Implement LRU eviction policy for LoRA adapters

python/sglang/srt/lora/eviction_policy.py

@@ -0,0 +1,139 @@
+# Copyright 2023-2024 SGLang Team
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+
+"""
+Eviction policies for LoRA adapter memory management.
+"""
+
+import logging
+import time
+from abc import ABC, abstractmethod
+from collections import OrderedDict
+from typing import Any, Dict, List, Optional, Set
+
+logger = logging.getLogger(__name__)
+
+
+class EvictionPolicy(ABC):
+    """Abstract base class for LoRA adapter eviction policies."""
+
+    @abstractmethod
+    def mark_used(self, uid: Optional[str]) -> None:
+        """Marks an adapter as used."""
+        pass
+
+    @abstractmethod
+    def select_victim(self, candidates: Set[Optional[str]]) -> Optional[str]:
+        """Selects an adapter to evict from candidates."""
+        pass
+
+    @abstractmethod
+    def remove(self, uid: Optional[str]) -> None:
+        """Removes an adapter from the policy's tracking."""
+        pass
+
+
+class LRUEvictionPolicy(EvictionPolicy):
+    """LRU eviction policy - evicts the least recently used adapter."""
+
+    def __init__(self):
+        self.access_order = OrderedDict()  # key=uid, value=last_access_time
+        self.total_accesses = 0
+        self.eviction_count = 0
+
+    def mark_used(self, uid: Optional[str]) -> None:
+        if uid is not None:
+            current_time = time.monotonic()
+            # Remove and re-add to move to end (most recent)
+            self.access_order.pop(uid, None)
+            self.access_order[uid] = current_time
+            self.total_accesses += 1
+            logger.debug(f"LoRA {uid} marked as used at {current_time}")
+
+    def select_victim(self, candidates: Set[Optional[str]]) -> Optional[str]:
+        """Select the least recently used adapter from candidates."""
+        # Base model (currently None, will be replaced with special UID in future)
+        # always has lowest priority - evict it first if available
+        BASE_MODEL_UID = None  # TODO: Replace with special UID constant
+        if BASE_MODEL_UID in candidates:
+            logger.debug(f"Selected base model for eviction (LRU)")
+            self.eviction_count += 1
+            return BASE_MODEL_UID
+
+        # Iterate through access_order (oldest first) to find LRU victim
+        for uid in list(self.access_order.keys()):
+            if uid in candidates:
+                logger.debug(f"Selected LoRA {uid} for eviction (LRU)")
+                self.eviction_count += 1
+                return uid
+
+        # Should never reach here if candidates is non-empty
+        assert False, f"Failed to select LRU victim from candidates: {candidates}"
+
+    def remove(self, uid: Optional[str]) -> None:
+        if uid is not None:
+            self.access_order.pop(uid, None)
+            logger.debug(f"Removed LoRA {uid} from LRU tracking")
+
+
+class FIFOEvictionPolicy(EvictionPolicy):
+    """FIFO eviction policy - for backward compatibility."""
+
+    def __init__(self):
+        self.insertion_order = (
+            OrderedDict()
+        )  # key=uid, OrderedDict maintains insertion order
+        self.eviction_count = 0
+
+    def mark_used(self, uid: Optional[str]) -> None:
+        """For FIFO, we only track insertion order (not access time)."""
+        if uid is not None and uid not in self.insertion_order:
+            self.insertion_order[uid] = (
+                True  # Value unused, OrderedDict tracks insertion order
+            )
+
+    def select_victim(self, candidates: Set[Optional[str]]) -> Optional[str]:
+        """Select the first inserted adapter from candidates."""
+        # Base model (currently None, will be replaced with special UID in future)
+        # always has lowest priority - evict it first if available
+        BASE_MODEL_UID = None  # TODO: Replace with special UID constant
+        if BASE_MODEL_UID in candidates:
+            logger.debug(f"Selected base model for eviction (FIFO)")
+            self.eviction_count += 1
+            return BASE_MODEL_UID
+
+        # Iterate through insertion_order (oldest first) to find FIFO victim
+        for uid in list(self.insertion_order.keys()):
+            if uid in candidates:
+                logger.debug(f"Selected LoRA {uid} for eviction (FIFO)")
+                self.eviction_count += 1
+                return uid
+
+        # Should never reach here if candidates is non-empty
+        assert False, f"Failed to select FIFO victim from candidates: {candidates}"
+
+    def remove(self, uid: Optional[str]) -> None:
+        if uid is not None:
+            self.insertion_order.pop(uid, None)
+
+
+def get_eviction_policy(policy_name: str) -> EvictionPolicy:
+    """Factory function to create eviction policy instances."""
+    policies = {
+        "fifo": FIFOEvictionPolicy,
+        "lru": LRUEvictionPolicy,
+    }
+    if policy_name not in policies:
+        raise ValueError(f"Unknown eviction policy: {policy_name}")
+    return policies[policy_name]()

