Single-node DSR1 FP8 sglang smoke on CoreWeave B300; prune matrix to dsr1-b300-cw + kimi multinode#2086
Single-node DSR1 FP8 sglang smoke on CoreWeave B300; prune matrix to dsr1-b300-cw + kimi multinode#2086JordanNanos wants to merge 1 commit into
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Thanks for the contribution! Please reach out to respective companies' CODEOWNER to fill in the latest PR_REVIEW_CHECKLIST.md before pinging core maintainer on Slack for review. In order for the signoff PR check bot to trigger, you must follow the PR_REVIEW_CHECKLIST.md template correctly, including the phrase For PR verification, add the PR authors are responsible for ensuring that after merging, all GitHub Action jobs fully pass. A lot of the time, failures are just flakes and simply re-running the failed jobs will fix it. See GitHub's docs on re-running failed jobs 感谢你的贡献!请联系相应公司的 CODEOWNER 填写最新的 PR_REVIEW_CHECKLIST.md,然后再在 Slack 上联系核心维护者进行审阅。为了触发 signoff PR 检查机器人,你必须正确遵循 PR_REVIEW_CHECKLIST.md 模板,包括保留英文语句 如需进行 PR 验证,请为此 PR 添加 PR 作者有责任确保合并后所有 GitHub Action 任务完全通过。 很多时候失败只是偶发抖动(flake),重新运行失败的任务即可解决。参见 GitHub 关于重新运行失败任务的文档 |
… to dsr1-b300-cw + kimi multinode Wire the CoreWeave B300 cluster (runner cluster:b300-cw) into the single-node benchmark pipeline and reduce the matrix to a focused test surface: - runners/launch_b300-cw.sh: single-node launcher for the CoreWeave B300 fleet (cloned from launch_b200-cw.sh; partition b300, gpu:b300 gres, node-local /tmp squash import under flock). - configs/runners.yaml: add hardware: cluster:b300-cw (8 GPUs/node). - configs/nvidia-master.yaml: add dsr1-fp8-b300-cw-sglang (DeepSeek-R1-0528 FP8 sglang, cluster:b300-cw), cloned from dsr1-fp8-b300-sglang. - perf-changelog.yaml: append the dsr1-fp8-b300-cw-sglang entry (triggers the sweep). The changelog is append-only/immutable, so prior entries are left intact. - Remove every other single-node benchmark and every non-kimi multinode benchmark (configs + orphaned scripts/recipes) across both master configs. Survivors: dsr1-fp8-b300-cw-sglang (single-node) and all kimik2.5 multinode configs (nvidia dynamo-trt/vllm gb200/gb300; amd mi355x vllm-disagg). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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see unofficial run visualizer at https://inferencex.semianalysis.com/inference?unofficialRun=28746749170 |
What
Wires the CoreWeave B300 cluster (runner
cluster:b300-cw) into the single-node benchmark pipeline and reduces the benchmark matrix to a focused test surface.Added
runners/launch_b300-cw.sh— single-node launcher for the CoreWeave B300 fleet. Cloned fromlaunch_b200-cw.sh(the proven CoreWeave template): partitionb300,gpu:b300gres, node-local/tmpsquash import underflock(avoids root-squash NFS enroot failures).configs/runners.yaml—hardware: cluster:b300-cw(8 GPUs/node).configs/nvidia-master.yaml—dsr1-fp8-b300-cw-sglang(DeepSeek-R1-0528 FP8, sglang,runner: cluster:b300-cw), cloned fromdsr1-fp8-b300-sglangwith the runner label repinned to the CoreWeave fleet.perf-changelog.yaml— appended thedsr1-fp8-b300-cw-sglangentry to trigger the sweep.Removed
Every other single-node benchmark and every non-kimi multinode benchmark — configs + orphaned scripts/recipes — across both master configs.
Survivors:
dsr1-fp8-b300-cw-sglangkimik2.5configs — nvidiadynamo-trt/dynamo-vllm(gb200/gb300) + amdmi355x-vllm-disaggNotes
perf-changelog.yamlis append-only and existing entries are immutable (enforced byvalidate_perf_changelog.py/process_changelog.py), so prior entries are left intact rather than pruned — deleting them would fail thecheck-changeloggate. Only-added-entries are validated against master, so the removed configs' historical entries are harmless.generate_sweep_configs.py full-sweepsucceeds on both pruned masters and on the new config;validate_perf_changelog.pyaccepts the diff.Test
Apply
sweep-enabledto run the single-node DSR1 FP8 sglang smoke oncluster:b300-cw(trimmed to the lowest concurrency per parallelism config).🤖 Generated with Claude Code