[QNN-EP] Implement file mapped weights feature #26952
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The observation is not entirely true. ORT memory map external weights. You have an ability to request a weight as an ORT Value from the EP. If the weight is external it will be memory mapped. See |
onnxruntime/core/providers/qnn/builder/qnn_windows_file_mapper.cc
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I suggest not to implement QNN specific mapping, but re-use code in ORT. |
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Discussed offline, the EP maps initializers form the binary context, not from the external weights files. |
added 3 commits
January 14, 2026 13:56
- Create file mapping callback interface class - Android expected to have support in the future - Implement Windows callbacks in WindowsFileMapper - New option disable_file_mapped_weights - Feature is enabled by default with retry logic
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Please, avoid force pushes. |
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Please, comment on all Copilot review issues before resolving them. |
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Add QnnHtpSharedAllocator to HTP check during unit testing to cover cases where RPCMEM is not available
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QnnBackendManager::SetupBackend if file mapping is not available
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Make file mapping callbacks more thread safe Do not destruct file_mapper_ until session destruction
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Description
Enables the file mapping of weights as well as the overall context bin. This feature is currently only enabled for ARM64 WIN devices
Motivation and Context
Currently, when reading the context bin, ORT allocates a large buffer on the heap. Assuming the same model is used, each ORT session will allocate a buffer for the context bin. This is incredibly wasteful when large models are used. Instead, WIN file mapping can be leveraged to map the context bin, then every time a context needs to be created with the context bin, the pointer to the context bin can be retrieved and used instead of some pre-allocated buffer, thus making QNN EP more memory-efficient. In the case of multiple ORT sessions, the context bin will only be loaded once for all sessions, increasing memory efficiency and overall initialization performance. This is very useful regarding the use of LLMs going forward.