move BLAS to a separate backend (#6210)
* move BLAS to a separate backend * rename GGML_USE_OPENBLAS to GGML_USE_BLAS * alloc : reuse same buffer when the same buffer type if used multiple times * set number of threads automatically for openblas and blis * sched : print assignments when GGML_SCHED_DEBUG env variable is set * sched : allow ops with weights on an incompatible buffer type This will cause the weight to be copied to a backend that supports the op, which is very costly. The weight should have been stored in a buffer of a backend that can run the op, but llama.cpp cannot do this automatically at the moment. --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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17 changed files with 821 additions and 379 deletions
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@ -17,13 +17,15 @@ extern "C" {
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struct ggml_backend_buffer_type_i {
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const char * (*GGML_CALL get_name) (ggml_backend_buffer_type_t buft);
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// allocate a buffer of this type
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ggml_backend_buffer_t (*GGML_CALL alloc_buffer) (ggml_backend_buffer_type_t buft, size_t size);
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size_t (*GGML_CALL get_alignment) (ggml_backend_buffer_type_t buft); // tensor alignment
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size_t (*GGML_CALL get_max_size) (ggml_backend_buffer_type_t buft); // allocation max size
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size_t (*GGML_CALL get_alloc_size) (ggml_backend_buffer_type_t buft, const struct ggml_tensor * tensor); // data size needed to allocate the tensor, including padding
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bool (*GGML_CALL supports_backend)(ggml_backend_buffer_type_t buft, ggml_backend_t backend); // check if the buffer type is usable by the backend
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// tensor alignment
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size_t (*GGML_CALL get_alignment) (ggml_backend_buffer_type_t buft);
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// max buffer size that can be allocated
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size_t (*GGML_CALL get_max_size) (ggml_backend_buffer_type_t buft);
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// data size needed to allocate the tensor, including padding
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size_t (*GGML_CALL get_alloc_size) (ggml_backend_buffer_type_t buft, const struct ggml_tensor * tensor);
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// check if tensor data is in host memory
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// should be equivalent to supports_backend(buft, ggml_backend_cpu_init())
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bool (*GGML_CALL is_host) (ggml_backend_buffer_type_t buft);
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};
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@ -92,27 +94,37 @@ extern "C" {
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void (*GGML_CALL synchronize)(ggml_backend_t backend);
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// compute graph with a plan (not used currently)
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// create a new plan for a graph
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ggml_backend_graph_plan_t (*GGML_CALL graph_plan_create) (ggml_backend_t backend, const struct ggml_cgraph * cgraph);
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void (*GGML_CALL graph_plan_free) (ggml_backend_t backend, ggml_backend_graph_plan_t plan);
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// update the plan with a new graph - this should be faster than creating a new plan when the graph has the same topology
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void (*GGML_CALL graph_plan_update) (ggml_backend_t backend, ggml_backend_graph_plan_t plan, const struct ggml_cgraph * cgraph);
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// compute the graph with the plan
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enum ggml_status (*GGML_CALL graph_plan_compute)(ggml_backend_t backend, ggml_backend_graph_plan_t plan);
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// compute graph with a plan
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enum ggml_status (*GGML_CALL graph_plan_compute)(ggml_backend_t backend, ggml_backend_graph_plan_t plan);
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// compute graph without a plan (async)
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enum ggml_status (*GGML_CALL graph_compute) (ggml_backend_t backend, struct ggml_cgraph * cgraph);
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// check if the backend supports an operation
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// check if the backend can compute an operation
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bool (*GGML_CALL supports_op)(ggml_backend_t backend, const struct ggml_tensor * op);
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// check if the backend can use tensors allocated in a buffer type
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bool (*GGML_CALL supports_buft)(ggml_backend_t backend, ggml_backend_buffer_type_t buft);
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// check if the backend wants to run an operation, even if the weights are allocated in a CPU buffer
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// these should be expensive operations with large batch sizes that may benefit from running on this backend
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// even if the weight has to be copied from the CPU temporarily
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bool (*GGML_CALL offload_op)(ggml_backend_t backend, const struct ggml_tensor * op);
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// (optional) event synchronization
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// create a new event that can record events on this backend instance
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ggml_backend_event_t (*GGML_CALL event_new) (ggml_backend_t backend);
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void (*GGML_CALL event_free) (ggml_backend_event_t event);
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// record an event on the backend instance that created it
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void (*GGML_CALL event_record) (ggml_backend_event_t event);
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// wait for an event on on a different backend instance
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void (*GGML_CALL event_wait) (ggml_backend_t backend, ggml_backend_event_t event);
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// block until an event is recorded
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void (*GGML_CALL event_synchronize) (ggml_backend_event_t event);
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};
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