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[router] power_of_two: in-flight request load for --dp-aware decode - #43483

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AMD-yanfeiwang:feat/router-p2c-request-load
Oct 13, 2026
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ShangmingCai merged 1 commit into
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AMD-yanfeiwang:feat/router-p2c-request-load

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@AMD-yanfeiwang AMD-yanfeiwang commented Oct 10, 2026 •

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Motivation

Follow-up to #42027, which this PR is stacked on (its commit is included until it merges).

With DP attention every decode step waits for the busiest DP rank, so what matters is how many requests each rank holds. p2c on num_total_tokens evens out KV across decode ranks but leaves their request counts as uneven as round_robin (tables below).

Modifications

SGLANG_ROUTER_P2C_LOAD_METRIC selects what power_of_two compares:

value compares ties
tokens (default) polled num_total_tokens, two random candidates (unchanged) in-flight requests
requests the router's in-flight requests, two random candidates polled tokens
least_requests the router's in-flight requests, every candidate polled tokens, then random

In-flight requests are counted from dispatch to the end of the response (#42027). For a decode rank that is its running batch, every queue (waiting, prealloc, transfer, retracted) and requests still in prefill: the set /v1/loads reports as num_running_reqs + num_waiting_reqs, but live instead of polled. least_requests skips workers the load monitor has no entry for unless none has one, and reads the counters without locking, so concurrent selections may pick the same worker.

The switch is an env var to keep the policy config and CLI unchanged; happy to turn it into a --p2c-load-metric flag instead.

Results (MI355X)

DeepSeek-V4-Pro AgentX trace replay, 1P1D, prefill TP8/EP8 and decode TP8, both with DP attention (8 decode ranks); router --policy consistent_hashing --dp-aware --worker-startup-check-interval 1 (the load monitor polls at that interval). Router built from this branch on lmsysorg/sglang-rocm:v0.5.21-rocm724-mi35x-20261007; each point is a 1 h measurement.

Absolute values; in parentheses, the change against round_robin. All power_of_two columns poll loads every 1 s.

Output throughput (tok/s/GPU)

conc round_robin tokens requests least_requests
192 369.9 366.7 (-0.9%) 375.5 (+1.5%) 372.8 (+0.8%)
256 439.4 438.4 (-0.2%) 446.3 (+1.6%) 444.3 (+1.1%)
384 563.5 568.4 (+0.9%) 570.1 (+1.2%) 570.0 (+1.2%)
512 590.7 601.1 (+1.8%) 602.6 (+2.0%) 594.3 (+0.6%)

TPOT p50 (ms)

conc round_robin tokens requests least_requests
192 12.45 12.63 (+1.4%) 11.90 (-4.4%) 11.80 (-5.2%)
256 13.92 14.07 (+1.1%) 13.57 (-2.5%) 13.08 (-6.0%)
384 17.34 16.67 (-3.9%) 15.92 (-8.2%) 15.65 (-9.7%)
512 18.45 18.72 (+1.5%) 17.74 (-3.8%) 17.99 (-2.5%)

TPOT p90 (ms)

conc round_robin tokens requests least_requests
192 14.82 14.85 (+0.2%) 13.81 (-6.8%) 13.75 (-7.2%)
256 16.35 16.58 (+1.4%) 15.99 (-2.2%) 15.48 (-5.3%)
384 20.67 19.82 (-4.1%) 18.57 (-10.2%) 18.56 (-10.2%)
512 22.22 22.21 (0.0%) 21.59 (-2.8%) 21.70 (-2.3%)

Decode-rank balance over the measured hour, per-second samples across the 8 ranks (round_robin / tokens / requests / least_requests); outstanding = running + all queues:

c192 c256 c384 c512
outstanding requests, CV 0.17 / 0.22 / 0.09 / 0.05 0.14 / 0.18 / 0.06 / 0.03 0.10 / 0.15 / 0.04 / 0.02 0.08 / 0.12 / 0.02 / 0.01
running batch, CV 0.22 / 0.24 / 0.17 / 0.14 0.19 / 0.20 / 0.14 / 0.13 0.16 / 0.17 / 0.13 / 0.13 0.17 / 0.15 / 0.14 / 0.14
busiest rank's batch 14.8 / 15.2 / 13.1 / 12.7 19.0 / 19.4 / 17.6 / 17.0 28.8 / 28.3 / 25.9 / 25.3 32.5 / 32.5 / 30.6 / 30.5
busiest / mean rank KV tokens 1.43 / 1.23 / 1.35 / 1.32 1.38 / 1.17 / 1.28 / 1.27 1.31 / 1.12 / 1.22 / 1.21 1.24 / 1.08 / 1.19 / 1.18

requests lowers the busiest rank's batch by 6-12% and least_requests by 6-14%, which is where the TPOT gain comes from. Throughput moves less because output is under 1% of the tokens in this input-heavy workload. TTFT stays within run-to-run noise except c384 (p50 +12% with requests, +15% with least_requests), to be rechecked.

