Kimi K3 B200 Day 0 AgentX Pipeline Parallelism (non-DSpark as it doesn't work with Pipeline yet, offloading & TP16 and DEP8PP2 to be done in followup PR) - #2391
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…ecipe Aggregated TP8 x PP2 across 2 B200 nodes (16 GPUs), plain TP (no expert parallelism) for the agentic-coding trace replay. Dedicated bring-up image vllm/vllm-openai:kimi-k3 with VLLM_ENABLE_K3_LATENT_MOE_TAIL_FUSION=1, fastsafetensors load format, kimi_k3 tool-call/reasoning parsers. Model pre-staged at /lustre/fsw/models/Kimi-K3; launch_b200-dgxc.sh gains the kimik3/fp4 model-path mapping, the agentic recipe overlay, and the agentic cache default_mounts used by the GB200/GB300 agentic paths. 中文:新增 Kimi-K3 MXFP4 B200 聚合式 TP8xPP2 Dynamo-vLLM 智能体编码基准测试配方 (2 节点 / 16 GPU,纯 TP,不启用专家并行(EP))。使用专用 bring-up 镜像 vllm/vllm-openai:kimi-k3(VLLM_ENABLE_K3_LATENT_MOE_TAIL_FUSION=1、 fastsafetensors 加载格式、kimi_k3 工具调用/推理解析器)。模型已预置于 /lustre/fsw/models/Kimi-K3;启动器 launch_b200-dgxc.sh 增加 kimik3/fp4 模型路径映射、智能体配方覆盖及智能体缓存挂载。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
中文:在更新日志条目与 MODELS 表格行中补充 PR #2355 链接。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
…oke test The cquil11/srt-slurm-nv cam/sa-submission-q2-2026 fork rejected the recipe (benchmark.aiperf_server_metrics: Unknown field). Switch the b200-dgxc agentic clone to upstream NVIDIA/srt-slurm v1.0.36 (validated in #2302/#2341), drop the aiperf_server_metrics field, pin dynamo wheel/router to 1.2.1 (the combination validated with v1.0.36), and reduce the bring-up to a single conc-8 smoke test. 中文:cquil11/srt-slurm-nv 分支的 srtctl 校验拒绝了配方字段 benchmark.aiperf_server_metrics(Unknown field)。将 b200-dgxc 智能体路径改用 上游 NVIDIA/srt-slurm v1.0.36(已在 #2302/#2341 验证),移除该字段,dynamo wheel/router 固定为 1.2.1,并将 bring-up 缩减为单并发(conc 8)冒烟测试。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
The dynamo-vllm worker entrypoint rejected --enable-auto-tool-choice --tool-call-parser kimi_k3 (unrecognized arguments; different arg parser than vllm serve). Chat parsing happens at the dynamo frontend — same convention as the DSv4 GB300 agentic recipes. Keep --reasoning-parser kimi_k3 (accepted by the worker). Also drop the explicit max-model-len and let vLLM derive the native 1M window from the model config, mirroring the agentic recipe convention. 中文:dynamo-vllm worker 入口不接受 --enable-auto-tool-choice 与 --tool-call-parser kimi_k3(unrecognized arguments,与 vllm serve 的参数解析器 不同),聊天解析由 dynamo 前端处理,与 DSv4 GB300 智能体配方约定一致;保留 worker 可接受的 --reasoning-parser kimi_k3。同时移除显式 max-model-len, 由 vLLM 从模型配置推导原生 1M 上下文窗口。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Third sweep attempt: the engine loaded and served (TP8xPP2 healthy in ~14 min), but dynamo 1.2.1's rust frontend tokenizer rejects Kimi-K3's tiktoken model_type 'kimi_k3' (supported: kimi, kimi_k2, kimi_k25, deepseek_v3), so the model never registered and all chat completions returned 404, aborting the AgentX warmup. Switch to the 1.2.0.dev20260426 wheel used by the DSv4 GB300/B200 Dynamo-vLLM recipes. Upstream published v1.4.0-kimi-k3-dev.1 (2026-07-27) as the day-zero K3 build if this wheel also lacks support. 中文:第三次扫描中引擎已成功加载并提供服务(TP8xPP2 约 14 分钟就绪),但 dynamo 1.2.1 的 rust 前端分词器不支持 Kimi-K3 的 tiktoken model_type 'kimi_k3',模型未能注册,所有请求返回 404,AgentX 预热中止。改用 DSv4 GB300/B200 Dynamo-vLLM 配方所用的 1.2.0.dev20260426 wheel;如仍不支持, 上游已于 2026-07-27 发布 day-zero 构建 v1.4.0-kimi-k3-dev.1。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Pin dynamo to ba83080ecd31c1ce918559e576d3c5bc9e092ff1 ("feat: Added
support for Kimi-K3", tag v1.4.0-kimi-k3-dev.1) via srt-slurm's
hash-cached source install: it adds the kimi_k3 tiktoken tokenizer to the
rust frontend (dynamo <=1.2.1 404s every request because the model never
registers) and accepts the kimi_k3 tool-call/reasoning parser worker args,
so restore --enable-auto-tool-choice --tool-call-parser kimi_k3
--reasoning-parser kimi_k3.
