[main] mlp weight prefetch in Qwen Dense Models (#2816)

### What this PR does / why we need it?
This PR prefetchs the weight of mlp layers in Qwen Dense Models to
optimize the performance in Decode phase mainly.

### Does this PR introduce _any_ user-facing change?
 No.

### How was this patch tested?
CI passed with new added/existing test.

- vLLM version: main
- vLLM main:
a1213fae5f

Signed-off-by: rjg-lyh <1318825571@qq.com>
Co-authored-by: Shuming19 <313093131@qq.com>

tests/ut/ops/test_activation.py

@@ -38,7 +38,12 @@ def test_QuickGELU_forward(mock_gelu, dummy_tensor):
 
 @pytest.mark.parametrize("is_310p_return", [True, False])
 @patch("torch_npu.npu_swiglu", side_effect=lambda x: x + 1)
-def test_SiluAndMul_forward(mock_swiglu, is_310p_return, dummy_tensor):
+@patch("torch.ops.vllm.maybe_wait_prefetch_done", side_effect=lambda x: None)
+@patch("torch.ops.vllm.maybe_prefetch_mlp_down_proj",
+       side_effect=lambda x: None)
+def test_SiluAndMul_forward(mock_maybe_prefetch_mlp_down_proj,
+                            mock_maybe_wait_prefetch_done, mock_swiglu,
+                            is_310p_return, dummy_tensor):
 
     with patch("vllm_ascend.utils.is_310p", return_value=is_310p_return):
         layer = SiluAndMul()
@@ -49,9 +54,15 @@ def test_SiluAndMul_forward(mock_swiglu, is_310p_return, dummy_tensor):
         else:
             expected_arg = dummy_tensor
 
+        # assert mock_maybe_prefetch_mlp_down_proj.call_count == 1
+        mock_maybe_prefetch_mlp_down_proj.assert_called_once()
+
         # assert mock_swiglu.call_count == 1
         mock_swiglu.assert_called_once()
 
+        # assert mock_maybe_wait_prefetch_done.call_count == 1
+        mock_maybe_wait_prefetch_done.assert_called_once()
+
         actual_arg = mock_swiglu.call_args[0][0]
         assert torch.allclose(
             actual_arg,