[CUDA] Add SparseAttention kernel for sm=75 (#20531)
### Description
Follow up of #20216 to add kernel for sm=75 (GPU like T4, Geforce RTX
2080, GeForce GTX 1650 Ti, NVIDIA TITAN RTX, RTX 4000 etc)
- [x] Add kernel for sm=75
- [x] Update dispatch code to use sm to call different kernel.
- [x] Update compile script to use num_stages=2 instead of 3 for sm=75
- [x] Refactor test script and add tests for bfloat16.
- [x] Fix performance test of token generation (previously we did not
concatenate past_key)
- [x] Fix debug build
- [x] Run performance test and update numbers.
For sm=70, the v1 kernel can be compiled but there is error in compiling
v2 kernel. So it is skipped in this pull request.
Performance Test on T4 GPU (using Standard_NC4as_T4_v3 Azure VM) with
`batch_size=4, num_heads=32, max_seq_len=8192, head_size=128,
sparse_block_size=64, local_blocks=16, vert_stride=8, num_layout=8`
We compare sparse attention to corresponding GQA with dense causal. Note
that GQA with dense need more computation since no sparsity is used. The
TORCH-GQA use naive implementation (using cuSPARSE Block-SpMM could be
faster).
```
prompt-sm75-batch4-head32-d128-local16-vert8-torch.float16:
sequence_length TORCH-GQA ORT-GQA-Dense ORT-SparseAtt
1 32.0 0.184173 2.994347 0.089064
2 64.0 0.303300 3.023986 0.107418
3 128.0 0.887795 3.073728 0.174213
4 256.0 2.797654 3.246899 0.357869
5 512.0 10.055048 3.814039 0.893903
6 1024.0 37.849937 5.818439 2.658720
7 2048.0 148.641785 13.638480 7.202690
8 4096.0 OOM 43.556847 17.680954
9 8192.0 OOM 161.628540 44.336670
token-sm75-batch4-head32-d128-local16-vert8-torch.float16:
past_sequence_length TORCH-GQA ORT-GQA-Dense ORT-SparseAtt
1 32.0 0.110353 2.996305 0.137509
2 64.0 0.145088 3.006860 0.165424
3 128.0 0.219500 3.036448 0.192001
4 256.0 0.347496 3.071341 0.249125
5 512.0 0.595842 3.135225 0.398726
6 1024.0 1.081216 3.261110 0.612744
7 2048.0 2.060307 3.515578 0.685670
8 4096.0 OOM 4.022986 0.819707
9 8191.0 OOM 5.024528 1.072912
```
### Motivation and Context
To inference Phi-3-small in T4 GPU
