Refactor group_concurrent_contiguous in NIXL (#6214)

Co-authored-by: luoyuan.luo <[email protected]>

Author: yuan-luo

python/sglang/srt/disaggregation/nixl/conn.py

@@ -35,29 +35,19 @@
 NixlEngineInfo: TypeAlias = Dict[str, Union[str, int]]
 
 
-# From Mooncake backend.
 def group_concurrent_contiguous(
     src_indices: npt.NDArray[np.int64], dst_indices: npt.NDArray[np.int64]
 ) -> Tuple[List[npt.NDArray[np.int64]], List[npt.NDArray[np.int64]]]:
-    src_groups = []
-    dst_groups = []
-    current_src = [src_indices[0]]
-    current_dst = [dst_indices[0]]
-
-    for i in range(1, len(src_indices)):
-        src_contiguous = src_indices[i] == src_indices[i - 1] + 1
-        dst_contiguous = dst_indices[i] == dst_indices[i - 1] + 1
-        if src_contiguous and dst_contiguous:
-            current_src.append(src_indices[i])
-            current_dst.append(dst_indices[i])
-        else:
-            src_groups.append(current_src)
-            dst_groups.append(current_dst)
-            current_src = [src_indices[i]]
-            current_dst = [dst_indices[i]]
+    """Vectorised NumPy implementation."""
+    if src_indices.size == 0:
+        return [], []
+
+    brk = np.where((np.diff(src_indices) != 1) | (np.diff(dst_indices) != 1))[0] + 1
+    src_groups = np.split(src_indices, brk)
+    dst_groups = np.split(dst_indices, brk)
 
-    src_groups.append(current_src)
-    dst_groups.append(current_dst)
+    src_groups = [g.tolist() for g in src_groups]
+    dst_groups = [g.tolist() for g in dst_groups]
 
     return src_groups, dst_groups