[HiCache] Fix sidecar pool life-time issue by stepinto · Pull Request #31668 · sgl-project/sglang

stepinto · 2026-07-18T12:43:23Z

Motivation

This PR fixes #31445.

Modifications

There is a life-time issue for sidecar pools. If a prefetch request is aborted before prefetch reads in the IO thread, the host indices are freed, result into a use-after-free hazard.

There 3 changes:

a) Move the prefetch code KV-derived pool to CacheController.page_transfer, and use the same variable PrefetchOperation.completed_tokens to track its progress. Do not save hits to PrefetchOperation.extra_pool_hit_pages. Only non-KV derived pools (e.g. SWA) are performed in HybridCacheController.

b) Use pool_transfer_done as a completion mark for non-KV derived pools, e.g. SWA. Use that variable to determine whether the scheduler thread or the prefetch IO thread to release memory when the prefetch operation is terminated early, e.g. in best effort mode.

c) There protection in the original code, as introduced by #27550, does not cover best_effort code path. It is removed in this PR. The original production (by checking pool_transfers_done in can_terminate) introduced another issue: If the prefetch thread stucks at reading side-car pool, the prefetch of that request will not be timeout in scheduler thread.

Tests

SWE-Bench

Tested SWE-Bench on a single-box sglang server with best_effort configuration and assertion enabled in prefetch IO thread to detect use-after-free in host memory pool. Scores are good. No assertion failure occured.

DSv4 Flash

Cache hit: L1=8.2% L2=18.4% L3=38.7

Group	Total	Resolved
Baseline	500	356
This PR	500	364

(*) Testing scores may vary due to randomness and environment issues.

GLM-5.2

Cache hit: L1=3.7% L2=1.6% L3=14.1%

Group	Total	Resolved
Baseline	500	405
This PR	500	400

(*) Testing scores may vary due to randomness and environment issues.

Multi-turn benchmark

Tested multiturn_bench on DSv4 flash and GLM5.2. The L3 cahce hit ratio seems good. (The last two rounds should hit L3.)

DSv4 Flash

nohup env HF_HUB_OFFLINE=1 \
SGLANG_ENABLE_UNIFIED_RADIX_TREE=1 \
sglang serve \
    --model=deepseek-ai/DeepSeek-V4-Flash \
    --tp-size 8 \
    --max-total-tokens=$((256*1024)) \
    --moe-runner-backend flashinfer_mxfp4 \
    --disable-cuda-graph \
    --mem-fraction-static 0.85 \
    --reasoning-parser deepseek-v4 \
    --tool-call-parser deepseekv4 \
    --host 0.0.0.0 \
    --port 30000 \
    --max-total-tokens=500000 \
    --swa-full-tokens-ratio=0.4 \
    --enable-metrics \
    --enable-hierarchical-cache \
    --hicache-storage-backend=mooncake \
    --hicache-storage-backend-extra-config '{"master_server_address": "127.0.0.1:50051", "local_hostname": "localhost", "metadata_server": "http://127.0.0.1:8080/metadata", "global_segment_size": "512gb", "protocol": "tcp"}' \
    > sglang.log &

python benchmark/hicache/bench_multiturn.py  \
    --num-clients=128 \
    --num-rounds=10 \
    --disable-auto-run  \
    --model=deepseek-ai/DeepSeek-V4-Flash  \
    --enable-round-barrier \
    --request-rate 1



