[BugFix] Fix ACLgraph bug in Qwen3_32b_int8 case (#3204)

### What this PR does / why we need it?
1. Solved the issue where sizes capture failed for the Qwen3-32b-int8
model when aclgraph, dp1, and tp4 were enabled.
2. Added the exception thrown when sizes capture fails and provided a
solution
3. Add this common problem to the FAQ doc
### Does this PR introduce _any_ user-facing change?
no

### How was this patch tested?
ut

- vLLM version: v0.10.2
- vLLM main:
https://github.com/vllm-project/vllm/commit/releases/v0.11.0

Signed-off-by: lilinsiman <lilinsiman@gmail.com>

vllm_ascend/utils.py

@@ -40,14 +40,6 @@ if TYPE_CHECKING:
 else:
     VllmConfig = None
 
-# NOTE: Currently, we can only capture 1800 graphs at most,
-# due to the limitation of ACL graph. This number is bounded by
-# the number of streams, which is 2048, we save 248 streams
-# as a buffer.
-# Maximum number of graphs that can be captured by ACL Graph
-# TODO: Find out whether we need to solve allreduce function
-MAX_CAPTURE_SIZE = 1800
-
 ASCEND_QUANTIZATION_METHOD = "ascend"
 SOC_VERSION_INFERENCE_SERIES = ["Ascend310P3"]
 REGISTERED_ASCEND_OPS = {}
@@ -293,6 +285,14 @@ def get_max_hidden_layers(hf_config) -> int:
 
 def update_aclgraph_sizes(vllm_config: VllmConfig) -> None:
     """Update ACL graph capture sizes based on hardware limitations"""
+    # NOTE: Currently, we can only capture 1800 graphs at most,
+    # due to the limitation of ACL graph. This number is bounded by
+    # the number of streams, which is 2048, we save 248 streams
+    # as a buffer.
+    # Maximum number of graphs that can be captured by ACL Graph
+    # TODO: Find out whether we need to solve allreduce function
+    MAX_CAPTURE_SIZE = 1800
+
     # Store original configuration and temporarily clear it
     compilation_config = vllm_config.compilation_config
     original_sizes, compilation_config.cudagraph_capture_sizes = \
@@ -326,6 +326,11 @@ def update_aclgraph_sizes(vllm_config: VllmConfig) -> None:
                     "multistream_overlap_shared_expert", False))
         if is_moe_model(vllm_config):
             parallel_factor += (parallel_config.data_parallel_size > 1)
+        else:
+            # When AIV mode is enabled, the allreduce operator of the dense
+            # layer model will occupy additional streams, which are buffered here.
+            MAX_CAPTURE_SIZE = MAX_CAPTURE_SIZE - parallel_factor * resources_per_graph
+
         # Calculate maximum supported batch sizes considering model architecture on the A2 Hardware Device
         # Assume the following case:
         # MAX_CAPTURE_SIZE = 1920, num_hidden_layers = 48, data_parallel_size is 1, tensor_parallel_size is 4,