chore: clean up stale B60 measurement data by mandy-li · Pull Request #579 · ai-dynamo/aisimulate

mandy-li · 2026-10-23T23:59:41Z

Why and what changed

Removes the B60 0.20.0-era perf tables. Deleting a version dir isn't inert —
the resolver uses older dirs as a fallback channel. Five of six removed dirs
contribute zero unique rows (bit-exact on projections). comm/oneccl/2021.15.9
kept: it came with the 0.26.0 upgrade and is the only num_gpus=8 source.

gemm/vllm/0.20.0 held 3,822 rows at k>12288 because feature_sizes in the
vllm_xpu sweep is the k axis and was capped at 12288, leaving llama3-8B
tp1 down_proj (k=14336) to extrapolate. Adds k=16384, 32768 and recollects
the 1,932 cases in XPU-graph mode to match the deployed table. Now 21,168 rows.

Review map

Risk level: medium
Start with: collector/cases/base_ops/gemm.yaml, then the 0.28.0 sidecar +
parquet, then the six deletions.
Public or serialized contract changed: yes — sidecar to schema_version: 2
(existing schema, already used by 66 of 544 deployed sidecars). No column change.
Compatibility or rollback concern: revert restores prior behaviour.

Evidence

Tests: 12,103 unit pass; 78 failures pre-existing (identical set on pristine
tree). ruff clean. check_collector_data R1–R7 OK, backend_facts --check OK.

Modeling or data provenance

Measured on B60, freq pinned 2350–2400 MHz, runtime
vllm/vllm-openai-xpu:v0.28.0 — same image as the existing rows. Collected
twice: model-reachable rows (n ≥ 2048) agree to 4.26% max. The 22 rows over
5% are all n < 2048 filler, worst 4.1 µs, unreachable at k ≥ 16384.
collected_at: '2026-10-19' on the first event is derived from the deploying
commit — the old v1 sidecar had no such field.

gemm/vllm/0.28.0/gemm_perf.parquet (modified)
keys: [gemm_dtype, m, n, k] value: latency units: ms/op
rows: 19236 -> 21168 (+1932 added, 0 removed/modified, 0 dup, 0 key overlap)
schema: 10 cols, unchanged. identity cols unchanged (VLLM/0.28.0/B60/vllm_default)
added: k=[16384, 32768], n=32..65536, m=1..8192, bf16+fp8 (966 each), 0.0096..525.4 ms
coverage: out-of-grid k combos across 124 packaged configs 27 -> 3
(3 left = tp1-only 405B/Kimi-K3/V4-Pro, none fit 24GB B60 at tp1)
anomalies (collected twice):
run-to-run: n>=2048 (1260 rows) median 0.21% / p95 1.58% / max 4.26%
n<2048 (672 rows) median 0.60% / p95 3.93% / max 29.67%
-> that 29.67% is 4.1us on a 13us row; all 22 rows >5% are n<2048
spikes 2/1932 (both reproduced in both runs = real dispatch; deployed 5/19236)
monotonicity 0.54% vs 0.85% deployed; 0 sub-SOL rows; 0 of 1534 >=1GF above 10x SOL

deleted (unique_keys_lost = absent from every retained table)
attention 0.20.0 ctx/gen 16188 / 26322 0
moe 0.20.0 1944 0
comm/vllm 0.20.0 / 0.12.0 69 / 69 0
comm/oneccl 2021.17.2 252 3 (never loaded: oneCCL resolution
is primary-only, pinned 2022.0.0)
gemm 0.20.0 22176 1890 (all k in {51200,65536} — deliberate,
unreachable at any feasible tp on B60)

consumer proof — llama3.1-8B tp1 down_proj (n=4096, k=inter_size=14336)
before: max k at n=4096 = 12288 -> bracket [12288, none] -> EXTRAPOLATION
after: max k at n=4096 = 32768 -> bracket [12288, 16384] -> INTERPOLATION
consequence: llama3 tp1 TPOT MAE 1.85% -> 1.30% over 73 bench configs

Signed-off-by: mandy-li <mandy.j.li@intel.com>

copy-pr-bot · 2026-10-23T23:59:44Z

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coderabbitai · 2026-10-24T00:00:03Z

📝 Summary

Risk level: Moderate. The three areas needing the most human attention are removal of B60 0.20.0 backend facts, the expanded GEMM data and metadata, and revised data-reuse counts.