Concurrency 512 over the hour

p2c token and p2c in-flight requests below are tokens and requests.

All four arms over the hour, concurrency 512

requests keeps outstanding requests flat across decode ranks for the whole hour (bottom) and least_requests flatter still, while tokens is less even than round_robin. At 512 more than half (55-57%) of each rank's in-flight requests are still waiting on KV transfer, so equal in-flight counts no longer mean equal running batches: the busiest rank's batch (top) improves less than at lower concurrency, and evening out in-flight requests further with least_requests (CV 0.01 vs 0.02) leaves it unchanged (30.5 vs 30.6).

Running requests per decode rank, p2c in-flight requests (1s), concurrency 512

With requests every rank's hourly mean running batch is within 2% of the 8-rank mean, and no rank is the busiest more than 17% of the time (round_robin: DP6 at +6.3% and 21%; 12.5% if even).

Test

Two new unit tests: requests prefers fewer in-flight requests over a lower token load, and least_requests picks the global minimum while skipping workers without a polled load. cargo test --lib (398 passed), cargo clippy --all-targets --all-features -- -D warnings and cargo +nightly fmt -- --check pass.


CI States

Latest PR Test (Base): ✅ Run #38356273395
Latest PR Test (Extra): ❌ Run #38356273155
Latest PR Test (AMD ROCm 10): ➖ No AMD PR run found for this commit.

@AMD-yanfeiwang
AMD-yanfeiwang marked this pull request as ready for review October 10, 2026 03:45
@AMD-yanfeiwang
AMD-yanfeiwang force-pushed the feat/router-p2c-request-load branch from 9049397 to 6fe0571 Compare October 10, 2026 04:44
AMD-yanfeiwang added a commit to AMD-yanfeiwang/smg that referenced this pull request Oct 10, 2026
…ests

With DP attention, an engine's ranks step together and each decode step
waits for the busiest rank, so the number of requests a rank holds is
what sets TPOT. power_of_two scores candidates by the least-load
expected wait, which divides by each rank's reported gen_throughput; on
DP-attention ranks that throughput grows with the rank's running batch,
so the score does not separate ranks by the requests they hold.

--power-of-two-load-metric (load_metric on the power_of_two policy
config, power_of_two_load_metric in the Python bindings) selects what
the policy compares:

- expected_wait: two random workers by expected wait (default, unchanged)
- requests: two random workers by the router's in-flight requests
- least_requests: every worker with a load report, or every worker when
  none has one, by the router's in-flight requests

Both new metrics narrow the candidates to the fewest in-flight requests
and let the expected-wait scorer choose among them, so the expected wait
breaks a tie and the winner's since-poll credit is booked as before.

Ported from sgl-project/sglang#43483, where the metric is set by the
SGLANG_ROUTER_P2C_LOAD_METRIC environment variable.

Signed-off-by: Yanfei Wang <yanfei.wang@amd.com>
AMD-yanfeiwang added a commit to AMD-yanfeiwang/smg that referenced this pull request Oct 10, 2026
…ests

With DP attention, an engine's ranks step together and each decode step
waits for the busiest rank, so the number of requests a rank holds is
what sets TPOT. power_of_two scores candidates by the least-load
expected wait, which divides by each rank's reported gen_throughput; on
DP-attention ranks that throughput grows with the rank's running batch,
so the score does not separate ranks by the requests they hold.

--power-of-two-load-metric (load_metric on the power_of_two policy
config, power_of_two_load_metric in the Python bindings) selects what
the policy compares:

- expected_wait: two random workers by expected wait (default, unchanged)
- requests: two random workers by the router's in-flight requests
- least_requests: every healthy worker by the router's in-flight requests

Both new metrics narrow the candidates to the fewest in-flight requests
and let the expected-wait scorer choose among them, so the expected wait
breaks a tie and the winner's since-poll credit is booked as before.

Ported from sgl-project/sglang#43483, where the metric is set by the
SGLANG_ROUTER_P2C_LOAD_METRIC environment variable.

Signed-off-by: Yanfei Wang <yanfei.wang@amd.com>
AMD-yanfeiwang added a commit to AMD-yanfeiwang/smg that referenced this pull request Oct 12, 2026
…ests

With DP attention, an engine's ranks step together and each decode step
waits for the busiest rank, so the number of requests a rank holds is
what sets TPOT. power_of_two scores candidates by the least-load
expected wait, which divides by each rank's reported gen_throughput; on
DP-attention ranks that throughput grows with the rank's running batch,
so the score does not separate ranks by the requests they hold.

--power-of-two-load-metric (load_metric on the power_of_two policy
config, power_of_two_load_metric in the Python bindings) selects what
the policy compares:

- expected_wait: two random workers by expected wait (default, unchanged)
- requests: two random workers by the router's in-flight requests
- least_requests: every healthy worker by the router's in-flight requests

Both new metrics narrow the candidates to the fewest in-flight requests
and let the expected-wait scorer choose among them, so the expected wait
breaks a tie and the winner's since-poll credit is booked as before.