中文:将 dynamo 固定到 day-zero Kimi-K3 提交 ba83080("feat: Added support
for Kimi-K3",标签 v1.4.0-kimi-k3-dev.1),通过 srt-slurm 的哈希缓存源码
安装:该提交为 rust 前端新增 kimi_k3 tiktoken 分词器(dynamo <=1.2.1 因模型
无法注册而全部返回 404),worker 亦支持 kimi_k3 解析器参数,故恢复
--enable-auto-tool-choice --tool-call-parser kimi_k3 --reasoning-parser kimi_k3。
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Replace the vLLM OpenAI-frontend spellings (--enable-auto-tool-choice / --tool-call-parser) with dynamo's namespaced worker args: --dyn-tool-call-parser kimi_k3 --reasoning-parser kimi_k3 --dyn-reasoning-parser kimi_k3. 中文:将 vLLM OpenAI 前端风格参数(--enable-auto-tool-choice / --tool-call-parser)替换为 dynamo 命名空间的 worker 参数: --dyn-tool-call-parser kimi_k3 --reasoning-parser kimi_k3 --dyn-reasoning-parser kimi_k3。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Fifth sweep attempt: the day-zero dynamo registered the kimi_k3 tiktoken tokenizer and the engine served, but all warmup requests got 400 — aiperf's conv-aware routing emits nvext.session_control, a removed POC field this dynamo build rejects (schema moved to router/routing_constraints/ agent_hints). Opt out via AIPERF_USE_DYNAMO_CONV_AWARE_ROUTING=0, matching the GB300 aggregate AgentX recipes; a single aggregate worker has no P/D routing to bind anyway. 中文:第五次扫描中 day-zero dynamo 已成功注册 kimi_k3 tiktoken 分词器并正常 服务,但全部预热请求返回 400——aiperf 的会话感知路由会发送 nvext.session_control(已被移除的 POC 字段,schema 已迁移至 router/routing_constraints/agent_hints)。通过 AIPERF_USE_DYNAMO_CONV_AWARE_ROUTING=0 关闭,与 GB300 聚合式 AgentX 配方 一致;单聚合 worker 本无需 P/D 路由绑定。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Sixth sweep attempt (both A and C variants): warmup requests 500 then the model 503s — the image's first decode step crashes in the KDA hybrid-state postprocess (mamba_hybrid.py postprocess_state, IndexError: index_fill_(): Expected dtype int64 for index; torch requires an int64 index but the runner passes the int32 idx_mapping). Ship an in-container patch through srt-slurm's setup_script hook (same pattern as configs/patches/ vllm_numa_bind_hash_fix.py): coerce the index with .long(), idempotent, refuses to run if the image layout changed. 中文:第六次扫描(A、C 两个变体一致):预热请求先 500、随后模型 503——镜像 首个解码步在 KDA 混合状态后处理中崩溃(mamba_hybrid.py postprocess_state, IndexError: index_fill_() 需要 int64 索引,但 runner 传入 int32 idx_mapping)。 通过 srt-slurm 的 setup_script 钩子在容器内打补丁:将索引用 .long() 转换, 幂等,且镜像布局变化时拒绝执行。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Serve Kimi-K3 directly with vllm serve (srt-slurm PR #278 frontend.type: vllm, branch kylliang/direct-aggregate-vllm): no dynamo frontend/worker/ router, which removes the dynamo tokenizer/schema gaps entirely, and the OpenAI-frontend flags --enable-auto-tool-choice --tool-call-parser kimi_k3 --reasoning-parser kimi_k3 become legitimate. PR #278 validates single-node only, so ship patches/srt-slurm-pr278-direct-vllm-multinode.patch extending it to vLLM-native multi-node serve (--master-addr/--nnodes/--node-rank, headless non-leader ranks) for the 2-node TP8xPP2 topology. Keeps the mamba_hybrid index-dtype container patch (engine bug is frontend-agnostic). 中文:智能体实验变体 D——通过 srt-slurm PR #278(frontend.type: vllm)直接以 vllm serve 提供服务:去除 dynamo 前端/worker/router,从根本上规避 dynamo 的 分词器与 schema 兼容问题,OpenAI 前端参数 --enable-auto-tool-choice --tool-call-parser kimi_k3 --reasoning-parser kimi_k3 因此可用。PR #278 仅 支持单节点,故新增补丁将其扩展为 vLLM 原生多节点 serve(--master-addr/ --nnodes/--node-rank,非主节点 headless),以运行 2 节点 TP8xPP2 拓扑。保留 mamba_hybrid 索引类型容器补丁(引擎缺陷与前端无关)。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
