Microbench 3 (connector_tax): infrastructure for KV connector substrate tax
Validates the elastic_migration_v2 finding that kv_role=kv_both adds
TTFT p90 +45% even when PD-sep never fires. Replicates under
single-instance, synthetic, open-loop workload to disambiguate
mechanism cost from 8-instance feedback amplification.
Configurations (8):
plain, noop_connector, mooncake_{producer,consumer,both},
nixl_both, lmcache_only, multi_mooncake_lmcache.
Pre-flight verification gates risky configs (kv_consumer needs dummy
bootstrap, multi-connector composition, NoOp custom class loading).
Workload: two-phase sweep
Phase A: rate {0.5..32} req/s × shape (4096, 256), saturation criteria
Phase B: ref_safe rate × cartesian (input ∈ {512,4k,32k}, output ∈ {64,256,1024})
Step-timing patch enriches vLLM's existing AGENTIC_STEP_LOG_PATH emit
with step_duration_us and build_meta_us — directly measures per-step
substrate cost, not just user-visible TTFT/TPOT.
run_all.sh runs as 5-stage barrier:
0 pre-flight + apply patch
1 Phase A all configs
2 pick ref_safe / ref_load
3 Phase B all configs
4 revert patch + analyze + plot
Outputs aggregate.{json,csv}, MANIFEST.tsv, and 5 figures.
Estimated runtime: 4-5.5 hours on idle dash0 H20.
This commit is contained in:
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microbench/connector_tax/plot_connector_tax.py
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263
microbench/connector_tax/plot_connector_tax.py
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#!/usr/bin/env python3
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"""Plot Figures 1-5 from connector_tax aggregate.
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Requires aggregate.json + aggregate.csv from analyze.py.
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Figure 1: TTFT p90 vs send rate, line per config (Phase A)
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Figure 2: TPOT p90 vs send rate
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Figure 3: Achieved throughput vs requested
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Figure 4: Substrate tax bar at ref_safe and ref_load
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Figure 5: Shape-dependent tax heatmap (Phase B)
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"""
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import argparse
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import json
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from collections import defaultdict
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from pathlib import Path
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import numpy as np
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import matplotlib
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matplotlib.use("Agg")
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import matplotlib.pyplot as plt
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CONFIG_COLORS = {
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"plain": "#000000",
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"noop_connector": "#7f7f7f",
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"mooncake_producer": "#1f77b4",
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"mooncake_consumer": "#17becf",
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"mooncake_both": "#d62728",
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"nixl_both": "#ff7f0e",
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"lmcache_only": "#2ca02c",
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"multi_mooncake_lmcache": "#9467bd",
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}
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def load(root: Path):
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agg = json.loads((root / "aggregate.json").read_text())
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return agg
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def fig1_2_3(agg, out_dir):
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configs = agg["configs"]
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# Rates
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rates = agg["rates_swept"]
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# ----- fig 1: TTFT p90 -----
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fig, ax = plt.subplots(figsize=(10, 5.5))
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for cfg, d in configs.items():
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cells = sorted(d["phase_a"], key=lambda c: c["rate_target"])
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xs = [c["rate_target"] for c in cells]
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ys = [c.get("ttft_ms_p90") for c in cells]
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ax.plot(xs, ys, "o-", label=cfg,
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color=CONFIG_COLORS.get(cfg, None), linewidth=2)
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# mark saturation
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for c in cells:
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if c.get("saturated"):
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ax.plot([c["rate_target"]], [c["ttft_ms_p90"]], "x",
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markersize=12, mew=2,
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color=CONFIG_COLORS.get(cfg, "red"))
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ax.set_xscale("log", base=2)
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ax.set_yscale("log")
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ax.set_xticks(rates)
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ax.set_xticklabels([str(r) for r in rates])
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ax.set_xlabel("Send rate (req/s)")
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ax.set_ylabel("TTFT p90 (ms, log)")
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ax.set_title("Figure 1 — TTFT p90 vs send rate (Phase A)\n"
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"× = saturation criterion fired")
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ax.grid(True, which="both", linestyle="--", alpha=0.4)
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ax.legend(fontsize=8, loc="upper left")
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fig.tight_layout()
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fig.savefig(out_dir / "fig1_ttft_vs_rate.png", dpi=160)
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plt.close(fig)
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# ----- fig 2: TPOT p90 -----
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fig, ax = plt.subplots(figsize=(10, 5.5))
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for cfg, d in configs.items():
