[Common/PyTorch] Grouped GEMM via multi-stream cuBLAS

[yaox12]

Description

Grouped GEMM for fp32/bf16/fp16 via multi-stream cuBLAS. This is for MoE training.

I'll add FP8 support and a GroupedLinear layer in future PRs.

Type of change

• [ ] Documentation change (change only to the documentation, either a fix or a new content)
• [ ] Bug fix (non-breaking change which fixes an issue)
• [x] New feature (non-breaking change which adds functionality)
• [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)

Changes

Please list the changes introduced in this PR:

• Add a multi-stream cuBLAS based Grouped GEMM implementation and the corresponding PyTorch binding.

Checklist:

• [x] I have read and followed the contributing guidelines
• [x] The functionality is complete
• [x] I have commented my code, particularly in hard-to-understand areas
• [x] I have made corresponding changes to the documentation
• [x] My changes generate no new warnings
• [x] I have added tests that prove my fix is effective or that my feature works
• [x] New and existing unit tests pass locally with my changes