cann_guid(),
/* .interface = */ ggml_backend_cann_interface,
/* .device = */ nullptr,
/* .context = */ ctx};
return cann_backend;
}
GGML_CALL bool ggml_backend_is_cann(ggml_backend_t backend) {
bool ggml_backend_is_cann(ggml_backend_t backend) {
return backend != NULL &&
ggml_guid_matches(backend->guid, ggml_backend_cann_guid());
}
GGML_CALL int32_t ggml_backend_cann_get_device_count() {
int32_t ggml_backend_cann_get_device_count() {
return ggml_cann_info().device_count;
}
GGML_CALL void ggml_backend_cann_get_device_description(
void ggml_backend_cann_get_device_description(
int32_t device, char* description, size_t description_size) {
ggml_cann_set_device(device);
const char* soc_name = aclrtGetSocName();
snprintf(description, description_size, "%s", soc_name);
}
GGML_CALL void ggml_backend_cann_get_device_memory(int32_t device, size_t* free,
size_t* total) {
void ggml_backend_cann_get_device_memory(int32_t device, size_t* free,
size_t* total) {
ggml_cann_set_device(device);
ACL_CHECK(aclrtGetMemInfo(ACL_HBM_MEM, free, total));
}
// backend registry
/**
* @brief Initializes a CANN backend based on the provided parameters.
*
* This function initializes a CANN backend using the device index and then
* initializes the backend using `ggml_backend_cann_init`.
*
* @param params Parameters for initialization (unused in this implementation).
* @param user_data User data containing the device index to initialize the
* backend.
* @return ggml_backend_t The initialized CANN backend.
*/
GGML_CALL static ggml_backend_t ggml_backend_reg_cann_init(const char* params,
void* user_data) {
ggml_backend_t cann_backend =
ggml_backend_cann_init((int)(intptr_t)user_data);
return cann_backend;
GGML_UNUSED(params);
}
extern "C" GGML_CALL int ggml_backend_cann_reg_devices();
/**
* @brief Registers CANN (Ascend) devices as backend options.
*
* This function initializes ACL, retrieves the number of available CANN
* devices, and registers each device as a backend option using
* `ggml_backend_register`. Each device is given a unique name based on
* `GGML_CANN_NAME` followed by its index.
*
* @return int The number of CANN devices registered.
*/
GGML_CALL int ggml_backend_cann_reg_devices() {
uint32_t device_count = ggml_backend_cann_get_device_count();
// initialization
for (uint32_t i = 0; i < device_count; i++) {
char name[128];
snprintf(name, sizeof(name), "CANN%d", i);
ggml_backend_register(name, ggml_backend_reg_cann_init,
ggml_backend_cann_buffer_type(i),
(void*)(intptr_t)i);
}
return device_count;
}

556
ggml/src/ggml-cuda.cu
View File

@ -101,11 +101,11 @@ void ggml_cuda_error(const char * stmt, const char * func, const char * file, in
int id = -1; // in case cudaGetDevice fails
cudaGetDevice(&id);
GGML_CUDA_LOG_ERROR("CUDA error: %s\n", msg);
GGML_CUDA_LOG_ERROR(GGML_CUDA_NAME " error: %s\n", msg);
GGML_CUDA_LOG_ERROR(" current device: %d, in function %s at %s:%d\n", id, func, file, line);
GGML_CUDA_LOG_ERROR(" %s\n", stmt);
// abort with GGML_ASSERT to get a stack trace
GGML_ABORT("CUDA error");
// abort with GGML_ABORT to get a stack trace
GGML_ABORT(GGML_CUDA_NAME " error");
}
// this is faster on Windows
@ -329,7 +329,7 @@ struct ggml_cuda_pool_leg : public ggml_cuda_pool {
return;
}
}
GGML_CUDA_LOG_WARN("Cuda buffer pool full, increase MAX_CUDA_BUFFERS\n");
GGML_CUDA_LOG_WARN(GGML_CUDA_NAME " buffer pool full, increase MAX_CUDA_BUFFERS\n");
ggml_cuda_set_device(device);
CUDA_CHECK(cudaFree(ptr));
pool_size -= size;
@ -459,26 +459,26 @@ struct ggml_backend_cuda_buffer_context {
}
};
GGML_CALL static const char * ggml_backend_cuda_buffer_get_name(ggml_backend_buffer_t buffer) {
static const char * ggml_backend_cuda_buffer_get_name(ggml_backend_buffer_t buffer) {
ggml_backend_cuda_buffer_context * ctx = (ggml_backend_cuda_buffer_context *)buffer->context;
return ctx->name.c_str();
}
GGML_CALL static bool ggml_backend_buffer_is_cuda(ggml_backend_buffer_t buffer) {
static bool ggml_backend_buffer_is_cuda(ggml_backend_buffer_t buffer) {
return buffer->iface.get_name == ggml_backend_cuda_buffer_get_name;
}
GGML_CALL static void ggml_backend_cuda_buffer_free_buffer(ggml_backend_buffer_t buffer) {
static void ggml_backend_cuda_buffer_free_buffer(ggml_backend_buffer_t buffer) {
ggml_backend_cuda_buffer_context * ctx = (ggml_backend_cuda_buffer_context *)buffer->context;
delete ctx;
}
GGML_CALL static void * ggml_backend_cuda_buffer_get_base(ggml_backend_buffer_t buffer) {
static void * ggml_backend_cuda_buffer_get_base(ggml_backend_buffer_t buffer) {
ggml_backend_cuda_buffer_context * ctx = (ggml_backend_cuda_buffer_context *)buffer->context;
return ctx->dev_ptr;
}
GGML_CALL static void ggml_backend_cuda_buffer_init_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor) {
static void ggml_backend_cuda_buffer_init_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor) {
ggml_backend_cuda_buffer_context * ctx = (ggml_backend_cuda_buffer_context *)buffer->context;
if (tensor->view_src != NULL) {
@ -498,7 +498,7 @@ GGML_CALL static void ggml_backend_cuda_buffer_init_tensor(ggml_backend_buffer_t
}
}
GGML_CALL static void ggml_backend_cuda_buffer_memset_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, uint8_t value, size_t offset, size_t size) {
static void ggml_backend_cuda_buffer_memset_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, uint8_t value, size_t offset, size_t size) {
ggml_backend_cuda_buffer_context * ctx = (ggml_backend_cuda_buffer_context *)buffer->context;
ggml_cuda_set_device(ctx->device);
@ -506,7 +506,7 @@ GGML_CALL static void ggml_backend_cuda_buffer_memset_tensor(ggml_backend_buffer
CUDA_CHECK(cudaStreamSynchronize(cudaStreamPerThread));
}
GGML_CALL static void ggml_backend_cuda_buffer_set_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
static void ggml_backend_cuda_buffer_set_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
ggml_backend_cuda_buffer_context * ctx = (ggml_backend_cuda_buffer_context *)buffer->context;
ggml_cuda_set_device(ctx->device);
@ -514,7 +514,7 @@ GGML_CALL static void ggml_backend_cuda_buffer_set_tensor(ggml_backend_buffer_t
CUDA_CHECK(cudaStreamSynchronize(cudaStreamPerThread));
}
GGML_CALL static void ggml_backend_cuda_buffer_get_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * tensor, void * data, size_t offset, size_t size) {
static void ggml_backend_cuda_buffer_get_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * tensor, void * data, size_t offset, size_t size) {
ggml_backend_cuda_buffer_context * ctx = (ggml_backend_cuda_buffer_context *)buffer->context;
ggml_cuda_set_device(ctx->device);
@ -522,7 +522,7 @@ GGML_CALL static void ggml_backend_cuda_buffer_get_tensor(ggml_backend_buffer_t
CUDA_CHECK(cudaStreamSynchronize(cudaStreamPerThread));
}
GGML_CALL static bool ggml_backend_cuda_buffer_cpy_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * src, ggml_tensor * dst) {
static bool ggml_backend_cuda_buffer_cpy_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * src, ggml_tensor * dst) {
if (ggml_backend_buffer_is_cuda(src->buffer)) {
ggml_backend_cuda_buffer_context * src_ctx = (ggml_backend_cuda_buffer_context *)src->buffer->context;
ggml_backend_cuda_buffer_context * dst_ctx = (ggml_backend_cuda_buffer_context *)dst->buffer->context;
@ -543,7 +543,7 @@ GGML_CALL static bool ggml_backend_cuda_buffer_cpy_tensor(ggml_backend_buffer_t
GGML_UNUSED(buffer);
}
GGML_CALL static void ggml_backend_cuda_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) {
static void ggml_backend_cuda_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) {
ggml_backend_cuda_buffer_context * ctx = (ggml_backend_cuda_buffer_context *)buffer->context;
ggml_cuda_set_device(ctx->device);
@ -552,7 +552,7 @@ GGML_CALL static void ggml_backend_cuda_buffer_clear(ggml_backend_buffer_t buffe
CUDA_CHECK(cudaDeviceSynchronize());
}
static ggml_backend_buffer_i ggml_backend_cuda_buffer_interface = {
static const ggml_backend_buffer_i ggml_backend_cuda_buffer_interface = {
/* .get_name = */ ggml_backend_cuda_buffer_get_name,
/* .free_buffer = */ ggml_backend_cuda_buffer_free_buffer,
/* .get_base = */ ggml_backend_cuda_buffer_get_base,
@ -571,17 +571,17 @@ struct ggml_backend_cuda_buffer_type_context {
std::string name;
};
GGML_CALL static const char * ggml_backend_cuda_buffer_type_name(ggml_backend_buffer_type_t buft) {
static const char * ggml_backend_cuda_buffer_type_get_name(ggml_backend_buffer_type_t buft) {
ggml_backend_cuda_buffer_type_context * ctx = (ggml_backend_cuda_buffer_type_context *)buft->context;
return ctx->name.c_str();
}
static bool ggml_backend_buft_is_cuda(ggml_backend_buffer_type_t buft) {
return buft->iface.get_name == ggml_backend_cuda_buffer_type_name;
return buft->iface.get_name == ggml_backend_cuda_buffer_type_get_name;
}
GGML_CALL static ggml_backend_buffer_t ggml_backend_cuda_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
static ggml_backend_buffer_t ggml_backend_cuda_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
ggml_backend_cuda_buffer_type_context * buft_ctx = (ggml_backend_cuda_buffer_type_context *)buft->context;
ggml_cuda_set_device(buft_ctx->device);
@ -602,13 +602,13 @@ GGML_CALL static ggml_backend_buffer_t ggml_backend_cuda_buffer_type_alloc_buffe
return ggml_backend_buffer_init(buft, ggml_backend_cuda_buffer_interface, ctx, size);
}
GGML_CALL static size_t ggml_backend_cuda_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
static size_t ggml_backend_cuda_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
return 128;
GGML_UNUSED(buft);
}
GGML_CALL static size_t ggml_backend_cuda_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) {
static size_t ggml_backend_cuda_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) {
size_t size = ggml_nbytes(tensor);
int64_t ne0 = tensor->ne[0];
@ -623,8 +623,8 @@ GGML_CALL static size_t ggml_backend_cuda_buffer_type_get_alloc_size(ggml_backen
GGML_UNUSED(buft);
}
static ggml_backend_buffer_type_i ggml_backend_cuda_buffer_type_interface = {
/* .get_name = */ ggml_backend_cuda_buffer_type_name,
static const ggml_backend_buffer_type_i ggml_backend_cuda_buffer_type_interface = {
/* .get_name = */ ggml_backend_cuda_buffer_type_get_name,
/* .alloc_buffer = */ ggml_backend_cuda_buffer_type_alloc_buffer,
/* .get_alignment = */ ggml_backend_cuda_buffer_type_get_alignment,
/* .get_max_size = */ NULL, // defaults to SIZE_MAX
@ -632,7 +632,7 @@ static ggml_backend_buffer_type_i ggml_backend_cuda_buffer_type_interface = {
/* .is_host = */ NULL,
};
GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_buffer_type(int device) {
ggml_backend_buffer_type_t ggml_backend_cuda_buffer_type(int device) {
static std::mutex mutex;
std::lock_guard<std::mutex> lock(mutex);
@ -645,9 +645,10 @@ GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_buffer_type(int device) {
static bool ggml_backend_cuda_buffer_type_initialized = false;
if (!ggml_backend_cuda_buffer_type_initialized) {
for (int i = 0; i < GGML_CUDA_MAX_DEVICES; i++) {
for (int i = 0; i < ggml_backend_cuda_get_device_count(); i++) {
ggml_backend_cuda_buffer_types[i] = {
/* .iface = */ ggml_backend_cuda_buffer_type_interface,
/* .device = */ ggml_backend_reg_dev_get(ggml_backend_cuda_reg(), i),
/* .context = */ new ggml_backend_cuda_buffer_type_context{i, GGML_CUDA_NAME + std::to_string(i)},
};
}
@ -717,7 +718,7 @@ struct ggml_backend_cuda_split_buffer_context {
std::vector<ggml_tensor_extra_gpu *> tensor_extras;
};
GGML_CALL static const char * ggml_backend_cuda_split_buffer_get_name(ggml_backend_buffer_t buffer) {
static const char * ggml_backend_cuda_split_buffer_get_name(ggml_backend_buffer_t buffer) {
return GGML_CUDA_NAME "_Split";
GGML_UNUSED(buffer);
@ -728,19 +729,19 @@ static bool ggml_backend_buffer_is_cuda_split(ggml_backend_buffer_t buffer) {
GGML_UNUSED(ggml_backend_buffer_is_cuda_split); // only used in debug builds currently, avoid unused function warning in release builds
}
GGML_CALL static void ggml_backend_cuda_split_buffer_free_buffer(ggml_backend_buffer_t buffer) {
static void ggml_backend_cuda_split_buffer_free_buffer(ggml_backend_buffer_t buffer) {
ggml_backend_cuda_split_buffer_context * ctx = (ggml_backend_cuda_split_buffer_context *)buffer->context;
delete ctx;
}
GGML_CALL static void * ggml_backend_cuda_split_buffer_get_base(ggml_backend_buffer_t buffer) {
static void * ggml_backend_cuda_split_buffer_get_base(ggml_backend_buffer_t buffer) {
// the pointers are stored in the tensor extras, this is just a dummy address and never dereferenced
return (void *)0x1000;
GGML_UNUSED(buffer);
}
GGML_CALL static void ggml_backend_cuda_split_buffer_init_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor) {
static void ggml_backend_cuda_split_buffer_init_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor) {
GGML_ASSERT(tensor->view_src == nullptr); // views of split tensors are not supported
ggml_backend_cuda_split_buffer_context * ctx = (ggml_backend_cuda_split_buffer_context *)buffer->context;
