Add CUDA kernel for per_token_group_quant_fp8

[mgoin]

Currently failing some shapes

E       AssertionError: assert False
E        +  where False = <built-in method allclose of type object at 0x76f6c14c5280>(tensor([[176., 240.,  11.,  ..., 256.,  11., 384.],\n        [448., 288., 224.,  ..., 256.,  52., 320.],\n        [ 96.,...      [112., 384., 256.,  ..., 384.,  40., 288.],\n        [416., 144., 416.,  ...,  88., 288., 256.]], device='cuda:0'), tensor([[176., 240.,  11.,  ..., 256.,  11., 384.],\n        [448., 288., 224.,  ..., 256.,  52., 320.],\n        [ 96.,...      [112., 384., 256.,  ..., 384.,  40., 288.],\n        [416., 144., 416.,  ...,  88., 288., 256.]], device='cuda:0'), rtol=0.15)
E        +    where <built-in method allclose of type object at 0x76f6c14c5280> = torch.allclose
E        +    and   tensor([[176., 240.,  11.,  ..., 256.,  11., 384.],\n        [448., 288., 224.,  ..., 256.,  52., 320.],\n        [ 96.,...      [112., 384., 256.,  ..., 384.,  40., 288.],\n        [416., 144., 416.,  ...,  88., 288., 256.]], device='cuda:0') = <built-in method to of Tensor object at 0x76f52b91a7b0>(torch.float32)
E        +      where <built-in method to of Tensor object at 0x76f52b91a7b0> = tensor([[176., 240.,  11.,  ..., 256.,  11., 384.],\n        [448., 288., 224.,  ..., 256.,  52., 320.],\n        [ 96.,....,  40., 288.],\n        [416., 144., 416.,  ...,  88., 288., 256.]], device='cuda:0',\n       dtype=torch.float8_e4m3fn).to
E        +      and   torch.float32 = torch.float32
E        +    and   tensor([[176., 240.,  11.,  ..., 256.,  11., 384.],\n        [448., 288., 224.,  ..., 256.,  52., 320.],\n        [ 96.,...      [112., 384., 256.,  ..., 384.,  40., 288.],\n        [416., 144., 416.,  ...,  88., 288., 256.]], device='cuda:0') = <built-in method to of Tensor object at 0x76f52ba25040>(torch.float32)
E        +      where <built-in method to of Tensor object at 0x76f52ba25040> = tensor([[176., 240.,  11.,  ..., 256.,  11., 384.],\n        [448., 288., 224.,  ..., 256.,  52., 320.],\n        [ 96.,....,  40., 288.],\n        [416., 144., 416.,  ...,  88., 288., 256.]], device='cuda:0',\n       dtype=torch.float8_e4m3fn).to
E        +      and   torch.float32 = torch.float32

tests/kernels/test_block_fp8.py:198: AssertionError
--------------------------------------------------------------------------------------------------------- Captured stdout call ---------------------------------------------------------------------------------------------------------
num_tokens=83, d=13824, dtype=torch.bfloat16, group_size=64, seed=0
ref_out tensor([[176., 240.,  11.,  ..., 256.,  11., 384.],
        [448., 288., 224.,  ..., 256.,  52., 320.],
        [ 96., 144., 256.,  ..., 288.,  80., 320.],
        ...,
        [128., 416.,  72.,  ..., 384., 352., 128.],
        [112., 384., 256.,  ..., 384.,  40., 288.],
        [416., 144., 416.,  ...,  88., 288., 256.]], device='cuda:0')
out     tensor([[176., 240.,  11.,  ..., 256.,  11., 384.],
        [448., 288., 224.,  ..., 256.,  52., 320.],
        [ 96., 144., 256.,  ..., 288.,  80., 320.],
        ...,
        [128., 416.,  72.,  ..., 384., 352., 128.],
        [112., 384., 256.,  ..., 384.,  40., 288.],
        [416., 144., 416.,  ...,  88., 288., 256.]], device='cuda:0')
tensor([[0., 0., 0.,  ..., 0., 0., 0.],
        [0., 0., 0.,  ..., 0., 0., 0.],
        [0., 0., 0.,  ..., 0., 0., 0.],
        ...,
        [0., 0., 0.,  ..., 0., 0., 0.],
        [0., 0., 0.,  ..., 0., 0., 0.],
        [0., 0., 0.,  ..., 0., 0., 0.]], device='cuda:0')
tensor(32., device='cuda:0')
======================================================================================================= short test summary info ========================================================================================================
FAILED tests/kernels/test_block_fp8.py::test_cuda_per_token_group_quant_fp8[83-13824-dtype28-64-0] - AssertionError: assert False
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
============================================================================================= 1 failed, 28 passed, 208 deselected in 7.64s =============================================================================================

[github-actions]

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[tlrmchlsmth]

where does the 512.f come from?

[mgoin]

I copied this from dynamic_per_token_scaled_fp8_quant_kernel

vllm/csrc/quantization/fp8/common.cu

Line 33 in f89978a

float const min_scaling_factor = 1.0f / (FP8_E4M3_MAX * 512.f);

[LucasWilkinson]

Seeing a minor boost over: #14476 when combined with that

  backend  input_tokens  output_tokens  output_toks/s     req/s  median_itl_ms  median_ttft_ms
3    vllm          1000           1000     982.249267  0.982249      42.002411     2403.797040
2    vllm          5000           1000     521.687045  0.521687      38.893414     6001.047062
4    vllm         10000           1000     331.643844  0.331644      36.228126    54635.778229
1    vllm         32000           1000     113.265287  0.113265      36.442538   183086.203407

[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @mgoin.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork