[Kernel] Remove cumsum in groupedmatmul (vllm-project#987)

### What this PR does / why we need it remove cumsum operator in MOE to improve performance

### How was this patch tested?
it should be tested on a case with mc2 operator and graph mode enabled

Signed-off-by: zhky <hahazhky@163.com>
Co-authored-by: 洪炜杰 <hongweijie1@huawei.com>

Author: hahazhky

vllm_ascend/ops/fused_moe.py

@@ -88,15 +88,14 @@ def fused_experts_with_mc2(hidden_states: torch.Tensor,
         0:5]
 
     w1 = w1.transpose(1, 2)
-    expert_token_nums = torch.cumsum(expert_token_nums,
-                                     dim=0,
-                                     dtype=torch.int64)
+
     group_list = expert_token_nums.to(torch.int64)
     gate_up_out_list = torch_npu.npu_grouped_matmul(
         x=[expand_x],
         weight=[w1],
         split_item=2,
-        group_list_type=0,
+        # 1 means count mode, to avoid cumulative operation of the group list
+        group_list_type=1,
         group_type=0,
         group_list=group_list,
     )
@@ -110,7 +109,7 @@ def fused_experts_with_mc2(hidden_states: torch.Tensor,
         x=[gate_up_out],
         weight=[w2],
         split_item=2,
-        group_list_type=0,
+        group_list_type=1,
         group_type=0,
         group_list=group_list,
     )