[DeepSeek-V4] Enable non-paged indexer by default for large prefill chunks (#30140)

python/sglang/srt/environ.py

@@ -842,7 +842,10 @@ class Envs:
     SGLANG_OPT_FUSE_MHC_POST_PRE = EnvBool(False)
     SGLANG_OPT_USE_TILELANG_INDEXER = EnvBool(False)
     SGLANG_OPT_USE_AITER_INDEXER = EnvBool(False)
-    SGLANG_OPT_DSV4_NONPAGED_INDEXER = EnvBool(False)
+    SGLANG_OPT_DSV4_NONPAGED_INDEXER = EnvBool(True)
+    # Per-rank local query rows (after DP-attention sharding when enabled),
+    # not request ISL.
+    SGLANG_OPT_DSV4_NONPAGED_INDEXER_MIN_QUERY_TOKENS = EnvInt(8192)
     SGLANG_OPT_USE_JIT_INDEXER_METADATA = EnvBool(True)
     SGLANG_OPT_USE_ONLINE_COMPRESS = EnvBool(False)
     SGLANG_EXPERIMENTAL_ONLINE_C128_MTP = EnvBool(False)

python/sglang/srt/layers/attention/dsv4/indexer.py

@@ -482,6 +482,8 @@ class C4IndexerBackendMixin:
         c4_seq_lens: torch.Tensor,
         query_rows: int,
     ) -> Optional[NonPagedIndexerPlan]:
+        if query_rows < envs.SGLANG_OPT_DSV4_NONPAGED_INDEXER_MIN_QUERY_TOKENS.get():
+            return None
         if not self._can_use_nonpaged_indexer(
             c4_indexer=c4_indexer,
             forward_batch=forward_batch,

test/registered/unit/layers/test_dsv4_nonpaged_indexer.py

@@ -55,7 +55,10 @@ class TestDSV4NonPagedIndexer(CustomTestCase):
             )
 
     def test_eligibility_is_fail_closed(self):
-        self.assertIs(envs.SGLANG_OPT_DSV4_NONPAGED_INDEXER.default, False)
+        self.assertIs(envs.SGLANG_OPT_DSV4_NONPAGED_INDEXER.default, True)
+        self.assertEqual(
+            envs.SGLANG_OPT_DSV4_NONPAGED_INDEXER_MIN_QUERY_TOKENS.default, 8192
+        )
         self.assertTrue(self._is_eligible())
         for case in (
             {"enabled": False},
@@ -98,6 +101,10 @@ class TestDSV4NonPagedIndexer(CustomTestCase):
                 query_rows=query_rows,
             )
 
+        threshold = envs.SGLANG_OPT_DSV4_NONPAGED_INDEXER_MIN_QUERY_TOKENS
+        with threshold.override(threshold.default):
+            self.assertIsNone(build_plan())
+        with threshold.override(query_rows):
             plan = build_plan()
         self.assertEqual(
             (plan.seq_len_sum, plan.max_seqlen_k, plan.query_rows),
@@ -109,6 +116,7 @@ class TestDSV4NonPagedIndexer(CustomTestCase):
 
         metadata.nonpaged_plan = None
         batch.extend_seq_lens_cpu = [2, 2]
+        with threshold.override(0):
             self.assertIsNone(build_plan())
 
     def test_extreme_plan_metadata_is_bounded_and_fail_closed(self):
@@ -140,6 +148,8 @@ class TestDSV4NonPagedIndexer(CustomTestCase):
                 query_rows=query_rows,
             )
 
+        threshold = envs.SGLANG_OPT_DSV4_NONPAGED_INDEXER_MIN_QUERY_TOKENS
+        with threshold.override(query_rows):
             plan = build_plan()
         self.assertEqual(plan.seq_len_sum, 125_000)
         self.assertEqual(plan.max_seq_len, 125_000)
@@ -151,8 +161,54 @@ class TestDSV4NonPagedIndexer(CustomTestCase):
         batch.extend_seq_lens_cpu = [2, 2]
         batch.extend_seq_lens = torch.tensor([2, 2], dtype=torch.int32)
         batch.extend_start_loc = torch.tensor([0, 2], dtype=torch.int32)
+        with threshold.override(query_rows):
             self.assertIsNone(build_plan())
 
+    def test_query_threshold_boundary(self):
+        can_use_nonpaged_indexer = MagicMock(return_value=True)
+        backend = SimpleNamespace(_can_use_nonpaged_indexer=can_use_nonpaged_indexer)
+        c4_indexer = SimpleNamespace(use_fp4_indexer=False)
+        metadata = SimpleNamespace(nonpaged_plan=None, c4_page_size=64)
+
+        def build_plan(query_rows):
+            batch = SimpleNamespace(
+                seq_lens=torch.tensor([query_rows], dtype=torch.int32),
+                seq_lens_cpu=[query_rows],
+                extend_seq_lens_cpu=[query_rows],
+                extend_seq_lens=torch.tensor([query_rows], dtype=torch.int32),
+                extend_start_loc=torch.tensor([0], dtype=torch.int32),
+                extend_num_tokens=query_rows,
+            )
+            c4_seq_lens = torch.div(
+                torch.arange(1, query_rows + 1, dtype=torch.int32),
+                4,
+                rounding_mode="floor",
+            ).clamp_min_(1)
+            return C4IndexerBackendMixin._get_nonpaged_indexer_plan(
+                backend,
+                c4_indexer=c4_indexer,
+                forward_batch=batch,
+                indexer_metadata=metadata,
+                page_table=torch.zeros((query_rows, 1), dtype=torch.int32),
+                c4_seq_lens=c4_seq_lens,
+                query_rows=query_rows,
+            )
+
+        for query_rows, expected in ((8191, False), (8192, True), (8193, True)):
+            with self.subTest(query_rows=query_rows):
+                metadata.nonpaged_plan = None
+                can_use_nonpaged_indexer.reset_mock()
+                self.assertIs(build_plan(query_rows) is not None, expected)
+                if expected:
+                    can_use_nonpaged_indexer.assert_called_once()
+                else:
+                    can_use_nonpaged_indexer.assert_not_called()
+
+        metadata.nonpaged_plan = None
+        threshold = envs.SGLANG_OPT_DSV4_NONPAGED_INDEXER_MIN_QUERY_TOKENS
+        with threshold.override(8193):
+            self.assertIsNone(build_plan(8192))
+
     def test_nonpaged_dispatch_uses_gathered_kv_contract(self):
         query_rows = 4
         plan = NonPagedIndexerPlan(