ci: Update sm12X minimum cuda capability to 12.9 in aot.py (#2188)

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## 📌 Description

[CUDA Release
notes](https://docs.nvidia.com/cuda/parallel-thread-execution/#release-notes)
indicate full sm120 support on CUDA 12.8 and sm121 on 12.9. Changing the
version noted in `aot.py`.

The change alters the coverage in `flashinfer-jit-cache` -- today some
sm120 kernels are not compiled & shipped in cuda 12.9, but are included
in 13.0. The change here will insure kernels are included.


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## Summary by CodeRabbit

* **Bug Fixes**
  * Adjusted GPU capability detection and CUDA version requirements:
    * SM110 now requires CUDA 13.0 (raised from 12.9).
    * SM120 support expanded to CUDA 12.8 (lowered from 13.0).
    * SM121 support updated to CUDA 12.9 (from 13.0).

* **Impact**
* Broader compatibility for SM120/SM121 on slightly older CUDA; SM110
now requires a newer CUDA runtime.

<sub>✏️ Tip: You can customize this high-level summary in your review
settings.</sub>
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Author: bkryu

flashinfer/aot.py

@@ -742,9 +742,9 @@ def has_sm(compute: str, version: str) -> bool:
         "sm100": has_sm("compute_100", "12.8"),
         "sm100f": has_sm("compute_100", "12.9"),
         "sm103": has_sm("compute_103", "12.9"),
-        "sm110": has_sm("compute_110", "12.9"),
-        "sm120": has_sm("compute_120", "13.0"),
-        "sm121": has_sm("compute_121", "13.0"),
+        "sm110": has_sm("compute_110", "13.0"),
+        "sm120": has_sm("compute_120", "12.8"),
+        "sm121": has_sm("compute_121", "12.9"),
     }