Ported from sgl-project/sglang#43483, where the metric is set by the
SGLANG_ROUTER_P2C_LOAD_METRIC environment variable.

Signed-off-by: Yanfei Wang <yanfei.wang@amd.com>
AMD-yanfeiwang added a commit to AMD-yanfeiwang/sglang that referenced this pull request Oct 12, 2026
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hi, @ShangmingCai , could you please help on review this PR and #42027. This PR improves load balancing in the PD (prefill–decode disaggregation) setup.

We will try to land these optimizations in the experimental router later. That will take some time.

With DP attention every decode step waits for the busiest DP rank, so the
number of requests a rank holds matters more than its KV tokens.

SGLANG_ROUTER_P2C_LOAD_METRIC selects what power_of_two compares:
- tokens (default): polled token load, then in-flight requests (unchanged).
- requests: the router's in-flight requests, then polled token load.
- least_requests: as requests, over every worker with a polled load instead
  of two random ones.
@AMD-yanfeiwang
AMD-yanfeiwang force-pushed the feat/router-p2c-request-load branch from 6fe0571 to b2ee501 Compare October 13, 2026 06:21

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LGTM

@ShangmingCai

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/tag-and-rerun-ci

@github-actions github-actions Bot added the run-ci CI: run the baseline test suite on this PR label Oct 13, 2026
@ShangmingCai
ShangmingCai merged commit d8f8522 into sgl-project:main Oct 13, 2026
134 of 142 checks passed
Jianhong-Zhang added a commit to Jianhong-Zhang/sglang that referenced this pull request Oct 21, 2026
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* [Unified Radix] Invalidate lazy Mamba checkpoints before in-place tracking (sgl-project#43567)

* [diffusion] perf: encode LTX video/audio through the shared bounded MP4 path (sgl-project#43656)

Co-authored-by: Mick Qian <mickqian@users.noreply.github.com>

* [HiCache] Keep storage workers alive on backend exceptions (sgl-project#43550)

* Build Mamba host pools from device buffer infos (sgl-project#43596)

* Share MLA host capacity initialization (sgl-project#43595)

* Preserve serialized page dtype in NIXL copy fallback (sgl-project#43593)

* [diffusion] fix: select VSA-H3 for FastH3 when no transformer backend is given (sgl-project#43690)

Co-authored-by: Mick Qian <mickqian@users.noreply.github.com>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>

* [KV Events] Publish LoRA adapter names and namespaced block hashes (sgl-project#42455)

Signed-off-by: Banruo Liu <lichangxinlivingshade@gmail.com>
Co-authored-by: Shangming Cai <csmthu@gmail.com>

* [DSpark] Run every markov head through one step interface (sgl-project#43620)

* [DSpark] Add `MarkovSampleStep`, one op for a markov draft step's add and token pick (sgl-project#43621)

* [DSpark] Draft the eager markov block through `MarkovSampleStep` (sgl-project#43622)

* [DSpark] Run the same markov block in the draft graph tail; drop `SGLANG_DSPARK_FOLDED_SAMPLING` (sgl-project#43668)

* [DSpark] Merge the draft TP sync sites into `dspark-draft` (sgl-project#43669)

* [DSpark] Add `SGLANG_DSPARK_USE_GREEDY_DRAFT`, an argmax draft accepted as one-hot (sgl-project#43670)

* [DSpark] Apply `SGLANG_SIMULATE_ACC_LEN` inside the accept instead of switching paths (sgl-project#43623)

* [diffusion] fix: shard Qwen-Image adaLN modulation and text FFN under TP (sgl-project#43691)

* [diffusion] perf: layerwise offload for the LTX-2.5 Gemma-4 text encoder (sgl-project#43683)

* [diffusion] perf: split and batch LTX-2.3 one-stage guidance passes under CFG parallel (sgl-project#43684)

Co-authored-by: Mick Qian <mickqian@users.noreply.github.com>

* [Fix] Initialize BF16 GEMM dispatch in the one-batch benchmark (sgl-project#43702)

* Fix Mistral-native format detection when the Hub is unreachable (sgl-project#43446)

* [MoE] Skip block-padding rows in the TMA down activation and quant (sgl-project#42212)

* [MemCache] Split the SWA mapping move out of locked-full recovery as `RecoverEvictedSWA` (sgl-project#43721)

Co-authored-by: Hanming Lu <69857889+hanming-lu@users.noreply.github.com>
Co-authored-by: Jialin <Jialin@users.noreply.github.com>

* [Rust] Lock hyper 1.12.0 and want 0.3.2 in the rust workspace (sgl-project#43724)

Co-authored-by: hanminglu <hanminglu@users.noreply.github.com>
Co-authored-by: shodoco <shodoco@users.noreply.github.com>

