Ascend NPU Ring-SP Performance (Wan2.1-T2V-1.3B)

This page reports Ring-SP performance on Ascend NPU with torch_npu==2.10.0.

Baseline config: ulysses=1, ring=1 (short: u1r1)
Ring-SP config: ulysses=1, ring=2 (short: u1r2)

Benchmark Setup

Model: Wan2.1-T2V-1.3B-Diffusers
Prompt: "a cat is playing piano"
Framework command: sglang generate
Runtime: torch_npu==2.10.0

Generate Commands

Baseline (`u1r1`)

sglang generate --model-path /nas/disk1/Wan2.1-T2V-1.3B-Diffusers \
    --prompt "a cat is playing piano" --num-gpus 1 --ring-degree 1 \
    --save-output

Ring-SP (`u1r2`)

sglang generate --model-path /nas/disk1/Wan2.1-T2V-1.3B-Diffusers \
    --prompt "a cat is playing piano" --num-gpus 2 --ring-degree 2 \
    --save-output

Benchmarks

Benchmark Disclaimer

These numbers are from one fixed setup and one prompt case. Actual performance may vary by model settings, environment, and workload.

Stage Time Breakdown

Stage / Metric	`u1r2` (s)	`u1r1` baseline (s)	Speedup
InputValidation	0.0003	0.0002	0.67x
TextEncoding	3.5936	3.5820	1.00x
LatentPreparation	0.0007	0.0055	7.86x
TimestepPreparation	0.0008	0.0007	0.88x
Denoising	121.2788	239.2580	1.97x
Decoding	13.8685	16.4969	1.19x
Total (Pixel data generated)	141.86	266.50	1.88x

Summary

With torch_npu==2.10.0, Ring-SP (u1r2) runs successfully on NPU for this case.
End-to-end generation time improves from 266.50s to 141.86s (1.88x).
The main gain comes from DenoisingStage (1.97x), while decoding also improves (1.19x).

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