Performance metrics summary:
  Total requests: 1280 at 1.0 requests per second
  Average Prompt Length: 3104.00 tokens
  Average Output Length: 64.00 tokens
  P90 Prompt Length: 5696 tokens
  P99 Prompt Length: 5696 tokens
  P90 Output Length: 64 tokens
  P99 Output Length: 64 tokens
  Average TTFT: 0.36
  P90 TTFT: 0.45
  P99 TTFT: 0.53
  Median TTFT: 0.35
  Max TTFT: 0.91
  Average ITL: 0.1430
  P90 ITL: 0.2494
  P99 ITL: 0.3968
  Median ITL: 0.1239
  Max ITL: 0.7457
  Average latency: 9.37
  P90 latency: 10.14
  P99 latency: 11.19
  Median latency: 9.33
  Max latency: 11.69
  Input token throughput: 2485.35 tokens per second
  Output token throughput: 51.24 tokens per second
  Request Throughput: 0.80 requests per second
  Cache Hit Rate: 0.806765
Per-round metrics:
  Round 0: Average TTFT = 0.34s, Cache Hit Rate = 0.000000 (128 requests, 128 clients)
  Round 1: Average TTFT = 0.34s, Cache Hit Rate = 0.470588 (128 requests, 128 clients)
  Round 2: Average TTFT = 0.34s, Cache Hit Rate = 0.615385 (128 requests, 128 clients)
  Round 3: Average TTFT = 0.35s, Cache Hit Rate = 0.685714 (128 requests, 128 clients)
  Round 4: Average TTFT = 0.34s, Cache Hit Rate = 0.813210 (128 requests, 128 clients)
  Round 5: Average TTFT = 0.37s, Cache Hit Rate = 0.830189 (128 requests, 128 clients)
  Round 6: Average TTFT = 0.36s, Cache Hit Rate = 0.838710 (128 requests, 128 clients)
  Round 7: Average TTFT = 0.37s, Cache Hit Rate = 0.845070 (128 requests, 128 clients)
  Round 8: Average TTFT = 0.36s, Cache Hit Rate = 0.893750 (128 requests, 128 clients)
  Round 9: Average TTFT = 0.41s, Cache Hit Rate = 0.898876 (128 requests, 128 clients)

GLM-5.2

nohup env HF_HUB_OFFLINE=1 \
SGLANG_ENABLE_UNIFIED_RADIX_TREE=1 \
sglang serve \
  --model-path=PhalaCloud/GLM-5.2-W4AFP8 \
  --tp-size=8 \
  --max-total-tokens=$((256*1024)) \
  --enable-hierarchical-cache \
  --hicache-ratio=2 \
  --log-level=debug \
  --enable-metrics \
  --host=0.0.0.0 \
  --mem-fraction-static=0.75 \
  --hicache-ratio=2 \
  --reasoning-parser glm45 \
  --tool-call-parser glm47 \
  --hicache-storage-backend=mooncake \
  --hicache-storage-backend-extra-config '{"master_server_address": "127.0.0.1:50051", "local_hostname": "localhost", "metadata_server": "http://127.0.0.1:8080/metadata", "global_segment_size": "512gb", "protocol": "tcp"}' \
  > sglang.log &

python benchmark/hicache/bench_multiturn.py  \
    --num-clients=128 \
    --num-rounds=10 \
    --disable-auto-run  \
    --model=PhalaCloud/GLM-5.2-W4AFP8  \
    --enable-round-barrier \
    --request-rate 1

