attention: milestone-gqa-llama70b figures + MILESTONE_FAST (sub-cycle 4c, 5/6)

Add 5 of the 6 figure renderers ADR-0057 D3 sub-cycle 4c specifies:
  - gqa_op_log_{panel}.png × 4 — per-panel bar chart of the 5 op_log
    counts (gemm, ipcq_send, ipcq_recv, dma_read, dma_write).
  - gqa_comparison.png — cross-panel grouped bars over the same 5 series.

Sixth figure (gqa_scaling.png) depends on sub-cycle 4b's Q/cube ∈
{1, 2, 4} sweep on multi_user_* panels and is deferred until that
data exists; emit_all_gqa_plots returns just the 5 in-scope paths.

Add MILESTONE_FAST=1 mode to run(): skip the panel sweep, reuse the
committed sweep.json, render figures only. Validation mode unchanged.
The runtime errors clearly when neither env var is set, listing the
two supported modes.

Renderers live in the bench module (the milestone-1h-gemm pattern);
tests/gqa/_gqa_plot_helpers.py re-exports them for figure tests.

Tests: tests/gqa/test_plot_gqa_figures.py — 7 tests, all green:
  - 4 parametrized per-panel emit assertions
  - 1 comparison emit assertion
  - 1 emit_all returns exactly 5 PNG paths
  - 1 default out_dir matches the bench _OUTPUT_DIR

Commits the 5 PNG baselines under the bench output dir alongside
sweep.json, mirroring milestone-1h-gemm's committed-figures pattern.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
2026-06-01 22:23:28 -07:00
parent e748a62264
commit b3ca532023
8 changed files with 342 additions and 30 deletions
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@@ -196,6 +196,168 @@ def _run_panel(panel: str, topology: str) -> dict:
}
# ── Figure renderers (sub-cycle 4c, 5 of 6 figures) ──────────────────
#
# Sixth figure ``gqa_scaling.png`` is deferred to after sub-cycle 4b
# lands the Q/cube ∈ {1, 2, 4} sweep on multi_user_* panels — it needs
# multiple sweep.json rows per multi_user panel to be meaningful.
_OP_LOG_KEYS = (
"gemm_count",
"ipcq_send_count",
"ipcq_recv_count",
"dma_read_count",
"dma_write_count",
)
_OP_LOG_DISPLAY = {
"gemm_count": "GEMM",
"ipcq_send_count": "IPCQ send",
"ipcq_recv_count": "IPCQ recv",
"dma_read_count": "DMA read",
"dma_write_count": "DMA write",
}
_OP_LOG_COLORS = {
"gemm_count": "#F59E0B",
"ipcq_send_count": "#3B82F6",
"ipcq_recv_count": "#10B981",
"dma_read_count": "#A855F7",
"dma_write_count": "#EF4444",
}
_PANEL_DISPLAY = {
"single_user_prefill": "single_user / prefill",
"multi_user_prefill": "multi_user / prefill",
"single_user_decode": "single_user / decode",
"multi_user_decode": "multi_user / decode",
}
def _load_sweep_data(sweep_json: Path | str) -> dict:
sweep_json = Path(sweep_json)
if not sweep_json.exists():
return {"rows": [], "config": {}, "panels": []}
return json.loads(sweep_json.read_text())
def _row_for(rows: list, panel: str) -> dict | None:
for r in rows:
if r.get("panel") == panel:
return r
return None
def emit_panel_op_log_summary(
panel: str,
sweep_json: Path | str = _SWEEP_JSON,
out_dir: Path | str = _OUTPUT_DIR,
) -> str | None:
"""One bar chart of the 5 op_log counts for ``panel``.
Returns the written PNG path, or ``None`` when sweep.json is empty
or the requested panel is absent.