The vLLM XPU GEMM sweep adds k=16384 and k=32768. The expected case count rises from 9,891 to 10,857.
B60 vLLM 0.28.0 GEMM metadata changes to schema version 2 and reports 21,168 rows, including a new 1,932-row collection.
The change removes B60 vLLM 0.20.0 backend facts and metadata, plus metadata for oneCCL 2021.17.2 and vLLM 0.12.0 all-reduce. The PR objectives say oneccl/2021.15.9 is retained because it supplies the only num_gpus=8 rows.
The hybrid-validation test now uses the B60/vLLM 0.28.0 data slot. Its expected validation failure is unchanged.
The reuse manifest updates row and deduplication counts for six entries.

Evidence: The PR objectives report that the removals lose no unique rows, that 1,932 cases were newly collected, and that two collections of model-reachable rows agree within 4.26%. They also report 12,103 unit tests passing, 78 pre-existing failures, clean Ruff, and passing collector-data and backend-facts checks. These results are reported, not independently verified.

Technical quality and merge readiness: The described changes address stale data and extend coverage. Current review findings were not supplied, so severity counts are unavailable. Available evidence does not establish merge readiness.

The vLLM XPU GEMM sweep now includes larger feature sizes. The b60 performance metadata, backend facts, reuse counts, and related test expectations are updated.

Changes: b60 performance data

Layer / File(s)	Summary
Expand GEMM sweep `python/aisimulate/collector/cases/base_ops/gemm.yaml`, `python/aisimulate/tests/unit/collector/test_model_cases.py`	The vLLM XPU sweep adds `16384` and `32768`. The expected case count rises to 10,857, and the first expected case uses `k=32768`.
Update vLLM 0.28.0 GEMM collection `python/aisimulate/src/aisimulate_core/systems/data/b60/gemm/vllm/0.28.0/collection_meta.yaml`, `python/aisimulate/tests/unit/sdk/task_v2/test_task_config.py`	The metadata advances to schema version 2 and records 21,168 rows across two collections. The validation test uses backend version 0.28.0.
Revise legacy b60 data records `python/aisimulate/collector/op_backend_facts.yaml`, `python/aisimulate/src/aisimulate_core/systems/data/b60/.../collection_meta.yaml`, `python/aisimulate/src/aisimulate_core/systems/perf_data_reuse_manifest.yaml`	Older collection metadata and vLLM backend facts are removed. The reuse manifest reports lower raw-row counts for the listed performance entries, with lower deduplication counts for several entries.

Priority: ➖ Normal

Estimated code review effort: 2 (Simple) | ~12 minutes

Merge Risk: 🟡 Moderate · up to 50b31

The new GEMM measurements may improve predictions, but their coverage and use by the prediction path have not been demonstrated as required. Supply that evidence before merging.

Pre-merge checks: 8

Check name	Status	Explanation
Title check		The title 'chore: clean up stale B60 measurement data' names the change area (stale B60 measurement data) and the action (cleanup). The changeset deletes six B60 0.20.0-era perf metadata files and add…
Linked Issues check		Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check		Check skipped because no linked issues were found for this pull request.
Cross-Layer Contract		PASS. The changed contracts have matching consumers and tests. The GEMM YAML `feature_sizes` feeds `get_gemm_case_specs()` through `case_generator.py:1683-1735`; `test_model_cases.py:884-887` updates …
Modeling And Data Evidence		The PR supplies provenance and reproducible performance evidence. The authored description identifies B60, the pinned frequency, the vLLM 0.28.0 image, two collection runs, the 4.26% agreement result,…
Compatibility Boundaries		No compatibility-boundary failure is introduced. The PR changes only collector/data YAML, Parquet data, and tests; it changes no Python or Rust public declaration, binding, package version, Cargo mani…
Review Evidence		The description reports relevant validation and results: 12,103 unit tests passed, 78 failures matched a pristine-tree baseline, ruff was clean, and `check_collector_data` R1–R7 plus `backend_facts --…
Description check		The description is mostly complete and directly explains the cleanup, GEMM data expansion, compatibility impact, provenance, validation results, and measured outcomes. It omits the template's Tracking…

Full details: Title check

Explanation

The title 'chore: clean up stale B60 measurement data' names the change area (stale B60 measurement data) and the action (cleanup). The changeset deletes six B60 0.20.0-era perf metadata files and adds the 16384/32768 GEMM sweep with a 0.28.0 data update. The title only partially covers the change: it omits the GEMM k-axis expansion and recollection, which is a behavioral change. The 'clean up' wording is also close to the vague terms the requirements reject. Status is PASS because the title is related to the main change and is not misleading.