Performance metrics summary:
  Total requests: 1280 at 1.0 requests per second
  Average Prompt Length: 3104.00 tokens
  Average Output Length: 64.00 tokens
  P90 Prompt Length: 5696 tokens
  P99 Prompt Length: 5696 tokens
  P90 Output Length: 64 tokens
  P99 Output Length: 64 tokens
  Average TTFT: 0.36
  P90 TTFT: 0.60
  P99 TTFT: 0.98
  Median TTFT: 0.24
  Max TTFT: 1.30
  Average ITL: 0.0202
  P90 ITL: 0.0211
  P99 ITL: 0.2124
  Median ITL: 0.0146
  Max ITL: 0.9828
  Average latency: 1.63
  P90 latency: 2.27
  P99 latency: 3.21
  Median latency: 1.54
  Max latency: 4.48
  Input token throughput: 2870.08 tokens per second
  Output token throughput: 59.18 tokens per second
  Request Throughput: 0.92 requests per second
  Cache Hit Rate: 0.834729
Per-round metrics:
  Round 0: Average TTFT = 0.27s, Cache Hit Rate = 0.000000 (128 requests, 128 clients)
  Round 1: Average TTFT = 0.26s, Cache Hit Rate = 0.527574 (128 requests, 128 clients)
  Round 2: Average TTFT = 0.27s, Cache Hit Rate = 0.691707 (128 requests, 128 clients)
  Round 3: Average TTFT = 0.27s, Cache Hit Rate = 0.770982 (128 requests, 128 clients)
  Round 4: Average TTFT = 0.30s, Cache Hit Rate = 0.818182 (128 requests, 128 clients)
  Round 5: Average TTFT = 0.31s, Cache Hit Rate = 0.848467 (128 requests, 128 clients)
  Round 6: Average TTFT = 0.36s, Cache Hit Rate = 0.870716 (128 requests, 128 clients)
  Round 7: Average TTFT = 0.45s, Cache Hit Rate = 0.887104 (128 requests, 128 clients)
  Round 8: Average TTFT = 0.50s, Cache Hit Rate = 0.899707 (128 requests, 128 clients)
  Round 9: Average TTFT = 0.59s, Cache Hit Rate = 0.910025 (128 requests, 128 clients)

Reproduce case

Passed the reproduce case (#32197).

Checklist

Format your code according to the Format code with pre-commit.
Add unit tests according to the Run and add unit tests.
Update documentation according to Write documentations.
Provide accuracy and speed benchmark results according to Test the accuracy and Benchmark the speed.
Follow the SGLang code style guidance.

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After green CI and required approvals, ask Merge Oncalls or people with Write permission to merge the PR.

CI States

Latest PR Test (Base): ❌ Run #31145822964
Latest PR Test (Extra): ✅ Run #31145822817

gemini-code-assist

Code Review

This pull request introduces synchronization and validation logic for hybrid prefetch results across attention groups to enforce an all-or-nothing policy. If any hybrid pool falls short, the prefetch result is discarded and resources are released. Feedback on the changes points out a potential race condition in hiradix_cache.py where extra_pools are released unconditionally even if the pool transfers are not yet complete, suggesting to only release them when operation.pool_transfers_done is true.

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gemini-code-assist · 2026-07-18T12:44:17Z

+            self.cache_controller.append_host_mem_release(
+                host_indices=operation.host_indices[:completed_tokens],
+                extra_pools=pool_transfers,
+            )


In _sync_and_check_hybrid_prefetch_result, extra_pools is released unconditionally as pool_transfers. However, if the prefetch operation has not completed its pool transfers yet (operation.pool_transfers_done is False), the background IO thread might still be holding or writing to these transfer buffers. Releasing them prematurely can lead to a race condition or use-after-free/double-free issues.

To prevent this, we should only release pool_transfers if operation.pool_transfers_done is True, matching the logic used in unified_radix_cache.py.

Suggested change

self.cache_controller.append_host_mem_release(

host_indices=operation.host_indices[:completed_tokens],

extra_pools=pool_transfers,

)

self.cache_controller.append_host_mem_release(

host_indices=operation.host_indices[:completed_tokens],

extra_pools=pool_transfers if operation.pool_transfers_done else None,

)

hzh0425 · 2026-07-23T12:16:55Z

-            and getattr(operation, "pool_transfers", None)
-            and not getattr(operation, "pool_transfers_done", True)
-        ):
-            can_terminate = False

        operation_terminated = operation.is_terminated()


But under can_terminate_prefetch, does wait_complete still need to check pool_transfers_done?

huangtingwei9988 · 2026-07-24T11:03:35Z

/tag-and-rerun-ci

stepinto · 2026-07-27T01:41:58Z

Rebase to latest code of main branch.

hzh0425 · 2026-07-30T09:24:14Z

-                transfer.host_indices = operation.host_indices
-                if transfer.keys is None:
-                    transfer.keys = operation.hash_value
+                pass


should this be passed?