* [MemCache] Add shared component size and path APIs to the tree core interface (sgl-project#43722)

Co-authored-by: Hanming Lu <69857889+hanming-lu@users.noreply.github.com>
Co-authored-by: Jialin <Jialin@users.noreply.github.com>

* [CI] Fix TestQwenImageModulationCache after Qwen-Image modulation sharding (sgl-project#43747)

Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>

* [Bugfix] Preserve available host memory for integrated MUSA devices (sgl-project#43398)

Signed-off-by: Xucheng Zhou <aden1350@outlook.com>

* [Tokenizer] Require fastokens>=0.3.2 and include it in the all extra (sgl-project#43104)

* [AMD][V4.1][*/N] Fix DP attention + TP MoE decode NaN and support bounded replay (sgl-project#43077)

Co-authored-by: wunhuang <wunhuang@amd.com>
Co-authored-by: HAI <hixiao@gmail.com>

* Support kv cache sharding for DSA indexer (sgl-project#40925)

* [AMD][MORI] Add MORI EP V2 support (sgl-project#40666)

* [PD] Retract transferred decode requests on a retract pause (sgl-project#43757)

* [DSV4.1] Reduce eager Engram extend preparation (sgl-project#42159)

Co-authored-by: Shangming Cai <csmthu@gmail.com>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>

* [Test] Re-anchor the VLM flashinfer throughput floor (sgl-project#43762)

Co-authored-by: Mohammad Angkad <mohammad.angkad@radixark.ai>

* [Fix] scheduler: stop latching batch_is_full when nothing can run (sgl-project#41872)

Co-authored-by: hnyls2002 <lsyincs@gmail.com>
Co-authored-by: Liangsheng Yin <hnyls2002@gmail.com>

* [RL] Return a failed weight update when the cache flush is refused (sgl-project#43758)

* [CI] Skip eval retries in the PD transfer-failure test (sgl-project#43769)

* docs: sync LMSYS SGLang blog cards (sgl-project#43462)

Co-authored-by: sglang-bot <sglang-bot@users.noreply.github.com>

* [Deps] Bump FlashInfer to 0.7.1 (sgl-project#43494)

Co-authored-by: Mohammad Angkad <mohammad.angkad@radixark.ai>

* [XPU CI] Optimize PR CI per-file timeouts and fail hanging tests fast (sgl-project#42048)

* [Fix] Adapt to transformers 5.18 / 5.19 changes (sgl-project#43688)

Co-authored-by: Mohammad Angkad <mohammad.angkad@radixark.ai>

* [diffusion][xpu] FLUX.2: enable the bit-exact Triton SwiGLU on XPU (sgl-project#41940)

Co-authored-by: Claude Opus 5 <noreply@anthropic.com>
Co-authored-by: Mick Qian <mickqian@users.noreply.github.com>

* docs: clarify prefill CP terminology and simplify wording (sgl-project#43787)

* [Fix] Link cuda_ipc JIT against CUDA driver stubs dir (sgl-project#43764)

* [Perf] Route BF16 mixed-batch decode tails through decode attention (sgl-project#43238)

Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
Co-authored-by: Xiaoyu Zhang <1182563586@qq.com>

* [PD] Poison the deferred abort ack when a Mooncake send fails (sgl-project#43719)

Co-authored-by: Claude Fable 5.1 <noreply@anthropic.com>

* [HiCache] Support Mamba in buffer-only host memory mode (sgl-project#36345)

* [HiCache] Preserve all MTP KV and recurrent state (sgl-project#40223)

Co-authored-by: alphabetc1 <2508695655@qq.com>
Co-authored-by: Shuwen Wang <47200617+alphabetc1@users.noreply.github.com>

* [CI] Move tests that do not need GB300 off the per-PR GB300 suite (sgl-project#43784)

Co-authored-by: Mohammad Angkad <mohammad.angkad@radixark.ai>

* Capture KV host transfer buffers (sgl-project#43711)

* Keep NIXL Mamba checkpoint keys separate by TP rank (sgl-project#43594)

* [XPU] Support decode context parallelism (DCP) on Intel XPU (sgl-project#34355)

Co-authored-by: Siju Samuel <siju.samuel@intel.com>

* [BCG][DSV4-Flash][CP] Support DeepSeek V4 prefill with interleave CP and breakable CUDA graphs (sgl-project#38603)

* [DSV4.1][PD][1/N] Support prefill node use cp parallel strategy (sgl-project#40323)

* [Docs] Update GLM-5.3-Flash playground: B300 default, CP8, EP and PD (sgl-project#43802)

* [Docs] Cookbook: refresh SemiAnalysis AgentX launches (GLM-5.2 B300, DeepSeek-V4.1 GB300) (sgl-project#43799)

Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>

* [NPU] Stabilize HiCache and registered CI tests (sgl-project#43308)

