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Description

Backport of #12150 to branch/3.6.x.

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[miscco]

/ok to test 7d7a59d

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😬 CI Workflow Results

🟥 Finished in 1h 30m: Pass: 98%/147 | Total: 2d 05h | Max: 1h 24m | Hits: 99%/557452

See results here.

AI failure analysis

1. shared_memory_barrier no-report status decoding aborts on H100 · 2 jobs

Explanation: Both H100 jobs abort in the newly enabled block-scope test with the same fabric-status decoder assertion. Source inspection shows `check_success_status` confirms that no report exists and then queries its error count, while `operation_status::__error_count` unconditionally passes the absent report value to `cudaFabricOpErrorStatusCount`; its non-success result triggers `_CCCL_VERIFY`.

Evidence:

2026-10-26T10:29:46.2690398Z /home/coder/cccl/lib/cmake/libcudacxx/../../../libcudacxx/include/cuda/__barrier/shared_memory_barrier.h:165: __verify_fabric_status: block: [0,0,0], thread: [0,0,0] Assertion `failed to decode shared_memory_barrier status` failed.
2026-10-26T10:34:01.0272609Z /home/coder/cccl/lib/cmake/libcudacxx/../../../libcudacxx/include/cuda/__barrier/shared_memory_barrier.h:165: __verify_fabric_status: block: [0,0,0], thread: [0,0,0] Assertion `failed to decode shared_memory_barrier status` failed.
2026-10-26T10:29:46.2680872Z   2/134 Test   #2: libcudacxx.test.cuda.barrier.shared_memory_barrier ........................................................Subprocess aborted***Exception:   0.56 sec

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Repository: https://github.com/NVIDIA/cccl
Workflow run: https://github.com/NVIDIA/cccl/actions/runs/40301374534
Failure group: shared_memory_barrier no-report status decoding aborts on H100
Affected jobs:
- libcu++ nvcc GCC / H8 / [CTK13.4 GCC16 C++23] Test(amd64, H100): https://github.com/NVIDIA/cccl/actions/runs/40301374534/job/121517953522
- libcu++ nvcc GCC / IM / [CTK13.4 GCC16 C++23] Test(amd64, H100 2-GPU): sm{90}: https://github.com/NVIDIA/cccl/actions/runs/40301374534/job/121519808835

Verify and fix the CUDA 13.4 H100 failure in `libcudacxx.test.cuda.barrier.shared_memory_barrier`. Reproduce it narrowly and confirm that `check_success_status` observes `!status.has_report()` before `get_error_count(cuda::status_source::generic_fabric)` invokes `cudaFabricOpErrorStatusCount` and aborts. If the existing zero-error contract is correct, update `operation_status::__error_count` in `libcudacxx/include/cuda/__barrier/shared_memory_barrier.h` to return zero without invoking the CUDA decoder when `__report_predicate_` is false; a focused implementation is `if (!__report_predicate_ || !__encodes_fabric_errors(__source)) { return 0; }`. Ensure `for_each_error` also becomes a no-op for absent reports, while `classify` still rejects statuses without reports and `__error_status` remains reachable only for positive decoded counts. Retain the driver and compute-capability gates, review the public contract and nearby tests, then run the targeted libcudacxx CTest target with CUDA 13.4 on sm90/H100 plus focused compile or precompile validation.

Jobs:

• libcu++ nvcc GCC / H8 / [CTK13.4 GCC16 C++23] Test(amd64, H100)
• libcu++ nvcc GCC / IM / [CTK13.4 GCC16 C++23] Test(amd64, H100 2-GPU): sm{90}