[diffusion][doc]: add ring sp performance benchmark page (#20998)
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
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@@ -30,6 +30,12 @@ cache/index
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profiling
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```
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## Current Baseline Snapshot
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For Ring SP benchmark details, see:
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- [Ring SP Performance](ring_sp_performance.md)
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## References
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- [Cache-DiT Repository](https://github.com/vipshop/cache-dit)
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@@ -0,0 +1,67 @@
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# Ring SP Benchmark: Wan2.2-TI2V-5B (u1r2 vs Baseline)
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This page reports Ring-SP performance for `Wan2.2-TI2V-5B-Diffusers` using:
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- Parallel config: `sp=2, ulysses=1, ring=2` (short: `u1r2`)
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- Baseline config: `sp=1, ulysses=1, ring=1` (short: `u1r1`)
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## Benchmark Setup
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- Model: `Wan2.2-TI2V-5B-Diffusers`
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- GPU: `48G RTX40 series * 2`
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## Online Serving
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### Ring SP (`u1r2`)
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```bash
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sglang serve \
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--model-type diffusion \
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--model-path /model/HuggingFace/Wan-AI/Wan2.2-TI2V-5B-Diffusers \
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--num-gpus 2 --sp-degree 2 --ulysses-degree 1 --ring-degree 2 \
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--port 8898
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```
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### Baseline (`u1r1`)
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```bash
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sglang serve \
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--model-type diffusion \
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--model-path /model/HuggingFace/Wan-AI/Wan2.2-TI2V-5B-Diffusers \
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--num-gpus 1 --sp-degree 1 --ulysses-degree 1 --ring-degree 1 \
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--port 8898
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```
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## Benchmarks
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### Benchmark Disclaimer
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These benchmarks are provided for reference under one specific setup and command configuration. Actual performance may vary with model settings, runtime environment, and request patterns.
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### Stage Time Breakdown
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| Stage / Metric | `u1r2` (s) | `u1r1` baseline (s) | Speedup |
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|---|---:|---:|---:|
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| InputValidation | 0.1060 | 0.1029 | 0.97x |
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| TextEncoding | 1.3965 | 2.2261 | 1.59x |
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| LatentPreparation | 0.0002 | 0.0002 | 1.00x |
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| TimestepPreparation | 0.0003 | 0.0004 | 1.33x |
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| Denoising | 52.6358 | 71.6785 | 1.36x |
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| Decoding | 7.6708 | 13.4314 | 1.75x |
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| **Total** | **63.74** | **90.63** | **1.42x** |
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### Memory Usage
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| Memory Metric | `u1r2` (GB) | `u1r1` baseline (GB) | Delta |
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|---|---:|---:|---:|
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| Peak GPU Memory | 20.07 | 27.40 | -7.33 |
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| Peak Allocated | 13.35 | 20.40 | -7.05 |
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| Memory Overhead | 6.72 | 7.00 | -0.28 |
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| Overhead Ratio | 33.5% | 25.6% | +7.9pp |
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## Summary
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- End-to-end latency improves from `90.63s` to `63.74s` (`1.42x`).
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- Main gains come from `Denoising` (`1.36x`) and `Decoding` (`1.75x`).
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- Absolute memory usage drops noticeably on Ring-SP (`Peak GPU Memory -7.33GB`, `Peak Allocated -7.05GB`).
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- Overhead ratio rises (`+7.9pp`), so future tuning can focus on reducing communication/runtime overhead while preserving the latency gain.
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@@ -86,6 +86,8 @@ Its core features include:
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diffusion/compatibility_matrix
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diffusion/api/cli
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diffusion/api/openai_api
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diffusion/performance/index
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diffusion/performance/ring_sp_performance
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diffusion/performance/attention_backends
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diffusion/performance/cache/index
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diffusion/quantization
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