* [sgl-router] Serve the Anthropic Messages API on /v1/messages (sgl-project#42316)

Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
Co-authored-by: Xinyuan Tong <115166877+JustinTong0323@users.noreply.github.com>

* [Fix] Make tokenizer request-state initialization atomic (sgl-project#41911)

Co-authored-by: Cheng Wan <54331508+ch-wan@users.noreply.github.com>

* [XPU] Upgrade XPU backend to PyTorch 2.14 (sgl-project#42003)

Co-authored-by: Ashwini Rathi <arathi@habana.ai>
Co-authored-by: Y <ashwini.rathi@intel.com>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* [PD][Spec] Give a PD decode's first EAGLE draft step a proposal distribution (sgl-project#41783)

Co-authored-by: Shangming Cai <csmthu@gmail.com>

* [Fix] Adapt NPU Qwen-VL processor patch to transformers 5.19 resize() signature change (sgl-project#43309)

* [NPU] Diffusion CI fixes (sgl-project#43210)

* [diffusion] chore: bind worker CPUs to the GPU's NUMA node when memory policy is not permitted (sgl-project#43756)

Co-authored-by: Mick Qian <mickqian@users.noreply.github.com>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>

* [CI][Diffusion] Add caching for npu GT images in CI (sgl-project#37426)

Co-authored-by: Артем Савкин <58187114+OrangeRedeng@users.noreply.github.com>

* [QSA] Bound the decode indexer's work by the context length (sgl-project#43463)

Co-authored-by: luoyuan.luo <luoyuan.luo@antgroup.com>

* Prebuild fixup_zero_kv JIT module at TRTLLM-MLA backend init (sgl-project#37525)

Co-authored-by: Claude Fable 5 <noreply@anthropic.com>

* [Unified Cache] Abort requests whose external linker load fails instead of crashing the scheduler (sgl-project#40896)

* [DSpark] Share draft params, logits dtype, confidence and the accept tail between graph and eager (sgl-project#43790)

* [DFlash] Decide the Domino candidate pool in one place and apply simulated acceptance inside the accept (sgl-project#43791)

* Fix autograd retention in CUDA graph capture tail hooks (sgl-project#43854)

* [ROCm] Eliminate HiCache migration stalls and use exact-size host allocations (sgl-project#42553)

Signed-off-by: JohnQinAMD <yanyuan.qin@amd.com>
Co-authored-by: JohnQinAMD <yanyuan.qin@amd.com>

* [AMD] Keep the FP4 varctx schedule test off AITER's 2048-row compile (sgl-project#41793)

* [AMD] Add flydsl mxfp8 dense gemm kernel for dpsk v4.1 prefill (sgl-project#43803)

* [AMD] Fix test_compact_attention_hip.py CI (sgl-project#43836)

* [AMD] [Docker] Update MoRI to v1.2.4 (sgl-project#43834)

* [Kernel] Expose bundled FlashMLA MegaAttention kernels and APIs (sgl-project#43918)

* [DeepSeek-V4.1] Admit the NIXL transfer backend for DSpark PD (sgl-project#43734)

* [AMD] Recalibrate test_quark_mxfp4 GSM8K thresholds to observed MI355X noise (sgl-project#41980)

* [DSV4][CP] Write low-ratio page indices when CP prefill runs paged attention (sgl-project#43935)

* [Build][CI] Drop Python 3.10: require Python 3.11+ and run CUDA CI on Python 3.12 (sgl-project#43021)

Co-authored-by: Mohammad Angkad <mohammad.angkad@radixark.ai>
Co-authored-by: Mohammad Miadh Angkad <176301910+mmangkad@users.noreply.github.com>

* [DeepSeek-V4.1] mHC: drop seam_open, narrow precomputed stats in take_rows (sgl-project#43833)

Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>

* [DSv4.1] Reduce sparse-prefill workspace padding (sgl-project#43921)

* [HiCache] Avoid full-store scans for uncached file prefix lookups (sgl-project#42077)

Signed-off-by: apex-mochen <2756823972@qq.com>
Co-authored-by: apex-mochen <265981728+apex-mochen@users.noreply.github.com>
Co-authored-by: Zhiqiang Xie <xiezhq@stanford.edu>

* [Fix] Preserve HTTP errors for non-streaming /v1/messages (sgl-project#43796)

Co-authored-by: Xinyuan Tong <xinyuantong.cs@gmail.com>
Co-authored-by: Xinyuan Tong <115166877+JustinTong0323@users.noreply.github.com>

* [DSv4.1] Temporarily disable B300 PD/CP accuracy test (sgl-project#43948)

* [PD] Recompute retracted DeepSeek-V4 requests on prefill instead of crashing decode (sgl-project#43936)

* [Fix] Account for captured inputs in DeepGEMM masked workspace budget (sgl-project#43563)

* [AMD] Update v4 amd cookbook 1012 (sgl-project#43962)

* [CI] Remove Mistral Small 4 e2e test (sgl-project#43973)

