# Frontier vs vLLM H20 Alignment Summary Date: 2026-06-25 This document summarizes the current ReplayServe comparison between Frontier simulation and real vLLM runs on H20 for Qwen3-30B-A3B. It covers TP=1/2/4, different timestamp scales, and 100/200/500-request windows from `qwen_coder_blksz_16.jsonl`. The source data and plots are generated by: ```bash ~/.venv/plot/bin/python tools/build_frontier_vllm_alignment_report.py ``` Generated artifacts: - `docs/assets/frontier_vllm_alignment/frontier_vllm_alignment.csv` - `docs/assets/frontier_vllm_alignment/frontier_vllm_alignment.json` - `docs/assets/frontier_vllm_alignment/throughput_ratio.png` - `docs/assets/frontier_vllm_alignment/latency_ratios.png` - `docs/assets/frontier_vllm_alignment/tp_scaling_total_tps.png` - `docs/assets/frontier_vllm_alignment/completion_prefix.png` ## Bottom Line Functional replay is now usable for the clean 200-request runs: - TP1 scale 2/3 after the Frontier lifecycle fix: `200/200` completed. - TP2/TP4 scale 2/3: `200/200` completed, no preemption on either side, matched vLLM KV block counts, and exact trace-side prefix reuse ratio. Performance is not fully calibrated: - TP1 scale 2/3 is the closest current operating point: Frontier throughput is about `0.74x` vLLM and TPOT p50/p95 is close. - TP2/TP4 is functionally aligned but slower: Frontier throughput is only `0.55-0.63x` vLLM, and TP4 TPOT is too pessimistic. - Frontier underestimates the TP2->TP4 speedup. vLLM improves total throughput by `1.15-1.20x`; Frontier improves by only `1.07-1.10x`. Current use: acceptable for integration work and rough qualitative trends, not yet acceptable as a calibrated absolute performance predictor. ## Run Matrix All vLLM runs use vLLM 0.11.1, H20, Qwen3-30B-A3B, `max_model_len=32768`, `max_num_seqs=64`, `max_num_batched_tokens=32768`, `gpu_memory_utilization=0.85`, prefix caching, and chunked prefill. | run | Frontier rows | preempt F/V | prefix hit F/V | total tok/s F/V | ratio | TPOT p50 F/V | E2E p95 F/V | |---|---:|---:|---:|---:|---:|---:|---:| | TP1 N100 raw | 96/100 | 0/8 | 0.249/0.251 | 2349/3832 | 0.61 | 0.0569/0.0661s | 119.6/97.4s | | TP1 N500 raw | 439/500 | 0/63 | 0.119/0.387 | 4734/5283 | 0.90 | 0.0564/0.0498s | 397.3/417.4s | | TP1 N200 scale 0.667 | 176/200 | 0/26 | 0.170/0.270 | 3913/4865 | 0.80 | 0.0584/0.0515s | 189.2/183.7s | | TP1 N200 scale 2 | 200/200 | 33/43 | 0.231/0.270 | 3506/4743 | 0.74 | 0.0542/0.0497s | 174.5/142.3s | | TP1 N200 scale 3 | 200/200 | 20/16 | 0.218/0.270 | 3390/4608 | 0.74 | 0.0534/0.0462s | 154.5/122.8s | | TP2 N200 scale 2 | 200/200 | 0/0 | 0.270/0.270 | 4581/7547 | 0.61 | 0.0430/0.0300s | 106.8/72.5s | | TP2 N200 scale 3 | 200/200 | 0/0 | 0.270/0.270 | 4062/6426 | 0.63 | 0.0394/0.0191s | 101.6/54.0s | | TP4 N200 scale 2 | 200/200 | 0/0 | 0.270/0.270 | 5035/9073 | 0.55 | 0.0337/0.0163s | 84.9/43.6s | | TP4 N200 scale 3 | 200/200 | 0/0 | 0.270/0.270 | 4355/7403 | 0.59 | 0.0311/0.0094s | 83.0/27.9s | Important prefix caveat: the vLLM prefix-hit column in this table is the trace-side synthetic estimate from the vLLM summaries. For TP1 runs with preemption and finite KV pressure, the observed vLLM scheduler `computed:` signal is the better comparator. Earlier analysis in `docs/rs4_frontier_h20_tp1_alignment.md` records those finite-cache comparisons. For TP2/TP4, no preemption occurs and the trace-side prefix ratio matches Frontier exactly. ## Plots ![Throughput ratio](assets/frontier_vllm_alignment/throughput_ratio.png) ![Latency ratios](assets/frontier_vllm_alignment/latency_ratios.png) ![TP scaling](assets/frontier_vllm_alignment/tp_scaling_total_tps.png) ![Completion and prefix