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Combining Teacache with xDiT to Accelerate Visual Generation Models

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MingXiangL/Teacache-xDiT

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TeaCache+xDiT

This repository implements multi-GPU parallelization of TeaCache within the xDiT framework. The supported models include:

Please run the appropriate script (run_[your_model].sh) to get started.

Note: All following experiments are conducted on the A800

Performance on CogVideoX

Model Method 1x 2x 4x 8x
CogvideoX Ulysses 133.5 77.7 59.41 36.68
Ours(slow) 103.3 60.9 46.8 29.6
Ours(fast) 78 46.7 36.5 23.7

Performance on HunyuanVideo

Model Method 1x 2x 4x 8x
HunyuanVideo Ulysses 3086.5 1624.4 856.6 480.4
Ours(slow) 1884.5 1001 540.8 312.9
Ours(fast) 1395.2 753.9 418.4 254.1

Performance on Flux

Model Method 1x 2x 4x 8x
Flux Ulysses 12.9 7.91 4.4 3.61
Ours(slow) 12.1 4.61 2.68 2.24
Ours(fast) 7.9 2.45 1.53 1.3

Performance on ConsistID

Model Method 1x 2x 3x 6x
ConsistID Ulysses 218.64 123.84 88.6 54.09
Ours(slow)-0.1 142.18 81.39 60.71 39.77
Ours(fast)-0.2 90.34 53.82 41.34 27.18

Acknowledgement

This respotory is built based on TeaCache and xDiT, thanks for their contributors!

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Combining Teacache with xDiT to Accelerate Visual Generation Models

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