for dsv4, some sidecar components may share indices with swa, not kv

This else branch is transfer.indices_from_pool == PoolName.KV. The case you mentioned are in the previous if branch, not removed.

hzh0425 · 2026-07-30T09:30:39Z

        self._barrier_attn_groups()
        self.dec_host_lock_ref(last_host_node_id, anchor_lock_params)
        del self.ongoing_prefetch[rid]
+        pool_transfers = [x for xfers in comp_xfers.values() for x in xfers]


pls add some unit test for this case

Done. Added test_release_aborted_request_l3_prefetch_io_in_progress and test_release_aborted_request_l3_prefetch_io_done.

hzh0425

Almost lgtm, just a bit worried that this might break the dsv4 hicache

hzh0425 · 2026-07-30T09:43:23Z

        prefix_keys = operation.prefix_keys
+        kv_derived_transfers = [
+            transfer
+            for transfer in getattr(operation, "pool_transfers", [])


For full-only model, this might throw error?

Fixed. Tested Qwen3-32B with L3.

hzh0425 · 2026-07-30T09:44:47Z

@@ -28,6 +28,7 @@
    HiCacheStorageExtraInfo,


btw, We need to benchmark to see if the current segmented KV + sidecar mode causes any performance regression.
We can use moocnake to benchmark the latency under patterns like 256k and 512k

Done. I have tested that for 256K. My box cannot test 512K.

stepinto · 2026-08-04T02:26:29Z

I tested GLM 5.2 w4a8 on H20 box with 256K L3 prefetch.

Testing method:

# sglang
nohup env HF_HUB_OFFLINE=1 \
SGLANG_ENABLE_UNIFIED_RADIX_TREE=1 \
sglang serve \
  --model-path=PhalaCloud/GLM-5.2-W4AFP8 \
  --tp-size=8 \
  --kv-cache-dtype fp8_e4m3 \
  --enable-hierarchical-cache \
  --hicache-storage-prefetch-policy wait_complete \
  --hicache-ratio=2 \
  --enable-metrics \
  --host=0.0.0.0 \
  --mem-fraction-static=0.75 \
  --hicache-ratio=2 \
  --reasoning-parser glm45 \
  --tool-call-parser glm47 \
  --hicache-storage-backend=mooncake \
  --hicache-storage-backend-extra-config '{"master_server_address": "127.0.0.1:50051", "local_hostname": "localhost", "metadata_server": "http://127.0.0.1:8080/metadata", "global_segment_size": "512gb", "protocol": "tcp"}' \
  > sglang.log 2>&1 &

# Run this command for 11 times.  The first time will fill L3 cache.  The rest are prefetch from L3.
python benchmark/hicache/bench_multiturn.py  \
    --num-clients=1 \
    --num-rounds=1 \
    --disable-auto-run  \
    --model=PhalaCloud/GLM-5.2-W4AFP8  \
    --request-rate 1 \
    --request-length $((256*1024)) \
    --output-length 64

I ran this for baseline (131bd51) and this PR (b137657).

The results are very interesting. After this PR, TTFT is reduced ~10s -> ~9s.

The reason is, before this PR, there is a large sidecar read in the end of prefetch, which results into long-tail.

Here are a prefetch for baseline and PR. The first is baseline. There are large requests that other requests in the end.

stepinto · 2026-08-06T07:24:41Z

Rebased to latest code.

stepinto · 2026-08-06T09:10:54Z

Replay the same benchmark as #30393.

Run sharegpt benchmark. Flush cache. Re-run sharegpt benchmark, loading from L3.

The accept len and accept rate seems similar before flush cache.