Co-authored-by: Mohammad Angkad <mohammad.angkad@radixark.ai>

* Reuse Hugging Face LFM2-MoE configuration (sgl-project#43939)

Co-authored-by: Codex <codex@openai.com>

* fix(openai): honor tool_choice=none in DeepSeek encoders (sgl-project#43006)

Co-authored-by: ai-jz <ai-jz@users.noreply.github.com>
Co-authored-by: Xinyuan Tong <115166877+JustinTong0323@users.noreply.github.com>

* [diffusion] comfyui: run MiniMax H3, FastH3 and VDN in SGLD integrated mode (sgl-project#43504)

* [diffusion] fix: keep MiniMax-H3 VAE fused norms off ROCm (sgl-project#43350)

* [diffusion] fix: avoid redundant LoRA scaling while preserving exact numerics (sgl-project#43028)

Co-authored-by: Mick Qian <mickqian@users.noreply.github.com>

* tokenizer perf optimization (sgl-project#39771)

Co-authored-by: BBuf <1182563586@qq.com>
Co-authored-by: Xinyuan Tong <xinyuantong.cs@gmail.com>

* [diffusion] perf: implement paint_use_remesh (decimate to 40k faces before UV unwrap) for Hunyuan3D (sgl-project#42770)

Co-authored-by: Mick Qian <mickqian@users.noreply.github.com>

* [AMD][Kimi-K3] Use public FlyDSL APIs in KDA decode kernels (sgl-project#43968)

Co-authored-by: wunhuang <wunhuang@amd.com>

* [AMD] Fix Flux2 kv-gather abort on non-contiguous K/V (sgl-project#43793)

Co-authored-by: Mick Qian <mickqian@users.noreply.github.com>

* [AMD] Fuse prefill index-Q RoPE fake-quant and fp4 quantize kernels in DSV4.1 (sgl-project#42911)

* [AMD][DI][CI] dsv4pro-fp8 2p1d-ep16-mtp: raise prefill mem fraction for MORI EP v2 memory (sgl-project#43944)

* [router] Fix power_of_two with --dp-aware (sgl-project#42027)

* [ROCm][Spec] Route NGRAM tree reconstruction to the JIT kernel on HIP (sgl-project#43328)

Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Thomas Wang <thomawan@amd.com>

* [PD] Support heterogeneous TP for hybrid SWA KV transfer (sgl-project#40909)

* [Diffusion] Speed up LTX-2 guidance and video output (sgl-project#43667)

* [AMD][PD] enable mori transfer for PD decode DCP (sgl-project#37358)

Signed-off-by: inkcherry <mingzhi.liu@amd.com>
Co-authored-by: Duyi-Wang <duyi.wang@amd.com>
Co-authored-by: HAI <hixiao@gmail.com>
Co-authored-by: Shangming Cai <csmthu@gmail.com>

* [Docs] Cookbook: refresh SemiAnalysis AgentX launches (DeepSeek-V4.1 GB200/GB300, GLM-5.2 FP8 B300) (sgl-project#43983)

Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>

* [PD][NIXL] Fix staging buffer startup by accepting slot_layer_ids (sgl-project#43723)

Co-authored-by: Po-Han Huang (NVIDIA) <53919306+nvpohanh@users.noreply.github.com>

* [router] power_of_two: in-flight request load for --dp-aware decode (sgl-project#43483)

* [Perf] Enable fast-math for JIT activations on Blackwell (sgl-project#43236)

Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>

* [NVIDIA][MegaMoE] Fix the default spec decoding moe backend when the target model uses flashinfer megamoe (sgl-project#40772)

Co-authored-by: Po-Han Huang (NVIDIA) <53919306+nvpohanh@users.noreply.github.com>

* [HiCache][PD] Allow DSA index-K elision under HiCache and disaggregation (sgl-project#41769)

Co-authored-by: Anish Shanbhag <ashanbhag@nvidia.com>

* [CI] Use sgl-eval for GLM-5.3-Flash GSM8K tests (sgl-project#43975)

Co-authored-by: Mohammad Angkad <mohammad.angkad@radixark.ai>

* [FlashInfer] Add startup autotuning for MegaMoE (sgl-project#43789)

* [Perf] Compact GDN causal-conv grids for skewed prefill batches (sgl-project#43570)

* [AMD][CI] Run test_tracing.py in the extra tier, matching CUDA (sgl-project#43928)

Co-authored-by: Claude Opus 5.5 (1M context) <noreply@anthropic.com>

* Fix EVS for NemotronH_Omni_Reasoning_V3 (sgl-project#42933)

Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
Co-authored-by: Po-Han Huang (NVIDIA) <53919306+nvpohanh@users.noreply.github.com>

* fix(multimodal): convert grayscale tensors to RGB in PIL backend (sgl-project#42127)

