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authorMahantesh Salimath <mahantesh@nvidia.com>2026-09-10 16:11:24 +0000
committerJens Wiklander <jens.wiklander@oss.qualcomm.com>2026-10-02 16:08:05 +0200
commit3c0d2f1f431c51a11253f28763be723ac782fd7a (patch)
treeab6bc3db9c0489542e335f9aed7f28042f89677c /tools/lib/python/kdoc/python_version.py
parentc108feca0a096f8db25d1b69130035025e9e936d (diff)
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tee: optee: ffa: support shared memory offsets on large-page kernels
OP-TEE FF-A memory objects use 4 KiB pages, while the kernel page size may be larger. Consequently, tee_shm->offset can be greater than or equal to FFA_PAGE_SIZE, but OP-TEE rejects such a value in internal_offs. Do not encode the excess page offset in offs_low/offs_high. Those fields describe the logical memref offset and are copied back into tee_param->shm_offs on return. Folding the page offset into them breaks parameter round trips when a memref is reused. They are also ignored by the OPTEE_RPC_CMD_SHM_ALLOC response path, which uses only global_id and internal_offs to construct the shared-memory mobj. Instead, start the FF-A descriptor at the 4 KiB page containing the shared buffer, the same approach as optee_fill_pages_list() in the SMC ABI. Store the remaining in-page offset in internal_offs and preserve shm_offs in offs_low/offs_high. This keeps internal_offs within the FF-A page size, maps RPC allocations at the correct address, and preserves normal memref offsets across repeated invocations. Tested on ARMv8-A with 64 KiB PAGE_SIZE. OP-TEE OS ran as a secure partition under Hafnium (SPMC) over FF-A. Verified registered shared memory with tee_shm->offset >= 4 KiB, memref reuse on the same TEEC_Operation, and RPC OPTEE_RPC_CMD_SHM_ALLOC (xtest regression 6007-6009). optee_hello_world, optee_aes, and xtest regression 1005, 1007, 1008, 4001-4003 and 6001-6003 also passed. Fixes: 4615e5a34b95 ("optee: add FF-A support") Acked-by: Liming Sun <limings@nvidia.com> Acked-by: James Hurley <jahurley@nvidia.com> Acked-by: Dave Thompson <davthompson@nvidia.com> Signed-off-by: Mahantesh Salimath <mahantesh@nvidia.com> Reviewed-by: Sumit Garg <sumit.garg@oss.qualcomm.com> Signed-off-by: Jens Wiklander <jens.wiklander@oss.qualcomm.com>
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