add dispatch_gmm_combine kernel (#3532)

### What this PR does / why we need it?

This PR introduces the Ascend implementation of the
`dispatch_ffn_combine` kernel and wires it into the vLLM-Ascend runtime,
together with follow‑up fixes to ensure the kernel builds and runs
correctly in CI.

- Add full host and device implementation of the `dispatch_ffn_combine`
kernel under `csrc/dispatch_ffn_combine`, including tiling logic, MOE
routing helpers, and kernel utilities for quantized FFN dispatch.
- Integrate the new kernel with the PyTorch binding
(csrc/torch_binding.cpp, csrc/torch_binding_meta.cpp) and the Ascend
runtime (vllm_ascend/ascend_forward_context.py,
vllm_ascend/worker/model_runner_v1.py).
- Extend fused MoE communication and token dispatch support in
`vllm_ascend/ops/fused_moe`, adding methods/utilities needed by the new
dispatch path.
- Update quantization logic in vllm_ascend/quantization/w8a8_dynamic.py
to support the new FFN dispatch flow.
- Fix kernel build issues by adjusting `csrc/build_aclnn.sh`, CMake
configuration, and include/namespace usage in the new kernel files.
- Add an end‑to‑end nightly test
`tests/e2e/nightly/ops/test_dispatch_ffn_combine.py` and helper
utilities in `vllm_ascend/utils.py` to validate the new kernel.

### Does this PR introduce _any_ user-facing change?

### How was this patch tested?


- vLLM version: v0.12.0
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.12.0

---------

Signed-off-by: mojave2 <chenchen145@huawei.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>

vllm_ascend/worker/model_runner_v1.py

@@ -2217,8 +2217,9 @@ class NPUModelRunner(LoRAModelRunnerMixin, ECConnectorModelRunnerMixin):
             return None
 
         soc_version = get_ascend_device_type()
-        quant_type = getattr(self.vllm_config.model_config.hf_config,
-                             'moe_quantize', None)
+        quant_type = getattr(
+            self.vllm_config.model_config.hf_config, 'moe_quantize',
+            getattr(self.vllm_config.model_config.hf_config, 'quantize', None))
         model_type = self.vllm_config.model_config.hf_config.model_type
 
         if not self.parallel_config.enable_expert_parallel:
@@ -2237,7 +2238,8 @@ class NPUModelRunner(LoRAModelRunnerMixin, ECConnectorModelRunnerMixin):
         elif soc_version in {AscendDeviceType._910_93}:
             moe_comm_type = (MoECommType.MC2
                              if num_tokens <= self.mc2_tokens_capacity else
-                             MoECommType.ALLTOALL)
+                             MoECommType.FUSED_ALLTOALL if quant_type
+                             == "w8a8_dynamic" else MoECommType.ALLTOALL)
         else:
             raise ValueError(f"Unsupported soc_version: {soc_version}")