[Disaggregated Prefill] P2P Disaggregated Prefill based on llm_datadist (#694)

### What this PR does / why we need it?
- This PR proposes a P2P version of Disaggregated Prefill based on
llm_datadist which manages data transfer.

- This solution reconstructs previous offline single-node Disaggregated
Prefill solution, and supports multi-node and online serveing now.

- Currently this solution supports 1P1D situation of Deepseek hybrid
parallelism (P: TP+EP, D: DP+EP). Note that xPyD situation is considered
in the solution design, and will be supported soon within v1 engine.

---------

Signed-off-by: hw_whx <wanghexiang7@huawei.com>
Signed-off-by: ganyi <pleaplusone.gy@gmail.com>
Co-authored-by: hw_whx <wanghexiang7@huawei.com>
Co-authored-by: ganyi <pleaplusone.gy@gmail.com>

vllm_ascend/distributed/kv_transfer/utils.py

@@ -0,0 +1,40 @@
+#
+# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
+# This file is a part of the vllm-ascend project.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+import llm_datadist  # type: ignore
+import torch
+
+TORCH_DTYPE_TO_NPU_DTYPE = {
+    torch.half: llm_datadist.DataType.DT_FLOAT16,
+    torch.float16: llm_datadist.DataType.DT_FLOAT16,
+    torch.bfloat16: llm_datadist.DataType.DT_BF16,
+    torch.float: llm_datadist.DataType.DT_FLOAT,
+    torch.float32: llm_datadist.DataType.DT_FLOAT,
+    torch.int8: llm_datadist.DataType.DT_INT8,
+    torch.int64: llm_datadist.DataType.DT_INT64,
+    torch.int32: llm_datadist.DataType.DT_INT32,
+}
+
+NPU_DTYPE_TO_TORCH_DTYPE = {
+    llm_datadist.DataType.DT_FLOAT16: torch.half,
+    llm_datadist.DataType.DT_FLOAT16: torch.float16,
+    llm_datadist.DataType.DT_BF16: torch.bfloat16,
+    llm_datadist.DataType.DT_FLOAT: torch.float,
+    llm_datadist.DataType.DT_FLOAT: torch.float32,
+    llm_datadist.DataType.DT_INT8: torch.int8,
+    llm_datadist.DataType.DT_INT64: torch.int64,
+    llm_datadist.DataType.DT_INT32: torch.int32,
+}