@ -788,7 +789,7 @@ GGML_CALL static void ggml_backend_cuda_split_buffer_init_tensor(ggml_backend_bu
tensor->extra = extra;
}
GGML_CALL static void ggml_backend_cuda_split_buffer_set_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
static void ggml_backend_cuda_split_buffer_set_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
// split tensors must always be set in their entirety at once
GGML_ASSERT(offset == 0);
GGML_ASSERT(size == ggml_nbytes(tensor));
@ -826,7 +827,7 @@ GGML_CALL static void ggml_backend_cuda_split_buffer_set_tensor(ggml_backend_buf
}
}
GGML_CALL static void ggml_backend_cuda_split_buffer_get_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * tensor, void * data, size_t offset, size_t size) {
static void ggml_backend_cuda_split_buffer_get_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * tensor, void * data, size_t offset, size_t size) {
// split tensors must always be set in their entirety at once
GGML_ASSERT(offset == 0);
GGML_ASSERT(size == ggml_nbytes(tensor));
@ -864,12 +865,12 @@ GGML_CALL static void ggml_backend_cuda_split_buffer_get_tensor(ggml_backend_buf
}
}
GGML_CALL static void ggml_backend_cuda_split_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) {
static void ggml_backend_cuda_split_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) {
GGML_UNUSED(buffer);
GGML_UNUSED(value);
}
static struct ggml_backend_buffer_i ggml_backend_cuda_split_buffer_interface = {
static const ggml_backend_buffer_i ggml_backend_cuda_split_buffer_interface = {
/* .get_name = */ ggml_backend_cuda_split_buffer_get_name,
/* .free_buffer = */ ggml_backend_cuda_split_buffer_free_buffer,
/* .get_base = */ ggml_backend_cuda_split_buffer_get_base,
@ -884,17 +885,17 @@ static struct ggml_backend_buffer_i ggml_backend_cuda_split_buffer_interface = {
// cuda split buffer type
GGML_CALL static const char * ggml_backend_cuda_split_buffer_type_name(ggml_backend_buffer_type_t buft) {
static const char * ggml_backend_cuda_split_buffer_type_get_name(ggml_backend_buffer_type_t buft) {
return GGML_CUDA_NAME "_Split";
GGML_UNUSED(buft);
}
static bool ggml_backend_buft_is_cuda_split(ggml_backend_buffer_type_t buft) {
return buft->iface.get_name == ggml_backend_cuda_split_buffer_type_name;
return buft->iface.get_name == ggml_backend_cuda_split_buffer_type_get_name;
}
GGML_CALL static ggml_backend_buffer_t ggml_backend_cuda_split_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
static ggml_backend_buffer_t ggml_backend_cuda_split_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
// since we don't know the exact split after rounding, we cannot allocate the device buffers at this point
// instead, we allocate them for each tensor separately in init_tensor
// however, the size still represents the maximum cumulative size of all the device buffers after the tensors are allocated,
@ -904,13 +905,13 @@ GGML_CALL static ggml_backend_buffer_t ggml_backend_cuda_split_buffer_type_alloc
return ggml_backend_buffer_init(buft, ggml_backend_cuda_split_buffer_interface, ctx, size);
}
GGML_CALL static size_t ggml_backend_cuda_split_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
static size_t ggml_backend_cuda_split_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
return 128;
GGML_UNUSED(buft);
}
GGML_CALL static size_t ggml_backend_cuda_split_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) {
static size_t ggml_backend_cuda_split_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) {
ggml_backend_cuda_split_buffer_type_context * ctx = (ggml_backend_cuda_split_buffer_type_context *)buft->context;
size_t total_size = 0;
@ -937,14 +938,14 @@ GGML_CALL static size_t ggml_backend_cuda_split_buffer_type_get_alloc_size(ggml_
return total_size;
}
GGML_CALL static bool ggml_backend_cuda_split_buffer_type_is_host(ggml_backend_buffer_type_t buft) {
static bool ggml_backend_cuda_split_buffer_type_is_host(ggml_backend_buffer_type_t buft) {
return false;
GGML_UNUSED(buft);
}
static ggml_backend_buffer_type_i ggml_backend_cuda_split_buffer_type_interface = {
/* .get_name = */ ggml_backend_cuda_split_buffer_type_name,
static const ggml_backend_buffer_type_i ggml_backend_cuda_split_buffer_type_interface = {
/* .get_name = */ ggml_backend_cuda_split_buffer_type_get_name,
/* .alloc_buffer = */ ggml_backend_cuda_split_buffer_type_alloc_buffer,
/* .get_alignment = */ ggml_backend_cuda_split_buffer_type_get_alignment,
/* .get_max_size = */ NULL, // defaults to SIZE_MAX
@ -952,7 +953,7 @@ static ggml_backend_buffer_type_i ggml_backend_cuda_split_buffer_type_interface
/* .is_host = */ ggml_backend_cuda_split_buffer_type_is_host,
};
GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_split_buffer_type(const float * tensor_split) {
ggml_backend_buffer_type_t ggml_backend_cuda_split_buffer_type(const float * tensor_split) {
static std::mutex mutex;
std::lock_guard<std::mutex> lock(mutex);
@ -981,6 +982,7 @@ GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_split_buffer_type(const f
struct ggml_backend_buffer_type buft {
/* .iface = */ ggml_backend_cuda_split_buffer_type_interface,
/* .device = */ ggml_backend_reg_dev_get(ggml_backend_cuda_reg(), 0),
/* .context = */ new ggml_backend_cuda_split_buffer_type_context{tensor_split_arr},
};
@ -990,19 +992,19 @@ GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_split_buffer_type(const f
// host buffer type
GGML_CALL static const char * ggml_backend_cuda_host_buffer_type_name(ggml_backend_buffer_type_t buft) {
static const char * ggml_backend_cuda_host_buffer_type_name(ggml_backend_buffer_type_t buft) {
return GGML_CUDA_NAME "_Host";
GGML_UNUSED(buft);
}
GGML_CALL static const char * ggml_backend_cuda_host_buffer_name(ggml_backend_buffer_t buffer) {
static const char * ggml_backend_cuda_host_buffer_name(ggml_backend_buffer_t buffer) {
return GGML_CUDA_NAME "_Host";
GGML_UNUSED(buffer);
}
GGML_CALL static void ggml_backend_cuda_host_buffer_free_buffer(ggml_backend_buffer_t buffer) {
static void ggml_backend_cuda_host_buffer_free_buffer(ggml_backend_buffer_t buffer) {
CUDA_CHECK(cudaFreeHost(buffer->context));
}
@ -1024,7 +1026,7 @@ static void * ggml_cuda_host_malloc(size_t size) {
return ptr;
}
GGML_CALL static ggml_backend_buffer_t ggml_backend_cuda_host_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
static ggml_backend_buffer_t ggml_backend_cuda_host_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
void * ptr = ggml_cuda_host_malloc(size);
if (ptr == nullptr) {
@ -1040,7 +1042,7 @@ GGML_CALL static ggml_backend_buffer_t ggml_backend_cuda_host_buffer_type_alloc_
return buffer;
}
GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_host_buffer_type() {
ggml_backend_buffer_type_t ggml_backend_cuda_host_buffer_type() {
static struct ggml_backend_buffer_type ggml_backend_cuda_buffer_type_host = {
/* .iface = */ {
/* .get_name = */ ggml_backend_cuda_host_buffer_type_name,
@ -1050,6 +1052,7 @@ GGML_CALL ggml_backend_buffer_type_t ggml_backend_cuda_host_buffer_type() {
/* .get_alloc_size = */ ggml_backend_cpu_buffer_type()->iface.get_alloc_size,
/* .is_host = */ ggml_backend_cpu_buffer_type()->iface.is_host,
},
/* .device = */ ggml_backend_reg_dev_get(ggml_backend_cuda_reg(), 0),
/* .context = */ nullptr,
};
@ -2383,26 +2386,26 @@ static bool ggml_cuda_compute_forward(ggml_backend_cuda_context & ctx, struct gg
// backend
GGML_CALL static const char * ggml_backend_cuda_name(ggml_backend_t backend) {
static const char * ggml_backend_cuda_get_name(ggml_backend_t backend) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
return cuda_ctx->name.c_str();
}
GGML_CALL static void ggml_backend_cuda_free(ggml_backend_t backend) {
static void ggml_backend_cuda_free(ggml_backend_t backend) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
delete cuda_ctx;
delete backend;
}
GGML_CALL static ggml_backend_buffer_type_t ggml_backend_cuda_get_default_buffer_type(ggml_backend_t backend) {
static ggml_backend_buffer_type_t ggml_backend_cuda_get_default_buffer_type(ggml_backend_t backend) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
return ggml_backend_cuda_buffer_type(cuda_ctx->device);
}
GGML_CALL static void ggml_backend_cuda_set_tensor_async(ggml_backend_t backend, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
static void ggml_backend_cuda_set_tensor_async(ggml_backend_t backend, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
ggml_backend_buffer_t buf = tensor->view_src ? tensor->view_src->buffer : tensor->buffer;
@ -2411,7 +2414,7 @@ GGML_CALL static void ggml_backend_cuda_set_tensor_async(ggml_backend_t backend,
CUDA_CHECK(cudaMemcpyAsync((char *)tensor->data + offset, data, size, cudaMemcpyHostToDevice, cuda_ctx->stream()));
}
GGML_CALL static void ggml_backend_cuda_get_tensor_async(ggml_backend_t backend, const ggml_tensor * tensor, void * data, size_t offset, size_t size) {
static void ggml_backend_cuda_get_tensor_async(ggml_backend_t backend, const ggml_tensor * tensor, void * data, size_t offset, size_t size) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
ggml_backend_buffer_t buf = tensor->view_src ? tensor->view_src->buffer : tensor->buffer;
@ -2420,7 +2423,7 @@ GGML_CALL static void ggml_backend_cuda_get_tensor_async(ggml_backend_t backend,
CUDA_CHECK(cudaMemcpyAsync(data, (const char *)tensor->data + offset, size, cudaMemcpyDeviceToHost, cuda_ctx->stream()));
}
GGML_CALL static bool ggml_backend_cuda_cpy_tensor_async(ggml_backend_t backend_src, ggml_backend_t backend_dst, const ggml_tensor * src, ggml_tensor * dst) {
static bool ggml_backend_cuda_cpy_tensor_async(ggml_backend_t backend_src, ggml_backend_t backend_dst, const ggml_tensor * src, ggml_tensor * dst) {
ggml_backend_buffer_t buf_src = src->view_src ? src->view_src->buffer : src->buffer;
ggml_backend_buffer_t buf_dst = dst->view_src ? dst->view_src->buffer : dst->buffer;
@ -2475,7 +2478,7 @@ GGML_CALL static bool ggml_backend_cuda_cpy_tensor_async(ggml_backend_t backend_
return true;
}
GGML_CALL static void ggml_backend_cuda_synchronize(ggml_backend_t backend) {
static void ggml_backend_cuda_synchronize(ggml_backend_t backend) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
CUDA_CHECK(cudaStreamSynchronize(cuda_ctx->stream()));
@ -2534,7 +2537,7 @@ static bool ggml_graph_node_has_matching_properties(ggml_tensor * node, ggml_gra
return true;
}
GGML_CALL static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t backend, ggml_cgraph * cgraph) {
static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t backend, ggml_cgraph * cgraph) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
ggml_cuda_set_device(cuda_ctx->device);
@ -2806,8 +2809,187 @@ GGML_CALL static enum ggml_status ggml_backend_cuda_graph_compute(ggml_backend_t
return GGML_STATUS_SUCCESS;
}
GGML_CALL static bool ggml_backend_cuda_supports_op(ggml_backend_t backend, const ggml_tensor * op) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *) backend->context;
static void ggml_backend_cuda_event_record(ggml_backend_t backend, ggml_backend_event_t event) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
CUDA_CHECK(cudaEventRecord((cudaEvent_t)event->context, cuda_ctx->stream()));
}
static void ggml_backend_cuda_event_wait(ggml_backend_t backend, ggml_backend_event_t event) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
if (ggml_backend_is_cuda(backend)) {
CUDA_CHECK(cudaStreamWaitEvent(cuda_ctx->stream(), (cudaEvent_t)event->context, 0));
} else {
#if 0
// untested
auto wait_fn = [](void * user_data) {
ggml_backend_event_t event = (ggml_backend_event_t)user_data;
ggml_backend_event_synchronize(event);
};
CUDA_CHECK(cudaLaunchHostFunc(cuda_ctx->stream(), wait_fn, event));
#endif
GGML_ABORT("fatal error");
}
}
static const ggml_backend_i ggml_backend_cuda_interface = {
/* .get_name = */ ggml_backend_cuda_get_name,
/* .free = */ ggml_backend_cuda_free,
/* .get_default_buffer_type = */ ggml_backend_cuda_get_default_buffer_type,
/* .set_tensor_async = */ ggml_backend_cuda_set_tensor_async,
/* .get_tensor_async = */ ggml_backend_cuda_get_tensor_async,
/* .cpy_tensor_async = */ ggml_backend_cuda_cpy_tensor_async,
/* .synchronize = */ ggml_backend_cuda_synchronize,
/* .graph_plan_create = */ NULL,
/* .graph_plan_free = */ NULL,
/* .graph_plan_update = */ NULL,
/* .graph_plan_compute = */ NULL,
/* .graph_compute = */ ggml_backend_cuda_graph_compute,
/* .supports_op = */ NULL, // moved to device
/* .supports_buft = */ NULL, // moved to device
/* .offload_op = */ NULL, // moved to device
/* .event_record = */ ggml_backend_cuda_event_record,
/* .event_wait = */ ggml_backend_cuda_event_wait,
};
static ggml_guid_t ggml_backend_cuda_guid() {
static ggml_guid guid = { 0x2c, 0xdd, 0xe8, 0x1c, 0x65, 0xb3, 0x65, 0x73, 0x6a, 0x12, 0x88, 0x61, 0x1c, 0xc9, 0xdc, 0x25 };
return &guid;
}
bool ggml_backend_is_cuda(ggml_backend_t backend) {
return backend != NULL && ggml_guid_matches(backend->guid, ggml_backend_cuda_guid());
}
int ggml_backend_cuda_get_device_count() {
return ggml_cuda_info().device_count;
}