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cells = sorted(d["phase_a"], key=lambda c: c["rate_target"])
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xs = [c["rate_target"] for c in cells]
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ys = [c.get("tpot_ms_p90") for c in cells]
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ax.plot(xs, ys, "o-", label=cfg,
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color=CONFIG_COLORS.get(cfg, None), linewidth=2)
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ax.set_xscale("log", base=2)
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ax.set_xticks(rates)
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ax.set_xticklabels([str(r) for r in rates])
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ax.set_xlabel("Send rate (req/s)")
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ax.set_ylabel("TPOT p90 (ms)")
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ax.set_title("Figure 2 — TPOT p90 vs send rate (Phase A)")
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ax.grid(True, linestyle="--", alpha=0.4)
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ax.legend(fontsize=8, loc="upper left")
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fig.tight_layout()
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fig.savefig(out_dir / "fig2_tpot_vs_rate.png", dpi=160)
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plt.close(fig)
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# ----- fig 3: throughput -----
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fig, ax = plt.subplots(figsize=(10, 5.5))
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max_x = max(rates) if rates else 1
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ax.plot([0, max_x], [0, max_x], "k--", alpha=0.4, label="ideal y=x")
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for cfg, d in configs.items():
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cells = sorted(d["phase_a"], key=lambda c: c["rate_target"])
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xs = [c["rate_target"] for c in cells]
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ys = [c.get("throughput_effective_rps") for c in cells]
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ax.plot(xs, ys, "o-", label=cfg,
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color=CONFIG_COLORS.get(cfg, None), linewidth=2)
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ax.set_xlabel("Send rate (req/s)")
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ax.set_ylabel("Effective throughput (req/s)")
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ax.set_title("Figure 3 — Throughput tracking (Phase A)")
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ax.grid(True, linestyle="--", alpha=0.4)
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ax.legend(fontsize=8, loc="upper left")
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fig.tight_layout()
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fig.savefig(out_dir / "fig3_throughput_vs_rate.png", dpi=160)
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plt.close(fig)
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def fig4(agg, out_dir):
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configs = agg["configs"]
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if "plain" not in configs:
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return
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plain = configs["plain"]
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def cell_at(d, r):
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for c in d["phase_a"]:
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if abs(c["rate_target"] - r) < 1e-6:
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return c
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return None
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def tax(c_cfg, c_plain, key):
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if c_cfg is None or c_plain is None:
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return None
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a, b = c_cfg.get(key), c_plain.get(key)
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if not a or not b:
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return None
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return a / b - 1
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rates_used = []
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if agg.get("ref_safe") is not None:
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rates_used.append(("ref_safe", agg["ref_safe"]))
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if agg.get("ref_load") is not None and agg["ref_load"] != agg.get("ref_safe"):
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rates_used.append(("ref_load", agg["ref_load"]))
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if not rates_used:
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return
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cfg_names = [c for c in configs if c != "plain"]
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fig, axes = plt.subplots(1, 2, figsize=(13, 5))
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if len(rates_used) == 1:
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axes = [axes[0]]
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for ax, (label, r) in zip(axes, rates_used):
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plain_cell = cell_at(plain, r)
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ttft_taxes = []
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tpot_taxes = []
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for cfg in cfg_names:
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c = cell_at(configs[cfg], r)
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ttft_taxes.append(tax(c, plain_cell, "ttft_ms_p90") or 0)
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tpot_taxes.append(tax(c, plain_cell, "tpot_ms_p90") or 0)
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x = np.arange(len(cfg_names))
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w = 0.4
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ax.bar(x - w/2, [v * 100 for v in ttft_taxes], width=w,
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label="TTFT p90 tax %", color="#d62728", alpha=0.85)
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ax.bar(x + w/2, [v * 100 for v in tpot_taxes], width=w,
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label="TPOT p90 tax %", color="#1f77b4", alpha=0.85)
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ax.axhline(0, color="black", linewidth=0.5)
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ax.set_xticks(x)
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ax.set_xticklabels(cfg_names, rotation=30, ha="right", fontsize=8)
