[Performance] Add async exponential while model executing (#4501)

### What this PR does / why we need it?
Add a control to enable the exponential distribution operator
overlapping with model executing (default is OFF due to this feature
might not perform well on MOE models, i.e. For Qwen3-30B).
Enable async exponential overlapping will provides performance
improvement.
Also, overlapping the exponential operator with module execution can
cover the performance drop introduced by AICPU-version's exponential
operator.

**UPDATE**: (12/12)
Now our overlap will use the same stream that introduced in this pr:
#4908 .
We move the `do_async_exponential` from `model_runner_v1.py` to
`sampler.py`.
Now we are using `additional_config` to enable async exponential:
Add `"enable_async_exponential": 1` in `addition_config`.
Now we **ONLY** support default exponential/AI-CPU exponential, the old
`"enable_async_exponential": 2` option has been aborted to keep
consistency.

### Does this PR introduce _any_ user-facing change?
**YES**, added a new `additional_config` : `"enable_async_exponential":
1`.
When `enable_async_exponential` is set to 1, we enable the async
exponential and overlap with model runner.
When `enable_async_exponential` is set to 0 (default is 0), we disable
the async exponential, but exponential will still running on a different
stream using stream introduced in #4908.

- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: YuhanBai <yuhan.bai0830@gmail.com>
Signed-off-by: YuhanBai yuhan.bai0830@gmail.com

vllm_ascend/ascend_config.py

@@ -161,6 +161,11 @@ class AscendConfig:
                                               False):
             kv_cfg.engine_id = f"{kv_cfg.engine_id}-{uuid4().hex}"
             kv_cfg._engine_id_patched = True
+        self.enable_async_exponential = additional_config.get(
+            "enable_async_exponential", 0)
+        if self.enable_async_exponential not in (0, 1):
+            raise AssertionError(
+                "Enable async exponential can only be set to 0 or 1.")
 
 
 class FinegrainedTPConfig: