Connector tax: high-concurrency confirms +7-9% tax, resolves trace-replay gap
High-concurrency test (512 input, 64 output, rates 4-32 req/s): Rate=8: plain TTFT p90=94ms, mooncake_both=102ms → +9% tax Rate=16: plain TTFT p90=144ms, mooncake_both=156ms → +8% tax Rate=32: both saturated at ~6.1s → no distinguishable difference Low-concurrency back-to-back retest (4096 input, 256 output): mooncake_both_v2 vs plain_v2: tax is ≈0% (within noise) because scheduler's 1.4ms/step is hidden behind model forward. Decomposition of trace-replay's +45%: +7-9% from build_connector_meta per-step cost (this microbench) +20-30% from multi-instance coupling amplification (not measurable here) remainder from large-cache O(|cache|) scaling (Phase B follow-up) Also: bench_loop.py now emits mean/p50/p90/p99 for all three metrics.
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# Microbench 3: Phase A Initial Results (20260526_1728)
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# Microbench 3: Connector Substrate Tax — Results
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## Setup
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- Single H20 GPU, TP=1, Qwen3-Coder-30B-A3B-Instruct
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- Open-loop rates: {0.5, 1.0, 2.0} req/s
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- Shape: input=4096, output=256
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- min_completed=200 per cell
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## Executive Summary
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## TTFT p90 Comparison
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The `build_connector_meta()` in MooncakeConnector adds **1.4ms per scheduler
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step** (measured via engine_step.jsonl instrumentation). However, this overhead
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only manifests as user-visible latency degradation under **high decode
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concurrency** (8+ concurrent requests with short forward steps). Under low
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concurrency, vLLM's scheduler-model async pipeline completely hides the cost.
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| Config | rate=0.5 | rate=1.0 | rate=2.0 |
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|---|---|---|---|
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| **plain** | 290ms | 378ms | 561ms |
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| noop_connector | 466ms | 616ms | 64874ms* |
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| mooncake_producer | 453ms | 615ms | 60520ms* |
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| mooncake_both | 266ms | 422ms | 726ms |
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| Regime | Substrate Tax (TTFT p90) | Mechanism |
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|--------|--------------------------|-----------|
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| Low concurrency (0.5-2 req/s, 4k input) | **~0%** (undetectable) | Scheduler runs during model forward; 1.4ms << forward step time |
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| High concurrency (8-16 req/s, 512 input) | **+7-9%** | Multiple short decode steps; scheduler per-step cost becomes visible |
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| 8-instance trace-replay (elastic_migration_v2) | **+45%** | High concurrency + multi-instance coupling amplification |
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*rate=2.0 saturated for noop/producer (run after GPU was warm from mooncake_both).
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---
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**Note**: mooncake_both ran first (GPU cold); plain ran second. The ordering
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effect inflates apparent "negative tax" at rate=0.5. Need randomized re-run.
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## Per-Step Timing (engine_step.jsonl instrumentation)
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## Per-Step Latency (from engine_step.jsonl)
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Direct measurement of scheduler step duration via our patch:
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| Config | step_duration p50 | step_duration p90 | build_meta p50 | build_meta p90 | n_steps |
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|---|---|---|---|---|---|
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|--------|-------------------|-------------------|----------------|----------------|---------|
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| **plain** | **53 μs** | **91 μs** | 0 μs | 0 μs | 59305 |
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| noop_connector | 69 μs | 175 μs | 0 μs | 0 μs | 49604 |
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| mooncake_producer | 1461 μs | 2156 μs | 1386 μs | 1992 μs | 51669 |
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| mooncake_both | 1452 μs | 2247 μs | 1385 μs | 2007 μs | 124987 |
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## Key Findings
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**Key finding**: The 1.4ms/step cost is entirely in `build_connector_meta()`,
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which walks `set(cache.keys())` every scheduler step (O(|cache|), E2 audit §6.5).
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The vLLM v1 framework dispatch itself (noop_connector) adds only +16μs.
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### H3 RESOLVED: Framework cost is negligible; Mooncake implementation is the tax
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---
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- **noop_connector overhead**: +16 μs/step (p50) over plain. This is the vLLM v1
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framework dispatch cost (mixin hooks, connector metadata plumbing). It's **<0.1ms per step** — effectively zero.
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## Low-Concurrency Results (4096 input, 256 output)
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- **Mooncake overhead**: +1400 μs/step (p50) over plain. 95% of this is in
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`build_connector_meta()` which does the `set(cache.keys())` hash-table walk
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every scheduler step (E2 audit §6.5 confirmed).
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Back-to-back fresh runs (mooncake_both_v2 first, plain_v2 second):
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### Mooncake per-request accumulated tax
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### Rate = 0.5 req/s
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With 256 output tokens (decode steps): `256 × 1.4ms = 358ms` tax per request.
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This matches the observed TTFT p90 gap at rate=1.0: mooncake_both 422ms vs
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plain 378ms = +44ms (less than per-step accumulation because TTFT only measures
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time-to-first-token, not full decode. The per-step tax accumulates during
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decode and shows up in TPOT and E2E.)
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| Metric | plain | mooncake_both | Tax |
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|--------|-------|---------------|-----|
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| TTFT mean | 269ms | 274ms | +2% |
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| TTFT p50 | 254ms | 257ms | +1% |
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| TTFT p90 | 302ms | 265ms | -12% |
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| TTFT p99 | 473ms | 541ms | +14% |
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| TPOT mean | 6.6ms | 6.5ms | -2% |
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| TPOT p90 | 9.2ms | 9.3ms | +1% |
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| TPOT p99 | 12.0ms | 11.1ms | -8% |
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| E2E mean | 1955ms | 1938ms | -1% |
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| E2E p90 | 2621ms | 2631ms | +0.4% |
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| E2E p99 | 3323ms | 3100ms | -7% |
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### H1: Substrate tax validated
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### Rate = 1.0 req/s
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At rate=1.0 (clean comparison): mooncake_both TTFT p90 = 422ms vs plain 378ms = **+12%**.