Before flush cache: accept len ≈ 3.58，accept rate ≈ 0.52
After flush cahce: accept len ≈ 3.54，accept rate ≈ 0.51

The results are similar to the results in #30393.

nohup env HF_HUB_OFFLINE=1 \
SGLANG_ENABLE_UNIFIED_RADIX_TREE=1 \
sglang serve \
    --model=deepseek-ai/DeepSeek-V4-Flash-0731 \
    --tp-size 4 \
    --max-total-tokens=$((256*1024)) \
    --moe-runner-backend flashinfer_mxfp4 \
    --speculative-algorithm DSPARK \
    --disable-cuda-graph \
    --mem-fraction-static 0.90 \
    --chunked-prefill-size 4096 \
    --reasoning-parser deepseek-v4 \
    --tool-call-parser deepseekv4 \
    --host 0.0.0.0 \
    --port 30000 \
    --max-total-tokens=500000 \
    --swa-full-tokens-ratio=0.1 \
    --enable-metrics \
    --enable-hierarchical-cache \
    --hicache-storage-backend=mooncake \
    --hicache-storage-backend-extra-config '{"master_server_address": "127.0.0.1:50051", "local_hostname": "localhost", "metadata_server": "http://127.0.0.1:8080/metadata", "global_segment_size": "512gb", "protocol": "tcp"}' \
    > sglang.log &


  python -m sglang.bench_serving \
    --backend sglang \
    --host 127.0.0.1 --port 30000 \
    --model deepseek-ai/DeepSeek-V4-Flash-0731 \
    --dataset-name sharegpt \
    --num-prompts 200

stepinto · 2026-08-06T10:06:41Z

Tested dsv4 flash 0731 with EAGLE3. Got similar results as in link. Need to patch #33344.

Before flush cache: 2.461 / 0.487
After flush cache: 2.340 / 0.447

nohup env HF_HUB_OFFLINE=1 \
SGLANG_ENABLE_UNIFIED_RADIX_TREE=1 \
sglang serve \
  --trust-remote-code \
  --mem-fraction-static 0.8 \
  --model-path deepseek-ai/DeepSeek-V4-Flash-0731 \
  --moe-runner-backend marlin \
  --speculative-draft-model-path AQ-MedAI/DeepSeek-V4-Flash-0731-eagle3 \
  --tp-size 8 \
  --speculative-algorithm EAGLE3 \
  --speculative-num-steps 3 \
  --speculative-eagle-topk 1 \
  --speculative-num-draft-tokens 4 \
  --speculative-draft-attention-backend fa3 \
  --host 0.0.0.0 \
  --port 30000 > sglang.log 2>&1 &

  python -m sglang.bench_serving \
    --backend sglang \
    --host 127.0.0.1 --port 30000 \
    --model deepseek-ai/DeepSeek-V4-Flash-0731 \
    --dataset-name sharegpt \
    --num-prompts 200

…project#32035 sgl-project#33656 sgl-project#32183 sgl-project#33145) Applied PRs (latest from GitHub): sgl-project#33288 Indexer logits OOM fix sgl-project#30393 HiCache packed/sidecar draft caches sgl-project#31170 DPA prefix_affinity load balancing sgl-project#33795 DSpark compact ragged-verify CUDA graph JIT race sgl-project#32467 C128 plan-kernel warp barrier sgl-project#33865 DSpark x prefill CP unblock sgl-project#30371 SWA state pool sizing (storage page) sgl-project#33358 FlashMLA norm-rope K-tokens-per-block ILP sgl-project#33872 num_draft_tokens clamp + extend_len==0 skip (supersede sgl-project#32183) sgl-project#34002 Sidecar backup vacuously-successful fix (replaces sgl-project#33656, with tests) sgl-project#33862 Reclaim redundant host mirrors after storage backup sgl-project#31315 Avoid repeated Mooncake gets after stale hits sgl-project#32327 Q8KV8 sparse MLA prefill backend (flashmla_sparse_q8) sgl-project#31668 Fix sidecar pool life-time (use-after-free on prefetch abort) sgl-project#31195 TP0 verify-token-budget broadcast (adapted to get_schedule() API) Dropped (per user request or superseded): sgl-project#32771 IndexCache C4 top-k reuse — has bug sgl-project#32035 DSpark C128 online compressor — has bug sgl-project#33656 Superseded by sgl-project#34002 (same fix + unit tests) sgl-project#32183 Superseded by sgl-project#33872 (included in supersede PR) sgl-project#33145 Base f01f706 already has superior reasoning-effort profile system Conflicts resolved: sgl-project#31195: adapted to base get_schedule().disable_overlap_schedule API sgl-project#32327: path remapped jit_kernel/ -> kernels/jit/ and kernels/ops/attention/ sgl-project#31668: applied cleanly on top of sgl-project#30393+sgl-project#34002+sgl-project#33862 modifications

