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[NV] Add GB300 AgentX Qwen3.5 recipes #2121
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484c8a5
feat(qwen3.5-gb300-agentx): add Qwen3.5-NVFP4 GB300 SGLang AgentX ben…
xinli-sw b078ddf
Merge remote-tracking branch 'origin/main' into nv-qwen35-agentx-gb300
csahithi f0f925f
qwen3.5 agentic: image 20260715-50d1edaa; prefill NEXTN MTP; fix agg …
csahithi 028f2ff
qwen3.5 agentic: bump image to 20260716-b0b2dfbd
csahithi c808170
Merge remote-tracking branch 'origin/main' into nv-qwen35-agentx-gb300
csahithi f1e6bca
runners: add gb300-nv hardware metadata (available-cpu-dram-mib, gpus…
csahithi a46700e
qwen3.5 agentic: bump image to 20260724-433429b1
csahithi 3dc16dc
Merge remote-tracking branch 'origin/main' into nv-qwen35-agentx-gb300
csahithi 32289c3
run-sweep: drop unneeded agentic collect-results gate
csahithi 75473fe
qwen3.5 agentic: pin Dynamo to ai-dynamo/dynamo#12081 (read-only Serv…
csahithi a258569
Merge remote-tracking branch 'origin/main' into nv-qwen35-agentx-gb300
csahithi 5c871a2
qwen3.5 agentic: migrate disagg recipes to X-Dynamo-Session-ID sessio…
csahithi 90d2947
Merge remote-tracking branch 'origin/main' into nv-qwen35-agentx-gb300
csahithi b547248
benchmark_lib: honor AIPERF_HTTP_X_DYNAMO_SESSION_ID_FROM_CORRELATION_ID
csahithi 3f5d74e
qwen3.5 c128: raise SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK 25…
csahithi 220701e
Merge remote-tracking branch 'origin/main' into nv-qwen35-agentx-gb300
csahithi 64729c6
Merge remote-tracking branch 'origin/main' into pr-2121-reuse-74060
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114 changes: 114 additions & 0 deletions
114
...urm-recipes/sglang/qwen3.5/gb300-fp4/agentic/agg-gb300-tp4-c1-mtp-hicache-jid2191933.yaml
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,114 @@ | ||
| name: "agg-gb300-tp4-c1-mtp-hicache-jid2191933" | ||
|
|
||
| # Agentic-coding SGLang aggregated recipe for Qwen3.5-397B-A17B-NVFP4 on GB300 | ||
| # (single aggregated worker, TP4, NEXTN MTP + hierarchical cache). | ||
| # | ||
| # Ported from the manually-run srtctl base:/zip_override_conc: starter to the | ||
| # flat single-variant agentic schema. Pure sglang (no dynamo): frontend.type | ||
| # sglang serves directly. Concurrency comes from the GHA matrix (exported as | ||
| # CONC into agentic_srt.sh), not the recipe. Serving tuning preserved verbatim | ||
| # from the source run; only CI scaffolding is added. | ||
|
|
||
| model: | ||
| path: "qwen3.5-fp4" | ||
| container: "dynamo-sglang" | ||
| precision: "fp4" | ||
|
|
||
| slurm: | ||
| time_limit: "8:00:00" | ||
|
|
||
| health_check: | ||
| max_attempts: 1440 | ||
| interval_seconds: 10 | ||
|
|
||
| resources: | ||
| gpu_type: "gb300" | ||
| gpus_per_node: 4 | ||
| agg_nodes: 1 | ||
| agg_workers: 1 | ||
| gpus_per_agg: 4 | ||
|
|
||
| infra: | ||
| nats_max_payload_mb: 8 | ||
|
|
||
| frontend: | ||
| type: sglang | ||
|
|
||
| backend: | ||
| type: sglang | ||
| aggregated_environment: | ||
| SGLANG_SIMULATE_ACC_LEN: '3.39' | ||
| SGLANG_SIMULATE_ACC_METHOD: match-expected | ||
| SGLANG_SIMULATE_ACC_TOKEN_MODE: "real-draft-token" | ||
| TORCH_CUDA_ARCH_LIST: '10.0' | ||
| PYTHONNOUSERSITE: '1' | ||
| NCCL_NVLS_ENABLE: '1' | ||
| SGL_ENABLE_JIT_DEEPGEMM: 'false' | ||
| SGLANG_ENABLE_FLASHINFER_GEMM: 'true' | ||
| sglang_config: | ||
| aggregated: | ||
| served-model-name: nvidia/Qwen3.5-397B-A17B-NVFP4 | ||
| model-path: /model/ | ||
