Add harness early stop ablation

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2026-05-02 08:08:14 +08:00
parent 6d3459c82d
commit 1a3d628268
9 changed files with 837 additions and 29 deletions

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@@ -26,11 +26,11 @@ The harness turns each LLM proposal from open-ended config search into a bottlen
- `gpu-memory-utilization`: memory headroom after topology and batching are stable.
- Each family has `use_when`, `procedure`, `guards`, and `active_now` fields.
4. Proposal discipline
4. Proposal discipline and early stop
- The prompt requires the LLM to choose at most one primary knob family unless history proves a coupled change is needed.
- It must use adjacent legal topology choices and stay inside topology constraints.
- It receives tested config signatures, so it should not repeat already-tried configs.
- It can return `should_stop=true` when no adjacent harness-guided probe is justified.
- A deterministic harness stop can now emit `should_stop=true` before calling the LLM when completed validation evidence says another trial is not justified.
5. Baseline-first loop
- LLM-driven `study tune` now evaluates the initial engine config first unless `--skip-baseline` is passed.
@@ -44,10 +44,10 @@ The speedup comes from reducing wasted proposal families, not from changing the
- For long-prompt, low-cache-reuse windows, the harness activates the TP harness before speculative runtime knobs.
- Example: qwen27b 0-8k chat reached `TP=2, DP=1` at iter 2 under harness replay, while the original run spent iter 2 on `DP=2` and iter 3 on `DP=4`.
2. Guarded stop after a strong incumbent
2. Guarded stop after validation, not immediately after a strong incumbent
- If the newest trial is the incumbent and improves per-GPU throughput by at least `1.8x` over baseline, the harness requires direct evidence before trying runtime-only tweaks.
- Without that guard, the LLM still proposed weak MBT trials after finding the qwen27b best config.
- With the guard, it emits `should_stop=true`.
- It does not stop at the first large gain. It requires post-incumbent validation trials across nearby topology/runtime families, and stops only if those trials fail to produce a feasible per-GPU improvement.
- With the guard, `study tune` can write a `harness-stop-XXXX` proposal and exit without spending another GPU trial.
3. All-infeasible plateau detection
- When recent all-infeasible trials at the same sampling threshold stop improving pass rate and p95 TTFT, the harness blocks repeating the same primary knob family.
@@ -78,6 +78,6 @@ Result:
## Current Risks
- The harness is prompt-guided, not a hard verifier for every rule. If future LLM outputs ignore a fired guard, proposal validation should reject the blocked family explicitly.
- Strong-incumbent stopping is intentionally biased toward fewer GPU trials once a large gain is already reached. Workloads with very narrow runtime sweet spots may still need a "continue local refinement" exception when the user wants absolute best throughput rather than fastest convergence to a good config.
- The harness is still prompt-guided for choosing the next non-stop proposal. The deterministic stop path is hard-coded in `study tune`, but proposal-family blocking is not yet enforced by a separate validator.
- Strong-incumbent stopping is intentionally biased toward fewer GPU trials after validation evidence accumulates. Workloads with very narrow runtime sweet spots may still need a "continue local refinement" exception when the user wants absolute best throughput rather than fastest convergence to a good config.
- Full fresh reruns on large models are expensive. Strict replay is useful for measuring proposal-path improvements when the proposed configs already exist in prior measured runs, but publication-quality claims still need fresh no-relaunch runs when time allows.

