[Perf] Cuda Kernel for Int8 Per Token Group Quant (#21476)

Signed-off-by: yewentao256 <zhyanwentao@126.com>

vllm/model_executor/layers/quantization/utils/int8_utils.py

@@ -238,13 +238,20 @@ def per_token_group_quant_int8(
     int8_min = iinfo.min
 
     x_q = torch.empty_like(x, device=x.device, dtype=dtype)
-    M = x.numel() // group_size
-    N = group_size
     x_s = torch.empty(
         x.shape[:-1] + (x.shape[-1] // group_size, ),
         device=x.device,
         dtype=torch.float32,
     )
+    # prefer CUDA kernel if available
+    if current_platform.is_cuda():
+        torch.ops._C.per_token_group_quant_int8(x, x_q, x_s, group_size, eps,
+                                                float(int8_min),
+                                                float(int8_max))
+        return x_q, x_s
+
+    M = x.numel() // group_size
+    N = group_size
 
     BLOCK = triton.next_power_of_2(N)
     # heuristics for number of warps