"""
import matplotlib.pyplot as plt
data = _load_sweep_data(sweep_json)
row = _row_for(data.get("rows", []), panel)
if row is None:
return None
summary = row.get("op_log_summary", {})
n_ranks = row.get("n_ranks")
labels = [_OP_LOG_DISPLAY[k] for k in _OP_LOG_KEYS]
values = [summary.get(k, 0) for k in _OP_LOG_KEYS]
colors = [_OP_LOG_COLORS[k] for k in _OP_LOG_KEYS]
fig, ax = plt.subplots(figsize=(8, 5))
bars = ax.bar(labels, values, color=colors)
for b, v in zip(bars, values):
ax.text(b.get_x() + b.get_width() / 2, b.get_height(),
f"{int(v)}", ha="center", va="bottom", fontsize=9)
ax.set_title(
f"{_PANEL_DISPLAY.get(panel, panel)} (n_ranks={n_ranks})",
fontsize=12, fontweight="bold",
)
ax.set_ylabel("count")
ax.grid(True, axis="y", alpha=0.3)
fig.tight_layout()
out_dir = Path(out_dir)
out_dir.mkdir(parents=True, exist_ok=True)
out = out_dir / f"gqa_op_log_{panel}.png"
fig.savefig(out, dpi=120)
plt.close(fig)
return str(out)
def emit_gqa_comparison(
sweep_json: Path | str = _SWEEP_JSON,
out_dir: Path | str = _OUTPUT_DIR,
) -> str | None:
"""Grouped-bar chart comparing the 5 op_log counts across all panels."""
import matplotlib.pyplot as plt
import numpy as np
data = _load_sweep_data(sweep_json)
panels_in = data.get("panels") or list(_PANELS_V1)
rows = data.get("rows", [])
panels = [p for p in panels_in if _row_for(rows, p) is not None]
if not panels:
return None
n_groups = len(panels)
n_series = len(_OP_LOG_KEYS)
x = np.arange(n_groups)
width = 0.8 / n_series
fig, ax = plt.subplots(figsize=(11, 6))
for i, key in enumerate(_OP_LOG_KEYS):
offset = (i - (n_series - 1) / 2) * width
vals = [_row_for(rows, p)["op_log_summary"].get(key, 0)
for p in panels]
ax.bar(x + offset, vals, width,
label=_OP_LOG_DISPLAY[key], color=_OP_LOG_COLORS[key])
ax.set_xticks(x)
ax.set_xticklabels(
[f"{_PANEL_DISPLAY.get(p, p)}\n(n_ranks={_row_for(rows, p)['n_ranks']})"
for p in panels],
fontsize=8,
)
ax.set_ylabel("count")
ax.set_title("GQA Llama-70B — op_log summary across panels",
fontsize=13, fontweight="bold")
ax.legend(fontsize=8, loc="upper right")
ax.grid(True, axis="y", alpha=0.3)
fig.tight_layout()
out_dir = Path(out_dir)
out_dir.mkdir(parents=True, exist_ok=True)
out = out_dir / "gqa_comparison.png"
fig.savefig(out, dpi=120)
plt.close(fig)
return str(out)
def emit_all_gqa_plots(
sweep_json: Path | str = _SWEEP_JSON,
out_dir: Path | str = _OUTPUT_DIR,
) -> list[str]:
"""Render all 5 in-scope figures and return the written paths.
Sub-cycle 4c v1 emits 5 of the 6 figures ADR-0057 D3 lists; the
6th (gqa_scaling.png) needs sub-cycle 4b's Q/cube sweep data.
"""
paths: list[str] = []
for panel in _PANELS_V1:
p = emit_panel_op_log_summary(panel, sweep_json, out_dir)
if p is not None:
paths.append(p)
comp = emit_gqa_comparison(sweep_json, out_dir)
if comp is not None:
paths.append(comp)
return paths
# ── Bench entry ────────────────────────────────────────────────────────
@@ -204,42 +366,58 @@ def _run_panel(panel: str, topology: str) -> dict:
description="1H milestone: GQA Llama-70B 4-panel sweep (ADR-0057 v1).",
)
def run(torch) -> None:
"""Drive the four GQA panels at validation scale; write sweep.json.
"""Drive the four GQA panels at validation scale; write sweep.json and figures.
v1 only supports validation mode (``GQA_VALIDATION=1``). Headline
mode and figures are deferred to sub-cycles 4b and 4c per ADR-0057 D3.
Modes (mutually exclusive):
MILESTONE_FAST=1 Skip the sweep; re-render figures from the
committed sweep.json. Seconds, no simulator.
GQA_VALIDATION=1 Run the four-panel validation sweep + figures.
~1-2h on the full simulator.