python/sglang/srt/lora/lora_manager.py

@@ -68,6 +68,9 @@ def __init__(
         self.tp_size: int = tp_size
         self.tp_rank: int = tp_rank
 
+        # Store eviction policy from server args
+        self.eviction_policy = server_args.lora_eviction_policy
+
         # LoRA backend for running sgemm kernels
         logger.info(f"Using {lora_backend} as backend of LoRA kernels.")
         backend_type = get_backend_from_name(lora_backend)
@@ -131,6 +134,16 @@ def load_lora_adapter(self, lora_ref: LoRARef) -> LoRAUpdateOutput:
             lora_ref.lora_id not in self.loras
         ), f"LoRA adapter with ID {lora_ref.lora_id} is already loaded. This should have been verified before request is sent to the backend."
 
+        if lora_ref.pinned and self.num_pinned_loras >= self.max_loras_per_batch - 1:
+            return self.create_lora_update_result(
+                success=False,
+                error_message=(
+                    f"Already have {self.num_pinned_loras} pinned adapters, "
+                    f"max allowed is {self.max_loras_per_batch - 1} (reserving 1 slot for dynamic use). "
+                    f"Please unpin some adapters or increase max_loras_per_batch."
+                ),
+            )
+
         try:
             # load configs
             new_adapter = LoRAConfig(lora_ref.lora_path)
@@ -411,6 +424,7 @@ def init_memory_pool(self):
             max_lora_rank=self.max_lora_rank,
             target_modules=self.target_modules,
             base_model=self.base_model,
+            eviction_policy=self.eviction_policy,
         )
 
     def set_lora_module(self, module_name, module):

python/sglang/srt/lora/mem_pool.py

@@ -4,6 +4,8 @@
 import torch
 
 from sglang.srt.distributed import divide
+from sglang.srt.hf_transformers_utils import AutoConfig
+from sglang.srt.lora.eviction_policy import get_eviction_policy
 from sglang.srt.lora.layers import BaseLayerWithLoRA
 from sglang.srt.lora.lora import LoRAAdapter
 from sglang.srt.lora.lora_config import LoRAConfig
@@ -54,6 +56,7 @@ def __init__(
         max_lora_rank: int,
         target_modules: Set[str],
         base_model: torch.nn.Module,
+        eviction_policy: str,
     ):
         self.base_hf_config: AutoConfig = base_hf_config
         self.num_layer: int = base_hf_config.num_hidden_layers
@@ -64,6 +67,9 @@ def __init__(
         self.max_lora_rank: int = max_lora_rank
         self.target_modules: Set[str] = target_modules
 
+        # Initialize eviction policy
+        self.eviction_policy = get_eviction_policy(eviction_policy)
+
         # Both A_buffer and B_buffer maps lora weight names to its buffer space.
         # A_buffer contains num_layer number of row-major tensors with shape
         #   (max_loras_per_batch, stacked_num * max_lora_dim, input_dim)
@@ -189,31 +195,50 @@ def prepare_lora_batch(
         lora_refs: Dict[str, LoRARef],
     ):
         def get_available_buffer_slot():
+            # 1. Prioritize empty slots
             for buffer_id in range(self.max_loras_per_batch):
-                # Prioritize empty slots
                 if self.buffer_id_to_uid[buffer_id] == EMPTY_SLOT:
                     return buffer_id
 
+            # 2. Memory pool is full, need to evict using policy
+            candidates = set()
+
             for buffer_id in range(self.max_loras_per_batch):
                 uid = self.buffer_id_to_uid[buffer_id]
 