| trust-remote-code: true | ||
| tensor-parallel-size: 4 | ||
| data-parallel-size: 1 | ||
| expert-parallel-size: 1 | ||
| enable-symm-mem: true | ||
| quantization: modelopt_fp4 | ||
| kv-cache-dtype: fp8_e4m3 | ||
| mamba-ssm-dtype: bfloat16 | ||
| mamba-scheduler-strategy: extra_buffer | ||
| mamba-track-interval: 8192 | ||
| attention-backend: trtllm_mha | ||
| moe-runner-backend: flashinfer_trtllm | ||
| speculative-algorithm: NEXTN | ||
| speculative-num-steps: 3 | ||
| speculative-eagle-topk: 1 | ||
| speculative-num-draft-tokens: 4 | ||
| cuda-graph-max-bs: 256 | ||
| max-running-requests: 1024 | ||
| max-prefill-tokens: 16384 | ||
| chunked-prefill-size: 16384 | ||
| mem-fraction-static: 0.8 | ||
| max-mamba-cache-size: 1024 | ||
| allow-auto-truncate: true | ||
| stream-interval: 50 | ||
| scheduler-recv-interval: 10 | ||
| tokenizer-worker-num: 6 | ||
| page-size: 64 | ||
| enable-hierarchical-cache: true | ||
| hicache-ratio: 1.01 | ||
| hicache-io-backend: kernel | ||
| hicache-mem-layout: page_first_direct | ||
| hicache-write-policy: write_through | ||
|
|
||
| sbatch_directives: | ||
| mem: "0" | ||
| cpus-per-task: "144" | ||
|
|
||
| srun_options: | ||
| mem: "0" | ||
| # gb300-nv: pyxis maps the calling user into the container as a non-root uid; | ||
| # agentic_srt.sh's apt-get install git step needs EUID 0. Remap to uid 0 inside | ||
| # the container. srt-slurm renders empty-string values as flag-only srun args. | ||
| container-remap-root: "" | ||
|
|
||
| benchmark: | ||
| type: custom | ||
| command: bash /infmax-workspace/benchmarks/multi_node/agentic_srt.sh | ||
| env: | ||
| INFMAX_CONTAINER_WORKSPACE: /infmax-workspace | ||
| RESULT_DIR: /logs/agentic | ||
| PORT: "8000" | ||
| # Aggregated: one worker serves both prefill and decode, so GPU accounting is | ||
| # the single-worker form num_gpus = TP (not the disagg prefill+decode sum). | ||
| # Force the single-node post-proc path; TP must match sglang_config tp-size. | ||
| IS_MULTINODE: "false" | ||
| TP: "4" | ||
| # Match the source run's dataset (256k cc-traces-with-subagents variant). | ||
| WEKA_LOADER_OVERRIDE: semianalysis_cc_traces_weka_062126_256k | ||
| # Container-side path of the aiperf mmap dataset cache; host-side mount wired | ||
| # via launch_gb300-nv.sh srtslurm.yaml default_mounts. | ||
| AIPERF_DATASET_MMAP_CACHE_DIR: "/aiperf_mmap_cache" | ||
| # Persistent HF hub cache (also via default_mounts). | ||
| HF_HUB_CACHE: "/hf_hub_cache" | ||
114 changes: 114 additions & 0 deletions
114
...rm-recipes/sglang/qwen3.5/gb300-fp4/agentic/agg-gb300-tp4-c96-mtp-hicache-jid2195211.yaml
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,114 @@ | ||
| name: "agg-gb300-tp4-c96-mtp-hicache-jid2195211" | ||
|
|
||
| # Agentic-coding SGLang aggregated recipe for Qwen3.5-397B-A17B-NVFP4 on GB300 | ||
| # (single aggregated worker, TP4, NEXTN MTP + hierarchical cache). | ||
| # | ||
| # Ported from the manually-run srtctl base:/zip_override_conc: starter to the | ||
| # flat single-variant agentic schema. Pure sglang (no dynamo): frontend.type | ||
| # sglang serves directly. Concurrency comes from the GHA matrix (exported as | ||
| # CONC into agentic_srt.sh), not the recipe. Serving tuning preserved verbatim | ||
| # from the source run; only CI scaffolding is added. | ||
|
|
||
| model: | ||
| path: "qwen3.5-fp4" | ||
| container: "dynamo-sglang" | ||
| precision: "fp4" | ||
|
|
||
| slurm: | ||