Headline-scale mode is deferred to sub-cycle 4c (figures landed
here; headline-scale + scaling figure await sub-cycle 4b).
A sentinel tensor is submitted at the end so run_bench's ADR-0045 D4
"at least one request" contract is satisfied even though the panels
drive their own engines.
"at least one request" contract is satisfied even when the panels
are skipped via MILESTONE_FAST=1.
"""
if not os.environ.get("GQA_VALIDATION"):
raise RuntimeError(
"milestone-gqa-llama70b v1 only supports validation mode. "
"Set GQA_VALIDATION=1 to run. Headline mode is deferred to "
"sub-cycle 4b/4c per ADR-0057 D3."
)
_OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
topology = os.environ.get("GQA_TOPOLOGY", "topology.yaml")
fast = bool(os.environ.get("MILESTONE_FAST"))
if not fast and not os.environ.get("GQA_VALIDATION"):
raise RuntimeError(
"milestone-gqa-llama70b v1 needs GQA_VALIDATION=1 (run the "
"sweep) or MILESTONE_FAST=1 (reuse committed sweep.json). "
"Headline mode is deferred to sub-cycle 4b/4c per ADR-0057 D3."
)
rows = [_run_panel(panel, topology) for panel in _PANELS_V1]
if not fast:
topology = os.environ.get("GQA_TOPOLOGY", "topology.yaml")
rows = [_run_panel(panel, topology) for panel in _PANELS_V1]
sweep = {
"version": 1,
"validation_scale": True,
"panels": list(_PANELS_V1),
"config": {
"S_q_prefill": _S_Q_PREFILL,
"S_kv_per_rank": _S_KV_PER_RANK,
"h_q": _H_Q,
"h_kv": _H_KV,
"d_head": _D_HEAD,
"n_ranks_single_user": _N_RANKS_SINGLE_USER,
"n_ranks_multi_user": _N_RANKS_MULTI_USER,
},
"rows": rows,
}
_SWEEP_JSON.write_text(json.dumps(sweep, indent=2))
print(f" milestone-gqa-llama70b: {len(rows)} rows -> {_SWEEP_JSON}")
elif not _SWEEP_JSON.exists():
raise RuntimeError(
f"MILESTONE_FAST=1 requires {_SWEEP_JSON} to exist; "
"run with GQA_VALIDATION=1 once to seed it."
)
sweep = {
"version": 1,
"validation_scale": True,
"panels": list(_PANELS_V1),
"config": {
"S_q_prefill": _S_Q_PREFILL,
"S_kv_per_rank": _S_KV_PER_RANK,
"h_q": _H_Q,
"h_kv": _H_KV,
"d_head": _D_HEAD,
"n_ranks_single_user": _N_RANKS_SINGLE_USER,
"n_ranks_multi_user": _N_RANKS_MULTI_USER,
},
"rows": rows,
}
_SWEEP_JSON.write_text(json.dumps(sweep, indent=2))
print(f" milestone-gqa-llama70b: {len(rows)} rows -> {_SWEEP_JSON}")
paths = emit_all_gqa_plots()
print(f" milestone-gqa-llama70b: {len(paths)} figures -> {_OUTPUT_DIR} "
f"(fast={fast})")
# Sentinel tensor (ADR-0045 D4 / ADR-0054 D2 carve-out).
torch.zeros(
+25
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@@ -0,0 +1,25 @@
"""Thin re-export shim for the GQA figure tests.
Not a test module (no ``test_`` prefix → pytest does not collect it).
Mirrors ``tests/gemm/_gemm_plot_helpers.py``. The renderer logic lives in
``kernbench.benches.milestone_gqa_llama70b`` (production single home,
ADR-0054). Defaults still target the bench's ``_OUTPUT_DIR``.
"""
from __future__ import annotations
from kernbench.benches.milestone_gqa_llama70b import (
_OUTPUT_DIR as GQA_PLOTS_DIR,
_SWEEP_JSON as GQA_SWEEP_JSON,
emit_all_gqa_plots,
emit_gqa_comparison,
emit_panel_op_log_summary,
)
__all__ = [
"GQA_PLOTS_DIR",
"GQA_SWEEP_JSON",
"emit_all_gqa_plots",
"emit_gqa_comparison",
"emit_panel_op_log_summary",
]
+109
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@@ -0,0 +1,109 @@
"""Phase 1 spec test for GQA figure renderers (sub-cycle 4c).