Full details: Cross-Layer Contract

Explanation

PASS. The changed contracts have matching consumers and tests. The GEMM YAML feature_sizes feeds get_gemm_case_specs() through case_generator.py:1683-1735; test_model_cases.py:884-887 updates the XPU count and boundary case. The schema-2 sidecar is valid: tables.gemm_perf.rows is 21,168 and equals the two collection event totals. Python validation supports schema 2 in sdk/perf_database.py:675-803, the collector writer supports it in collector/provenance.py, the checker handles collection events in check_collector_data.py:321-360, and the schema and data-format tests cover it. The Rust resolver consumes the same sidecar mapping and table coverage in source_resolution.rs:303-329; its resolver contract does not depend on the event-only fields. The data-format documentation describes schema 2 at docs/perf-model/collector/data-format.md:82-88. The replacement parquet keeps the existing columns (framework, version, device, op_name, kernel_source, gemm_dtype, m, n, k, latency). Removed B60 0.20-era paths have no remaining backend-facts entries, and B60's query slots remain current=0.28.0 and previous=0.26.0 in systems/query_versions.yaml:34-38. The task validation test was moved to 0.28.0. No stale Rust, Python, CLI, serialization, documentation, or test consumer was found.

Full details: Modeling And Data Evidence

Explanation

The PR supplies provenance and reproducible performance evidence. The authored description identifies B60, the pinned frequency, the vLLM 0.28.0 image, two collection runs, the 4.26% agreement result, and the counted/analyzed outliers. The changed vLLM 0.28.0 sidecar records the image digest, collector references and hashes, case-plan hashes, dates, and the before/new row counts (21,168 total, including 19,236 and 1,932 rows) at python/aisimulate/src/aisimulate_core/systems/data/b60/gemm/vllm/0.28.0/collection_meta.yaml:4-25. The reuse manifest records before/after raw-row and deduplication counts for the affected tables. The GEMM case diff explains the added k values and the coverage gap. The binary Parquet changes therefore have supporting machine-readable summaries, provenance, and anomaly/repeatability evidence rather than binary-only or unexplained refresh validation.

Full details: Compatibility Boundaries

Explanation

No compatibility-boundary failure is introduced. The PR changes only collector/data YAML, Parquet data, and tests; it changes no Python or Rust public declaration, binding, package version, Cargo manifest, dependency, or build configuration. The new collection_meta.yaml is schema v2, which the Python loader supports (perf_database.py:675-803), and its aggregate row count is internally consistent: 19,236 + 1,932 = 21,168. B60 queryable versions remain 0.28.0 and 0.26.0 (query_versions.yaml:34-38), matching the retained data and removed 0.20-era facts. Historical support-matrix rows are intentionally filtered to queryable versions by the unchanged CLI logic (legacy_cli/main.py:73-83, 121-129). The unified-wheel workflow and exact-one-wheel checks are unchanged, and no crate or artifact files are changed in the PR range.

Full details: Review Evidence

Explanation

The description reports relevant validation and results: 12,103 unit tests passed, 78 failures matched a pristine-tree baseline, ruff was clean, and check_collector_data R1–R7 plus backend_facts --check passed. It includes boundary and negative evidence for removed rows, retained num_gpus=8 coverage, k > 12288, n ≥ 2048, and the 5% comparison threshold. It separates baseline/parity checks from repeated B60 measurements and deployed-image provenance; it makes no fake-runner or hosted-CI claim. The reviewed diff changes no workflow files, and the description does not cite an inactive nested workflow as hosted CI.

Full details: Description check

Explanation

The description is mostly complete and directly explains the cleanup, GEMM data expansion, compatibility impact, provenance, validation results, and measured outcomes. It omits the template's Tracking section and does not provide separate Fast CI, Full CI, CodeRabbit, Codex, negative-case, expected-value, or before/after evidence entries.

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Actionable comments posted: 1