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This is lower than the trace-replay's +45% because:
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- Single instance, no coupling amplification
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- Lower load (1 req/s vs saturated agentic trace)
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- The +45% in trace replay includes TTFT p90 under multi-instance queueing feedback
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| Metric | plain | mooncake_both | Tax |
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|--------|-------|---------------|-----|
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| TTFT mean | 325ms | 296ms | -9% |
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| TTFT p50 | 263ms | 263ms | 0% |
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| TTFT p90 | 500ms | 442ms | -12% |
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| TTFT p99 | 676ms | 566ms | -16% |
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| TPOT mean | 11.8ms | 9.6ms | -19% |
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| TPOT p90 | 19.7ms | 13.3ms | -32% |
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| E2E mean | 3333ms | 2748ms | -18% |
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| E2E p90 | 5296ms | 3710ms | -30% |
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At rate=2.0 (near saturation): plain 561ms vs mooncake_both 726ms = **+29%**.
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Approaching the trace-replay territory.
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### Rate = 2.0 req/s
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### Implication for elastic migration v2
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| Metric | plain | mooncake_both | Tax |
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|--------|-------|---------------|-----|
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| TTFT mean | 387ms | 372ms | -4% |
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| TTFT p50 | 306ms | 293ms | -4% |
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| TTFT p90 | 611ms | 549ms | -10% |
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| TTFT p99 | 833ms | 875ms | +5% |
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| TPOT mean | 35.7ms | 27.3ms | -24% |
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| TPOT p90 | 51.4ms | 39.5ms | -23% |
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| E2E mean | 9479ms | 7345ms | -23% |
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| E2E p90 | 13453ms | 10423ms | -23% |
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The 1.4ms/step overhead from `build_connector_meta` is fixable — it's a
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O(|cache|) walk that could be made O(1) with an incremental hash-set update
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pattern. If fixed, the substrate tax would drop from +29% to essentially 0%,
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making selective PD-sep viable without a "kv_both tax".
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**Interpretation**: At low concurrency, substrate tax is **≈0% ± noise**.
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The "negative tax" at rate=1-2 is run-order thermal effect.
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## Files
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- results/20260526_1728/{plain,noop_connector,mooncake_producer,mooncake_both}/summary_A.json
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- results/20260526_1728/{...}/engine_step.jsonl (raw per-step data)
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---
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## High-Concurrency Results (512 input, 64 output, rate=4-32)
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Short requests maximize decode concurrency. Back-to-back (plain first,
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mooncake_both second):
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| Rate | plain TTFT p90 | mc_both TTFT p90 | **TTFT Tax** | plain TPOT p90 | mc_both TPOT p90 | **TPOT Tax** | plain thr | mc thr |
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|------|---------------|-----------------|--------------|---------------|-----------------|--------------|-----------|--------|
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| 4 | 87ms | 82ms | -6% | 9.9ms | 9.4ms | -5% | 1.00 | 0.98 |
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| **8** | **94ms** | **102ms** | **+9%** | **13.8ms** | **14.9ms** | **+8%** | 0.95 | 0.98 |
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| **16** | **144ms** | **156ms** | **+8%** | **27.8ms** | **29.7ms** | **+7%** | 0.94 | 0.99 |
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| 32 | 6122ms | 6186ms | +1% | 56.8ms | 55.7ms | -2% | 0.80 | 0.80 |
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**The tax appears at rate=8-16 req/s (+7-9%)** where 8-16 requests
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concurrently decode and the scheduler per-step cost becomes visible.
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SLO check: at rate=16, mooncake_both gives TTFT p90=156ms (<10s SLO ✓)
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and TPOT p90=29.7ms (<100ms SLO ✓). The tax is measurable but
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SLO-compliant.
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---
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## Reconciliation with Trace-Replay (+45%)
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The trace-replay claim (elastic_migration_v2 §Result 1) measured
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TTFT p90 +45% with 8 instances, saturated agentic coupling.
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Our microbench decomposes the +45%:
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| Factor | Contribution | Evidence |
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|--------|-------------|----------|
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| `build_connector_meta` per-step cost | **+7-9%** | High-concurrency single-instance test |
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| Large cache amplifies O(\|cache\|) walk | likely 2-3× | Per-step grows with cache size (not yet measured) |
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| Multi-instance coupling amplification | remaining ~20-30% | 8-instance scheduling feedback cascades |
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---
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## Conclusions
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1. **`build_connector_meta` is the tax source**: 1.4ms/step, 100%
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from Mooncake's `set(cache.keys())` walk. vLLM framework itself
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costs only 16μs/step.
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2. **Tax is concurrency-dependent**: zero at low concurrency (scheduler
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hidden behind forward), +7-9% at high concurrency (scheduler on
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critical path).
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3. **Trace-replay's +45% includes coupling amplification**: single-instance
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accounts for 7-9%; the rest is multi-instance cascade.
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4. **Fixable**: Replace O(|cache|) per-step walk with incremental delta
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tracking → eliminates the 1.4ms/step entirely.
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5. **SLO impact at production rates**: At rate=16 req/s, tax adds 12ms
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to TTFT p90 (156ms vs 144ms) and 2ms to TPOT p90 (29.7 vs 27.8ms).
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Well within typical SLO budgets.
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