void ggml_backend_cuda_get_device_description(int device, char * description, size_t description_size) {
cudaDeviceProp prop;
CUDA_CHECK(cudaGetDeviceProperties(&prop, device));
snprintf(description, description_size, "%s", prop.name);
}
void ggml_backend_cuda_get_device_memory(int device, size_t * free, size_t * total) {
ggml_cuda_set_device(device);
CUDA_CHECK(cudaMemGetInfo(free, total));
}
bool ggml_backend_cuda_register_host_buffer(void * buffer, size_t size) {
if (getenv("GGML_CUDA_REGISTER_HOST") == nullptr) {
return false;
}
#if CUDART_VERSION >= 11100 || defined(GGML_USE_MUSA)
cudaError_t err = cudaHostRegister(buffer, size, cudaHostRegisterPortable | cudaHostRegisterReadOnly);
if (err != cudaSuccess) {
// clear the error
cudaGetLastError();
GGML_CUDA_LOG_WARN("%s: failed to register %.2f MiB of pinned memory: %s\n", __func__,
size / 1024.0 / 1024.0, cudaGetErrorString(err));
return false;
}
return true;
#else
return false;
#endif
}
void ggml_backend_cuda_unregister_host_buffer(void * buffer) {
if (getenv("GGML_CUDA_REGISTER_HOST") == nullptr) {
return;
}
cudaError_t err = cudaHostUnregister(buffer);
if (err != cudaSuccess) {
// clear the error
cudaGetLastError();
}
}
// backend device
struct ggml_backend_cuda_device_context {
int device;
std::string name;
std::string description;
};
static const char * ggml_backend_cuda_device_get_name(ggml_backend_dev_t dev) {
ggml_backend_cuda_device_context * ctx = (ggml_backend_cuda_device_context *)dev->context;
return ctx->name.c_str();
}
static const char * ggml_backend_cuda_device_get_description(ggml_backend_dev_t dev) {
ggml_backend_cuda_device_context * ctx = (ggml_backend_cuda_device_context *)dev->context;
return ctx->description.c_str();
}
static void ggml_backend_cuda_device_get_memory(ggml_backend_dev_t dev, size_t * free, size_t * total) {
ggml_backend_cuda_device_context * ctx = (ggml_backend_cuda_device_context *)dev->context;
ggml_cuda_set_device(ctx->device);
CUDA_CHECK(cudaMemGetInfo(free, total));
}
static enum ggml_backend_dev_type ggml_backend_cuda_device_get_type(ggml_backend_dev_t dev) {
GGML_UNUSED(dev);
return GGML_BACKEND_DEVICE_TYPE_GPU_FULL;
}
static void ggml_backend_cuda_device_get_props(ggml_backend_dev_t dev, ggml_backend_dev_props * props) {
props->name = ggml_backend_cuda_device_get_name(dev);
props->description = ggml_backend_cuda_device_get_description(dev);
props->type = ggml_backend_cuda_device_get_type(dev);
ggml_backend_cuda_device_get_memory(dev, &props->memory_free, &props->memory_total);
bool host_buffer = getenv("GGML_CUDA_NO_PINNED") == nullptr;
#ifdef GGML_CUDA_NO_PEER_COPY
bool events = false;
#else
bool events = true;
#endif
props->caps = {
/* async */ true,
/* host_buffer */ host_buffer,
/* events */ events,
};
}
static ggml_backend_t ggml_backend_cuda_device_init(ggml_backend_dev_t dev, const char * params) {
GGML_UNUSED(params);
ggml_backend_cuda_device_context * ctx = (ggml_backend_cuda_device_context *)dev->context;
return ggml_backend_cuda_init(ctx->device);
}
static ggml_backend_buffer_type_t ggml_backend_cuda_device_get_buffer_type(ggml_backend_dev_t dev) {
ggml_backend_cuda_device_context * ctx = (ggml_backend_cuda_device_context *)dev->context;
return ggml_backend_cuda_buffer_type(ctx->device);
}
static ggml_backend_buffer_type_t ggml_backend_cuda_device_get_host_buffer_type(ggml_backend_dev_t dev) {
GGML_UNUSED(dev);
return ggml_backend_cuda_host_buffer_type();
}
static ggml_backend_buffer_t ggml_backend_cuda_device_buffer_from_host_ptr(ggml_backend_dev_t dev, void * ptr, size_t size, size_t max_tensor_size) {
GGML_UNUSED(dev);
GGML_UNUSED(ptr);
GGML_UNUSED(size);
GGML_UNUSED(max_tensor_size);
return nullptr;
}
// TODO: move these functions here
static bool ggml_backend_cuda_device_supports_op(ggml_backend_dev_t dev, const ggml_tensor * op) {
ggml_backend_cuda_device_context * dev_ctx = (ggml_backend_cuda_device_context *) dev->context;
switch (op->op) {
case GGML_OP_UNARY:
switch (ggml_get_unary_op(op)) {
@ -3021,7 +3203,7 @@ GGML_CALL static bool ggml_backend_cuda_supports_op(ggml_backend_t backend, cons
if (op->src[0]->ne[0] == 256 && op->src[1]->type == GGML_TYPE_F16 && op->src[2]->type == GGML_TYPE_F16) {
return true;
}
const int cc = ggml_cuda_info().devices[cuda_ctx->device].cc;
const int cc = ggml_cuda_info().devices[dev_ctx->device].cc;
return cc >= CC_VOLTA && cc < CC_OFFSET_AMD && op->src[1]->type == GGML_TYPE_F16 && op->src[2]->type == GGML_TYPE_F16;
}
case GGML_OP_CROSS_ENTROPY_LOSS:
@ -3031,115 +3213,170 @@ GGML_CALL static bool ggml_backend_cuda_supports_op(ggml_backend_t backend, cons
default:
return false;
}
GGML_UNUSED(backend);
}
GGML_CALL static bool ggml_backend_cuda_supports_buft(ggml_backend_t backend, ggml_backend_buffer_type_t buft) {
static bool ggml_backend_cuda_device_supports_buft(ggml_backend_dev_t dev, ggml_backend_buffer_type_t buft) {
if (ggml_backend_buft_is_cuda_split(buft)) {
return true;
}
if (ggml_backend_buft_is_cuda(buft)) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
ggml_backend_cuda_device_context * dev_ctx = (ggml_backend_cuda_device_context *)dev->context;
ggml_backend_cuda_buffer_type_context * buft_ctx = (ggml_backend_cuda_buffer_type_context *)buft->context;
return buft_ctx->device == cuda_ctx->device;
return buft_ctx->device == dev_ctx->device;
}
return false;
}
GGML_CALL static bool ggml_backend_cuda_offload_op(ggml_backend_t backend, const ggml_tensor * op) {
static bool ggml_backend_cuda_device_offload_op(ggml_backend_dev_t dev, const ggml_tensor * op) {
const int min_batch_size = 32;
return (op->ne[1] >= min_batch_size && op->op != GGML_OP_GET_ROWS) ||
(op->ne[2] >= min_batch_size && op->op == GGML_OP_MUL_MAT_ID);
GGML_UNUSED(backend);
GGML_UNUSED(dev);
}
static ggml_backend_event_t ggml_backend_cuda_event_new(ggml_backend_t backend) {
static ggml_backend_event_t ggml_backend_cuda_device_event_new(ggml_backend_dev_t dev) {
#ifdef GGML_CUDA_NO_PEER_COPY
return nullptr;
#else
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
ggml_backend_cuda_device_context * dev_ctx = (ggml_backend_cuda_device_context *)dev->context;
ggml_cuda_set_device(cuda_ctx->device);
ggml_cuda_set_device(dev_ctx->device);
cudaEvent_t event;
CUDA_CHECK(cudaEventCreateWithFlags(&event, cudaEventDisableTiming));
return new ggml_backend_event {
/* .backend = */ backend,
/* .device = */ dev,
/* .context = */ event,
};
#endif
}
static void ggml_backend_cuda_event_free(ggml_backend_event_t event) {
CUDA_CHECK(cudaEventDestroy((cudaEvent_t)event->context));
static void ggml_backend_cuda_device_event_free(ggml_backend_dev_t dev, ggml_backend_event_t event) {
GGML_UNUSED(dev);
CUDA_CHECK(cudaEventDestroy((cudaEvent_t)event->context));
delete event;
}
static void ggml_backend_cuda_event_record(ggml_backend_event_t event) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)event->backend->context;
CUDA_CHECK(cudaEventRecord((cudaEvent_t)event->context, cuda_ctx->stream()));
}
static void ggml_backend_cuda_event_wait(ggml_backend_t backend, ggml_backend_event_t event) {
ggml_backend_cuda_context * cuda_ctx = (ggml_backend_cuda_context *)backend->context;
if (ggml_backend_is_cuda(event->backend)) {
CUDA_CHECK(cudaStreamWaitEvent(cuda_ctx->stream(), (cudaEvent_t)event->context, 0));
} else {
#if 0
// untested
auto wait_fn = [](void * user_data) {
ggml_backend_event_t event = (ggml_backend_event_t)user_data;
ggml_backend_event_synchronize(event);
};
CUDA_CHECK(cudaLaunchHostFunc(cuda_ctx->stream(), wait_fn, event));
#endif
GGML_ABORT("fatal error");
}
}
static void ggml_backend_cuda_event_synchronize(ggml_backend_event_t event) {
static void ggml_backend_cuda_device_event_synchronize(ggml_backend_dev_t dev, ggml_backend_event_t event) {
GGML_UNUSED(dev);
CUDA_CHECK(cudaEventSynchronize((cudaEvent_t)event->context));
}
static ggml_backend_i ggml_backend_cuda_interface = {
/* .get_name = */ ggml_backend_cuda_name,
/* .free = */ ggml_backend_cuda_free,
/* .get_default_buffer_type = */ ggml_backend_cuda_get_default_buffer_type,
/* .set_tensor_async = */ ggml_backend_cuda_set_tensor_async,
/* .get_tensor_async = */ ggml_backend_cuda_get_tensor_async,
/* .cpy_tensor_async = */ ggml_backend_cuda_cpy_tensor_async,
/* .synchronize = */ ggml_backend_cuda_synchronize,
/* .graph_plan_create = */ NULL,
/* .graph_plan_free = */ NULL,
/* .graph_plan_update = */ NULL,
/* .graph_plan_compute = */ NULL,
/* .graph_compute = */ ggml_backend_cuda_graph_compute,
/* .supports_op = */ ggml_backend_cuda_supports_op,
/* .supports_buft = */ ggml_backend_cuda_supports_buft,
/* .offload_op = */ ggml_backend_cuda_offload_op,
/* .event_new = */ ggml_backend_cuda_event_new,
/* .event_free = */ ggml_backend_cuda_event_free,
/* .event_record = */ ggml_backend_cuda_event_record,
/* .event_wait = */ ggml_backend_cuda_event_wait,
/* .event_synchronize = */ ggml_backend_cuda_event_synchronize,
static const ggml_backend_device_i ggml_backend_cuda_device_interface = {
/* .get_name = */ ggml_backend_cuda_device_get_name,
/* .get_description = */ ggml_backend_cuda_device_get_description,
/* .get_memory = */ ggml_backend_cuda_device_get_memory,
/* .get_type = */ ggml_backend_cuda_device_get_type,
/* .get_props = */ ggml_backend_cuda_device_get_props,
/* .init_backend = */ ggml_backend_cuda_device_init,
/* .get_buffer_type = */ ggml_backend_cuda_device_get_buffer_type,
/* .get_host_buffer_type = */ ggml_backend_cuda_device_get_host_buffer_type,
/* .buffer_from_host_ptr = */ ggml_backend_cuda_device_buffer_from_host_ptr,
/* .supports_op = */ ggml_backend_cuda_device_supports_op,
/* .supports_buft = */ ggml_backend_cuda_device_supports_buft,
/* .offload_op = */ ggml_backend_cuda_device_offload_op,
/* .event_new = */ ggml_backend_cuda_device_event_new,
/* .event_free = */ ggml_backend_cuda_device_event_free,
/* .event_synchronize = */ ggml_backend_cuda_device_event_synchronize,
};
static ggml_guid_t ggml_backend_cuda_guid() {
static ggml_guid guid = { 0x2c, 0xdd, 0xe8, 0x1c, 0x65, 0xb3, 0x65, 0x73, 0x6a, 0x12, 0x88, 0x61, 0x1c, 0xc9, 0xdc, 0x25 };
return &guid;
// backend reg
struct ggml_backend_cuda_reg_context {
std::vector<ggml_backend_dev_t> devices;
};
static const char * ggml_backend_cuda_reg_get_name(ggml_backend_reg_t reg) {
GGML_UNUSED(reg);
return GGML_CUDA_NAME;
}
GGML_CALL ggml_backend_t ggml_backend_cuda_init(int device) {
static size_t ggml_backend_cuda_reg_get_device_count(ggml_backend_reg_t reg) {
ggml_backend_cuda_reg_context * ctx = (ggml_backend_cuda_reg_context *)reg->context;
return ctx->devices.size();
}
static ggml_backend_dev_t ggml_backend_cuda_reg_get_device(ggml_backend_reg_t reg, size_t index) {
ggml_backend_cuda_reg_context * ctx = (ggml_backend_cuda_reg_context *)reg->context;
GGML_ASSERT(index < ctx->devices.size());
return ctx->devices[index];
}
static void * ggml_backend_cuda_reg_get_proc_address(ggml_backend_reg_t reg, const char * name) {
GGML_UNUSED(reg);
if (strcmp(name, "ggml_backend_split_buffer_type") == 0) {
return (void *)ggml_backend_cuda_split_buffer_type;
}
if (strcmp(name, "ggml_backend_register_host_buffer") == 0) {
return (void *)ggml_backend_cuda_register_host_buffer;
}
if (strcmp(name, "ggml_backend_unregister_host_buffer") == 0) {
return (void *)ggml_backend_cuda_unregister_host_buffer;
}
return nullptr;
}
static void ggml_backend_cuda_reg_set_log_callback(ggml_backend_reg_t reg, ggml_log_callback log_callback, void * user_data) {
GGML_UNUSED(reg);
ggml_backend_cuda_log_set_callback(log_callback, user_data);
}
static const ggml_backend_reg_i ggml_backend_cuda_reg_interface = {
/* .get_name = */ ggml_backend_cuda_reg_get_name,
/* .get_device_count = */ ggml_backend_cuda_reg_get_device_count,
/* .get_device_get = */ ggml_backend_cuda_reg_get_device,
/* .get_proc_address = */ ggml_backend_cuda_reg_get_proc_address,
/* .set_log_callback = */ ggml_backend_cuda_reg_set_log_callback,
};
// backend registry
ggml_backend_reg_t ggml_backend_cuda_reg() {
static ggml_backend_reg reg;
static bool initialized = false;
{
static std::mutex mutex;
std::lock_guard<std::mutex> lock(mutex);
if (!initialized) {
ggml_backend_cuda_reg_context * ctx = new ggml_backend_cuda_reg_context;
for (int i = 0; i < ggml_cuda_info().device_count; i++) {
ggml_backend_cuda_device_context * dev_ctx = new ggml_backend_cuda_device_context;
dev_ctx->device = i;
dev_ctx->name = GGML_CUDA_NAME + std::to_string(i);
ggml_cuda_set_device(i);
cudaDeviceProp prop;
CUDA_CHECK(cudaGetDeviceProperties(&prop, i));
dev_ctx->description = prop.name;
ggml_backend_dev_t dev = new ggml_backend_device {
/* .interface = */ ggml_backend_cuda_device_interface,
/* .reg = */ &reg,
/* .context = */ dev_ctx
};
ctx->devices.push_back(dev);
}
reg = ggml_backend_reg {
/* .interface = */ ggml_backend_cuda_reg_interface,
/* .context = */ ctx
};
}
initialized = true;
}
return &reg;
}
ggml_backend_t ggml_backend_cuda_init(int device) {
if (device < 0 || device >= ggml_backend_cuda_get_device_count()) {
GGML_CUDA_LOG_ERROR("%s: invalid device %d\n", __func__, device);
return nullptr;
