Add limited RTX PRO 6000 coverage.

[alliepiper]

The cuda-python team offered to let us use their hw while we wait for our much larger order to arrive. Adding minimal CUB coverage to ensure that our blackwell implementations don't regress.

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[alliepiper]

/ok to test

[bernhardmgruber]

I see a CI test failure in:

91/123 Test #336: cub.test.device.segmented_scan_api.lid_0 ......................***Failed    0.41 sec
  -- >> Running:
  	/home/coder/cccl/build/cuda13.0-gcc14/cub/bin/cub.test.device.segmented_scan_api.lid_0
  /home/coder/cccl/lib/cmake/libcudacxx/../../../libcudacxx/include/cuda/__cmath/fast_modulo_division.h:112: operator/: block: [0,0,0], thread: [0,0,0] Assertion `dividend must be non-negative` failed.

Funny, it's an API test. The test was added recently in #6022.

Also, the test runtime here seems a bit excessive. Is this normal?

          Start 455: cub.test.device.radix_sort_decomposer_fail.lid_0
  119/123 Test #455: cub.test.device.radix_sort_decomposer_fail.lid_0 ..............   Passed  1258.18 sec

[alliepiper]

@oleksandr-pavlyk can you take a look at the segmented scan issue? This is failing on RTX PRO 6000 (sm120).

Also, the test runtime here seems a bit excessive. Is this normal? cub.test.device.radix_sort_decomposer_fail.lid_0 1258.18 sec

Those _fail tests invoke compilers internally and check that compilation fails with a specific error. That does seem excessive, even for the less-powerful CPUs on the GPU runners. Looking at results on other runners from the nightlies, it takes about half as long on RTXA6000 + H100

H100: https://github.com/NVIDIA/cccl/actions/runs/19846009437/job/56871704747
A6000: https://github.com/NVIDIA/cccl/actions/runs/19846009437/job/56871704740

It's a very simple TU, might be worth seeing if we can trigger the failure sooner.

[bernhardmgruber]

I opened #6845 for the long test time.

[oleksandr-pavlyk]

I opened #6868 to fix assertions failing the segmented scan API test.

[alliepiper]

/ok to test

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🥳 CI Workflow Results

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[bernhardmgruber]

Thank you @alliepiper and @kkraus14 for making that happen!