| time_limit: "8:00:00" | ||
|
|
||
| health_check: | ||
| max_attempts: 1440 | ||
| interval_seconds: 10 | ||
|
|
||
| resources: | ||
| gpu_type: "gb300" | ||
| gpus_per_node: 4 | ||
| agg_nodes: 1 | ||
| agg_workers: 1 | ||
| gpus_per_agg: 4 | ||
|
|
||
| infra: | ||
| nats_max_payload_mb: 8 | ||
|
|
||
| frontend: | ||
| type: sglang | ||
|
|
||
| backend: | ||
| type: sglang | ||
| aggregated_environment: | ||
| SGLANG_SIMULATE_ACC_LEN: '3.39' | ||
| SGLANG_SIMULATE_ACC_METHOD: match-expected | ||
| SGLANG_SIMULATE_ACC_TOKEN_MODE: "real-draft-token" | ||
| TORCH_CUDA_ARCH_LIST: '10.0' | ||
| PYTHONNOUSERSITE: '1' | ||
| NCCL_NVLS_ENABLE: '1' | ||
| SGL_ENABLE_JIT_DEEPGEMM: 'false' | ||
| SGLANG_ENABLE_FLASHINFER_GEMM: 'true' | ||
| sglang_config: | ||
| aggregated: | ||
| served-model-name: nvidia/Qwen3.5-397B-A17B-NVFP4 | ||
| model-path: /model/ | ||
| trust-remote-code: true | ||
| tensor-parallel-size: 4 | ||
| data-parallel-size: 1 | ||
| expert-parallel-size: 1 | ||
| enable-symm-mem: true | ||
| quantization: modelopt_fp4 | ||
| kv-cache-dtype: fp8_e4m3 | ||
| mamba-ssm-dtype: bfloat16 | ||
| mamba-scheduler-strategy: extra_buffer | ||
| mamba-track-interval: 8192 | ||
| attention-backend: trtllm_mha | ||
| moe-runner-backend: flashinfer_trtllm | ||
| speculative-algorithm: NEXTN | ||
| speculative-num-steps: 3 | ||
| speculative-eagle-topk: 1 | ||
| speculative-num-draft-tokens: 4 | ||
| cuda-graph-max-bs: 256 | ||
| max-running-requests: 1024 | ||
| max-prefill-tokens: 16384 | ||
| chunked-prefill-size: 16384 | ||
| mem-fraction-static: 0.8 | ||
| max-mamba-cache-size: 1024 | ||
| allow-auto-truncate: true | ||
| stream-interval: 50 | ||
| scheduler-recv-interval: 10 | ||
| tokenizer-worker-num: 6 | ||
| page-size: 64 | ||
| enable-hierarchical-cache: true | ||
| hicache-ratio: 1.05 | ||
| hicache-io-backend: kernel | ||
| hicache-mem-layout: page_first_direct | ||
| hicache-write-policy: write_through | ||
|
|
||
| sbatch_directives: | ||
| mem: "0" | ||
| cpus-per-task: "144" | ||
|
|
||
| srun_options: | ||
| mem: "0" | ||
| # gb300-nv: pyxis maps the calling user into the container as a non-root uid; | ||
| # agentic_srt.sh's apt-get install git step needs EUID 0. Remap to uid 0 inside | ||
| # the container. srt-slurm renders empty-string values as flag-only srun args. | ||
| container-remap-root: "" | ||
|
|
||
| benchmark: | ||
| type: custom | ||
| command: bash /infmax-workspace/benchmarks/multi_node/agentic_srt.sh | ||
| env: | ||
| INFMAX_CONTAINER_WORKSPACE: /infmax-workspace | ||
| RESULT_DIR: /logs/agentic | ||
| PORT: "8000" | ||
| # Aggregated: one worker serves both prefill and decode, so GPU accounting is | ||
| # the single-worker form num_gpus = TP (not the disagg prefill+decode sum). | ||
| # Force the single-node post-proc path; TP must match sglang_config tp-size. | ||
| IS_MULTINODE: "false" | ||
| TP: "4" | ||
| # Match the source run's dataset (256k cc-traces-with-subagents variant). | ||
| WEKA_LOADER_OVERRIDE: semianalysis_cc_traces_weka_062126_256k | ||
| # Container-side path of the aiperf mmap dataset cache; host-side mount wired | ||
| # via launch_gb300-nv.sh srtslurm.yaml default_mounts. | ||
| AIPERF_DATASET_MMAP_CACHE_DIR: "/aiperf_mmap_cache" | ||
| # Persistent HF hub cache (also via default_mounts). | ||
| HF_HUB_CACHE: "/hf_hub_cache" |
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started about discussion about AgentX MTP +viz @kedarpotdar-nv