Kevin Pouget
ffaafde16f
* ggml-virtgpu-backend: validate the consistency of the received objects This patch adds consistency checks in the ggml-virtgpu-backend (running on the host side) to ensure that the data received from the guest is consistent (valid pointers, valid sizes and offsets). * ggml-virtgpu-backend: add fallback/skips for optional ggml backend methods ``` 1. bck->iface.synchronize(bck) 2. buft->iface.get_alloc_size(buft, op) 3. buft->iface.get_max_size(buft) ``` these three methods are optional in the GGML interface. `get_max_size` was already properly defaulted, but `backend sychronize` and `butf get_max_size` would have segfaulted the backend if not implemented. * ggml-virtgpu-backend: fix log format missing argument * ggml-virtgpu-backend: improve the abort message * ggml-virtgpu-backend: more safety checks * ggml-virtgpu-backend: new error code * ggml-virtgpu-backend: initialize all the error codes * ggml-virtgpu: add a missing comment generated by the code generator * ggml-virtgpu: add the '[virtgpu]' prefix to the device/buffer names * ggml-virtgpu: apir_device_buffer_from_ptr: improve the error message * ggml-virtgpu: shared: make it match the latest api_remoting.h of Virglrenderer APIR (still unmerged) * ggml-virtgpu: update the code generator to have dispatch_command_name in a host/guest shared file * ggml-virtgpu: REMOTE_CALL: fail if the backend returns an error * docs/backend/VirtGPU.md: indicate that the RAM+VRAM size is limed to 64 GB with libkrun * ggml-virtgpu: turn off clang-format header ordering for some of the files Compilation breaks when ordered alphabetically. * ggml-virtgpu: clang-format * ggml-virtgpu/backend/shared/api_remoting: better comments for the APIR return codes
54 lines
3.5 KiB
C
54 lines
3.5 KiB
C
#pragma once
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/* device */
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void apir_device_get_device_count(struct virtgpu * gpu);
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int apir_device_get_count(struct virtgpu * gpu);
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char * apir_device_get_name(struct virtgpu * gpu);
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char * apir_device_get_description(struct virtgpu * gpu);
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uint32_t apir_device_get_type(struct virtgpu * gpu);
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void apir_device_get_memory(struct virtgpu * gpu, size_t * free, size_t * total);
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bool apir_device_supports_op(struct virtgpu * gpu, const ggml_tensor * op);
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apir_buffer_type_host_handle_t apir_device_get_buffer_type(struct virtgpu * gpu);
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void apir_device_get_props(struct virtgpu * gpu,
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bool * async,
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bool * host_buffer,
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bool * buffer_from_host_ptr,
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bool * events);
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apir_buffer_context_t apir_device_buffer_from_ptr(struct virtgpu * gpu, size_t size, size_t max_tensor_size);
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/* buffer-type */
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char * apir_buffer_type_get_name(struct virtgpu * gpu, apir_buffer_type_host_handle_t host_handle);
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size_t apir_buffer_type_get_alignment(struct virtgpu * gpu, apir_buffer_type_host_handle_t host_handle);
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size_t apir_buffer_type_get_max_size(struct virtgpu * gpu, apir_buffer_type_host_handle_t host_handle);
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/* apir_buffer_type_is_host is deprecated. */
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apir_buffer_context_t apir_buffer_type_alloc_buffer(struct virtgpu * gpu,
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apir_buffer_type_host_handle_t host_handle,
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size_t size);
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size_t apir_buffer_type_get_alloc_size(struct virtgpu * gpu,
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apir_buffer_type_host_handle_t host_handle,
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const ggml_tensor * op);
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/* buffer */
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void * apir_buffer_get_base(struct virtgpu * gpu, apir_buffer_context_t * buffer_context);
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void apir_buffer_set_tensor(struct virtgpu * gpu,
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apir_buffer_context_t * buffer_context,
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ggml_tensor * tensor,
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const void * data,
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size_t offset,
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size_t size);
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void apir_buffer_get_tensor(struct virtgpu * gpu,
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apir_buffer_context_t * buffer_context,
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const ggml_tensor * tensor,
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void * data,
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size_t offset,
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size_t size);
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bool apir_buffer_cpy_tensor(struct virtgpu * gpu,
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apir_buffer_context_t * buffer_context,
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const ggml_tensor * src,
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const ggml_tensor * dst);
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void apir_buffer_clear(struct virtgpu * gpu, apir_buffer_context_t * buffer_context, uint8_t value);
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void apir_buffer_free_buffer(struct virtgpu * gpu, apir_buffer_context_t * buffer_context);
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/* backend */
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ggml_status apir_backend_graph_compute(struct virtgpu * gpu, ggml_cgraph * cgraph);
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