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Review comments at
@python/aisimulate/src/aisimulate_core/systems/data/b60/gemm/vllm/0.28.0/collection_meta.yaml:
- Line 12: Expand the metadata around the rows entry with a machine-readable
summary of the GEMM table’s keys, shapes, units, row counts, coverage, and
anomalies. Add one consumer query using n ≥ 2048 and an actual newly collected k
value from gemm_perf.parquet that demonstrates table selection rather than
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python/aisimulate/src/aisimulate_core/systems/data/b60/attention/vllm/0.20.0/context_attention_perf.parquet is excluded by !**/*.parquet and included by python/**
python/aisimulate/src/aisimulate_core/systems/data/b60/attention/vllm/0.20.0/generation_attention_perf.parquet is excluded by !**/*.parquet and included by python/**
python/aisimulate/src/aisimulate_core/systems/data/b60/comm/oneccl/2021.17.2/oneccl_perf.parquet is excluded by !**/*.parquet and included by python/**
python/aisimulate/src/aisimulate_core/systems/data/b60/comm/vllm/0.12.0/custom_allreduce_perf.parquet is excluded by !**/*.parquet and included by python/**
python/aisimulate/src/aisimulate_core/systems/data/b60/comm/vllm/0.20.0/custom_allreduce_perf.parquet is excluded by !**/*.parquet and included by python/**
python/aisimulate/src/aisimulate_core/systems/data/b60/gemm/vllm/0.20.0/gemm_perf.parquet is excluded by !**/*.parquet and included by python/**
python/aisimulate/src/aisimulate_core/systems/data/b60/gemm/vllm/0.28.0/gemm_perf.parquet is excluded by !**/*.parquet and included by python/**
python/aisimulate/src/aisimulate_core/systems/data/b60/moe/vllm/0.20.0/moe_perf.parquet is excluded by !**/*.parquet and included by python/**

📒 Files selected for processing: 12

python/aisimulate/collector/cases/base_ops/gemm.yaml
python/aisimulate/collector/op_backend_facts.yaml
python/aisimulate/src/aisimulate_core/systems/data/b60/attention/vllm/0.20.0/collection_meta.yaml
python/aisimulate/src/aisimulate_core/systems/data/b60/comm/oneccl/2021.17.2/collection_meta.yaml
python/aisimulate/src/aisimulate_core/systems/data/b60/comm/vllm/0.12.0/collection_meta.yaml
python/aisimulate/src/aisimulate_core/systems/data/b60/comm/vllm/0.20.0/collection_meta.yaml
python/aisimulate/src/aisimulate_core/systems/data/b60/gemm/vllm/0.20.0/collection_meta.yaml
python/aisimulate/src/aisimulate_core/systems/data/b60/gemm/vllm/0.28.0/collection_meta.yaml
python/aisimulate/src/aisimulate_core/systems/data/b60/moe/vllm/0.20.0/collection_meta.yaml
python/aisimulate/src/aisimulate_core/systems/perf_data_reuse_manifest.yaml
python/aisimulate/tests/unit/collector/test_model_cases.py
python/aisimulate/tests/unit/sdk/task_v2/test_task_config.py

🔗 Linked repositories identified

CodeRabbit considers these linked repositories for cross-repo context during reviews:

ai-dynamo/dynamo (manual)
ai-dynamo/aiconfigurator (manual)

💤 Files with no reviewable changes: 7

python/aisimulate/src/aisimulate_core/systems/data/b60/gemm/vllm/0.20.0/collection_meta.yaml
python/aisimulate/src/aisimulate_core/systems/data/b60/moe/vllm/0.20.0/collection_meta.yaml
python/aisimulate/src/aisimulate_core/systems/data/b60/attention/vllm/0.20.0/collection_meta.yaml
python/aisimulate/src/aisimulate_core/systems/data/b60/comm/oneccl/2021.17.2/collection_meta.yaml
python/aisimulate/src/aisimulate_core/systems/data/b60/comm/vllm/0.20.0/collection_meta.yaml
python/aisimulate/collector/op_backend_facts.yaml
python/aisimulate/src/aisimulate_core/systems/data/b60/comm/vllm/0.12.0/collection_meta.yaml

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python/aisimulate/.claude/rules/collector/failure_handling.md — configured
python/aisimulate/.claude/rules/collector/layer_permissions.md — configured
python/aisimulate/.claude/rules/collector/case_authoring.md — configured
python/aisimulate/.claude/rules/rust-core/parity.md — configured
python/aisimulate/.claude/rules/perfmodel-api.md — auto-discovered
AGENTS.md — configured
REVIEW.md — configured
python/aisimulate/.claude/rules/repo-guide.md — auto-discovered

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python/aisimulate/tests/unit/collector/test_model_cases.py
python/aisimulate/src/aisimulate_core/systems/data/b60/gemm/vllm/0.28.0/collection_meta.yaml
python/aisimulate/collector/cases/base_ops/gemm.yaml
python/aisimulate/src/aisimulate_core/systems/perf_data_reuse_manifest.yaml
python/aisimulate/tests/unit/sdk/task_v2/test_task_config.py

Applicability reference: AGENTS.md: # AGENTS Before making any change under `python/aisimulate/collector/**` MUST read: `python/aisimulate/.claude/rules/collector/failure_handling.md` Source excerpt: Core doctrine: **obser...