@ -3154,82 +3391,9 @@ GGML_CALL ggml_backend_t ggml_backend_cuda_init(int device) {
ggml_backend_t cuda_backend = new ggml_backend {
/* .guid = */ ggml_backend_cuda_guid(),
/* .interface = */ ggml_backend_cuda_interface,
/* .context = */ ctx
/* .device = */ ggml_backend_reg_dev_get(ggml_backend_cuda_reg(), device),
/* .context = */ ctx,
};
return cuda_backend;
}
GGML_CALL bool ggml_backend_is_cuda(ggml_backend_t backend) {
return backend != NULL && ggml_guid_matches(backend->guid, ggml_backend_cuda_guid());
}
GGML_CALL int ggml_backend_cuda_get_device_count() {
return ggml_cuda_info().device_count;
}
GGML_CALL void ggml_backend_cuda_get_device_description(int device, char * description, size_t description_size) {
cudaDeviceProp prop;
CUDA_CHECK(cudaGetDeviceProperties(&prop, device));
snprintf(description, description_size, "%s", prop.name);
}
GGML_CALL void ggml_backend_cuda_get_device_memory(int device, size_t * free, size_t * total) {
ggml_cuda_set_device(device);
CUDA_CHECK(cudaMemGetInfo(free, total));
}
GGML_CALL bool ggml_backend_cuda_register_host_buffer(void * buffer, size_t size) {
if (getenv("GGML_CUDA_REGISTER_HOST") == nullptr) {
return false;
}
#if CUDART_VERSION >= 11100 || defined(GGML_USE_MUSA)
cudaError_t err = cudaHostRegister(buffer, size, cudaHostRegisterPortable | cudaHostRegisterReadOnly);
if (err != cudaSuccess) {
// clear the error
cudaGetLastError();
GGML_CUDA_LOG_WARN("%s: failed to register %.2f MiB of pinned memory: %s\n", __func__,
size / 1024.0 / 1024.0, cudaGetErrorString(err));
return false;
}
return true;
#else
return false;
#endif
}
GGML_CALL void ggml_backend_cuda_unregister_host_buffer(void * buffer) {
if (getenv("GGML_CUDA_REGISTER_HOST") == nullptr) {
return;
}
cudaError_t err = cudaHostUnregister(buffer);
if (err != cudaSuccess) {
// clear the error
cudaGetLastError();
}
}
// backend registry
GGML_CALL static ggml_backend_t ggml_backend_reg_cuda_init(const char * params, void * user_data) {
ggml_backend_t cuda_backend = ggml_backend_cuda_init((int) (intptr_t) user_data);
return cuda_backend;
GGML_UNUSED(params);
}
extern "C" GGML_CALL int ggml_backend_cuda_reg_devices();
GGML_CALL int ggml_backend_cuda_reg_devices() {
int device_count = ggml_backend_cuda_get_device_count();
//int device_count = 1; // DEBUG: some tools require delaying CUDA initialization
for (int i = 0; i < device_count; i++) {
char name[128];
snprintf(name, sizeof(name), "%s%d", GGML_CUDA_NAME, i);
ggml_backend_register(name, ggml_backend_reg_cuda_init, ggml_backend_cuda_buffer_type(i), (void *) (intptr_t) i);
}
return device_count;
}

25
ggml/src/ggml-kompute.cpp
View File

@ -1921,6 +1921,7 @@ ggml_backend_buffer_type_t ggml_backend_kompute_buffer_type(int device) {
for (const auto & dev : devices) {
vec.push_back({
/* .iface = */ ggml_backend_kompute_buffer_type_interface,
/* .device = */ nullptr,
/* .context = */ new ggml_backend_kompute_buffer_type_context(dev.index, dev.bufferAlignment, dev.maxAlloc)
});
}
@ -1989,11 +1990,8 @@ static struct ggml_backend_i kompute_backend_i = {
/* .supports_op = */ ggml_backend_kompute_supports_op,
/* .supports_buft = */ ggml_backend_kompute_supports_buft,
/* .offload_op = */ NULL,
/* .event_new = */ NULL,
/* .event_free = */ NULL,
/* .event_record = */ NULL,
/* .event_wait = */ NULL,
/* .event_synchronize = */ NULL,
};
static ggml_guid_t ggml_backend_kompute_guid() {
@ -2008,6 +2006,7 @@ ggml_backend_t ggml_backend_kompute_init(int device) {
ggml_backend_t kompute_backend = new ggml_backend {
/* .guid = */ ggml_backend_kompute_guid(),
/* .interface = */ kompute_backend_i,
/* .device = */ nullptr,
/* .context = */ s_kompute_context,
};
@ -2017,23 +2016,3 @@ ggml_backend_t ggml_backend_kompute_init(int device) {
bool ggml_backend_is_kompute(ggml_backend_t backend) {
return backend != NULL && ggml_guid_matches(backend->guid, ggml_backend_kompute_guid());
}
static ggml_backend_t ggml_backend_reg_kompute_init(const char * params, void * user_data) {
GGML_UNUSED(params);
return ggml_backend_kompute_init(intptr_t(user_data));
}
extern "C" int ggml_backend_kompute_reg_devices();
int ggml_backend_kompute_reg_devices() {
auto devices = ggml_vk_available_devices_internal(0);
for (const auto & device : devices) {
ggml_backend_register(
ggml_kompute_format_name(device.index).c_str(),
ggml_backend_reg_kompute_init,
ggml_backend_kompute_buffer_type(device.index),
reinterpret_cast<void *>(intptr_t(device.index))
);
}
return devices.size();
}

49
ggml/src/ggml-metal.m
View File

@ -3201,13 +3201,13 @@ static void ggml_backend_metal_free_device(void) {
}
}
GGML_CALL static const char * ggml_backend_metal_buffer_get_name(ggml_backend_buffer_t buffer) {
static const char * ggml_backend_metal_buffer_get_name(ggml_backend_buffer_t buffer) {
return "Metal";
UNUSED(buffer);
}
GGML_CALL static void ggml_backend_metal_buffer_free_buffer(ggml_backend_buffer_t buffer) {
static void ggml_backend_metal_buffer_free_buffer(ggml_backend_buffer_t buffer) {
struct ggml_backend_metal_buffer_context * ctx = (struct ggml_backend_metal_buffer_context *)buffer->context;
for (int i = 0; i < ctx->n_buffers; i++) {
@ -3226,25 +3226,25 @@ GGML_CALL static void ggml_backend_metal_buffer_free_buffer(ggml_backend_buffer_
free(ctx);
}
GGML_CALL static void * ggml_backend_metal_buffer_get_base(ggml_backend_buffer_t buffer) {
static void * ggml_backend_metal_buffer_get_base(ggml_backend_buffer_t buffer) {
struct ggml_backend_metal_buffer_context * ctx = (struct ggml_backend_metal_buffer_context *)buffer->context;
return ctx->all_data;
}
GGML_CALL static void ggml_backend_metal_buffer_set_tensor(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
static void ggml_backend_metal_buffer_set_tensor(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
memcpy((char *)tensor->data + offset, data, size);
UNUSED(buffer);
}
GGML_CALL static void ggml_backend_metal_buffer_get_tensor(ggml_backend_buffer_t buffer, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size) {
static void ggml_backend_metal_buffer_get_tensor(ggml_backend_buffer_t buffer, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size) {
memcpy(data, (const char *)tensor->data + offset, size);
UNUSED(buffer);
}
GGML_CALL static bool ggml_backend_metal_buffer_cpy_tensor(ggml_backend_buffer_t buffer, const struct ggml_tensor * src, struct ggml_tensor * dst) {
static bool ggml_backend_metal_buffer_cpy_tensor(ggml_backend_buffer_t buffer, const struct ggml_tensor * src, struct ggml_tensor * dst) {
if (ggml_backend_buffer_is_host(src->buffer)) {
memcpy(dst->data, src->data, ggml_nbytes(src));
return true;
@ -3254,7 +3254,7 @@ GGML_CALL static bool ggml_backend_metal_buffer_cpy_tensor(ggml_backend_buffer_t
UNUSED(buffer);
}
GGML_CALL static void ggml_backend_metal_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) {
static void ggml_backend_metal_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) {
struct ggml_backend_metal_buffer_context * ctx = (struct ggml_backend_metal_buffer_context *)buffer->context;
memset(ctx->all_data, value, ctx->all_size);
@ -3275,7 +3275,7 @@ static struct ggml_backend_buffer_i ggml_backend_metal_buffer_i = {
// default buffer type
GGML_CALL static const char * ggml_backend_metal_buffer_type_get_name(ggml_backend_buffer_type_t buft) {
static const char * ggml_backend_metal_buffer_type_get_name(ggml_backend_buffer_type_t buft) {
return "Metal";
UNUSED(buft);
@ -3306,7 +3306,7 @@ static void ggml_backend_metal_log_allocated_size(id<MTLDevice> device, size_t s
UNUSED(size_aligned);
}
GGML_CALL static ggml_backend_buffer_t ggml_backend_metal_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
static ggml_backend_buffer_t ggml_backend_metal_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
struct ggml_backend_metal_buffer_context * ctx = malloc(sizeof(struct ggml_backend_metal_buffer_context));
const size_t size_page = sysconf(_SC_PAGESIZE);
@ -3348,12 +3348,12 @@ GGML_CALL static ggml_backend_buffer_t ggml_backend_metal_buffer_type_alloc_buff
return ggml_backend_buffer_init(buft, ggml_backend_metal_buffer_i, ctx, size);
}
GGML_CALL static size_t ggml_backend_metal_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
static size_t ggml_backend_metal_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
return 32;
UNUSED(buft);
}
GGML_CALL static size_t ggml_backend_metal_buffer_type_get_max_size(ggml_backend_buffer_type_t buft) {
static size_t ggml_backend_metal_buffer_type_get_max_size(ggml_backend_buffer_type_t buft) {
id<MTLDevice> device = ggml_backend_metal_get_device();
size_t max_size = device.maxBufferLength;
ggml_backend_metal_free_device();
@ -3363,13 +3363,13 @@ GGML_CALL static size_t ggml_backend_metal_buffer_type_get_max_size(ggml_backend
UNUSED(buft);
}
GGML_CALL static bool ggml_backend_metal_buffer_type_is_host(ggml_backend_buffer_type_t buft) {
static bool ggml_backend_metal_buffer_type_is_host(ggml_backend_buffer_type_t buft) {
return true;
UNUSED(buft);
}
GGML_CALL ggml_backend_buffer_type_t ggml_backend_metal_buffer_type(void) {
ggml_backend_buffer_type_t ggml_backend_metal_buffer_type(void) {
static struct ggml_backend_buffer_type ggml_backend_buffer_type_metal = {
/* .iface = */ {
/* .get_name = */ ggml_backend_metal_buffer_type_get_name,
@ -3379,6 +3379,7 @@ GGML_CALL ggml_backend_buffer_type_t ggml_backend_metal_buffer_type(void) {
/* .get_alloc_size = */ NULL, // defaults to ggml_nbytes
/* .is_host = */ ggml_backend_metal_buffer_type_is_host,
},
/* .device = */ NULL,
/* .context = */ NULL,
};
@ -3387,7 +3388,7 @@ GGML_CALL ggml_backend_buffer_type_t ggml_backend_metal_buffer_type(void) {
// buffer from ptr
GGML_CALL ggml_backend_buffer_t ggml_backend_metal_buffer_from_ptr(void * data, size_t size, size_t max_size) {
ggml_backend_buffer_t ggml_backend_metal_buffer_from_ptr(void * data, size_t size, size_t max_size) {
struct ggml_backend_metal_buffer_context * ctx = malloc(sizeof(struct ggml_backend_metal_buffer_context));
ctx->all_data = data;
@ -3467,37 +3468,37 @@ GGML_CALL ggml_backend_buffer_t ggml_backend_metal_buffer_from_ptr(void * data,
// backend
GGML_CALL static const char * ggml_backend_metal_name(ggml_backend_t backend) {
static const char * ggml_backend_metal_name(ggml_backend_t backend) {
return "Metal";
UNUSED(backend);
}
GGML_CALL static void ggml_backend_metal_free(ggml_backend_t backend) {
static void ggml_backend_metal_free(ggml_backend_t backend) {
struct ggml_backend_metal_context * ctx = (struct ggml_backend_metal_context *)backend->context;
ggml_metal_free(ctx);
free(backend);
}
GGML_CALL static ggml_backend_buffer_type_t ggml_backend_metal_get_default_buffer_type(ggml_backend_t backend) {
static ggml_backend_buffer_type_t ggml_backend_metal_get_default_buffer_type(ggml_backend_t backend) {
return ggml_backend_metal_buffer_type();
UNUSED(backend);
}
GGML_CALL static enum ggml_status ggml_backend_metal_graph_compute(ggml_backend_t backend, struct ggml_cgraph * cgraph) {
static enum ggml_status ggml_backend_metal_graph_compute(ggml_backend_t backend, struct ggml_cgraph * cgraph) {
struct ggml_backend_metal_context * metal_ctx = (struct ggml_backend_metal_context *)backend->context;
return ggml_metal_graph_compute(metal_ctx, cgraph);
}
GGML_CALL static bool ggml_backend_metal_supports_op(ggml_backend_t backend, const struct ggml_tensor * op) {
static bool ggml_backend_metal_supports_op(ggml_backend_t backend, const struct ggml_tensor * op) {
struct ggml_backend_metal_context * metal_ctx = (struct ggml_backend_metal_context *)backend->context;
return ggml_metal_supports_op(metal_ctx, op);
}
GGML_CALL static bool ggml_backend_metal_supports_buft(ggml_backend_t backend, ggml_backend_buffer_type_t buft) {
static bool ggml_backend_metal_supports_buft(ggml_backend_t backend, ggml_backend_buffer_type_t buft) {
return buft->iface.get_name == ggml_backend_metal_buffer_type_get_name;
UNUSED(backend);
@ -3538,11 +3539,8 @@ static struct ggml_backend_i ggml_backend_metal_i = {
/* .supports_op = */ ggml_backend_metal_supports_op,
/* .supports_buft = */ ggml_backend_metal_supports_buft,
/* .offload_op = */ NULL,
/* .event_new = */ NULL,
/* .event_free = */ NULL,
/* .event_record = */ NULL,
/* .event_wait = */ NULL,
/* .event_synchronize = */ NULL,
};
void ggml_backend_metal_log_set_callback(ggml_log_callback log_callback, void * user_data) {
@ -3567,6 +3565,7 @@ ggml_backend_t ggml_backend_metal_init(void) {
*backend = (struct ggml_backend) {
/* .guid = */ ggml_backend_metal_guid(),
/* .interface = */ ggml_backend_metal_i,
/* .device = */ NULL,
/* .context = */ ctx,
};
@ -3603,9 +3602,9 @@ void ggml_backend_metal_capture_next_compute(ggml_backend_t backend) {
ctx->capture_next_compute = true;
}
GGML_CALL ggml_backend_t ggml_backend_reg_metal_init(const char * params, void * user_data); // silence warning
ggml_backend_t ggml_backend_reg_metal_init(const char * params, void * user_data); // silence warning
GGML_CALL ggml_backend_t ggml_backend_reg_metal_init(const char * params, void * user_data) {
