feat(hicache): Supports 3fs-hicache compatibility with dp-attention (#9372)

benchmark/hf3fs/bench_storage.py

@@ -59,7 +59,7 @@ def test():
         raise RuntimeError(f"Failed to dump config to {config_path}: {str(e)}")
 
     rank = 0
-    hicache_hf3fs = HiCacheHF3FS.from_env_config(rank, bytes_per_page, dtype)
+    hicache_hf3fs = HiCacheHF3FS.from_env_config(bytes_per_page, dtype, rank)
 
     numel = 2 * tokens_per_page * layer_num * head_num * head_dim
     assert numel * dtype.itemsize == bytes_per_page

python/sglang/srt/managers/cache_controller.py

@@ -269,7 +269,6 @@ class HiCacheController:
                     HiCacheHF3FS,
                 )
 
-                rank = get_tensor_model_parallel_rank()
                 if self.mem_pool_host.layout == "page_first":
                     bytes_per_page = (
                         mem_pool_host.get_ksize_per_token() * mem_pool_host.page_size
@@ -280,7 +279,7 @@ class HiCacheController:
                     )
                 dtype = mem_pool_host.dtype
                 self.storage_backend = HiCacheHF3FS.from_env_config(
-                    rank, bytes_per_page, dtype
+                    bytes_per_page, dtype
                 )
                 self.get_hash_str = get_hash_str
             else:

python/sglang/srt/mem_cache/hicache_storage.py

@@ -13,6 +13,11 @@ from sglang.srt.distributed import (
     get_tensor_model_parallel_rank,
     get_tensor_model_parallel_world_size,
 )
+from sglang.srt.layers.dp_attention import (
+    get_attention_tp_rank,
+    get_attention_tp_size,
+    is_dp_attention_enabled,
+)
 
 
 def get_hash_str(token_ids: List[int], prior_hash: str = None) -> str:
@@ -103,8 +108,13 @@ class HiCacheFile(HiCacheStorage):
 
     def __init__(self, file_path: str = "/tmp/hicache", is_mla: bool = False):
         self.file_path = os.getenv("SGLANG_HICACHE_FILE_BACKEND_STORAGE_DIR", file_path)
-        tp_rank = get_tensor_model_parallel_rank()
+        if is_dp_attention_enabled():
-        tp_size = get_tensor_model_parallel_world_size()
+            tp_rank = get_attention_tp_rank()
+            tp_size = get_attention_tp_size()
+        else:
+            tp_rank = get_tensor_model_parallel_rank()
+            tp_size = get_tensor_model_parallel_world_size()
+
         self.tp_suffix = f"_{tp_rank}_{tp_size}" if tp_size > 1 and not is_mla else ""
         if not os.path.exists(self.file_path) and tp_rank == 0:
             os.makedirs(self.file_path)

python/sglang/srt/mem_cache/storage/hf3fs/storage_hf3fs.py

@@ -11,6 +11,11 @@ from typing import Any, List, Optional, Tuple
 
 import torch
 
+from sglang.srt.distributed import get_tensor_model_parallel_rank
+from sglang.srt.layers.dp_attention import (
+    get_attention_tp_rank,
+    is_dp_attention_enabled,
+)
 from sglang.srt.mem_cache.hicache_storage import HiCacheStorage
 from sglang.srt.mem_cache.storage.hf3fs.client_hf3fs import Hf3fsClient
 
@@ -167,13 +172,20 @@ class HiCacheHF3FS(HiCacheStorage):
 
     @staticmethod
     def from_env_config(
-        rank: int, bytes_per_page: int, dtype: torch.dtype
+        bytes_per_page: int, dtype: torch.dtype, rank: int = None
     ) -> "HiCacheHF3FS":
         from sglang.srt.mem_cache.storage.hf3fs.mini_3fs_metadata_server import (
             Hf3fsGlobalMetadataClient,
             Hf3fsLocalMetadataClient,
         )
 
+        if rank is None:
+            rank = (
+                get_attention_tp_rank()
+                if is_dp_attention_enabled()
+                else get_tensor_model_parallel_rank()
+            )
+
         config_path = os.getenv(HiCacheHF3FS.default_env_var)
         if not config_path:
             return HiCacheHF3FS(