agentic-kvc/microbench/fresh_setup/fig_agg.py

"""Aggregate a set of MB5 run dirs into one comparison table.

Pulls the three core metrics the analysis cares about, per run:
  - E2E latency  (from replay_metrics.summary.json: latency_stats_s)
  - TPS          (output tokens / wall_clock_s)
  - GPU util by workers (gpu_util.csv over run_window, split prefill/decode by role)
plus honest reuse (producer-side APC from instance_apc.txt) and TTFT/TPOT for logs.

Arm + GPU role split + producer APC ports are inferred from the dir name:
  *_colo_*  -> 8 kv_both     ; apc ports 8000-8007 (all keep prefix)
  *_pd6_*   -> 6P+2D P0-5/D6-7 ; apc 8000-8005
  *_pd_*    -> 4P+4D P0-3/D4-7 ; apc 8000-8003   (note: "pd" not "pd4")
  *_pd2_*   -> 2P+6D P0-1/D2-7 ; apc 8000-8001

Usage: fig_agg.py <run_dir> [<run_dir> ...]
"""
from __future__ import annotations

import csv
import json
import re
import statistics
import sys
from pathlib import Path


def arm_of(name: str):
    # New driver naming (run_conc.sh / run_reuse_fixed.sh): "..._<CONFIG>_rep<r>".
    if "8C-proxy" in name:
        return "colo", list(range(8)), [], list(range(8000, 8008))
    if "6P+2D" in name:
        return "6P+2D", [0, 1, 2, 3, 4, 5], [6, 7], list(range(8000, 8006))
    if "2P+6D" in name:
        return "2P+6D", [0, 1], [2, 3, 4, 5, 6, 7], list(range(8000, 8002))
    if "4P+4D" in name:
        return "4P+4D", [0, 1, 2, 3], [4, 5, 6, 7], list(range(8000, 8004))
    # Legacy naming (original May-30 corrected runs).
    if "_colo_" in name or name.endswith("_colo"):
        return "colo", list(range(8)), [], list(range(8000, 8008))
    if "_pd6_" in name:
        return "6P+2D", [0, 1, 2, 3, 4, 5], [6, 7], list(range(8000, 8006))
    if "_pd2_" in name:
        return "2P+6D", [0, 1], [2, 3, 4, 5, 6, 7], list(range(8000, 8002))
    if "_pd4_" in name or "_pd_" in name:
        return "4P+4D", [0, 1, 2, 3], [4, 5, 6, 7], list(range(8000, 8004))
    return "?", list(range(8)), [], list(range(8000, 8008))


def util_split(run: Path, pgpus, dgpus):
    win = {}
    wp = run / "run_window.json"
    if wp.exists():
        win = json.load(open(wp))
    t0, t1 = win.get("t_start_unix"), win.get("t_end_unix")
    csvp = run / "gpu_util.csv"
    if not csvp.exists():
        return None, None
    by = {}
    for row in csv.DictReader(open(csvp)):
        try:
            ts = float(row["timestamp"]); g = int(row["gpu"]); u = float(row["util_pct"])
        except (ValueError, KeyError):
            continue
        if t0 and not (t0 <= ts <= t1):
            continue
        by.setdefault(g, []).append(u)
    pm = [v for g in pgpus for v in by.get(g, [])]
    dm = [v for g in dgpus for v in by.get(g, [])]
    return (statistics.fmean(pm) if pm else None,
            statistics.fmean(dm) if dm else None)


def apc(run: Path, ports):
    f = run / "instance_apc.txt"
    if not f.exists():
        return None
    q = h = 0
    for line in open(f):
        m = dict(re.findall(r"(\w+)=(\S+)", line))
        try:
            p = int(m.get("port", -1))
        except ValueError:
            continue
        if p in ports:
            q += float(m.get("queries", 0)); h += float(m.get("hits", 0))
    return (h / q) if q else None


def main():
    args = sys.argv[1:]
    as_json = False
    if "--json" in args:
        as_json = True
        args = [a for a in args if a != "--json"]
    rows = []
    for d in args:
        run = Path(d)
        sp = run / "replay_metrics.summary.json"
        if not sp.exists():
            continue
        s = json.load(open(sp))
        arm, pg, dg, ports = arm_of(run.name)
        lat = s.get("latency_stats_s", {})
        ttft = s.get("ttft_stats_s", {})
        tpot = s.get("tpot_stats_s", {})
        wall = s.get("wall_clock_s") or 1.0
        out = s.get("actual_output_tokens_stats", {})
        n = s.get("success_count", 0); req = s.get("request_count", 0)
        tot_out = out.get("count", 0) * out.get("mean", 0)
        tps = tot_out / wall
        pu, du = util_split(run, pg, dg)
        a = apc(run, ports)
        rows.append({
            "name": run.name, "arm": arm, "n": n, "req": req,
            "e2e_p50": lat.get("p50"), "e2e_p90": lat.get("p90"), "e2e_p99": lat.get("p99"),
            "e2e_mean": lat.get("mean"),
            "ttft_p90": ttft.get("p90"), "tpot_p99": tpot.get("p99"),
            "tps": tps, "wall": wall, "pu": pu, "du": du, "apc": a,
        })

    if as_json:
        print(json.dumps(rows))
        return

    def f(x, w=7, p=1):
        return f"{x:>{w}.{p}f}" if isinstance(x, (int, float)) else f"{'-':>{w}}"

    hdr = (f"{'run':<34}{'arm':>7}{'ok/req':>9}{'E2Ep50':>8}{'E2Ep90':>8}{'E2Ep99':>8}"
           f"{'TPS':>8}{'Putil':>7}{'Dutil':>7}{'APC%':>7}{'TTFTp90':>9}{'TPOTp99ms':>10}")
    print(hdr); print("-" * len(hdr))
    for r in sorted(rows, key=lambda r: r["name"]):
        print(f"{r['name']:<34}{r['arm']:>7}{str(r['n'])+'/'+str(r['req']):>9}"
              f"{f(r['e2e_p50'])}{f(r['e2e_p90'])}{f(r['e2e_p99'])}"
              f"{f(r['tps'],8,1)}{f(r['pu'])}{f(r['du'])}"
              f"{f((r['apc'] or 0)*100)}{f(r['ttft_p90'],9,2)}"
              f"{f((r['tpot_p99'] or 0)*1000,10,1)}")


if __name__ == "__main__":
    main()