ggml_backend_t ggml_backend_reg_metal_init(const char * params, void * user_data) {
return ggml_backend_metal_init();
GGML_UNUSED(params);

53
ggml/src/ggml-rpc.cpp
View File

@ -319,12 +319,12 @@ static std::shared_ptr<socket_t> get_socket(const std::string & endpoint) {
return sock;
}
GGML_CALL static const char * ggml_backend_rpc_buffer_get_name(ggml_backend_buffer_t buffer) {
static const char * ggml_backend_rpc_buffer_get_name(ggml_backend_buffer_t buffer) {
ggml_backend_rpc_buffer_context * ctx = (ggml_backend_rpc_buffer_context *)buffer->context;
return ctx->name.c_str();
}
GGML_CALL static void ggml_backend_rpc_buffer_free_buffer(ggml_backend_buffer_t buffer) {
static void ggml_backend_rpc_buffer_free_buffer(ggml_backend_buffer_t buffer) {
ggml_backend_rpc_buffer_context * ctx = (ggml_backend_rpc_buffer_context *)buffer->context;
// input serialization format: | remote_ptr (8 bytes) |
std::vector<uint8_t> input(sizeof(uint64_t), 0);
@ -337,7 +337,7 @@ GGML_CALL static void ggml_backend_rpc_buffer_free_buffer(ggml_backend_buffer_t
delete ctx;
}
GGML_CALL static void * ggml_backend_rpc_buffer_get_base(ggml_backend_buffer_t buffer) {
static void * ggml_backend_rpc_buffer_get_base(ggml_backend_buffer_t buffer) {
ggml_backend_rpc_buffer_context * ctx = (ggml_backend_rpc_buffer_context *)buffer->context;
if (ctx->base_cache.find(buffer) != ctx->base_cache.end()) {
return ctx->base_cache[buffer];
@ -388,7 +388,7 @@ static rpc_tensor serialize_tensor(const ggml_tensor * tensor) {
return result;
}
GGML_CALL static void ggml_backend_rpc_buffer_init_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor) {
static void ggml_backend_rpc_buffer_init_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor) {
UNUSED(buffer);
if (ggml_is_quantized(tensor->type)) {
// TODO: this check is due to MATRIX_ROW_PADDING in CUDA and should be generalized
@ -396,7 +396,7 @@ GGML_CALL static void ggml_backend_rpc_buffer_init_tensor(ggml_backend_buffer_t
}
}
GGML_CALL static void ggml_backend_rpc_buffer_set_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
static void ggml_backend_rpc_buffer_set_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
ggml_backend_rpc_buffer_context * ctx = (ggml_backend_rpc_buffer_context *)buffer->context;
// input serialization format: | rpc_tensor | offset (8 bytes) | data (size bytes) |
size_t input_size = sizeof(rpc_tensor) + sizeof(uint64_t) + size;
@ -410,7 +410,7 @@ GGML_CALL static void ggml_backend_rpc_buffer_set_tensor(ggml_backend_buffer_t b
GGML_ASSERT(status);
}
GGML_CALL static void ggml_backend_rpc_buffer_get_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * tensor, void * data, size_t offset, size_t size) {
static void ggml_backend_rpc_buffer_get_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * tensor, void * data, size_t offset, size_t size) {
ggml_backend_rpc_buffer_context * ctx = (ggml_backend_rpc_buffer_context *)buffer->context;
// input serialization format: | rpc_tensor | offset (8 bytes) | size (8 bytes) |
int input_size = sizeof(rpc_tensor) + 2*sizeof(uint64_t);
@ -427,7 +427,7 @@ GGML_CALL static void ggml_backend_rpc_buffer_get_tensor(ggml_backend_buffer_t b
memcpy(data, output.data(), size);
}
GGML_CALL static bool ggml_backend_rpc_buffer_cpy_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * src, ggml_tensor * dst) {
static bool ggml_backend_rpc_buffer_cpy_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * src, ggml_tensor * dst) {
// check if src and dst are on the same server
ggml_backend_buffer_t src_buffer = src->buffer;
ggml_backend_rpc_buffer_context * src_ctx = (ggml_backend_rpc_buffer_context *)src_buffer->context;
@ -452,7 +452,7 @@ GGML_CALL static bool ggml_backend_rpc_buffer_cpy_tensor(ggml_backend_buffer_t b
return output[0];
}
GGML_CALL static void ggml_backend_rpc_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) {
static void ggml_backend_rpc_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) {
ggml_backend_rpc_buffer_context * ctx = (ggml_backend_rpc_buffer_context *)buffer->context;
// serialization format: | bufptr (8 bytes) | value (1 byte) |
int input_size = sizeof(uint64_t) + sizeof(uint8_t);
@ -477,12 +477,12 @@ static ggml_backend_buffer_i ggml_backend_rpc_buffer_interface = {
/* .reset = */ NULL,
};
GGML_CALL static const char * ggml_backend_rpc_buffer_type_name(ggml_backend_buffer_type_t buft) {
static const char * ggml_backend_rpc_buffer_type_name(ggml_backend_buffer_type_t buft) {
ggml_backend_rpc_buffer_type_context * buft_ctx = (ggml_backend_rpc_buffer_type_context *)buft->context;
return buft_ctx->name.c_str();
}
GGML_CALL static ggml_backend_buffer_t ggml_backend_rpc_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
static ggml_backend_buffer_t ggml_backend_rpc_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
ggml_backend_rpc_buffer_type_context * buft_ctx = (ggml_backend_rpc_buffer_type_context *)buft->context;
// input serialization format: | size (8 bytes) |
int input_size = sizeof(uint64_t);
@ -522,7 +522,7 @@ static size_t get_alignment(const std::shared_ptr<socket_t> & sock) {
return alignment;
}
GGML_CALL static size_t ggml_backend_rpc_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
static size_t ggml_backend_rpc_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
ggml_backend_rpc_buffer_type_context * buft_ctx = (ggml_backend_rpc_buffer_type_context *)buft->context;
return buft_ctx->alignment;
}
@ -540,12 +540,12 @@ static size_t get_max_size(const std::shared_ptr<socket_t> & sock) {
return max_size;
}
GGML_CALL static size_t ggml_backend_rpc_get_max_size(ggml_backend_buffer_type_t buft) {
static size_t ggml_backend_rpc_get_max_size(ggml_backend_buffer_type_t buft) {
ggml_backend_rpc_buffer_type_context * buft_ctx = (ggml_backend_rpc_buffer_type_context *)buft->context;
return buft_ctx->max_size;
}
GGML_CALL static size_t ggml_backend_rpc_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) {
static size_t ggml_backend_rpc_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) {
UNUSED(buft);
return ggml_nbytes(tensor);
}
@ -559,24 +559,24 @@ static ggml_backend_buffer_type_i ggml_backend_rpc_buffer_type_interface = {
/* .is_host = */ NULL,
};
GGML_CALL static const char * ggml_backend_rpc_name(ggml_backend_t backend) {
static const char * ggml_backend_rpc_name(ggml_backend_t backend) {
ggml_backend_rpc_context * rpc_ctx = (ggml_backend_rpc_context *)backend->context;
return rpc_ctx->name.c_str();
}
GGML_CALL static void ggml_backend_rpc_free(ggml_backend_t backend) {
static void ggml_backend_rpc_free(ggml_backend_t backend) {
ggml_backend_rpc_context * rpc_ctx = (ggml_backend_rpc_context *)backend->context;
delete rpc_ctx;
delete backend;
}
GGML_CALL static ggml_backend_buffer_type_t ggml_backend_rpc_get_default_buffer_type(ggml_backend_t backend) {
static ggml_backend_buffer_type_t ggml_backend_rpc_get_default_buffer_type(ggml_backend_t backend) {
ggml_backend_rpc_context * ctx = (ggml_backend_rpc_context *)backend->context;
return ggml_backend_rpc_buffer_type(ctx->endpoint.c_str());
}
GGML_CALL static void ggml_backend_rpc_synchronize(ggml_backend_t backend) {
static void ggml_backend_rpc_synchronize(ggml_backend_t backend) {
UNUSED(backend);
// this is no-op because we don't have any async operations
}
@ -618,7 +618,7 @@ static void serialize_graph(const ggml_cgraph * cgraph, std::vector<uint8_t> & o
memcpy(out_tensors, tensors.data(), n_tensors * sizeof(rpc_tensor));
}
GGML_CALL static enum ggml_status ggml_backend_rpc_graph_compute(ggml_backend_t backend, ggml_cgraph * cgraph) {
static enum ggml_status ggml_backend_rpc_graph_compute(ggml_backend_t backend, ggml_cgraph * cgraph) {
ggml_backend_rpc_context * rpc_ctx = (ggml_backend_rpc_context *)backend->context;
std::vector<uint8_t> input;
serialize_graph(cgraph, input);
@ -630,14 +630,14 @@ GGML_CALL static enum ggml_status ggml_backend_rpc_graph_compute(ggml_backend_t
return (enum ggml_status)output[0];
}
GGML_CALL static bool ggml_backend_rpc_supports_op(ggml_backend_t backend, const ggml_tensor * op) {
static bool ggml_backend_rpc_supports_op(ggml_backend_t backend, const ggml_tensor * op) {
UNUSED(backend);
UNUSED(op);
//TODO: call the remote backend and cache the results
return true;
}
GGML_CALL static bool ggml_backend_rpc_supports_buft(ggml_backend_t backend, ggml_backend_buffer_type_t buft) {
static bool ggml_backend_rpc_supports_buft(ggml_backend_t backend, ggml_backend_buffer_type_t buft) {
if (!buft || buft->iface.get_name != ggml_backend_rpc_buffer_type_name) {
return false;
}
@ -662,14 +662,11 @@ static ggml_backend_i ggml_backend_rpc_interface = {
/* .supports_op = */ ggml_backend_rpc_supports_op,
/* .supports_buft = */ ggml_backend_rpc_supports_buft,
/* .offload_op = */ NULL,
/* .event_new = */ NULL,
/* .event_free = */ NULL,
/* .event_record = */ NULL,
/* .event_wait = */ NULL,
/* .event_synchronize = */ NULL,
};
GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_rpc_buffer_type(const char * endpoint) {
GGML_API ggml_backend_buffer_type_t ggml_backend_rpc_buffer_type(const char * endpoint) {
static std::mutex mutex;
std::lock_guard<std::mutex> lock(mutex);
// NOTE: buffer types are allocated and never freed; this is by design
@ -694,13 +691,14 @@ GGML_API GGML_CALL ggml_backend_buffer_type_t ggml_backend_rpc_buffer_type(const
ggml_backend_buffer_type_t buft = new ggml_backend_buffer_type {
/* .iface = */ ggml_backend_rpc_buffer_type_interface,
/* .device = */ nullptr,
/* .context = */ buft_ctx
};
buft_map[endpoint] = buft;
return buft;
}
GGML_CALL ggml_backend_t ggml_backend_rpc_init(const char * endpoint) {
ggml_backend_t ggml_backend_rpc_init(const char * endpoint) {
ggml_backend_rpc_context * ctx = new ggml_backend_rpc_context {
/* .endpoint = */ endpoint,
/* .name = */ "RPC[" + std::string(endpoint) + "]",
@ -709,12 +707,13 @@ GGML_CALL ggml_backend_t ggml_backend_rpc_init(const char * endpoint) {
ggml_backend_t backend = new ggml_backend {
/* .guid = */ ggml_backend_rpc_guid(),
/* .interface = */ ggml_backend_rpc_interface,
/* .device = */ nullptr,
/* .context = */ ctx
};
return backend;
}
GGML_API GGML_CALL bool ggml_backend_is_rpc(ggml_backend_t backend) {
GGML_API bool ggml_backend_is_rpc(ggml_backend_t backend) {
return backend != NULL && ggml_guid_matches(backend->guid, ggml_backend_rpc_guid());
}
@ -734,7 +733,7 @@ static void get_device_memory(const std::shared_ptr<socket_t> & sock, size_t * f
*total = total_mem;
}
GGML_API GGML_CALL void ggml_backend_rpc_get_device_memory(const char * endpoint, size_t * free, size_t * total) {
GGML_API void ggml_backend_rpc_get_device_memory(const char * endpoint, size_t * free, size_t * total) {
auto sock = get_socket(endpoint);
if (sock == nullptr) {
*free = 0;

107
ggml/src/ggml-sycl.cpp
View File

@ -4038,7 +4038,7 @@ bool ggml_sycl_compute_forward(ggml_backend_sycl_context & ctx, struct ggml_tens
return true;
}
GGML_API GGML_CALL void ggml_sycl_get_gpu_list(int *id_list, int max_len) try {
GGML_API void ggml_sycl_get_gpu_list(int *id_list, int max_len) try {
GGML_SYCL_DEBUG("[SYCL] call ggml_sycl_get_gpu_list\n");
for(int i=0;i<max_len;i++) id_list[i] = -1;
@ -4068,7 +4068,7 @@ catch (sycl::exception const &exc) {
std::exit(1);
}
GGML_API GGML_CALL void ggml_sycl_get_device_description(int device, char *description,
GGML_API void ggml_sycl_get_device_description(int device, char *description,
size_t description_size) try {
GGML_SYCL_DEBUG("[SYCL] call ggml_sycl_get_device_description\n");
dpct::device_info prop;
@ -4082,7 +4082,7 @@ catch (sycl::exception const &exc) {
std::exit(1);
}
GGML_CALL void ggml_backend_sycl_get_device_memory(int device, size_t *free,
void ggml_backend_sycl_get_device_memory(int device, size_t *free,
size_t *total) try {
GGML_SYCL_DEBUG("[SYCL] call ggml_backend_sycl_get_device_memory\n");
ggml_sycl_set_device(device);
@ -4135,12 +4135,12 @@ struct ggml_backend_sycl_buffer_context {
}
};
GGML_CALL static const char * ggml_backend_sycl_buffer_get_name(ggml_backend_buffer_t buffer) {
static const char * ggml_backend_sycl_buffer_get_name(ggml_backend_buffer_t buffer) {
ggml_backend_sycl_buffer_context * ctx = (ggml_backend_sycl_buffer_context *)buffer->context;
return ctx->name.c_str();
}
GGML_CALL static bool ggml_backend_buffer_is_sycl(ggml_backend_buffer_t buffer) {
static bool ggml_backend_buffer_is_sycl(ggml_backend_buffer_t buffer) {
return buffer->iface.get_name == ggml_backend_sycl_buffer_get_name;
}
@ -4162,7 +4162,7 @@ static void * ggml_backend_sycl_buffer_get_base(ggml_backend_buffer_t buffer) {
return ctx->dev_ptr;
}
GGML_CALL static void
static void
ggml_backend_sycl_buffer_init_tensor(ggml_backend_buffer_t buffer,
ggml_tensor *tensor) try {
ggml_backend_sycl_buffer_context * ctx = (ggml_backend_sycl_buffer_context *)buffer->context;
@ -4237,7 +4237,7 @@ catch (sycl::exception const &exc) {
std::exit(1);
}
GGML_CALL static bool
static bool
ggml_backend_sycl_buffer_cpy_tensor(ggml_backend_buffer_t buffer,
