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[ATOMesh][CI][benchmark] add GLM-5.2 CPP4+DCP4 ATOMesh coverage - #2134

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[ATOMesh][CI][benchmark] add GLM-5.2 CPP4+DCP4 ATOMesh coverage#2134
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@MengqingCao

@MengqingCao MengqingCao commented Sep 3, 2026

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Motivation

rely on #2121

Add ATOMesh CI coverage for GLM-5.2 MXFP4 on a single-node 1P1D CPP4+DCP4 topology (prefill PP4×TP1 + decode TP4+DCP4, with LMCache offload), and fix the supporting launch/result-processing bugs that blocked reliable runs and dashboard metrics.

Main Changes

  • three agentic 1M-token cases at concurrency 32/40/48, with prefill on GPUs 0–3 (--pipeline-parallel-size 4, LMCache + Mooncake KV producer) and decode on GPUs 4–7 (--decode-context-parallel-size 4, Mooncake KV consumer).
  • expose the three new cell IDs in workflow_dispatch and add extra single-node node orderings so scheduling can pick any eligible MI355X host.
  • Prefill/decode env isolation (pd_server_atom.sh, pd_matrix.py): unset role-specific env vars when switching roles so prefill-only settings (e.g. VLLM_PP_LAYER_PARTITION) do not leak into decode; also preserve ${HANDSHAKE_PORT} until launch-time substitution.
  • Result processing fixes (process_result.py): parse asymmetric TP (TP1-TP4), CPP/PP size, and PP from server args for correct GPU accounting; normalize Total/Input/Output tok/s/GPU to all divide by total_gpu so per-GPU columns are comparable on mixed prefill/decode topologies.

Submission Checklist

Wire single-node PD CPP4/DCP4 jobs, isolate prefill/decode env so PP partitions do not leak across roles, and divide per-GPU throughput by total cluster GPUs.

Co-authored-by: Cursor <cursoragent@cursor.com>
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github-actions Bot commented Sep 3, 2026

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🏷️ CI Guide

Runs automatically on every eligible PR before approval:

  • ✅ Pre Checkin: Black, Ruff, catalog schema validation, non-GPU unit tests

Heavy model tests:

  • ✅ Run after the PR is approved and Pre Checkin passes
  • ✅ Run immediately when an approval review is submitted
  • ✅ Can be requested before approval with labels
Label Tests
ci:full Run all heavy PR model tests: native ATOM, vLLM, and SGLang
ci:atom Run native ATOM model accuracy tests
ci:vllm Run ATOM vLLM OOT model accuracy tests
ci:sglang Run ATOM SGLang model accuracy tests

Heavy jobs are skipped when the PR is not approved and no matching ci:* label is present.
Add labels via the sidebar or gh pr edit 2134 --add-label <label>

@zufayu
zufayu requested a review from gyohuangxin September 4, 2026 23:44
Give glm-52-mxfp4-1p1d-tp4-agentic-1m c1/c2/c4/c8 an MTP draft of 4
tokens at a forced 0.5825 acceptance rate, so the small-concurrency
agentic points are measured on the same speculative path the
cpp4-dcp4 cases already use.

The DPA lmcache cases inherit this group's anchor without overriding
`server`, so the flags live in a named copy of the shared common_args
rather than in the anchor itself; the DPA group keeps running without
speculation.

Forced acceptance replaces every generated token's text with a
placeholder, which leaves SWE-bench Lite unscoreable, so c1 drops its
accuracy gate and reverts to the default runner time limit.

Drop the tp4 c48 case.
The prefill role already offloads to CPU DRAM, but the L3 tier that PR #1851
wired up was never enabled in the matrix, so a working set larger than the
256GiB hot cache simply fell out of the cache.

LMCACHE_LOCAL_DISK and LMCACHE_MAX_LOCAL_DISK_SIZE are required together, and
the size is per rank because scale_cpu_size_for_pp splits only the CPU budget
across PP stages: 4 x 500GiB on a pp4 prefill.

The tier lives on a host bind mount, so it outlives `docker run --rm` and would
otherwise serve one concurrency's KV to the next while holding its disk. The
launcher now empties the directory before the first prefill worker starts and
removes it on exit.
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2 participants