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python/aisimulate/src/aisimulate_core/systems/perf_data_reuse_manifest.yaml

Applicability reference: AGENTS.md: # AGENTS Before changing a performance model, its configuration, or a caller in Rust, Python, CLI, Sweeper, Replay, or Planner, MUST read and follow [`perfmodel-api.md`](python/aisimulat...

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python/aisimulate/collector/cases/base_ops/gemm.yaml
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python/aisimulate/tests/unit/sdk/task_v2/test_task_config.py

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python/aisimulate/collector/cases/base_ops/gemm.yaml
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🔀 Multi-repo context ai-dynamo/aiconfigurator

Linked repositories findings

ai-dynamo/aiconfigurator

The frozen reference still contains all targeted B60 vLLM 0.20.0 tables and legacy schema-1 sidecars: attention, all-reduce, GEMM, and MoE. [::ai-dynamo/aiconfigurator::aic-core/src/aiconfigurator_core/systems/data/b60/gemm/vllm/0.20.0/collection_meta.yaml:4-10]
Its reuse manifest explicitly lists B60 for vLLM attention, custom all-reduce, GEMM, and XPU MoE sources. [::ai-dynamo/aiconfigurator::aic-core/src/aiconfigurator_core/systems/perf_data_reuse_manifest.yaml:127-133] [::ai-dynamo/aiconfigurator::aic-core/src/aiconfigurator_core/systems/perf_data_reuse_manifest.yaml:267-273] [::ai-dynamo/aiconfigurator::aic-core/src/aiconfigurator_core/systems/perf_data_reuse_manifest.yaml:806-812] [::ai-dynamo/aiconfigurator::aic-core/src/aiconfigurator_core/systems/perf_data_reuse_manifest.yaml:1561-1573]
The B60 version selector retains 0.20.0 as the previous slot, and a task test explicitly relies on its FP8 GEMM data. [::ai-dynamo/aiconfigurator::aic-core/src/aiconfigurator_core/systems/query_versions.yaml:34-37] [::ai-dynamo/aiconfigurator::tests/unit/sdk/task_v2/test_task_config.py:2042-2046]
The database parser accepts collection metadata schema versions 1 and 2, so the PR’s schema-2 metadata is compatible with this consumer. [::ai-dynamo/aiconfigurator::aic-core/src/aiconfigurator_core/sdk/perf_database.py:609-627]
Collector validation requires every remaining parquet table to have a corresponding collection_meta.yaml table entry; ensure removed sidecars are accompanied by removed parquet data. [::ai-dynamo/aiconfigurator::tools/perf_database/check_collector_data.py:157-176]

ai-dynamo/dynamo

No exact references to the affected collection metadata, reuse manifest, B60 data paths, or vLLM 0.20.0/0.28.0 slots were found in the scoped downstream search.

🔇 Additional comments: 2

python/aisimulate/src/aisimulate_core/systems/perf_data_reuse_manifest.yaml: 2

126-127: 🗄️ Data Integrity & Integration

The claim that the manifest counts are stale cannot be decided from the supplied evidence.

The diff lowers total_raw_rows and within_framework_dedup_rows for five entries, and each entry still lists b60 in systems. Whether this is wrong depends on whether retained Parquet tables still contain B60 rows for each affected (op_file, kernel_source, system, framework) key. The supplied context does not include those row counts, the retained Parquet inventory, or the retained collection metadata paths.

The repository context states that the reuse manifest governs cross-backend and cross-version reuse, not all table coverage. It also states that binary parquet changes need a machine-readable summary of keys, row counts, and coverage. The PR supplies only the count change and the removal narrative, so the required reconciliation is missing.

830-831: 🗄️ Data Integrity & Integration

The Aiconfigurator copy is independent. Its own aic-core/src/aiconfigurator_core/systems/data/b60/gemm/vllm/0.20.0/collection_meta.yaml retains the FP8 GEMM table, and its test targets that repository’s b60/vllm 0.20.0 data. AISimulate’s diff removes only its own data path. No cross-repository update or row retention is required.

chore: clean up stale B60 measurement data

50b3185

Signed-off-by: mandy-li <mandy.j.li@intel.com>

mandy-li requested review from a team as code owners October 23, 2026 23:59

coderabbitai Bot reviewed Oct 24, 2026

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Comment thread python/aisimulate/src/aisimulate_core/systems/data/b60/gemm/vllm/0.28.0/collection_meta.yaml

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chore: clean up stale B60 measurement data - #579

chore: clean up stale B60 measurement data#579
mandy-li wants to merge 1 commit into
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mandy-li:cleanup

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mandy-li commented Oct 23, 2026 •

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