const ggml_tensor *src,
ggml_tensor *dst) try {
@ -4339,12 +4339,12 @@ struct ggml_backend_sycl_buffer_type_context {
queue_ptr stream = nullptr;
};
GGML_CALL static const char * ggml_backend_sycl_buffer_type_name(ggml_backend_buffer_type_t buft) {
static const char * ggml_backend_sycl_buffer_type_name(ggml_backend_buffer_type_t buft) {
ggml_backend_sycl_buffer_type_context * ctx = (ggml_backend_sycl_buffer_type_context *)buft->context;
return ctx->name.c_str();
}
GGML_CALL static ggml_backend_buffer_t
static ggml_backend_buffer_t
ggml_backend_sycl_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft,
size_t size) try {
ggml_backend_sycl_buffer_type_context * buft_ctx = (ggml_backend_sycl_buffer_type_context *)buft->context;
@ -4368,7 +4368,7 @@ catch (sycl::exception const &exc) {
std::exit(1);
}
GGML_CALL static size_t ggml_backend_sycl_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
static size_t ggml_backend_sycl_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
return 128;
UNUSED(buft);
}
@ -4379,7 +4379,7 @@ static size_t ggml_backend_sycl_buffer_type_get_max_size(ggml_backend_buffer_typ
UNUSED(buft);
}
GGML_CALL static size_t ggml_backend_sycl_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) {
static size_t ggml_backend_sycl_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) {
size_t size = ggml_nbytes(tensor);
int64_t ne0 = tensor->ne[0];
@ -4424,6 +4424,7 @@ ggml_backend_buffer_type_t ggml_backend_sycl_buffer_type(int device) {
queue_ptr stream = &(device_i.default_queue());
ggml_backend_sycl_buffer_types[i] = {
/* .iface = */ ggml_backend_sycl_buffer_type_interface,
/* .device = */ nullptr,
/* .context = */ new ggml_backend_sycl_buffer_type_context{i, GGML_SYCL_NAME + std::to_string(i), stream},
};
}
@ -4449,6 +4450,7 @@ ggml_backend_buffer_type_t ggml_backend_sycl_buffer_type(ggml_backend_sycl_conte
for (int i = 0; i < ggml_sycl_info().device_count; i++) {
ggml_backend_sycl_buffer_types[i] = {
/* .iface = */ ggml_backend_sycl_buffer_type_interface,
/* .device = */ nullptr,
/* .context = */ new ggml_backend_sycl_buffer_type_context{i, GGML_SYCL_NAME + std::to_string(i), ctx->stream(i, 0)},
};
}
@ -4513,7 +4515,7 @@ struct ggml_backend_sycl_split_buffer_context {
std::vector<queue_ptr> streams;
};
GGML_CALL static const char * ggml_backend_sycl_split_buffer_get_name(ggml_backend_buffer_t buffer) {
static const char * ggml_backend_sycl_split_buffer_get_name(ggml_backend_buffer_t buffer) {
return GGML_SYCL_NAME "_Split";
UNUSED(buffer);
@ -4523,19 +4525,19 @@ static bool ggml_backend_buffer_is_sycl_split(ggml_backend_buffer_t buffer) {
return buffer->iface.get_name == ggml_backend_sycl_split_buffer_get_name;
}
GGML_CALL static void ggml_backend_sycl_split_buffer_free_buffer(ggml_backend_buffer_t buffer) {
static void ggml_backend_sycl_split_buffer_free_buffer(ggml_backend_buffer_t buffer) {
ggml_backend_sycl_split_buffer_context * ctx = (ggml_backend_sycl_split_buffer_context *)buffer->context;
delete ctx;
}
GGML_CALL static void * ggml_backend_sycl_split_buffer_get_base(ggml_backend_buffer_t buffer) {
static void * ggml_backend_sycl_split_buffer_get_base(ggml_backend_buffer_t buffer) {
// the pointers are stored in the tensor extras, this is just a dummy address and never dereferenced
return (void *)0x1000;
UNUSED(buffer);
}
GGML_CALL static void
static void
ggml_backend_sycl_split_buffer_init_tensor(ggml_backend_buffer_t buffer,
ggml_tensor *tensor) try {
GGML_ASSERT(tensor->view_src == nullptr); // views of split tensors are not supported
@ -4618,7 +4620,7 @@ catch (sycl::exception const &exc) {
std::exit(1);
}
GGML_CALL static void
static void
ggml_backend_sycl_split_buffer_set_tensor(ggml_backend_buffer_t buffer,
ggml_tensor *tensor, const void *data,
size_t offset, size_t size) try {
@ -4671,7 +4673,7 @@ catch (sycl::exception const &exc) {
std::exit(1);
}
GGML_CALL static void
static void
ggml_backend_sycl_split_buffer_get_tensor(ggml_backend_buffer_t buffer,
const ggml_tensor *tensor, void *data,
size_t offset, size_t size) try {
@ -4724,7 +4726,7 @@ catch (sycl::exception const &exc) {
std::exit(1);
}
GGML_CALL static void ggml_backend_sycl_split_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) {
static void ggml_backend_sycl_split_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) {
UNUSED(buffer);
UNUSED(value);
}
@ -4742,13 +4744,13 @@ static struct ggml_backend_buffer_i ggml_backend_sycl_split_buffer_interface = {
/* .reset = */ NULL,
};
GGML_CALL static const char * ggml_backend_sycl_split_buffer_type_name(ggml_backend_buffer_type_t buft) {
static const char * ggml_backend_sycl_split_buffer_type_name(ggml_backend_buffer_type_t buft) {
return GGML_SYCL_NAME "_Split";
UNUSED(buft);
}
GGML_CALL static ggml_backend_buffer_t ggml_backend_sycl_split_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
static ggml_backend_buffer_t ggml_backend_sycl_split_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
// since we don't know the exact split after rounding, we cannot allocate the device buffers at this point
// instead, we allocate them for each tensor separately in init_tensor
// however, the size still represents the maximum cumulative size of all the device buffers after the tensors are allocated,
@ -4758,12 +4760,12 @@ GGML_CALL static ggml_backend_buffer_t ggml_backend_sycl_split_buffer_type_alloc
return ggml_backend_buffer_init(buft, ggml_backend_sycl_split_buffer_interface, ctx, size);
}
GGML_CALL static size_t ggml_backend_sycl_split_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
static size_t ggml_backend_sycl_split_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
return 128;
UNUSED(buft);
}
GGML_CALL static size_t ggml_backend_sycl_split_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) {
static size_t ggml_backend_sycl_split_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) {
ggml_backend_sycl_split_buffer_type_context * ctx = (ggml_backend_sycl_split_buffer_type_context *)buft->context;
size_t total_size = 0;
@ -4790,7 +4792,7 @@ GGML_CALL static size_t ggml_backend_sycl_split_buffer_type_get_alloc_size(ggml_
return total_size;
}
GGML_CALL static bool ggml_backend_sycl_split_buffer_type_is_host(ggml_backend_buffer_type_t buft) {
static bool ggml_backend_sycl_split_buffer_type_is_host(ggml_backend_buffer_type_t buft) {
return false;
UNUSED(buft);
@ -4805,7 +4807,7 @@ static ggml_backend_buffer_type_i ggml_backend_sycl_split_buffer_type_interface
/* .is_host = */ ggml_backend_sycl_split_buffer_type_is_host,
};
GGML_CALL ggml_backend_buffer_type_t ggml_backend_sycl_split_buffer_type(const float * tensor_split) {
ggml_backend_buffer_type_t ggml_backend_sycl_split_buffer_type(const float * tensor_split) {
static std::mutex mutex;
std::lock_guard<std::mutex> lock(mutex);
@ -4837,6 +4839,7 @@ GGML_CALL ggml_backend_buffer_type_t ggml_backend_sycl_split_buffer_type(const f
struct ggml_backend_buffer_type buft {
/* .iface = */ ggml_backend_sycl_split_buffer_type_interface,
/* .device = */ nullptr,
/* .context = */ new ggml_backend_sycl_split_buffer_type_context{tensor_split_arr},
};
@ -4846,13 +4849,13 @@ GGML_CALL ggml_backend_buffer_type_t ggml_backend_sycl_split_buffer_type(const f
// host buffer type
GGML_CALL static const char * ggml_backend_sycl_host_buffer_type_name(ggml_backend_buffer_type_t buft) {
static const char * ggml_backend_sycl_host_buffer_type_name(ggml_backend_buffer_type_t buft) {
return GGML_SYCL_NAME "_Host";
UNUSED(buft);
}
GGML_CALL static const char * ggml_backend_sycl_host_buffer_name(ggml_backend_buffer_t buffer) {
static const char * ggml_backend_sycl_host_buffer_name(ggml_backend_buffer_t buffer) {
return GGML_SYCL_NAME "_Host";
UNUSED(buffer);
@ -4890,6 +4893,7 @@ ggml_backend_buffer_type_t ggml_backend_sycl_host_buffer_type() {
/* .get_alloc_size = */ ggml_backend_cpu_buffer_type()->iface.get_alloc_size,
/* .is_host = */ ggml_backend_cpu_buffer_type()->iface.is_host,
},
/* .device = */ nullptr,
/* .context = */ nullptr,
};
@ -4898,14 +4902,14 @@ ggml_backend_buffer_type_t ggml_backend_sycl_host_buffer_type() {
// backend
GGML_CALL static const char * ggml_backend_sycl_name(ggml_backend_t backend) {
static const char * ggml_backend_sycl_name(ggml_backend_t backend) {
ggml_backend_sycl_context * sycl_ctx = (ggml_backend_sycl_context *)backend->context;
return sycl_ctx->name.c_str();
}
GGML_CALL static void ggml_backend_sycl_free(ggml_backend_t backend) {
static void ggml_backend_sycl_free(ggml_backend_t backend) {
ggml_backend_sycl_context * sycl_ctx = (ggml_backend_sycl_context *)backend->context;
delete sycl_ctx;
@ -4913,12 +4917,12 @@ GGML_CALL static void ggml_backend_sycl_free(ggml_backend_t backend) {
}
GGML_CALL static ggml_backend_buffer_type_t ggml_backend_sycl_get_default_buffer_type(ggml_backend_t backend) {
static ggml_backend_buffer_type_t ggml_backend_sycl_get_default_buffer_type(ggml_backend_t backend) {
ggml_backend_sycl_context * sycl_ctx = (ggml_backend_sycl_context *)backend->context;
return ggml_backend_sycl_buffer_type(sycl_ctx->device);
}
GGML_CALL static void ggml_backend_sycl_set_tensor_async(ggml_backend_t backend,
static void ggml_backend_sycl_set_tensor_async(ggml_backend_t backend,
ggml_tensor *tensor,
const void *data, size_t offset,
size_t size) try {
@ -4936,7 +4940,7 @@ catch (sycl::exception const &exc) {
std::exit(1);
}
GGML_CALL static void ggml_backend_sycl_get_tensor_async(ggml_backend_t backend,
static void ggml_backend_sycl_get_tensor_async(ggml_backend_t backend,
const ggml_tensor *tensor,
void *data, size_t offset,
size_t size) try {
@ -4954,9 +4958,9 @@ catch (sycl::exception const &exc) {
std::exit(1);
}
GGML_CALL static bool ggml_backend_sycl_cpy_tensor_async(ggml_backend_t backend,
const ggml_tensor *src,
ggml_tensor *dst) try {
static bool ggml_backend_sycl_cpy_tensor_async(ggml_backend_t backend,
const ggml_tensor *src,
ggml_tensor *dst) try {
ggml_backend_sycl_context * sycl_ctx = (ggml_backend_sycl_context *)backend->context;
if (dst->buffer->buft == ggml_backend_sycl_buffer_type(sycl_ctx->device) && ggml_backend_buffer_is_sycl(src->buffer)) {
/*
@ -4991,7 +4995,7 @@ catch (sycl::exception const &exc) {
std::exit(1);
}
GGML_CALL static ggml_status ggml_backend_sycl_graph_compute(ggml_backend_t backend, ggml_cgraph * cgraph) {
static ggml_status ggml_backend_sycl_graph_compute(ggml_backend_t backend, ggml_cgraph * cgraph) {
ggml_backend_sycl_context * sycl_ctx = (ggml_backend_sycl_context *)backend->context;
ggml_sycl_set_main_device(sycl_ctx->device);
@ -5019,7 +5023,7 @@ GGML_CALL static ggml_status ggml_backend_sycl_graph_compute(ggml_backend_t back
return GGML_STATUS_SUCCESS;
}
GGML_CALL static bool ggml_backend_sycl_supports_op(ggml_backend_t backend, const ggml_tensor * op) {
static bool ggml_backend_sycl_supports_op(ggml_backend_t backend, const ggml_tensor * op) {
switch (op->op) {
case GGML_OP_CONV_TRANSPOSE_1D:
{
@ -5166,13 +5170,13 @@ GGML_CALL static bool ggml_backend_sycl_supports_op(ggml_backend_t backend, cons
UNUSED(backend);
}
GGML_CALL static bool ggml_backend_sycl_offload_op(ggml_backend_t backend, const ggml_tensor * op) {
static bool ggml_backend_sycl_offload_op(ggml_backend_t backend, const ggml_tensor * op) {
const int min_batch_size = 32;
return op->ne[1] >= min_batch_size && op->op != GGML_OP_GET_ROWS && op->op != GGML_OP_MUL_MAT_ID;
GGML_UNUSED(backend);
}
GGML_CALL static bool ggml_backend_sycl_supports_buft(ggml_backend_t backend, ggml_backend_buffer_type_t buft) {
static bool ggml_backend_sycl_supports_buft(ggml_backend_t backend, ggml_backend_buffer_type_t buft) {
if (buft->iface.get_name != ggml_backend_sycl_buffer_type_name) {
return false;
}
@ -5197,11 +5201,8 @@ static ggml_backend_i ggml_backend_sycl_interface = {
/* .supports_op = */ ggml_backend_sycl_supports_op,
/* .supports_buft = */ ggml_backend_sycl_supports_buft,
/* .offload_op = */ ggml_backend_sycl_offload_op,
/* .event_new = */ NULL,
/* .event_free = */ NULL,
/* .event_record = */ NULL,
/* .event_wait = */ NULL,
/* .event_synchronize = */ NULL,
};
static ggml_guid_t ggml_backend_sycl_guid() {
@ -5209,7 +5210,7 @@ static ggml_guid_t ggml_backend_sycl_guid() {
return &guid;
}
GGML_CALL ggml_backend_t ggml_backend_sycl_init(int device) {
ggml_backend_t ggml_backend_sycl_init(int device) {
GGML_SYCL_DEBUG("[SYCL] call ggml_backend_sycl_init\n");
ggml_check_sycl();
@ -5224,6 +5225,7 @@ GGML_CALL ggml_backend_t ggml_backend_sycl_init(int device) {
ggml_backend_t sycl_backend = new ggml_backend {
/* .guid = */ ggml_backend_sycl_guid(),
/* .interface = */ ggml_backend_sycl_interface,
/* .device = */ nullptr,
/* .context = */ ctx
};
@ -5234,26 +5236,7 @@ bool ggml_backend_is_sycl(ggml_backend_t backend) {
return backend != NULL && ggml_guid_matches(backend->guid, ggml_backend_sycl_guid());
}
GGML_CALL int ggml_backend_sycl_get_device_count() {
int ggml_backend_sycl_get_device_count() {
GGML_SYCL_DEBUG("[SYCL] call ggml_backend_sycl_get_device_count\n");
return ggml_sycl_info().device_count;