reuse](assets/frontier_vllm_alignment/completion_prefix.png) ## Interpretation ### TP1 The early TP1 100/500/scale-0.667 runs are still useful as historical stress points, but they were run before the decode-preemption lifecycle fix. Frontier therefore missed rows in those runs: - `96/100` for N100 raw - `439/500` for N500 raw - `176/200` for N200 scale 0.667 After the lifecycle fix, TP1 scale 2 and scale 3 both complete `200/200`. Preemption is now in the same order as vLLM: - scale 2: Frontier 33 vs vLLM 43 - scale 3: Frontier 20 vs vLLM 16 TP1 timing is the closest current calibrated region. Throughput is about `0.74x` vLLM, TPOT p50/p95 is close, and E2E p95 is about `1.23-1.26x` vLLM. This is not perfect, but it is usable for integration-level trend checks. ### TP2 and TP4 The TP2/TP4 runs are functionally cleaner than TP1: - `200/200` completed for all four runs. - Frontier and vLLM both report no preemption. - Frontier uses explicit vLLM KV capacities: - TP2: 69,055 blocks - TP4: 177,077 blocks - Prefix hit ratio matches exactly: `0.2697549478`. We did profile TP2/TP4 true-mixed attention. The active RS12 profile includes: - `attention_tp2_tp4_combined.csv`: 36,163 rows, including 1,260 true-mixed prefill+decode rows for TP2/TP4. - `linear_op_tp2_tp4_full32k.csv`: covers up to 32,768 tokens. - `moe_tp2_tp4_full32k.csv`: covers up to 32,768 tokens. Without the true-mixed rows, Frontier fails with missing `attn_decode_in_mixed` predictions. With them, all RS12 runs complete. The remaining TP2/TP4 gap is therefore not a missing-profile blocker. It is a timing-model gap: - TP2 throughput is `0.61-0.63x` vLLM. - TP4 throughput is `0.55-0.59x` vLLM. - TP4 TPOT p50 is `2.06-3.30x` vLLM. ## Scaling For the same first-200 request fixtures: | fixture | metric | Frontier TP4/TP2 | vLLM TP4/TP2 | |---|---|---:|---:| | scale 2 | total tok/s | 1.10 | 1.20 | | scale 2 | decode tok/s | 1.10 | 1.20 | | scale 2 | TPOT p50 | 0.78 | 0.54 | | scale 3 | total tok/s | 1.07 | 1.15 | | scale 3 | decode tok/s | 1.07 | 1.15 | | scale 3 | TPOT p50 | 0.79 | 0.49 | Frontier sees some TP4 improvement, but much less than real vLLM. This is the clearest current evidence that the simulator is not yet modeling vLLM's TP-dependent decode execution path well enough. ## Likely Gap Sources The main unresolved issues are: - CPU/scheduler overhead is still skipped (`skip_cpu_overhead_modeling=true`). - Decode CUDA graph behavior is not modeled in the current Frontier runs (`decode_cuda_graph_mode=none`). - Random-forest predictors interpolate over profile grids, while real online mixed batches may concentrate on shapes not directly sampled. - Some TP4 predictor fit errors are nontrivial, for example `attn_kv_cache_save` MAPE around 11% in the TP4 profile log. - Frontier's scheduler and preemption behavior is close but not identical for TP1 under finite KV pressure. ## ReplayServe TODO 1. Rerun the 500-request TP1 stress after the decode-preemption lifecycle fix, so the 500-row result is no longer mixed with the old incomplete behavior. 2. Record vLLM observed scheduler prefix/preemption metrics in machine-readable summaries, not only in docs, especially first-start and last-start `computed:` ratios. 3. Add a shape-ledger analysis: compare Frontier's actual online batch shapes against the profile grid and identify hot shapes that are interpolated. 4. Profile or import vLLM CPU overhead and test `skip_cpu_overhead_modeling=false`. 5. Collect kernel-only / decode-CUDA-graph timing profiles before enabling a Frontier CUDA-graph decode mode. 6. Calibrate TP2/TP4 timing only after the above, because current functional replay is aligned but the TP scaling is not.