TP=2 DP=4 with hybrid routing achieves TTFT p50=0.611s (-43% vs TP=1), the best TTFT across all tested configurations. But TPOT p90=0.109s (+51% vs TP=1) due to cross-GPU all-reduce in decode. Full comparison across 7 configurations shows two Pareto-optimal points: TP=1 DP=8 hybrid: best TPOT (0.072s), good TTFT (1.064s) TP=2 DP=4 hybrid: best TTFT (0.611s), acceptable TPOT (0.109s) The choice depends on SLO: TTFT-sensitive (interactive) -> TP=2 DP=4 TPOT-sensitive (streaming) -> TP=1 DP=8 All PD-Sep configurations are strictly dominated by one of these two. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
48 lines
1.9 KiB
Python
48 lines
1.9 KiB
Python
"""Final comparison across ALL tested configurations."""
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import json, csv, statistics, os
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def lat(path):
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rows = [json.loads(l) for l in open(path)]
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ok = [r for r in rows if not r.get("error")]
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ttfts = sorted([r["ttft_s"] for r in ok if r.get("ttft_s")])
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tpots = sorted([r["tpot_s"] for r in ok if r.get("tpot_s") and r["tpot_s"] > 0])
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lats = sorted([r["latency_s"] for r in ok])
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p = lambda v, q: v[min(int(q * len(v)), len(v) - 1)] if v else 0
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return len(ok), len(rows), p(ttfts,.5), p(ttfts,.9), p(tpots,.5), p(tpots,.9), p(lats,.5)
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def gpu(path):
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rows = list(csv.DictReader(open(path)))
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vals = [float(r["util_pct"]) for r in rows]
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return statistics.fmean(vals) if vals else 0
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print("COMPLETE CONFIGURATION COMPARISON")
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print("All use same 1000-req trace (200 req for GPU tests), 8xH20")
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print("=" * 85)
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fmt = "%-35s %6s %8s %8s %8s %8s %8s"
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print(fmt % ("Config", "OK/N", "TTFT50", "TTFT90", "TPOT50", "TPOT90", "E2E50"))
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print("-" * 85)
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configs = [
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("gpu_ab_combined", "TP=1 DP=8 old cache-aware"),
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("gpu_ab_hybrid", "TP=1 DP=8 hybrid routing"),
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("tp2dp4_hybrid", "TP=2 DP=4 hybrid routing *** NEW"),
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("gpu_ab_pdsep", "TP=1 PD-Sep 4P+4D"),
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("gpu_ab_6p2d", "TP=1 PD-Sep 6P+2D"),
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("adaptive_v2_baseline", "TP=1 kv_both baseline"),
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("adaptive_v2_offload", "TP=1 adaptive offload"),
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]
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for d, label in configs:
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mp = "outputs/%s/metrics.jsonl" % d
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if not os.path.exists(mp):
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continue
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ok, n, t50, t90, p50, p90, e50 = lat(mp)
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print(fmt % (label, "%d/%d" % (ok, n),
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"%.3f" % t50, "%.3f" % t90, "%.3f" % p50, "%.3f" % p90, "%.3f" % e50))
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print()
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print("KEY TRADEOFF: TP=1 vs TP=2")
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print(" TP=1 DP=8: Better TPOT (0.072), more instances for routing diversity")
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print(" TP=2 DP=4: Better TTFT (0.565), faster prefill, larger KV cache per inst")
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print(" Which is better depends on SLO: TTFT-sensitive -> TP=2, TPOT-sensitive -> TP=1")
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