Add HSTU attention CuTe DSL kernels for Blackwell

[jiayus-nvidia]

Summary

• Add packed variable-length HSTU attention forward and backward CuTe DSL kernels for Blackwell SM100/SM103 GPUs.
• Support FP16/BF16 head dimensions 64, 128, and 256; full, causal, local, and arbitrary masks; paged-KV forward; and strided or preallocated gradient outputs.
• Add the experimental FE API, lazy top-level exports, documentation, and L0/L1 pytest coverage.
• Apply the repository's existing licensing pattern: NVIDIA-owned implementation, API, and test files use Apache-2.0, while seven retained low-level derived helpers use MIT and preserve their original author notices.
• Make explicit-stream execution allocation- and lifetime-safe, reject cross-device PyTorch streams, and validate output overlap with all read-only metadata.
• Preserve the original HSTU development history while adapting the port to the current develop package layout and conventions.

Validation

• pre-commit run --files <changed files>
• python -m compileall -q python/cudnn/hstu_attention
• cd test/python && PYTHONDONTWRITEBYTECODE=1 PYTHONPATH=../../python python -m pytest -p no:cacheprovider -q -m "L0 or L1" fe_api/hstu_attention/
  • 185 passed on NVIDIA B200 (SM100), CUDA 13.2, cuDNN 9.20, PyTorch 2.11, CUTLASS DSL 4.6.1
• License audit: 19 Apache-2.0 files and 7 MIT files in the HSTU package and tests, with no file-level BSD source in the HSTU tree.

Closes #369

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