[feat][torchair] support super kernel feat for quantized dsr1 (#3485)

### What this PR does / why we need it?
Port #1916 and #2157 to master branch to fuse operators in deepseek moe
layers, which can reduce scheduling overhead on devices. Note that this
feature is valid only when `tp_size = 1` and
`multistream_overlap_shared_expert` is enabled with torchair graph mode.

### Does this PR introduce _any_ user-facing change?
Users can enable this feature with `--additional-config
'{"torchair_graph_config":{"enabled":true, "enable_super_kernel":true},
"multistream_overlap_shared_expert":true}'`.

### How was this patch tested?
E2E deepseek serving with 2P1D disaggregated prefill scenarios.


- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0

---------

Signed-off-by: linfeng-yuan <1102311262@qq.com>

vllm_ascend/ascend_config.py

@@ -37,7 +37,8 @@ class AscendConfig:
 
         torchair_graph_config = additional_config.get("torchair_graph_config",
                                                       {})
-        self.torchair_graph_config = TorchairGraphConfig(torchair_graph_config)
+        self.torchair_graph_config = TorchairGraphConfig(
+            torchair_graph_config, vllm_config, additional_config)
 
         ascend_scheduler_config = additional_config.get(
             "ascend_scheduler_config", {})
@@ -133,7 +134,7 @@ class TorchairGraphConfig:
     Configuration Object for torchair_graph_config from additional_config
     """
 
-    def __init__(self, torchair_graph_config):
+    def __init__(self, torchair_graph_config, vllm_config, additional_config):
         self.enabled = torchair_graph_config.get("enabled", False)
         self.mode = torchair_graph_config.get("mode", '')
         self.use_cached_graph = torchair_graph_config.get(
@@ -151,6 +152,8 @@ class TorchairGraphConfig:
         self.enable_frozen_parameter = torchair_graph_config.get(
             "enable_frozen_parameter", True)
         self.enable_kv_nz = torchair_graph_config.get("enable_kv_nz", False)
+        self.enable_super_kernel = torchair_graph_config.get(
+            "enable_super_kernel", False)
 
         if not isinstance(self.graph_batch_sizes, list):
             raise TypeError("graph_batch_sizes must be list[int]")
@@ -186,6 +189,20 @@ class TorchairGraphConfig:
                 raise RuntimeError(
                     "enable_kv_nz is valid only when Torchair graph mode is enabled"
                 )
+            if self.enable_super_kernel:
+                raise RuntimeError(
+                    "enable_super_kernel is valid only when Torchair graph mode is enabled"
+                )
+        if self.enable_super_kernel:
+            if vllm_config.parallel_config.tensor_parallel_size != 1:
+                raise RuntimeError(
+                    "enable_super_kernel is valid only when tensor_parallel_size is 1"
+                )
+            if not additional_config.get("multistream_overlap_shared_expert",
+                                         False):
+                raise RuntimeError(
+                    "enable_super_kernel is valid only when multistream_overlap_shared_expert is enabled"
+                )
         if self.use_cached_kv_cache_bytes and not self.use_cached_graph:
             raise RuntimeError(
                 "use_cached_kv_cache_bytes is valid only when Torchair graph mode and use_cached_graph are enabled"