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Update benchmark results for SGLang with tiered prefix cache (llm-d#1921)
Signed-off-by: Rahul Gurnani <rahulgurnani@google.com>
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guides/tiered-prefix-cache/README.md

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Empirical benchmark reports demonstrating the impact of multi-tier prefix-cache offloading relative to HBM-only serving configurations under high-cache workloads:
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- **[Qwen/Qwen3-32B on vLLM (16×H100 CPU Offload)](./benchmark-results/vllm-qwen3-32b-h100.md)**: Headline throughput and latency comparisons across 16×H100 GPUs with CPU RAM offloading.
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- **[Qwen/Qwen3-32B on SGLang (16×H100 CPU Offload)](./benchmark-results/sglang-qwen3-32b-h100.md)**: Headline throughput and latency comparisons across 16×H100 GPUs with SGLang HiCache CPU RAM offloading.
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- **[openai/gpt-oss-120b on vLLM (16×H100 CPU Offload)](./benchmark-results/vllm-gpt-oss-120b-h100.md)**: Stage-by-stage throughput, latency, TPOT, and fleet cache hit rate breakdowns across 5–40 QPS.
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- **[Qwen/Qwen3-32B on vLLM (TPU v6e/v7 CPU Offload)](./benchmark-results/vllm-qwen3-32b-tpuv7.md)**: Headline throughput and latency effect of CPU RAM prefix offloading on Google TPU architectures.
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- **[Qwen/Qwen3-32B on vLLM (16×H100 Lustre Offload)](./benchmark-results/vllm-qwen3-32b-h100-lustre.md)**: Benchmark comparisons for shared POSIX filesystem offloading using LMCache and llm-d filesystem connectors.
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# Qwen/Qwen3-32B SGLang CPU Offloading Benchmark (16×H100)
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The benchmark runs on 16 × H100 GPUs, distributed across 8 model servers (2 H100s per server with TP=2) using Qwen3-32B and SGLang v0.5.13.post1.
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All results show the effect of enabling SGLang HiCache prefix-cache offloading (`--hicache-size 200`) relative to an HBM-only configuration, under a high-cache scenario where the working set exceeds HBM but fits within HBM + CPU RAM.
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* **Workload**: 250 prefix groups, 5 prompts per group, system prompt length of 16,000 tokens, question length of 256 tokens, output length of 256 tokens.
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* **GPU Cache Size (Total)**: 321,856 tokens per replica (includes ~78.6 GiB of the 160 GiB of total GPU memory across 2 H100 GPUs per replica).
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* **CPU Cache Size (Total)**: 819,200 tokens per replica (200 GiB / replica host RAM).
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* **Workload Unique Cache (Working Set)**: 4,640,000 tokens (~760 GB / 708 GiB).
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| Target Rate | Configuration | Mean TTFT (s) | P90 TTFT (s) | Mean E2E Latency (s) | P90 E2E Latency (s) | Throughput (tok/s) |
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| :---: | :--- | :---: | :---: | :---: | :---: | :---: |
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| **5.0 QPS** | HBM-only | 2.12 | 4.35 | 9.54 | 13.67 | 68,517.5 |
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| | HBM + CPU RAM | 0.95 (-55.2%) | 1.39 (-68.0%) | 10.26 (+7.5%) | 18.55 (+35.7%) | 73,860.3 (+7.8%) |
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| **10.0 QPS** | HBM-only | 9.76 | 19.66 | 25.62 | 34.78 | 111,155.9 |
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| | HBM + CPU RAM | 0.43 (-95.6%) | 1.27 (-93.5%) | 7.74 (-69.8%) | 11.08 (-68.1%) | 152,045.3 (+36.8%) |
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| **20.0 QPS** | HBM-only | 40.55 | 76.70 | 53.77 | 87.84 | 117,451.7 |
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| | HBM + CPU RAM | 1.56 (-96.2%) | 3.99 (-94.8%) | 9.61 (-82.1%) | 12.21 (-86.1%) | 280,447.9 (+138.8%) |
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| **40.0 QPS** | HBM-only | 107.88 | 185.77 | 121.07 | 199.02 | 115,459.0 |
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| | HBM + CPU RAM | 25.56 (-76.3%) | 47.25 (-74.6%) | 33.61 (-72.2%) | 54.66 (-72.5%) | 308,779.8 (+167.4%) |

guides/tiered-prefix-cache/modelserver/gpu/sglang/native/cpu/base/patch-sglang.yaml

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# tokenProcessorConfig.blockSize (default 64); SGLang's knob is
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# --page-size, where vLLM uses --block-size.
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- "--page-size=64"
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- "--mem-fraction-static=0.9"
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- "--enable-metrics"
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- "--enable-hierarchical-cache"
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- "--hicache-write-policy"

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