-                # Evict unneeded lora
-                if uid not in cur_uids:
-                    # Skip pinned LoRAs
-                    # TODO (lifuhuang): we might consider supporting pinning base model (uid == None) in the future.
-                    if uid is not None:
-                        lora_ref = lora_refs.get(uid)
-                        if lora_ref is not None and lora_ref.pinned:
-                            continue
-
-                    self.uid_to_buffer_id.pop(uid)
-                    logger.debug(f"Evicting LoRA {uid} from buffer slot {buffer_id}.")
-                    self.buffer_id_to_uid[buffer_id] = EMPTY_SLOT
-                    return buffer_id
+                # Skip if this adapter is needed by current batch
+                # TODO (lifuhuang): we might consider supporting pinning base model (uid == None) in the future.
+                if uid in cur_uids:
+                    continue
+
+                # Skip if this adapter is pinned (base model cannot be pinned, so can be evicted)
+                if uid is not None:
+                    lora_ref = lora_refs.get(uid)
+                    if lora_ref and lora_ref.pinned:
+                        continue
+                candidates.add(uid)
 
-            raise ValueError(
-                "No available buffer slots found. Please ensure the number of active loras is less than max_loras_per_batch."
+            if not candidates:
+                raise ValueError(
+                    "No available buffer slots found. Please ensure the number of active (pinned) loras is less than max_loras_per_batch."
+                )
+
+            # Select victim using eviction policy
+            victim_uid = self.eviction_policy.select_victim(candidates)
+
+            # Evict the selected victim
+            victim_buffer_id = self.uid_to_buffer_id[victim_uid]
+            self.uid_to_buffer_id.pop(victim_uid)
+            self.eviction_policy.remove(victim_uid)
+            self.buffer_id_to_uid[victim_buffer_id] = EMPTY_SLOT
+            logger.debug(
+                f"Evicting LoRA {victim_uid} from buffer slot {victim_buffer_id}."
             )
+            return victim_buffer_id
+
+        # Mark all adapters in current batch as used (for LRU tracking)
+        for uid in cur_uids:
+            self.eviction_policy.mark_used(uid)
 
         for uid in cur_uids:
             if uid not in self.uid_to_buffer_id:

python/sglang/srt/server_args.py

@@ -117,6 +117,8 @@
 
 DETERMINISTIC_ATTENTION_BACKEND_CHOICES = ["flashinfer", "fa3", "triton"]
 
+DEFAULT_LORA_EVICTION_POLICY = "lru"
+
 NSA_CHOICES = ["flashmla_prefill", "flashmla_decode", "fa3", "tilelang", "aiter"]
 
 RADIX_EVICTION_POLICY_CHOICES = ["lru", "lfu"]
@@ -278,6 +280,7 @@ class ServerArgs:
     ] = None
     max_loaded_loras: Optional[int] = None
     max_loras_per_batch: int = 8
+    lora_eviction_policy: str = DEFAULT_LORA_EVICTION_POLICY
     lora_backend: str = "triton"
     max_lora_chunk_size: Optional[int] = 16
 
@@ -1975,6 +1978,13 @@ def add_cli_args(parser: argparse.ArgumentParser):
             default=ServerArgs.max_loaded_loras,
             help="If specified, it limits the maximum number of LoRA adapters loaded in CPU memory at a time. The value must be greater than or equal to `--max-loras-per-batch`.",
         )
+        parser.add_argument(
+            "--lora-eviction-policy",
+            type=str,
+            default=DEFAULT_LORA_EVICTION_POLICY,
+            choices=["lru", "fifo"],
+            help="LoRA adapter eviction policy when memory pool is full. 'lru': Least Recently Used (default, better cache efficiency). 'fifo': First-In-First-Out.",
+        )
         parser.add_argument(
             "--lora-backend",
             type=str,

python/sglang/test/runners.py

@@ -519,6 +519,7 @@ def __init__(
         lora_target_modules: Optional[List[str]] = None,
         enable_lora: Optional[bool] = None,
         max_loaded_loras: Optional[int] = None,
+        lora_eviction_policy: str = "lru",
     ):
         self.model_type = model_type
         self.is_generation = model_type == "generation"
@@ -565,6 +566,7 @@ def __init__(
             lora_target_modules=lora_target_modules,
             enable_lora=enable_lora,
             max_loaded_loras=max_loaded_loras,
+            lora_eviction_policy=lora_eviction_policy,
             **spec_kwargs,
         )