sweep: 6 short-context CSVs (3 variants x prefill+decode) + 6 wall/util figures
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eusonice
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"""Generate 4 wall-clock comparison figures for the short-context GQA
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attention sweep (prefill + decode × A1/A2/A4/B × 3 variants × 4 contexts).
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Figures 1-3: mode comparison within one variant
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• 2 panels (prefill, decode), grouped bars per S_kv, hue=mode (A1/A2/A4/B)
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Figure 4: A1 variant comparison (best mode)
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• 2 panels, grouped bars per S_kv, hue=variant
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Output: docs/report/1H-codesign-paper/figures/gqa_short_context/
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"""
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from __future__ import annotations
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import csv
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from pathlib import Path
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import matplotlib.pyplot as plt
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import numpy as np
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ROOT = Path("/Users/lalicorne/Desktop/ahbm/kernbench2")
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SWEEPS = ROOT / "docs" / "sweeps"
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OUT = ROOT / "docs" / "report" / "1H-codesign-paper" / "figures" / "gqa_short_context"
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OUT.mkdir(parents=True, exist_ok=True)
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CONTEXTS = [8192, 16384, 32768, 65536]
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CONTEXT_LABELS = ["8K", "16K", "32K", "64K"]
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MODES = ["A1", "A2", "A4", "B"]
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MODE_LABEL = {"A1": "1-kv-per-cube", "A2": "2-kv-per-cube",
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"A4": "4-kv-per-cube", "B": "8-kv-per-cube"}
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MODE_COLOR = {MODE_LABEL["A1"]: "#1f77b4",
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MODE_LABEL["A2"]: "#2ca02c",
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MODE_LABEL["A4"]: "#ffd000",
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MODE_LABEL["B"]: "#d62728"}
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VARIANTS = [
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("baseline", "(1) without composite"),
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("composite", "(2) with composite (GEMM-only)"),
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("composite_fused", "(3) with composite + softmax_merge"),
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]
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VARIANT_COLOR = {
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"baseline": "#1f77b4",
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"composite": "#2ca02c",
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"composite_fused": "#d62728",
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}
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CSV_MAP = {
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("decode", "baseline"): SWEEPS / "short_context_decode_sweep.csv",
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("decode", "composite"): SWEEPS / "short_context_decode_composite_sweep.csv",
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("decode", "composite_fused"): SWEEPS / "short_context_decode_composite_fused_sweep.csv",
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("prefill", "baseline"): SWEEPS / "short_context_prefill_sweep.csv",
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("prefill", "composite"): SWEEPS / "short_context_prefill_composite_sweep.csv",
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("prefill", "composite_fused"): SWEEPS / "short_context_prefill_composite_fused_sweep.csv",
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}
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def load(phase, variant):
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"""Return {(mode, S_kv): wall_us}."""
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rows = {}
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with CSV_MAP[(phase, variant)].open() as f:
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for r in csv.DictReader(f):
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rows[(r["mode"], int(r["S_kv"]))] = float(r["wall_us"])
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return rows
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def _bar_chart(ax, *, x_labels, groups, group_color, ylabel, title,
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y_log=True):
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"""Grouped bars: x = x_labels, groups = list of (label, values).
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values is a list aligned with x_labels.
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"""
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n_groups = len(groups)
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n_x = len(x_labels)
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width = 0.8 / n_groups
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x = np.arange(n_x)
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for i, (label, values) in enumerate(groups):
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offset = (i - (n_groups - 1) / 2) * width
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bars = ax.bar(x + offset, values, width, label=label,
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color=group_color[label], edgecolor="black",
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linewidth=0.4)
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for bar, v in zip(bars, values):
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ax.text(bar.get_x() + bar.get_width() / 2,
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bar.get_height(),
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f"{v:.0f}", ha="center", va="bottom", fontsize=7,
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rotation=0)
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ax.set_xticks(x)
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ax.set_xticklabels(x_labels)
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ax.set_xlabel("S_kv")
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ax.set_ylabel(ylabel)
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ax.set_title(title)
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if y_log:
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ax.set_yscale("log")
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ax.grid(True, axis="y", alpha=0.3, which="both")
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ax.legend(fontsize=8, loc="upper left")
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def _fig_mode_compare(variant_key, variant_label, fname):
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"""Figure: 2 panels (prefill/decode), x=S_kv, grouped bars per mode."""
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fig, axes = plt.subplots(1, 2, figsize=(13, 4.8))
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for ax, phase in zip(axes, ("prefill", "decode")):
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rows = load(phase, variant_key)
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groups = []
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for mode in MODES:
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values = [rows[(mode, s)] for s in CONTEXTS]
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groups.append((MODE_LABEL[mode], values))
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_bar_chart(ax, x_labels=CONTEXT_LABELS, groups=groups,
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group_color=MODE_COLOR,
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ylabel="Wall-clock latency (μs)",
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title=f"{phase.capitalize()}")
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fig.suptitle(variant_label,
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fontsize=12, fontweight="bold")
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fig.tight_layout()
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out = OUT / fname
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fig.savefig(out, dpi=140, bbox_inches="tight")
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plt.close(fig)
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print(f" ✓ {out}")
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def _fig_a1_variant_compare(fname):
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"""Figure: A1 (best mode), 2 panels, x=S_kv, grouped bars per variant."""
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fig, axes = plt.subplots(1, 2, figsize=(13, 4.8))
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for ax, phase in zip(axes, ("prefill", "decode")):
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groups = []
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for variant_key, variant_label in VARIANTS:
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rows = load(phase, variant_key)
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values = [rows[("A1", s)] for s in CONTEXTS]
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groups.append((variant_key, values))
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_bar_chart(
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ax, x_labels=CONTEXT_LABELS, groups=groups,
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group_color=VARIANT_COLOR,
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ylabel="Wall-clock latency (μs)",
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title=f"{phase.capitalize()}",
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)
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# Custom legend labels
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handles, _ = ax.get_legend_handles_labels()
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readable = [v[1] for v in VARIANTS]
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ax.legend(handles, readable, fontsize=8, loc="upper left")
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fig.suptitle("1-kv-per-cube: variant comparison",
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fontsize=12, fontweight="bold")
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fig.tight_layout()
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out = OUT / fname
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fig.savefig(out, dpi=140, bbox_inches="tight")
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plt.close(fig)
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print(f" ✓ {out}")
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if __name__ == "__main__":
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print(f"Output dir: {OUT}")
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_fig_mode_compare("baseline",
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"(1) Without composite: latency mode comparison",
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"wall_variant1_mode_compare.png")
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_fig_mode_compare("composite",
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"(2) With composite (GEMM-only): latency mode comparison",
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"wall_variant2_mode_compare.png")
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_fig_mode_compare("composite_fused",
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"(3) With composite + softmax_merge: latency mode comparison",
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"wall_variant3_mode_compare.png")
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_fig_a1_variant_compare("wall_a1_variant_compare.png")
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print("\nDone.")
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