}
GGML_CALL static ggml_backend_t ggml_backend_reg_sycl_init(const char * params, void * user_data) {
ggml_backend_t sycl_backend = ggml_backend_sycl_init((int) (intptr_t) user_data);
return sycl_backend;
UNUSED(params);
}
extern "C" int ggml_backend_sycl_reg_devices();
int ggml_backend_sycl_reg_devices() {
assert(ggml_sycl_info().device_count>0);
for (int i = 0; i < ggml_sycl_info().device_count; i++) {
char name[128];
snprintf(name, sizeof(name), "%s%d", GGML_SYCL_NAME, i);
ggml_backend_register(name, ggml_backend_reg_sycl_init, ggml_backend_sycl_buffer_type(i), (void *) (intptr_t) i);
}
return ggml_sycl_info().device_count;
}

117
ggml/src/ggml-vulkan.cpp
View File

@ -119,11 +119,11 @@ struct ggml_backend_vk_buffer_type_context {
vk_device device;
};
GGML_CALL static const char * ggml_backend_vk_buffer_type_name(ggml_backend_buffer_type_t buft);
GGML_CALL static ggml_backend_buffer_t ggml_backend_vk_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size);
GGML_CALL static size_t ggml_backend_vk_buffer_type_get_alignment(ggml_backend_buffer_type_t buft);
GGML_CALL static size_t ggml_backend_vk_buffer_type_get_max_size(ggml_backend_buffer_type_t buft);
GGML_CALL static size_t ggml_backend_vk_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor);
static const char * ggml_backend_vk_buffer_type_name(ggml_backend_buffer_type_t buft);
static ggml_backend_buffer_t ggml_backend_vk_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size);
static size_t ggml_backend_vk_buffer_type_get_alignment(ggml_backend_buffer_type_t buft);
static size_t ggml_backend_vk_buffer_type_get_max_size(ggml_backend_buffer_type_t buft);
static size_t ggml_backend_vk_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor);
static ggml_backend_buffer_type_i ggml_backend_vk_buffer_type_interface = {
/* .get_name = */ ggml_backend_vk_buffer_type_name,
/* .alloc_buffer = */ ggml_backend_vk_buffer_type_alloc_buffer,
@ -622,7 +622,7 @@ static void ggml_vk_check_results_1(ggml_tensor * tensor);
typedef void (*ggml_vk_func_t)(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst);
GGML_CALL static void ggml_backend_vk_free(ggml_backend_t backend);
static void ggml_backend_vk_free(ggml_backend_t backend);
// variables to track number of compiles in progress
static uint32_t compile_count = 0;
@ -1953,6 +1953,7 @@ static vk_device ggml_vk_get_device(size_t idx) {
device->buffer_type = {
/* .iface = */ ggml_backend_vk_buffer_type_interface,
/* .device = */ nullptr,
/* .context = */ new ggml_backend_vk_buffer_type_context{ device->name, device },
};
@ -6147,13 +6148,13 @@ static void ggml_vk_cleanup(ggml_backend_vk_context * ctx) {
ctx->device->device.destroyFence(ctx->fence);
}
GGML_CALL static int ggml_vk_get_device_count() {
static int ggml_vk_get_device_count() {
ggml_vk_instance_init();
return vk_instance.device_indices.size();
}
GGML_CALL static void ggml_vk_get_device_description(int device, char * description, size_t description_size) {
static void ggml_vk_get_device_description(int device, char * description, size_t description_size) {
ggml_vk_instance_init();
std::vector<vk::PhysicalDevice> devices = vk_instance.instance.enumeratePhysicalDevices();
@ -6170,36 +6171,36 @@ GGML_CALL static void ggml_vk_get_device_description(int device, char * descript
// device backend
GGML_CALL static const char * ggml_backend_vk_buffer_get_name(ggml_backend_buffer_t buffer) {
static const char * ggml_backend_vk_buffer_get_name(ggml_backend_buffer_t buffer) {
ggml_backend_vk_buffer_context * ctx = (ggml_backend_vk_buffer_context *)buffer->context;
return ctx->name.c_str();
}
GGML_CALL static bool ggml_backend_buffer_is_vk(ggml_backend_buffer_t buffer) {
static bool ggml_backend_buffer_is_vk(ggml_backend_buffer_t buffer) {
return buffer->iface.get_name == ggml_backend_vk_buffer_get_name;
}
GGML_CALL static void ggml_backend_vk_buffer_free_buffer(ggml_backend_buffer_t buffer) {
static void ggml_backend_vk_buffer_free_buffer(ggml_backend_buffer_t buffer) {
VK_LOG_MEMORY("ggml_backend_vk_buffer_free_buffer()");
ggml_backend_vk_buffer_context * ctx = (ggml_backend_vk_buffer_context *)buffer->context;
ggml_vk_destroy_buffer(ctx->dev_buffer);
delete ctx;
}
GGML_CALL static void * ggml_backend_vk_buffer_get_base(ggml_backend_buffer_t buffer) {
static void * ggml_backend_vk_buffer_get_base(ggml_backend_buffer_t buffer) {
return vk_ptr_base;
UNUSED(buffer);
}
GGML_CALL static void ggml_backend_vk_buffer_init_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor) {
static void ggml_backend_vk_buffer_init_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor) {
VK_LOG_DEBUG("ggml_backend_vk_buffer_init_tensor(" << buffer << " (" << buffer->context << "), " << tensor << ")");
if (tensor->view_src != nullptr) {
GGML_ASSERT(tensor->view_src->buffer->buft == buffer->buft);
}
}
GGML_CALL static void ggml_backend_vk_buffer_set_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
static void ggml_backend_vk_buffer_set_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
VK_LOG_DEBUG("ggml_backend_vk_buffer_set_tensor(" << buffer << ", " << tensor << ", " << data << ", " << offset << ", " << size << ")");
ggml_backend_vk_buffer_context * buf_ctx = (ggml_backend_vk_buffer_context *)buffer->context;
vk_buffer buf = buf_ctx->dev_buffer;
@ -6207,7 +6208,7 @@ GGML_CALL static void ggml_backend_vk_buffer_set_tensor(ggml_backend_buffer_t bu
ggml_vk_buffer_write(buf, vk_tensor_offset(tensor) + tensor->view_offs + offset, data, size);
}
GGML_CALL static void ggml_backend_vk_buffer_get_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * tensor, void * data, size_t offset, size_t size) {
static void ggml_backend_vk_buffer_get_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * tensor, void * data, size_t offset, size_t size) {
VK_LOG_DEBUG("ggml_backend_vk_buffer_get_tensor(" << buffer << ", " << tensor << ", " << data << ", " << offset << ", " << size << ")");
ggml_backend_vk_buffer_context * buf_ctx = (ggml_backend_vk_buffer_context *)buffer->context;
@ -6216,7 +6217,7 @@ GGML_CALL static void ggml_backend_vk_buffer_get_tensor(ggml_backend_buffer_t bu
ggml_vk_buffer_read(buf, vk_tensor_offset(tensor) + tensor->view_offs + offset, data, size);
}
GGML_CALL static bool ggml_backend_vk_buffer_cpy_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * src, ggml_tensor * dst) {
static bool ggml_backend_vk_buffer_cpy_tensor(ggml_backend_buffer_t buffer, const ggml_tensor * src, ggml_tensor * dst) {
if (ggml_backend_buffer_is_vk(src->buffer)) {
ggml_backend_vk_buffer_context * src_buf_ctx = (ggml_backend_vk_buffer_context *)src->buffer->context;
ggml_backend_vk_buffer_context * dst_buf_ctx = (ggml_backend_vk_buffer_context *)dst->buffer->context;
@ -6233,7 +6234,7 @@ GGML_CALL static bool ggml_backend_vk_buffer_cpy_tensor(ggml_backend_buffer_t bu
UNUSED(buffer);
}
GGML_CALL static void ggml_backend_vk_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) {
static void ggml_backend_vk_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) {
ggml_backend_vk_buffer_context * ctx = (ggml_backend_vk_buffer_context *)buffer->context;
ggml_vk_buffer_memset(ctx->dev_buffer, 0, value, buffer->size);
@ -6253,13 +6254,13 @@ static ggml_backend_buffer_i ggml_backend_vk_buffer_interface = {
};
// vk buffer type
GGML_CALL static const char * ggml_backend_vk_buffer_type_name(ggml_backend_buffer_type_t buft) {
static const char * ggml_backend_vk_buffer_type_name(ggml_backend_buffer_type_t buft) {
ggml_backend_vk_buffer_type_context * ctx = (ggml_backend_vk_buffer_type_context *)buft->context;
return ctx->name.c_str();
}
GGML_CALL static ggml_backend_buffer_t ggml_backend_vk_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
static ggml_backend_buffer_t ggml_backend_vk_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
VK_LOG_MEMORY("ggml_backend_vk_buffer_type_alloc_buffer(" << size << ")");
ggml_backend_vk_buffer_type_context * ctx = (ggml_backend_vk_buffer_type_context *) buft->context;
@ -6275,23 +6276,23 @@ GGML_CALL static ggml_backend_buffer_t ggml_backend_vk_buffer_type_alloc_buffer(
return ggml_backend_buffer_init(buft, ggml_backend_vk_buffer_interface, bufctx, size);
}
GGML_CALL static size_t ggml_backend_vk_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
static size_t ggml_backend_vk_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
ggml_backend_vk_buffer_type_context * ctx = (ggml_backend_vk_buffer_type_context *) buft->context;
return ctx->device->properties.limits.minStorageBufferOffsetAlignment;
}
GGML_CALL static size_t ggml_backend_vk_buffer_type_get_max_size(ggml_backend_buffer_type_t buft) {
static size_t ggml_backend_vk_buffer_type_get_max_size(ggml_backend_buffer_type_t buft) {
ggml_backend_vk_buffer_type_context * ctx = (ggml_backend_vk_buffer_type_context *) buft->context;
return ctx->device->max_memory_allocation_size;
}
GGML_CALL static size_t ggml_backend_vk_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) {
static size_t ggml_backend_vk_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) {
return ggml_nbytes(tensor);
UNUSED(buft);
}
GGML_CALL ggml_backend_buffer_type_t ggml_backend_vk_buffer_type(size_t dev_num) {
ggml_backend_buffer_type_t ggml_backend_vk_buffer_type(size_t dev_num) {
ggml_vk_instance_init();
VK_LOG_DEBUG("ggml_backend_vk_buffer_type(" << dev_num << ")");
@ -6303,24 +6304,24 @@ GGML_CALL ggml_backend_buffer_type_t ggml_backend_vk_buffer_type(size_t dev_num)
// host buffer type
GGML_CALL static const char * ggml_backend_vk_host_buffer_type_name(ggml_backend_buffer_type_t buft) {
static const char * ggml_backend_vk_host_buffer_type_name(ggml_backend_buffer_type_t buft) {
return GGML_VK_NAME "_Host";
UNUSED(buft);
}
GGML_CALL static const char * ggml_backend_vk_host_buffer_name(ggml_backend_buffer_t buffer) {
static const char * ggml_backend_vk_host_buffer_name(ggml_backend_buffer_t buffer) {
return GGML_VK_NAME "_Host";
UNUSED(buffer);
}
GGML_CALL static void ggml_backend_vk_host_buffer_free_buffer(ggml_backend_buffer_t buffer) {
static void ggml_backend_vk_host_buffer_free_buffer(ggml_backend_buffer_t buffer) {
VK_LOG_MEMORY("ggml_backend_vk_host_buffer_free_buffer()");
ggml_vk_host_free(vk_instance.devices[0], buffer->context);
}
GGML_CALL static ggml_backend_buffer_t ggml_backend_vk_host_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
static ggml_backend_buffer_t ggml_backend_vk_host_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
VK_LOG_MEMORY("ggml_backend_vk_host_buffer_type_alloc_buffer(" << size << ")");
size += 32; // Behave like the CPU buffer type
@ -6344,7 +6345,7 @@ GGML_CALL static ggml_backend_buffer_t ggml_backend_vk_host_buffer_type_alloc_bu
UNUSED(buft);
}
GGML_CALL static size_t ggml_backend_vk_host_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
static size_t ggml_backend_vk_host_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
return vk_instance.devices[0]->properties.limits.minMemoryMapAlignment;
UNUSED(buft);
@ -6352,7 +6353,7 @@ GGML_CALL static size_t ggml_backend_vk_host_buffer_type_get_alignment(ggml_back
// Should be changed to return device-specific host buffer type
// but that probably requires changes in llama.cpp
GGML_CALL ggml_backend_buffer_type_t ggml_backend_vk_host_buffer_type() {
ggml_backend_buffer_type_t ggml_backend_vk_host_buffer_type() {
static struct ggml_backend_buffer_type ggml_backend_vk_buffer_type_host = {
/* .iface = */ {
/* .get_name = */ ggml_backend_vk_host_buffer_type_name,
@ -6362,6 +6363,7 @@ GGML_CALL ggml_backend_buffer_type_t ggml_backend_vk_host_buffer_type() {
/* .get_alloc_size = */ ggml_backend_cpu_buffer_type()->iface.get_alloc_size,
/* .is_host = */ ggml_backend_cpu_buffer_type()->iface.is_host,
},
/* .device = */ nullptr,
/* .context = */ nullptr,
};
@ -6375,13 +6377,13 @@ GGML_CALL ggml_backend_buffer_type_t ggml_backend_vk_host_buffer_type() {
// backend
GGML_CALL static const char * ggml_backend_vk_name(ggml_backend_t backend) {
static const char * ggml_backend_vk_name(ggml_backend_t backend) {
ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context;
return ctx->name.c_str();
}
GGML_CALL static void ggml_backend_vk_free(ggml_backend_t backend) {
static void ggml_backend_vk_free(ggml_backend_t backend) {
ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context;
VK_LOG_DEBUG("ggml_backend_vk_free(" << ctx->name << ")");
@ -6391,13 +6393,13 @@ GGML_CALL static void ggml_backend_vk_free(ggml_backend_t backend) {
delete backend;
}
GGML_CALL static ggml_backend_buffer_type_t ggml_backend_vk_get_default_buffer_type(ggml_backend_t backend) {
static ggml_backend_buffer_type_t ggml_backend_vk_get_default_buffer_type(ggml_backend_t backend) {
ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context;
return &ctx->device->buffer_type;
}
GGML_CALL static void ggml_backend_vk_set_tensor_async(ggml_backend_t backend, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
static void ggml_backend_vk_set_tensor_async(ggml_backend_t backend, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