中文:将更新日志条目与 MODELS 表格行链接指向实验 PR #2359。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Same engine-level OOM as the dynamo-frontend variants: the flashinfer trtllm MXFP4 MoE kernel allocates a ~1.6 GiB runtime workspace outside vLLM's memory pool on the first forward; at 0.95 a 178 GiB B200 has only ~1.35 GiB free. 中文:与 dynamo 前端变体相同的引擎级 OOM:flashinfer trtllm MXFP4 MoE 内核在 首个前向时于 vLLM 显存池外分配约 1.6 GiB 工作区,0.95 下仅剩约 1.35 GiB。 改为 0.90。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Inherited from the closed dynamo-frontend variants (#2355/#2358): at gpu-mem-util 0.90 the first long-context MLA prefill OOM'd on a 2.92 GiB transient while 3.39 GiB sat reserved-but-unallocated (fragmentation). Set PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True and drop NCCL_CUMEM_ENABLE. 中文:继承自已关闭的 dynamo 前端变体(#2355/#2358):0.90 显存利用率下首个 长上下文 MLA 预填充因 2.92 GiB 瞬时分配 OOM,而 3.39 GiB 处于已保留未分配 状态(碎片化)。设置 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True 并 移除 NCCL_CUMEM_ENABLE。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
…refill OOM)" This reverts commit 4370988. The superseded direct-vllm run served the agentic benchmark for 24 minutes on the original env (NCCL_CUMEM_ENABLE=1, no expandable_segments) without any OOM — the allocator change was precautionary carryover from the closed dynamo-frontend variants and was never justified by evidence from this serving path. Restore the env that was demonstrably running. 中文:回滚 4370988。被中断的 direct-vllm 运行在原始环境 (NCCL_CUMEM_ENABLE=1、未设 expandable_segments)下已稳定运行智能体基准测试 24 分钟且无 OOM——该分配器改动只是从已关闭的 dynamo 前端变体沿袭的预防性 措施,并无本服务路径上的证据支持。恢复已被验证可运行的环境。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Keep prefix-cache blocks alive across agentic turn gaps, matching the GB200/GB300 AgentX recipes. 中文:新增 VLLM_PREFIX_CACHE_RETENTION_INTERVAL=32768,使前缀缓存块在智能体 回合间隔内保持留存,与 GB200/GB300 AgentX 配方一致。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
中文:将智能体并发列表从单点 8 扩展为 1/8/16/32。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Engine init hard-fails on Kimi-K3 with the GB200/GB300 AgentX value: "VLLM_PREFIX_CACHE_RETENTION_INTERVAL (32768) must be non-negative and a multiple of scheduler_block_size (3145728)" — the KDA hybrid architecture gives K3 a 3.1M-token scheduler block. Default retention served fine in the earlier runs, so drop the override. 中文:移除 VLLM_PREFIX_CACHE_RETENTION_INTERVAL——Kimi-K3 的 KDA 混合架构使 scheduler_block_size 达 3145728,GB200/GB300 AgentX 的 32768 取值导致引擎 初始化直接失败(必须为其整数倍)。此前运行证明默认留存策略可正常服务, 故不再覆盖。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Identical GPU-resident direct-vllm config to variant D (#2359) plus VLLM_PREFIX_CACHE_RETENTION_INTERVAL=0. Any positive value must be a multiple of Kimi-K3's KDA-hybrid scheduler_block_size (3145728), so 0 is the only setting below one 3.1M-token scheduler block. 中文:智能体实验变体 G——与变体 D(#2359)完全相同的 GPU 常驻直接 vllm serve 配置,另加 VLLM_PREFIX_CACHE_RETENTION_INTERVAL=0(任何正值都必须是 Kimi-K3 KDA 混合架构 scheduler_block_size 3145728 的整数倍,0 是唯一低于 一个 3.1M token 调度块的取值)。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
中文:将更新日志条目与 MODELS 表格行链接指向实验 PR #2374。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
…ntic-direct-vllm-retention0 # Conflicts: # perf-changelog.yaml