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ax.set_ylabel("Tax vs plain (%)")
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ax.set_title(f"{label} (rate={r} req/s)")
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ax.grid(True, axis="y", linestyle="--", alpha=0.4)
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ax.legend(fontsize=8)
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fig.suptitle("Figure 4 — Substrate tax (TTFT p90 + TPOT p90) "
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"at reference rates", fontweight="bold")
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fig.tight_layout()
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fig.savefig(out_dir / "fig4_substrate_tax.png", dpi=160)
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plt.close(fig)
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def fig5(agg, out_dir):
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configs = agg["configs"]
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if "plain" not in configs:
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return
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# Build (input, output) → ttft_p90 per config
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cfg_names = [c for c in configs if c != "plain"]
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def shape_map(d):
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m = {}
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for c in d.get("phase_b", []):
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key = (c["input_tokens"], c["output_tokens"])
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m[key] = c.get("ttft_ms_p90")
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return m
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plain_map = shape_map(configs["plain"])
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if not plain_map:
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return
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inputs = sorted({k[0] for k in plain_map})
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outputs = sorted({k[1] for k in plain_map})
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n = len(cfg_names)
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cols = min(3, n)
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rows = (n + cols - 1) // cols
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fig, axes = plt.subplots(rows, cols, figsize=(5 * cols, 4 * rows))
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if n == 1:
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axes = np.array([[axes]])
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elif rows == 1:
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axes = axes.reshape(1, -1)
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for idx, cfg in enumerate(cfg_names):
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ax = axes[idx // cols][idx % cols]
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cmap = shape_map(configs[cfg])
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mat = np.full((len(outputs), len(inputs)), np.nan)
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for i, ip in enumerate(inputs):
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for j, op in enumerate(outputs):
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a = cmap.get((ip, op))
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b = plain_map.get((ip, op))
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if a and b:
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mat[j, i] = a / b - 1
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im = ax.imshow(mat * 100, cmap="YlOrRd", aspect="auto")
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ax.set_xticks(range(len(inputs)))
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ax.set_xticklabels([f"{x//1024}k" if x >= 1024 else str(x) for x in inputs])
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ax.set_yticks(range(len(outputs)))
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ax.set_yticklabels([str(y) for y in outputs])
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ax.set_xlabel("input")
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ax.set_ylabel("output")
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ax.set_title(cfg, fontsize=10)
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for i in range(len(inputs)):
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for j in range(len(outputs)):
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v = mat[j, i]
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if not np.isnan(v):
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txt = f"{v*100:.0f}%"
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ax.text(i, j, txt, ha="center", va="center",
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fontsize=9,
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color="white" if v * 100 > 30 else "black")
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plt.colorbar(im, ax=ax, fraction=0.04, pad=0.02)
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# Hide leftover axes
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for idx in range(n, rows * cols):
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axes[idx // cols][idx % cols].axis("off")
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fig.suptitle("Figure 5 — TTFT p90 substrate tax (%) by shape (Phase B)",
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fontweight="bold")
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fig.tight_layout()
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fig.savefig(out_dir / "fig5_shape_tax_heatmap.png", dpi=160)
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plt.close(fig)
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def main():
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ap = argparse.ArgumentParser()
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ap.add_argument("--root", type=Path, required=True)
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args = ap.parse_args()
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agg = load(args.root)
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out = args.root
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out.mkdir(parents=True, exist_ok=True)
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fig1_2_3(agg, out)
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fig4(agg, out)
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fig5(agg, out)
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print(f"Saved figures into {out}")
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if __name__ == "__main__":
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main()
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