feat(experiments): E1 sweep on 50-session deterministic subset
scripts/sample_trace_subset.py — file-order head-cut that takes the
first N sessions of a converted trace. No RNG, no hashing — same
input yields byte-identical output (the included assertion compares
md5 across two runs).
scripts/sweep_e1_naive_1p3d.sh — E1 of ONBOARDING_NEXT_AGENT_ZH §3.1:
mechanism=pd-disaggregation, policy=kv-aware, 1P3D, RDMA on
(mlx5_60). Defaults to outputs/inferact_50sess.jsonl so E1 and E2
can share the exact same subset; override via TRACE= env var to run
on the full 20,230-request trace.
Reproducing the subset:
uv run --no-sync python scripts/sample_trace_subset.py \\
--input outputs/inferact_codex_swebenchpro.jsonl \\
--output outputs/inferact_50sess.jsonl \\
--sessions 50
# expected output_md5: 7bb263a32600ef5a6ef5099ba340a487
# 1285 requests, mean input_length 67631 tokens
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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81
scripts/sample_trace_subset.py
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81
scripts/sample_trace_subset.py
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"""Deterministically slice the first N sessions of an agentic-pd-hybrid trace.
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Method: scan in file order, count records whose `parent_chat_id == -1` (= a
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session's turn 0), and write every record until the (N+1)-th such record is
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seen. No RNG, no hashing — re-running on the same input produces a byte-
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identical output. Used to derive matched subsets for paired sweeps (E1 vs E2)
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without spending GPU hours on the full trace.
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Usage:
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uv run --no-sync python scripts/sample_trace_subset.py \
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--input outputs/inferact_codex_swebenchpro.jsonl \
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--output outputs/inferact_50sess.jsonl \
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--sessions 50
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"""
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from __future__ import annotations
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import argparse
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import hashlib
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import json
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import sys
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from pathlib import Path
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def slice_first_n_sessions(input_path: Path, output_path: Path, n_sessions: int) -> dict:
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sessions_seen = 0
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requests_written = 0
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input_length_sum = 0
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output_length_sum = 0
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min_in = float("inf")
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max_in = 0
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with input_path.open("r", encoding="utf-8") as f_in, output_path.open(
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"w", encoding="utf-8"
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) as f_out:
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for line in f_in:
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rec = json.loads(line)
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if rec["parent_chat_id"] == -1:
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sessions_seen += 1
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if sessions_seen > n_sessions:
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break
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f_out.write(line)
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requests_written += 1
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il = int(rec["input_length"])
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input_length_sum += il
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output_length_sum += int(rec["output_length"])
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if il < min_in:
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min_in = il
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if il > max_in:
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max_in = il
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h = hashlib.md5(output_path.read_bytes()).hexdigest()
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return {
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"sessions": min(sessions_seen, n_sessions),
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"requests": requests_written,
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"input_length_mean": input_length_sum / max(1, requests_written),
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"input_length_min": int(min_in) if min_in != float("inf") else 0,
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"input_length_max": max_in,
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"output_length_mean": output_length_sum / max(1, requests_written),
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"output_md5": h,
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}
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def main() -> None:
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p = argparse.ArgumentParser(description=__doc__)
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p.add_argument(
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"--input",
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type=Path,
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default=Path("outputs/inferact_codex_swebenchpro.jsonl"),
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)
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p.add_argument("--output", type=Path, required=True)
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p.add_argument("--sessions", type=int, default=50)
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args = p.parse_args()
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args.output.parent.mkdir(parents=True, exist_ok=True)
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stats = slice_first_n_sessions(args.input, args.output, args.sessions)
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print(json.dumps(stats, indent=2), file=sys.stderr)
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if __name__ == "__main__":
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main()
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82
scripts/sweep_e1_naive_1p3d.sh
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scripts/sweep_e1_naive_1p3d.sh
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#!/usr/bin/env bash
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# E1 — naive 1P3D + kv-aware + RDMA, ts=1
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#
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# Tests hypothesis H1 from ONBOARDING_NEXT_AGENT_ZH §3.1: separate the
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# contribution of "1P3D topology + kv-aware policy" from "KVC layer
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# (admission / migration / direct-to-D)".