中文:变体 G 并发曲线扩展为 1/2/4/8/16/32(新增 2 与 4)。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Variant G (#2374, fully green) minus the kimi-k3-container-deps.sh in-container patch (setup_script reference, script file, and launcher copy), to verify whether the mamba_hybrid index_fill_ dtype patch is still required by the current vllm/vllm-openai:kimi-k3 image. Expected to fail at the first decode step if it is; results will be commented on the PR. 中文:探针变体 K——在全绿的变体 G(#2374)基础上移除 kimi-k3 容器内补丁 脚本(setup_script 引用、脚本文件与启动器复制),验证当前 vllm/vllm-openai:kimi-k3 镜像是否仍需 mamba_hybrid index_fill_ 类型补丁。 如仍需要,预计在首个解码步失败;结果将评论在 PR 中。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
中文:将更新日志条目与 MODELS 表格行链接指向实验 PR #2391。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
…ntic-direct-vllm-retention0-nodeps # Conflicts: # perf-changelog.yaml
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Additional findings (outside current diff — PR may have been updated during review):
-
🟡
perf-changelog.yaml:5139— The changelog bullet for kimik3-fp4-b200-dynamo-vllm-agentic (perf-changelog.yaml:5139) still says "conc 1/8/16/32", but the config it documents (configs/nvidia-master.yaml, same PR) actually sweeps conc-list: [1, 2, 4, 8, 16, 32]. Variant G added concurrency levels 2 and 4 to the config but the changelog prose was never updated to match, leaving a stale description of what was actually benchmarked.Extended reasoning...
The bug: The newly-added changelog entry for
kimik3-fp4-b200-dynamo-vllm-agenticinperf-changelog.yaml(line 5139, under the bullet describingmax-num-batched-tokens 8192/ prefix-caching / max-model-len behavior) ends with the phraseconc 1/8/16/32. This is meant to summarize the concurrency sweep performed for this config. However, the actual shipped config for this exact config-key —configs/nvidia-master.yaml'skimik3-fp4-b200-dynamo-vllm-agentic.scenarios.agentic-coding.search-space[0].conc-list— is[1, 2, 4, 8, 16, 32], added in this same PR family.Root cause / how it got stale: This changelog entry has accreted bullets across several "agentic experiment variant" probes for the same config-key (Variant D → Variant G → Variant K, per the bullet history visible in the diff). Variant G (commit
f14afdc, per the PR description: "conc 1/2/4/8/16/32") added concurrency levels 2 and 4 tonvidia-master.yaml'sconc-list, and the PR description for this very probe (Variant K) explicitly states the sweep uses "conc 1/2/4/8/16/32". But the specific changelog bullet that recites the sweep parameters ("... max-num-batched-tokens 8192 ...; conc 1/8/16/32") was carried over verbatim from the earlier Variant D text and never updated when Variant G's config change landed.Why nothing catches this: The changelog is free-text YAML documentation with no schema or CI check tying its prose back to the actual
conc-listvalues inconfigs/nvidia-master.yaml. Nothing enforces that the two stay in sync, so a partial edit (updating the config but not the accompanying changelog bullet) silently ships.Step-by-step proof:
- Open
configs/nvidia-master.yamlin this PR's diff — the newkimik3-fp4-b200-dynamo-vllm-agenticentry hassearch-space[0].conc-list: [1, 2, 4, 8, 16, 32]. - Open
perf-changelog.yamlin this PR's diff — the bullet ending "...max-num-batched-tokens 8192 so a single long prefill cannot OOM a pipeline stage; conc 1/8/16/32" (line 5139) omits2and4. - Cross-check against the PR's own title/description, which states the sweep is "conc 1/2/4/8/16/32" — confirming the config value is the intended/correct one and the changelog text is what's stale.