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@@ -0,0 +1,93 @@
# Qwen3-30B-A3B Community vLLM Harness Ablation, 2026-05-02
## Goal
Run a fresh dash0 experiment on the community vLLM latest release with the local community model:
`/home/admin/cpfs/wjh/models/Qwen/Qwen3-30B-A3B`
The comparison is:
| Variant | Spec | Harness |
| --- | --- | --- |
| no-harness | `configs/examples/dash0_qwen30b_a3b_community_vllm020_noharness.json` | disabled via `llm.use_harness=false` |
| harness | `configs/examples/dash0_qwen30b_a3b_community_vllm020_harness.json` | enabled, including deterministic stop proposal |
Both specs start from the same base vLLM configuration. The base contains only serving access fields: `host`, `port`, and `served-model-name`. It does not set performance flags such as TP, DP, EP, max model length, prefix cache, chunked prefill, max-num-seqs, max-num-batched-tokens, or gpu-memory-utilization. The first trial therefore measures community vLLM defaults for this model.
## vLLM Install
PyPI reports `vllm==0.20.0` as the current community release checked on 2026-05-02. The dash0 installation target is:
`/home/admin/cpfs/wjh/venvs/vllm-0.20.0`
Install log:
`/home/admin/cpfs/wjh/aituner/aituner/logs/install_vllm_0.20.0_20260502.log`
## Workload
The experiment reuses the 0-8k chat window that has already been used for qwen27b harness work:
| Field | Value |
| --- | --- |
| window | `chat_w20260311_1000` |
| source rows | 32606 |
| input filter | 0 to 8192 tokens |
| max requests per probe | 2048 |
| target pass rate | 0.95 |
| TTFT SLO | 2s up to 4k, 4s up to 32k, 6s above |
| TPOT SLO | 50ms |
| search high | 0.125 sampling_u |
| max probes per trial | 6 |
The `max_requests_per_probe=2048` cap keeps the fresh community-vLLM ablation practical while preserving a real trace-shaped replay, SLO scoring, and binary-search threshold probe.
## Harness Update Under Test
This run tests a stricter early-stop harness:
- The harness still injects L-C-A workload features, recent trial diagnostics, active bottleneck, legal topology candidates, tested signatures, and knob-family rules.
- A strong incumbent no longer means immediate stop. It means "validate nearby alternatives".
- Deterministic stop is allowed only after completed validation evidence says continuing is unlikely to be useful:
- the incumbent beats baseline by a generic large-gain ratio,
- at least two post-incumbent validation trials have run,
- those validation trials did not produce a feasible per-GPU improvement,
- the validation covered topology and runtime families, or accumulated at least three post-incumbent validation attempts.
- If the stop guard fires, `study tune` writes `harness-stop-XXXX` and exits without spending another GPU trial or asking the LLM for another proposal.
This is a generic harness rule, not a testcase-specific threshold. It does not depend on qwen27b, qwen235b, qwen30b, a fixed TP/DP value, or a hardcoded SLO number.
## Unit Tests
Local test command:
```bash
PYTHONPATH=src python3 -m unittest tests.test_core_flow -q
```
Result: passed, 74 tests.
The added coverage checks:
| Test | Purpose |
| --- | --- |
| `test_harness_does_not_stop_immediately_after_strong_incumbent` | strong incumbent requires validation first |
| `test_harness_stop_after_post_incumbent_validation_is_exhausted` | deterministic stop after validation exhaustion |
| `test_cli_tune_uses_harness_stop_before_llm` | `study tune` can stop without calling the LLM or launching another GPU trial |
| `test_prompt_can_disable_harness_for_ablation` | no-harness prompt removes structured harness context |
## Experiment Tracking
Pending dash0 runs:
| Variant | tmux session | Log | Study root |
| --- | --- | --- | --- |
| no-harness | `qwen30b_vllm020_noharness_20260502` | `logs/qwen30b_vllm020_noharness_20260502.log` | `.aituner-community-vllm020/studies/dash0-qwen30b-a3b-community-vllm020-chat-0-8k-noharness` |
| harness | `qwen30b_vllm020_harness_20260502` | `logs/qwen30b_vllm020_harness_20260502.log` | `.aituner-community-vllm020/studies/dash0-qwen30b-a3b-community-vllm020-chat-0-8k-harness` |
The harness run should be judged by best-so-far `request_rate_per_gpu` per tuning iteration, plus whether it stops only after validation evidence. The no-harness run should use the same trial budget so the ablation exposes whether the early-stop harness saves iterations without hiding a later better point.
## Results
Pending. This section will be filled after the dash0 experiments finish.