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#
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# Mechanism = pd-disaggregation (no KVC layer); policy = kv-aware.
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# Topology = 1P3D, RDMA on (mlx5_60 = cuda:0 NUMA-local).
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#
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# Prerequisites:
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# - source scripts/setup_env.sh (sets CUDA_HOME etc.)
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# - outputs/inferact_codex_swebenchpro.jsonl exists
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# (run scripts/convert_inferact_to_trace.py if not)
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#
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# Usage:
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# bash scripts/sweep_e1_naive_1p3d.sh
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#
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# Override defaults via env:
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# MODEL=/path TRACE=path OUTPUT=path IB_DEVICE=mlx5_XX bash scripts/sweep_e1_naive_1p3d.sh
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set -euo pipefail
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cd "$(dirname "$0")/.."
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if [ -z "${CUDA_HOME:-}" ]; then
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echo "ERROR: CUDA_HOME not set. Source scripts/setup_env.sh first." >&2
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exit 1
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fi
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MODEL=${MODEL:-/mnt/models/Qwen/Qwen3-30B-A3B-Instruct-2507}
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TRACE=${TRACE:-outputs/inferact_50sess.jsonl}
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OUTPUT=${OUTPUT:-outputs/e1_naive_1p3d_kvaware_rdma_50sess}
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IB_DEVICE=${IB_DEVICE:-mlx5_60}
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if [ ! -f "$TRACE" ]; then
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echo "ERROR: trace not found at $TRACE" >&2
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echo "Run: uv run --no-sync python scripts/convert_inferact_to_trace.py --output $TRACE" >&2
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exit 1
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fi
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mkdir -p "$OUTPUT"
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LOG="$OUTPUT/sweep.log"
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log() { echo "[$(date '+%Y-%m-%d %H:%M:%S')] $*" | tee -a "$LOG"; }
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log "=== E1: naive 1P3D kv-aware + RDMA, ts=1 ==="
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log "MODEL=$MODEL"
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log "TRACE=$TRACE ($(wc -l < $TRACE) requests)"
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log "OUTPUT=$OUTPUT"
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log "IB_DEVICE=$IB_DEVICE"
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label=e1_naive_1p3d_kvaware_run1
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log ""
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log "=== [E1] $label starting ==="
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uv run --no-sync python -m agentic_pd_hybrid.cli benchmark-live \
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--trace "$TRACE" \
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--output-root "$OUTPUT" \
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--mechanism pd-disaggregation \
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--policy kv-aware \
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--model-path "$MODEL" \
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--prefill-workers 1 --decode-workers 3 \
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--prefill-tp-size 1 --decode-tp-size 1 \
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--prefill-gpu-ids 0 --decode-gpu-ids 1,2,3 \
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--transfer-backend mooncake \
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--force-rdma --ib-device "$IB_DEVICE" \
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--gpu-budget 4 \
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--time-scale 1 \
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--session-sample-rate 1.0 \
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--target-duration-s 100000 \
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--concurrency-limit 32 \
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--timeout-s 1800 \
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--request-timeout-s 300 2>&1 | tee -a "$LOG"
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run_dir=$(ls -td "$OUTPUT"/pd-disaggregation-*/ 2>/dev/null | head -1)
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log "=== [E1] $label COMPLETED, artifacts at $run_dir ==="
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if [ -f "$run_dir/request-metrics.jsonl.summary.json" ]; then
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cp "$run_dir/request-metrics.jsonl.summary.json" "$OUTPUT/${label}_summary.json"
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cp "$run_dir/request-metrics.jsonl" "$OUTPUT/${label}_metrics.jsonl"
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log "=== summary saved to $OUTPUT/${label}_summary.json ==="
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fi
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