- A reader relying solely on the changelog (without cross-referencing the YAML config) would incorrectly conclude that concurrency levels 2 and 4 were never benchmarked for this config.
Impact: Purely a documentation/prose inaccuracy — the changelog is descriptive text and has no effect on what the sweep actually runs (the real
conc-listinnvidia-master.yamldrives execution). It does, however, misinform anyone reading the changelog about what was actually swept.Fix: Update the bullet at perf-changelog.yaml:5139 to read "conc 1/2/4/8/16/32" to match the shipped
conc-listand the PR's own stated sweep range. - Open
| health_check: | ||
| interval_seconds: 10 | ||
| max_attempts: 1440 | ||
|
|
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🟡 The recipe sets health_check.max_attempts: 1440 to give the ~1.4TB MXFP4 checkpoint load extra headroom, but the pre-existing sed at runners/launch_b200-dgxc.sh:296 unconditionally rewrites any max_attempts: N line to 720, silently halving the recipe's intentional margin back to 7200s. This is a pre-existing launcher behavior (not introduced by this PR) that applies to every recipe, and since this config is otherwise identical to the fully-green Variant G (#2374) which ran under the same 720 override, the 1440 value appears to be dead/misleading rather than functionally necessary — worth reconciling but not blocking.
Extended reasoning...
The bug: benchmarks/multi_node/srt-slurm-recipes/vllm/kimi-k3/agentic/agg-b200-tp8pp2-agentic.yaml sets:
health_check:
interval_seconds: 10
max_attempts: 1440at 2-space indentation, intended to give the ~1.4TB MXFP4 Kimi-K3 checkpoint load (off shared Lustre) double the usual health-check window (14400s vs the launcher's usual 7200s).
The code path: runners/launch_b200-dgxc.sh (line ~296, inside the IS_MULTINODE branch that this recipe hits since multinode: true) runs, right before srtctl apply:
sed -i 's/^ max_attempts: [0-9]*/ max_attempts: 720/' "${CONFIG_FILE%%:*}"The regex anchors on exactly two leading spaces before max_attempts:, which is precisely how the recipe indents it under health_check:. This is an unconditional overwrite, not a floor/max clamp — the accompanying comment ('Bump recipe health-check timeout from 360x10s=3600s to 720x10s=7200s ... so large-model loads finish in time') describes it as always raising from a smaller default, and doesn't anticipate a recipe deliberately setting a larger value. So the sed always forces the file to 720 regardless of what was there, silently overwriting the recipe's 1440 down to 720 before srtctl apply ever reads the config.
Why nothing in the codebase prevents this: there's no validation or diffing between the recipe's declared value and what the launcher writes, and the sed runs on every CONFIG_FILE unconditionally for every recipe launched through this script — this recipe has no special-casing to opt out.
Step-by-step proof:
- Recipe file on disk contains
max_attempts: 1440(2-space indent, matches PR diff lines 32-35). - Launcher does
sed -i 's/^ max_attempts: [0-9]*/ max_attempts: 720/' "${CONFIG_FILE%%:*}"on that same file. - The line
max_attempts: 1440matches^ max_attempts: [0-9]*(2 leading spaces + literal text + digits), so sed rewrites it in place tomax_attempts: 720. srtctl apply -f "$CONFIG_FILE"is invoked immediately after, reading the now-mutated 720 value.- Result: the effective health-check window for this job is 720 * 10s = 7200s, not the 1440 * 10s = 14400s the recipe author intended.
Impact: if the 1.4TB MXFP4 weight load off shared Lustre ever exceeds 7200s, the health check would exhaust and kill the job before it ever reaches the decode step the probe is meant to test. However, the impact here appears to be nil in practice: (1) this sed is pre-existing launcher behavior, unmodified by this PR, and applies identically to every recipe that goes through this launcher; (2) per the PR description, this config is otherwise identical to the already-merged, fully-green Variant G (#2374), which ran successfully under the exact same 1440-in-recipe/720-effective override — proving the model load completes comfortably within 7200s and the extra 1440 margin was never actually exercised. So the recipe's 1440 is effectively a dead/misleading value the launcher always clobbers, rather than a value that changes observed behavior.