ADR-0057 D3 sub-cycle 4c adds 6 figure renderers; this test pins the
5 of 6 that don't depend on sub-cycle 4b's Q/cube sweep:
- 4 per-panel op_log_summary PNGs (one per panel of v1's sweep.json)
- 1 cross-panel ``gqa_comparison.png`` (4-panel grouped bars over the
5 op_log_summary counts: gemm, ipcq_send, ipcq_recv, dma_read, dma_write)
The 6th, ``gqa_scaling.png``, needs the Q/cube ∈ {1, 2, 4} sweep from
sub-cycle 4b and is deferred.
Each test depends on the committed
``benches/1H_milestone_output/gqa/sweep.json`` (landed in commit
``e748a62``); they assert the renderer writes a non-empty PNG at the
expected path.
Phase 1 expectation: tests fail at import (renderer functions don't
exist yet on the bench module). Phase 2 lands them and the tests
turn green.
"""
from __future__ import annotations
from pathlib import Path
import pytest
from tests.gqa._gqa_plot_helpers import (
GQA_PLOTS_DIR,
GQA_SWEEP_JSON,
emit_all_gqa_plots,
emit_gqa_comparison,
emit_panel_op_log_summary,
)
_PANELS = (
"single_user_prefill",
"multi_user_prefill",
"single_user_decode",
"multi_user_decode",
)
@pytest.mark.skipif(
not GQA_SWEEP_JSON.exists(),
reason="gqa sweep.json absent; run milestone-gqa-llama70b first",
)
@pytest.mark.parametrize("panel", _PANELS)
def test_emit_panel_op_log_summary_writes_png_for_each_panel(panel):
out = emit_panel_op_log_summary(panel)
assert out is not None, f"{panel}: renderer returned None"
path = Path(out)
assert path.exists(), f"{panel}: expected PNG at {path}"
assert path.suffix == ".png", f"{panel}: not a PNG: {path}"
assert path.stat().st_size > 0, f"{panel}: empty PNG: {path}"
assert panel in path.stem, (
f"{panel}: panel name not in filename {path.name}"
)
@pytest.mark.skipif(
not GQA_SWEEP_JSON.exists(),
reason="gqa sweep.json absent; run milestone-gqa-llama70b first",
)
def test_emit_gqa_comparison_writes_png():
out = emit_gqa_comparison()
assert out is not None
path = Path(out)
assert path.exists()
assert path.name == "gqa_comparison.png"
assert path.stat().st_size > 0
@pytest.mark.skipif(
not GQA_SWEEP_JSON.exists(),
reason="gqa sweep.json absent; run milestone-gqa-llama70b first",
)
def test_emit_all_gqa_plots_writes_five_figures():
"""emit_all returns a list of 5 written PNG paths (deferring the
6th gqa_scaling.png to after sub-cycle 4b lands the Q/cube sweep)."""
paths = emit_all_gqa_plots()
assert isinstance(paths, list)
# 4 per-panel + 1 comparison.
assert len(paths) == 5, f"expected 5 PNGs, got {len(paths)}: {paths}"
for p in paths:
assert Path(p).exists() and Path(p).stat().st_size > 0
names = {Path(p).name for p in paths}
assert "gqa_comparison.png" in names
for panel in _PANELS:
assert any(panel in n for n in names), (
f"no per-panel PNG for {panel} in {names}"
)
def test_emit_all_gqa_plots_output_dir_matches_bench_output_dir():
"""The renderers must write under the bench's own _OUTPUT_DIR so
MILESTONE_FAST=1 reuse (and committed baselines) all point at the
same on-disk location."""
# Stub assertion that fails until emit_all_gqa_plots exists with a
# default ``out_dir`` argument identical to GQA_PLOTS_DIR.
import inspect
sig = inspect.signature(emit_all_gqa_plots)
assert "out_dir" in sig.parameters
default = sig.parameters["out_dir"].default
assert Path(default) == GQA_PLOTS_DIR, (
f"default out_dir {default} != bench _OUTPUT_DIR {GQA_PLOTS_DIR}"
)