[Perf] Create TMA-aligned input scale tensor for DeepGemm on Hopper (#32619)

Signed-off-by: Xin Yang <xyangx@amazon.com>

tests/kernels/quant_utils.py

@@ -9,6 +9,7 @@ from vllm.model_executor.layers.quantization.utils.quant_utils import (
     group_broadcast,
 )
 from vllm.platforms import current_platform
+from vllm.utils.deep_gemm import _ceil_to_ue8m0, is_deep_gemm_e8m0_used
 from vllm.utils.math_utils import round_up
 
 FP8_DTYPE = current_platform.fp8_dtype()
@@ -170,6 +171,8 @@ def native_per_token_group_quant_fp8(
     x_ = x.reshape(x.numel() // group_size, group_size)
     amax = x_.abs().max(dim=-1, keepdim=True)[0].clamp(min=eps).to(torch.float32)
     x_s = amax / fp8_max
+    if is_deep_gemm_e8m0_used():
+        x_s = _ceil_to_ue8m0(x_s)
     x_q = (x_ / x_s).clamp(min=fp8_min, max=fp8_max).to(dtype)
     x_q = x_q.reshape(x.shape)
     x_s = x_s.reshape(x.shape[:-1] + (x.shape[-1] // group_size,))