Co-authored-by: 周云昊 <zhouyunhao@zhouyunhaodeMacBook-Pro.local>

* [diffusion] comfyui: run Qwen-Image 2.1 in SGLD integrated mode (sgl-project#43581)

* [diffusion] feat: add configurable reference image resizing for MiniMax H3 Ref2VA (sgl-project#35839)

Co-authored-by: Mick Qian <mickqian@users.noreply.github.com>

* Fix/compressed tensors nvfp4 hopper (sgl-project#40022)

Co-authored-by: Claude Opus 5 <noreply@anthropic.com>

* [NPU] [DOC] update kimi k3 cookbook and supported features on NPU (sgl-project#44052)

* [DSA] Q8KV8 FP8 Sparse Prefill on GLM-5.3-Flash with BF16 KV Cache (sgl-project#41790)

Co-authored-by: Xiaoyu Zhang <1182563586@qq.com>

* [CI] Run test_pi05_modelopt_fp8_cuda in the kernel-unit lane (sgl-project#44055)

Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>

* fix(openai): omit absent tool_calls from chat responses (sgl-project#43027)

Co-authored-by: ai-jz <ai-jz@users.noreply.github.com>
Co-authored-by: Xinyuan Tong <xinyuantong.cs@gmail.com>

* Skip fully-masked KV tiles in sliding-window extend attention (sgl-project#39769)

Co-authored-by: Cursor <cursoragent@cursor.com>

* fix(openai): keep chat stream created timestamp stable (sgl-project#43026)

Co-authored-by: ai-jz <ai-jz@users.noreply.github.com>
Co-authored-by: Xinyuan Tong <115166877+JustinTong0323@users.noreply.github.com>

* fix(openai): preserve zero cached tokens when cache reporting is enabled (sgl-project#43005)

Co-authored-by: ai-jz <ai-jz@users.noreply.github.com>
Co-authored-by: Xinyuan Tong <115166877+JustinTong0323@users.noreply.github.com>

* [AMD][DI][CI] glm52 2p1d-ep16: capture CUDA graph on decode (eager decode is too slow) (sgl-project#43977)

* [AMD][DI][CI] kimik26 2p1d-ep16: capture CUDA graph on decode (eager decode is slow) (sgl-project#43985)

* [perf] [multi-lora] remove empty CTAs from fused LoRA expand and add split-K to shrink (sgl-project#41951)

Co-authored-by: Yanbin Jiang <jybsuper@gmail.com>

* Rainj me/rust bench (sgl-project#43950)

* [Observability] Report per-request storage prefetch and staging waits in meta_info (sgl-project#43946)

Co-authored-by: Hanming Lu <69857889+hanming-lu@users.noreply.github.com>
Co-authored-by: xiezhq-hermann <xiezhq-hermann@users.noreply.github.com>

* [lora] Support LoRA for the NemotronH_Nano_VL_V2 model family (sgl-project#39798)

Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
Co-authored-by: Po-Han Huang <pohanh@nvidia.com>
Co-authored-by: Yanbin Jiang <jybsuper@gmail.com>

* [Rust] Refuse an unsupported multimodal model before the Rust listener binds (sgl-project#43925)

Co-authored-by: Hanming Lu <69857889+hanming-lu@users.noreply.github.com>
Co-authored-by: shodoco <shodoco@users.noreply.github.com>

* [Core] Keep request priority within the signed 64-bit range in radix caches (sgl-project#43920)

Co-authored-by: Hanming Lu <69857889+hanming-lu@users.noreply.github.com>
Co-authored-by: qandrew <qandrew@users.noreply.github.com>

* [DCP] Decode context parallelism for DSA (GLM-5.2 / GLM-5.3) with MTP (sgl-project#43735)

Co-authored-by: vincentzed <207368749+vincentzed@users.noreply.github.com>

* [HiCache] Block-group pool hits, caller-owned load destinations, allocation-target FULL eviction (sgl-project#43868)

Co-authored-by: Hanming Lu <69857889+hanming-lu@users.noreply.github.com>
Co-authored-by: xiezhq-hermann <xiezhq-hermann@users.noreply.github.com>

* [Rust] Let an embedding package wrap the frontend HTTP app (sgl-project#43924)

Co-authored-by: hanminglu <hanminglu@users.noreply.github.com>
Co-authored-by: shodoco <shodoco@users.noreply.github.com>

* [Core] Add request-level customized_info keys and mark Full prefill capture batches (sgl-project#43772)

Co-authored-by: Hanming Lu <69857889+hanming-lu@users.noreply.github.com>
Co-authored-by: jiayisuse <jiayisuse@users.noreply.github.com>

* [HiCache] Extract the buffer-mode prefetch and load-back lifecycle into pipeline operations (sgl-project#43870)

Co-authored-by: Hanming Lu <69857889+hanming-lu@users.noreply.github.com>
Co-authored-by: xiezhq-hermann <xiezhq-hermann@users.noreply.github.com>