Fix: either make the launcher's sed only raise (not lower) the value, e.g. compare against the existing number and skip the rewrite if it's already >= 720, or drop the recipe's max_attempts override entirely (since it currently has no effect) and rely on the launcher's fixed 720, with a comment noting that. Given this is an explicitly not-to-merge probe PR whose entire purpose is a one-off empirical check, this is not blocking, but the author should reconcile the recipe's declared value with the launcher's clobbering behavior before this pattern is copied into a real (mergeable) recipe.
| VLLM_EXECUTE_MODEL_TIMEOUT_SECONDS: "1800" | ||
| # Prefix-cache retention (variant G): 0, on the otherwise-unchanged | ||
| # GPU-resident variant D config. Any positive value must be a multiple of | ||
| # Kimi-K3's KDA-hybrid scheduler_block_size (3145728; the GB recipes' | ||
| # 32768 is hard-rejected at engine init — verified on this PR family), so | ||
| # 0 is the only value below one 3.1M-token scheduler block. | ||
| VLLM_PREFIX_CACHE_RETENTION_INTERVAL: "0" | ||
| # No VLLM_PREFIX_CACHE_RETENTION_INTERVAL: the GB200/GB300 AgentX value | ||
| # (32768) hard-fails engine init on Kimi-K3 — the KDA hybrid gives it a | ||
| # scheduler_block_size of 3145728 and the interval must be a multiple of | ||
| # it ("VLLM_PREFIX_CACHE_RETENTION_INTERVAL (32768) must be non-negative | ||
| # and a multiple of scheduler_block_size (3145728)"). Default retention | ||
| # served fine in earlier runs. |
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🟡 The comment block right after VLLM_PREFIX_CACHE_RETENTION_INTERVAL: "0" (lines 72-77) still opens with 'No VLLM_PREFIX_CACHE_RETENTION_INTERVAL: ...', asserting the key is absent — directly contradicting the line right above it that sets it. This is leftover from before Variant G re-added the key set to 0; it's purely a stale comment with no runtime effect, but worth deleting so it doesn't mislead future readers.
Extended reasoning...
In benchmarks/multi_node/srt-slurm-recipes/vllm/kimi-k3/agentic/agg-b200-tp8pp2-agentic.yaml, the aggregated_environment block contains two comment blocks about the same environment variable that now contradict each other. Lines 66-70 correctly explain the current behavior: VLLM_PREFIX_CACHE_RETENTION_INTERVAL: "0" is set (Variant G), and the comment explains why 0 was chosen (any positive value must be a multiple of the KDA-hybrid scheduler_block_size of 3145728, so 0 is the only value below one full scheduler block). Line 71 sets the key to "0".
Immediately after that, lines 72-77 open with "No VLLM_PREFIX_CACHE_RETENTION_INTERVAL: the GB200/GB300 AgentX value (32768) hard-fails engine init..." — i.e., a comment asserting the key is absent from the config and that default retention is used instead. That is flatly false for this file: the key is set, right above, to "0".
How this happened: per the PR history (perf-changelog.yaml), this recipe evolved through several variants. In an earlier revision (Variant D era), VLLM_PREFIX_CACHE_RETENTION_INTERVAL was removed entirely, and the "No VLLM_PREFIX_CACHE_RETENTION_INTERVAL: ..." comment was written at that time to explain the omission. Variant G later re-added the key set to "0" along with its own new comment (lines 66-70), but the old "No ..." comment block was never deleted — it's a leftover duplicate that now describes a state that no longer exists in the file.
Step-by-step proof:
- Read line 71:
VLLM_PREFIX_CACHE_RETENTION_INTERVAL: "0"— the key IS present, with value0. - Read the very next comment, lines 72-73:
# No VLLM_PREFIX_CACHE_RETENTION_INTERVAL: the GB200/GB300 AgentX value (32768) hard-fails engine init...— this states the key is NOT set. - These two statements about the same key, three lines apart, cannot both be true. The comment is stale.