stepinto · 2026-08-14T08:10:43Z

This PR is moved to #27010.

… use-after-free)

stepinto · 2026-08-27T00:50:15Z

Close this issue, as #27010 has been merged.

stepinto requested review from Ying1123, alphabetc1, hanming-lu, hnyls2002, hzh0425, ispobock, merrymercy, xiezhq-hermann and yizhang2077 as code owners July 18, 2026 12:43

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stepinto force-pushed the fix_mamba_lifecycle_0718 branch from b7c5c2b to edb953b Compare July 18, 2026 12:56

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stepinto mentioned this pull request Jul 21, 2026

[HiCache] Fix PP inconsistency with HiCache L3 (#22607) #27010

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Comment thread python/sglang/srt/mem_cache/unified_radix_cache.py

stepinto force-pushed the fix_mamba_lifecycle_0718 branch from edb953b to 9b2a519 Compare July 23, 2026 11:48

stepinto changed the title ~~[WIP][HiCache] Fix sidecar pool life-time issue~~ [HiCache] Fix sidecar pool life-time issue Jul 23, 2026

hzh0425 added the high priority label Jul 23, 2026

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github-actions Bot added the hicache Hierarchical Caching for SGLang label Jul 24, 2026

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stepinto force-pushed the fix_mamba_lifecycle_0718 branch 2 times, most recently from 7e6f321 to 6de9b08 Compare July 27, 2026 01:41

benmyles mentioned this pull request Jul 27, 2026

Harden DeepSeek V4 DSpark DP2 serving shiftup-ai/sglang#1

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stepinto force-pushed the fix_mamba_lifecycle_0718 branch from a25e5ea to b137657 Compare August 3, 2026 03:04

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stepinto added 6 commits August 6, 2026 16:24

[HiCache] Fix sgl-project#31445 sidecar pool lifecycle issue

770156b

Make complete_pool_transfers atomic

cc06db6

Do not call batch_get_v2 if no sidecar pool

f28f00a

Fix a minor type error in _sync_and_check_hybrid_prefetch_result

af84e90

Add UT

5e94f11

Fix getattr(... "pool_transfer") for full-kv model

ee76c62

stepinto force-pushed the fix_mamba_lifecycle_0718 branch from 079467d to ee76c62 Compare August 6, 2026 08:24

Merge branch 'main' into fix_mamba_lifecycle_0718

d56db5f

hzh0425 added the bypass-fastfail label Aug 7, 2026

Merge branch 'main' into fix_mamba_lifecycle_0718

46f6eb0

stepinto mentioned this pull request Aug 14, 2026

[HiCache]: Optimize hybrid/DSA L3 prefetch result sync and usable-prefix clamping #31443

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Leoyzen added a commit to Leoyzen/sglang that referenced this pull request Aug 20, 2026

fix: add sgl-project#31668 sidecar pool life-time fix (prefetch abort…

e6d1d41

… use-after-free)

stepinto closed this Aug 27, 2026

flymysql mentioned this pull request Aug 30, 2026

UnifiedRadixCache: extra-pool prefetch lifecycle missing on abort (segfault under timeout policy) #31445

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Motivation

Modifications

Tests

SWE-Bench

DSv4 Flash

GLM-5.2

Multi-turn benchmark

DSv4 Flash

GLM-5.2

Reproduce case

Checklist

Review and Merge Process

CI States

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