* [unified memory pool] Prefer SWA reclaim quotas with a HiCache storage backend or on PD decode (sgl-project#43919)

Co-authored-by: Hanming Lu <69857889+hanming-lu@users.noreply.github.com>
Co-authored-by: ZYHowell <ZYHowell@users.noreply.github.com>

* [Rust] Serve any `model` name on the OpenAI chat and completions routes (sgl-project#43923)

Co-authored-by: Hanming Lu <69857889+hanming-lu@users.noreply.github.com>
Co-authored-by: shodoco <shodoco@users.noreply.github.com>

* docs: add MiniCPM-V 4.7 cookbook (sgl-project#43829)

* [Feature] Add Aaronson-Gumbel text watermarking (sgl-project#37577)

Co-authored-by: Nihar Patel <nihpat95@gmail.com>

* [HiSparse] Add speculative decoding support with multi-step KV cache swapping (sgl-project#37771)

* [gRPC] Move runtime.v1 bindings to tonic 0.14, report OpenAI status codes, return text on request (sgl-project#42673)

Co-authored-by: Kan Wu <kan.wu@radixark.ai>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>

* [DeepSeek-V4.1] Run decoder SWA bounded replay inside the breakable prefill CUDA graph (sgl-project#43736)

* fix(benchmark): request token IDs when counting OpenAI prompts (sgl-project#34511)

Co-authored-by: Zijie Xia <zijie.xia@radixark.ai>

* Mark FP32 redux asm volatile (sgl-project#44137)

* [Score] Send stacked GPU embedding overrides through a CUDA IPC pool (sgl-project#39730)

Co-authored-by: Sundara Raman Ramachandran <sundar24295@gmail.com>
Co-authored-by: hnyls2002 <lsyincs@gmail.com>

* [Feature] Return output top logprobs as flat base64 arrays on request (sgl-project#42890)

Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>

* [DSV4.1] Support decoder SWA bounded replay with CUDA DP attention (sgl-project#43812)

* GLM5.2 DSA Indexer Fallback (sgl-project#32947)

Co-authored-by: Shu Wang <shuw@login-hecate03.hecate.clusters.nvidia.com>
Co-authored-by: Po-Han Huang (NVIDIA) <53919306+nvpohanh@users.noreply.github.com>

* [Fix] Work around a CPython fork deadlock in the CPU preprocess pool (sgl-project#44143)

* [DSV4.1] Skip Mega mHC fusion on 0-row (DP-idle) batches (sgl-project#43993)

Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>

* [Chore] release: Cherry-pick [Disagg] Return prompt routed experts from the PD prefill server to release/v0.5.22 (sgl-project#44002) (sgl-project#44212)

Co-authored-by: William Arnold <7565007+Aphoh@users.noreply.github.com>
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* [Chore] release: Cherry-pick [CI] glm5.2: Temporarily disable PD HiSparse+MTP B300 test to release/v0.5.22 (sgl-project#44192) (sgl-project#44214)

Co-authored-by: Mohammad Miadh Angkad <176301910+mmangkad@users.noreply.github.com>
Co-authored-by: Mohammad Angkad <mohammad.angkad@radixark.ai>

* [XPU] Fix FP8 KV cache support for ModelOpt quantized models (e.g. Llama-3.3-70B-FP8)

* [XPU] Add MXFP4 W4A16 MoE inference support for Intel Xe2 (GPT-OSS)

Enable MXFP4 quantized inference on XPU using the native Xe2 SYCL
fused_experts kernel (sgl-kernel-xpu PR#184).

- quantization/__init__.py: register mxfp4 quantization method for XPU
- quantization/fp4_utils.py: broaden flashinfer import exception to avoid
  crash on XPU where flashinfer is unavailable
- quantization/mxfp4.py:
  - align intermediate size to 64 for XPU (create_weights)
  - skip CPU dequant on XPU; leave weights as packed uint8 in VRAM
    (process_weights_after_loading)
  - add XPU dispatch in apply(): call sgl_kernel.fused_experts with
    use_mxfp4_w4a16=True; convert UE8M0 uint8 scales to float32 via
    exp2(uint8 - 127); default gemm1_alpha=1.702 / gemm1_limit=7.0 to
    select activation_type=2 (ACT_SWIGLU_GPT_OSS, interleaved weight
    layout required by GPT-OSS MXFP4 checkpoints)
- models/gpt_oss.py: replace hardcoded .cuda() with .to(get_device())
  in weight loading to support XPU

* [XPU] Improvement for fp4 and fp8

 Optimize FP8 KV cache: lazy mirror buffer to avoid full cast per step
 Fix MXFP4 MoE: read activation/gemm1 params from model config instead of GPT-OSS hardcoded values

* Remove WA for FP8 KV cache

* Add analyze support for XPU

* [Intel][XPU] Allow mamba extra_buffer radix cache strategy on XPU (#9)

Co-authored-by: root <root@gnrsp-bmg3.iind.intel.com>

---------

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