- Confirmed against perf-changelog.yaml: the "Variant G" changelog entry explicitly says it "adds
VLLM_PREFIX_CACHE_RETENTION_INTERVAL=0" to the prior Variant D config, which is the config that originally didn't set the key (matching the stale comment's framing).
Impact: none on runtime behavior — YAML comments are not parsed, so the engine only sees VLLM_PREFIX_CACHE_RETENTION_INTERVAL=0 regardless of what the comments say. The only cost is to future readers/maintainers of this recipe, who could be confused about whether the key is set or not, or duplicate/re-derive the rationale that's already given correctly in lines 66-70.
Fix: delete the stale block (lines 72-77) since the correct, up-to-date rationale is already captured in lines 66-70. No functional change needed, just documentation cleanup.
This is an explicitly non-merge probe PR (Variant K, meant only to produce an empirical answer about whether an image patch is still needed), so there's no urgency to block on this — flagging as a nit for whenever the recipe is next touched.
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see unofficial run visualizer at https://inferencex.semianalysis.com/inference?unofficialRun=30385435921 |
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/stage-results 30385435921 |
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@functionstackx staged run 30385435921: https://inferencemax-app-git-staging-semianalysisai.vercel.app/inference?i_dates=2026-07-28~r30385435921 This shared staging slot remains available until the next |
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/reuse-sweep-run 30385435921 |
The srt-slurm PR #278 multi-node extension now lives as commits on functionstackx/srt-slurm-nv branch klaud/direct-vllm-multinode (head df5baa93), so the launcher clones that branch directly instead of applying srt-slurm-pr278-direct-vllm-multinode.patch onto the upstream kylliang/direct-aggregate-vllm branch. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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/reuse-sweep-run |
# Conflicts: # perf-changelog.yaml
Summary
Agentic experiment (Variant K) — a probe: Variant G (#2374) without the in-container patch script.
Removes
benchmarks/multi_node/srt-slurm-recipes/configs/kimi-k3-container-deps.shentirely (the recipe'ssetup_scriptreference, the script file, and the launcher copy step). Everything else is identical to the fully-green Variant G (direct multinodevllm serve, retention 0, conc 1/2/4/8/16/32).srt-slurm clone source: the launcher now clones functionstackx/srt-slurm-nv
klaud/direct-vllm-multinode, which carries srt-slurm PR NVIDIA/srt-slurm#278 (frontend.type: vllm) plus the multi-node extension as commits — replacing the previous clone ofkylliang/direct-aggregate-vllm+git apply patches/srt-slurm-pr278-direct-vllm-multinode.patch(patch file deleted).Purpose: verify empirically whether the
mamba_hybridindex_fill_dtype patch is still required by the currentvllm/vllm-openai:kimi-k3image. When the patch was introduced, the unpatched image crashed on the first decode step withIndexError: index_fill_(): Expected dtype int64 for index(KDA hybrid-state postprocess). If the image has since been fixed, this run goes green and the patch can be retired; if not, the failure will be documented in a comment below with the error logs.Not intended to merge as-is — this PR exists to produce a definitive answer; the outcome will be commented here.
中文说明
智能体实验变体 K——探针:去除容器内补丁脚本的变体 G(#2374)。
完整移除
kimi-k3-container-deps.sh(配方的setup_script引用、脚本文件与启动器复制步骤),其余与全绿的变体 G 完全一致(直接多节点 vllm serve、留存 0、并发 1/2/4/8/16/32)。srt-slurm 克隆来源:启动器现直接克隆 functionstackx/srt-slurm-nv
klaud/direct-vllm-multinode分支(已包含 srt-slurm PR NVIDIA/srt-slurm#278 及多节点扩展提交),取代此前"克隆kylliang/direct-aggregate-vllm后git apply补丁"的方式(补丁文件已删除)。目的:实证验证当前
vllm/vllm-openai:kimi-k3镜像是否仍需mamba_hybridindex_fill_类型补丁。引入该补丁时,未打补丁的镜像会在首个解码步崩溃(IndexError: index_fill_(): Expected dtype int64 for index)。若镜像已修复,本次运行将通过、补丁可退役;若仍需要,失败详情与错误日志将评论在下方。本 PR 不以合并为目的——仅为得出确定性结论,结果将在评论中给出。
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