VK_LOG_DEBUG("ggml_backend_vk_set_tensor_async(" << size << ")");
ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context;
GGML_ASSERT((tensor->buffer->buft == ggml_backend_vk_get_default_buffer_type(backend) || tensor->buffer->buft == ggml_backend_vk_host_buffer_type()) && "unsupported buffer type");
@ -6420,7 +6422,7 @@ GGML_CALL static void ggml_backend_vk_set_tensor_async(ggml_backend_t backend, g
ggml_vk_buffer_write_async(transfer_ctx, buf, vk_tensor_offset(tensor) + tensor->view_offs + offset, data, size);
}
GGML_CALL static void ggml_backend_vk_get_tensor_async(ggml_backend_t backend, const ggml_tensor * tensor, void * data, size_t offset, size_t size) {
static void ggml_backend_vk_get_tensor_async(ggml_backend_t backend, const ggml_tensor * tensor, void * data, size_t offset, size_t size) {
VK_LOG_DEBUG("ggml_backend_vk_get_tensor_async(" << size << ")");
ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context;
GGML_ASSERT((tensor->buffer->buft == ggml_backend_vk_get_default_buffer_type(backend) || tensor->buffer->buft == ggml_backend_vk_host_buffer_type()) && "unsupported buffer type");
@ -6443,7 +6445,7 @@ GGML_CALL static void ggml_backend_vk_get_tensor_async(ggml_backend_t backend, c
ggml_vk_buffer_read_async(transfer_ctx, buf, vk_tensor_offset(tensor) + tensor->view_offs + offset, data, size);
}
GGML_CALL static bool ggml_backend_vk_cpy_tensor_async(ggml_backend_t backend, const ggml_tensor * src, ggml_tensor * dst) {
static bool ggml_backend_vk_cpy_tensor_async(ggml_backend_t backend, const ggml_tensor * src, ggml_tensor * dst) {
VK_LOG_DEBUG("ggml_backend_vk_cpy_tensor_async()");
ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context;
if ((dst->buffer->buft == ggml_backend_vk_get_default_buffer_type(backend) || dst->buffer->buft == ggml_backend_vk_host_buffer_type()) && ggml_backend_buffer_is_vk(src->buffer)) {
@ -6471,7 +6473,7 @@ GGML_CALL static bool ggml_backend_vk_cpy_tensor_async(ggml_backend_t backend, c
return false;
}
GGML_CALL static void ggml_backend_vk_synchronize(ggml_backend_t backend) {
static void ggml_backend_vk_synchronize(ggml_backend_t backend) {
VK_LOG_DEBUG("ggml_backend_vk_synchronize()");
ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context;
if(ctx->transfer_ctx.expired()) {
@ -6501,7 +6503,7 @@ static bool ggml_vk_is_empty(ggml_tensor * node) {
return ggml_is_empty(node) || node->op == GGML_OP_NONE || node->op == GGML_OP_RESHAPE || node->op == GGML_OP_TRANSPOSE || node->op == GGML_OP_VIEW || node->op == GGML_OP_PERMUTE;
}
GGML_CALL static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cgraph * cgraph) {
static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cgraph * cgraph) {
VK_LOG_DEBUG("ggml_backend_vk_graph_compute(" << cgraph->n_nodes << " nodes)");
ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context;
@ -6564,7 +6566,7 @@ GGML_CALL static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backen
UNUSED(backend);
}
GGML_CALL static bool ggml_backend_vk_supports_op(ggml_backend_t backend, const ggml_tensor * op) {
static bool ggml_backend_vk_supports_op(ggml_backend_t backend, const ggml_tensor * op) {
// ggml_backend_vk_context * ctx = (ggml_backend_vk_context *) backend->context;
switch (op->op) {
@ -6687,7 +6689,7 @@ GGML_CALL static bool ggml_backend_vk_supports_op(ggml_backend_t backend, const
UNUSED(backend);
}
GGML_CALL static bool ggml_backend_vk_offload_op(ggml_backend_t backend, const ggml_tensor * op) {
static bool ggml_backend_vk_offload_op(ggml_backend_t backend, const ggml_tensor * op) {
const int min_batch_size = 32;
return (op->ne[1] >= min_batch_size && op->op != GGML_OP_GET_ROWS) ||
@ -6696,7 +6698,7 @@ GGML_CALL static bool ggml_backend_vk_offload_op(ggml_backend_t backend, const g
UNUSED(backend);
}
GGML_CALL static bool ggml_backend_vk_supports_buft(ggml_backend_t backend, ggml_backend_buffer_type_t buft) {
static bool ggml_backend_vk_supports_buft(ggml_backend_t backend, ggml_backend_buffer_type_t buft) {
if (buft->iface.get_name != ggml_backend_vk_buffer_type_name) {
return false;
}
@ -6724,11 +6726,8 @@ static ggml_backend_i ggml_backend_vk_interface = {
/* .supports_op = */ ggml_backend_vk_supports_op,
/* .supports_buft = */ ggml_backend_vk_supports_buft,
/* .offload_op = */ ggml_backend_vk_offload_op,
/* .event_new = */ NULL,
/* .event_free = */ NULL,
/* .event_record = */ NULL,
/* .event_wait = */ NULL,
/* .event_synchronize = */ NULL,
};
static ggml_guid_t ggml_backend_vk_guid() {
@ -6736,7 +6735,7 @@ static ggml_guid_t ggml_backend_vk_guid() {
return &guid;
}
GGML_CALL ggml_backend_t ggml_backend_vk_init(size_t dev_num) {
ggml_backend_t ggml_backend_vk_init(size_t dev_num) {
VK_LOG_DEBUG("ggml_backend_vk_init(" << dev_num << ")");
ggml_backend_vk_context * ctx = new ggml_backend_vk_context;
@ -6745,25 +6744,26 @@ GGML_CALL ggml_backend_t ggml_backend_vk_init(size_t dev_num) {
ggml_backend_t vk_backend = new ggml_backend {
/* .guid = */ ggml_backend_vk_guid(),
/* .interface = */ ggml_backend_vk_interface,
/* .device = */ nullptr,
/* .context = */ ctx,
};
return vk_backend;
}
GGML_CALL bool ggml_backend_is_vk(ggml_backend_t backend) {
bool ggml_backend_is_vk(ggml_backend_t backend) {
return backend != NULL && ggml_guid_matches(backend->guid, ggml_backend_vk_guid());
}
GGML_CALL int ggml_backend_vk_get_device_count() {
int ggml_backend_vk_get_device_count() {
return ggml_vk_get_device_count();
}
GGML_CALL void ggml_backend_vk_get_device_description(int device, char * description, size_t description_size) {
void ggml_backend_vk_get_device_description(int device, char * description, size_t description_size) {
ggml_vk_get_device_description(device, description, description_size);
}
GGML_CALL void ggml_backend_vk_get_device_memory(int device, size_t * free, size_t * total) {
void ggml_backend_vk_get_device_memory(int device, size_t * free, size_t * total) {
GGML_ASSERT(device < (int) vk_instance.device_indices.size());
vk::PhysicalDevice vkdev = vk_instance.instance.enumeratePhysicalDevices()[vk_instance.device_indices[device]];
@ -6779,27 +6779,6 @@ GGML_CALL void ggml_backend_vk_get_device_memory(int device, size_t * free, size
}
}
// backend registry
GGML_CALL static ggml_backend_t ggml_backend_reg_vk_init(const char * params, void * user_data) {
ggml_backend_t vk_backend = ggml_backend_vk_init((int) (intptr_t) user_data);
return vk_backend;
UNUSED(params);
}
extern "C" GGML_CALL int ggml_backend_vk_reg_devices();
GGML_CALL int ggml_backend_vk_reg_devices() {
ggml_vk_instance_init();
for (size_t i = 0; i < vk_instance.device_indices.size(); i++) {
char name[128];
snprintf(name, sizeof(name), "%s%ld", GGML_VK_NAME, i);
ggml_backend_register(name, ggml_backend_reg_vk_init, ggml_backend_vk_buffer_type(i), (void *) (intptr_t) i); // NOLINT
}
return vk_instance.device_indices.size();
}
// Extension availability
static bool ggml_vk_instance_validation_ext_available(const std::vector<vk::ExtensionProperties>& instance_extensions) {
#ifdef GGML_VULKAN_VALIDATE

46
ggml/src/ggml.c
View File

@ -461,7 +461,7 @@ struct ggml_arm_arch_features_type {
} ggml_arm_arch_features = {-1, -1, -1, 0};
#endif
GGML_CALL const char * ggml_status_to_string(enum ggml_status status) {
const char * ggml_status_to_string(enum ggml_status status) {
switch (status) {
case GGML_STATUS_ALLOC_FAILED: return "GGML status: error (failed to allocate memory)";
case GGML_STATUS_FAILED: return "GGML status: error (operation failed)";
@ -3384,19 +3384,19 @@ void ggml_print_objects(const struct ggml_context * ctx) {
GGML_PRINT("%s: --- end ---\n", __func__);
}
GGML_CALL int64_t ggml_nelements(const struct ggml_tensor * tensor) {
int64_t ggml_nelements(const struct ggml_tensor * tensor) {
static_assert(GGML_MAX_DIMS == 4, "GGML_MAX_DIMS is not 4 - update this function");
return tensor->ne[0]*tensor->ne[1]*tensor->ne[2]*tensor->ne[3];
}
GGML_CALL int64_t ggml_nrows(const struct ggml_tensor * tensor) {
int64_t ggml_nrows(const struct ggml_tensor * tensor) {
static_assert(GGML_MAX_DIMS == 4, "GGML_MAX_DIMS is not 4 - update this function");
return tensor->ne[1]*tensor->ne[2]*tensor->ne[3];
}
GGML_CALL size_t ggml_nbytes(const struct ggml_tensor * tensor) {
size_t ggml_nbytes(const struct ggml_tensor * tensor) {
size_t nbytes;
size_t blck_size = ggml_blck_size(tensor->type);
if (blck_size == 1) {
@ -3419,15 +3419,15 @@ size_t ggml_nbytes_pad(const struct ggml_tensor * tensor) {
return GGML_PAD(ggml_nbytes(tensor), GGML_MEM_ALIGN);
}
GGML_CALL int64_t ggml_blck_size(enum ggml_type type) {
int64_t ggml_blck_size(enum ggml_type type) {
return type_traits[type].blck_size;
}
GGML_CALL size_t ggml_type_size(enum ggml_type type) {
size_t ggml_type_size(enum ggml_type type) {
return type_traits[type].type_size;
}
GGML_CALL size_t ggml_row_size(enum ggml_type type, int64_t ne) {
size_t ggml_row_size(enum ggml_type type, int64_t ne) {
assert(ne % ggml_blck_size(type) == 0);
return ggml_type_size(type)*ne/ggml_blck_size(type);
}
@ -3436,15 +3436,15 @@ double ggml_type_sizef(enum ggml_type type) {
return ((double)(type_traits[type].type_size))/type_traits[type].blck_size;
}
GGML_CALL const char * ggml_type_name(enum ggml_type type) {
const char * ggml_type_name(enum ggml_type type) {
return type < GGML_TYPE_COUNT ? type_traits[type].type_name : "NONE";
}
GGML_CALL bool ggml_is_quantized(enum ggml_type type) {
bool ggml_is_quantized(enum ggml_type type) {
return type_traits[type].is_quantized;
}
GGML_CALL const char * ggml_op_name(enum ggml_op op) {
const char * ggml_op_name(enum ggml_op op) {
return GGML_OP_NAME[op];
}
@ -3456,7 +3456,7 @@ const char * ggml_unary_op_name(enum ggml_unary_op op) {
return GGML_UNARY_OP_NAME[op];
}
GGML_CALL const char * ggml_op_desc(const struct ggml_tensor * t) {
const char * ggml_op_desc(const struct ggml_tensor * t) {
if (t->op == GGML_OP_UNARY) {
enum ggml_unary_op uop = ggml_get_unary_op(t);
return ggml_unary_op_name(uop);
@ -3464,7 +3464,7 @@ GGML_CALL const char * ggml_op_desc(const struct ggml_tensor * t) {
return ggml_op_name(t->op);
}
GGML_CALL size_t ggml_element_size(const struct ggml_tensor * tensor) {
size_t ggml_element_size(const struct ggml_tensor * tensor) {
return ggml_type_size(tensor->type);
}
@ -3557,7 +3557,7 @@ size_t ggml_tensor_overhead(void) {
return GGML_OBJECT_SIZE + GGML_TENSOR_SIZE;
}
GGML_CALL bool ggml_is_transposed(const struct ggml_tensor * tensor) {
bool ggml_is_transposed(const struct ggml_tensor * tensor) {
return tensor->nb[0] > tensor->nb[1];
}
@ -3583,23 +3583,23 @@ static bool ggml_is_contiguous_n(const struct ggml_tensor * tensor, int n) {
return true;
}
GGML_CALL bool ggml_is_contiguous(const struct ggml_tensor * tensor) {
bool ggml_is_contiguous(const struct ggml_tensor * tensor) {
return ggml_is_contiguous_0(tensor);
}
GGML_CALL bool ggml_is_contiguous_0(const struct ggml_tensor * tensor) {
bool ggml_is_contiguous_0(const struct ggml_tensor * tensor) {
return ggml_is_contiguous_n(tensor, 0);
}
GGML_CALL bool ggml_is_contiguous_1(const struct ggml_tensor * tensor) {
bool ggml_is_contiguous_1(const struct ggml_tensor * tensor) {
return ggml_is_contiguous_n(tensor, 1);
}
GGML_CALL bool ggml_is_contiguous_2(const struct ggml_tensor * tensor) {
bool ggml_is_contiguous_2(const struct ggml_tensor * tensor) {
return ggml_is_contiguous_n(tensor, 2);
}
GGML_CALL bool ggml_is_permuted(const struct ggml_tensor * tensor) {
bool ggml_is_permuted(const struct ggml_tensor * tensor) {
static_assert(GGML_MAX_DIMS == 4, "GGML_MAX_DIMS is not 4 - update this function");
return tensor->nb[0] > tensor->nb[1] || tensor->nb[1] > tensor->nb[2] || tensor->nb[2] > tensor->nb[3];
@ -3614,7 +3614,7 @@ static inline bool ggml_is_padded_1d(const struct ggml_tensor * tensor) {
tensor->nb[3] == tensor->nb[2]*tensor->ne[2];
}
GGML_CALL bool ggml_is_empty(const struct ggml_tensor * tensor) {
bool ggml_is_empty(const struct ggml_tensor * tensor) {
for (int i = 0; i < GGML_MAX_DIMS; ++i) {
if (tensor->ne[i] == 0) {
// empty if any dimension has no elements
@ -4634,7 +4634,7 @@ float * ggml_get_data_f32(const struct ggml_tensor * tensor) {
return (float *)(tensor->data);
}
GGML_CALL enum ggml_unary_op ggml_get_unary_op(const struct ggml_tensor * tensor) {
enum ggml_unary_op ggml_get_unary_op(const struct ggml_tensor * tensor) {
GGML_ASSERT(tensor->op == GGML_OP_UNARY);
return (enum ggml_unary_op) ggml_get_op_params_i32(tensor, 0);
}
@ -12834,6 +12834,10 @@ static void ggml_compute_forward_out_prod_f32(
GGML_TENSOR_BINARY_OP_LOCALS
GGML_ASSERT(dst->type == GGML_TYPE_F32);
GGML_ASSERT(src0->type == GGML_TYPE_F32);
GGML_ASSERT(src1->type == GGML_TYPE_F32);
const int ith = params->ith;
const int nth = params->nth;
@ -14163,7 +14167,7 @@ static void ggml_rope_cache_init(
}
}
GGML_CALL void ggml_rope_yarn_corr_dims(
void ggml_rope_yarn_corr_dims(
int n_dims, int n_ctx_orig, float freq_base, float beta_fast, float beta_slow, float dims[2]
) {
// start and end correction dims