TCC calibrates cached representations in diffusion sampling via an offline iterative procedure that accounts for trajectory shifts, improving FID from 29.83 to 27.35 on PixArt-alpha while preserving reuse policies.
Huanpeng Chu, Wei Wu, Guanyu Fen, and Yutao Zhang
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DiSC accelerates DiT and PixArt-Sigma diffusion models 3.47-4.74x over A100 GPUs by reusing cached tokens across denoising steps and reusing sparsity masks in attention, using hash-based bank distribution to run sparse workloads on standard compute units.
citing papers explorer
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Trajectory-Consistent Calibration for Cache-Accelerated Diffusion Models
TCC calibrates cached representations in diffusion sampling via an offline iterative procedure that accounts for trajectory shifts, improving FID from 29.83 to 27.35 on PixArt-alpha while preserving reuse policies.
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DiSC: Resolution-Scalable Acceleration of Diffusion Models by Exploiting Sparsity and Cached Token Reuse with Hash-based Distribution
DiSC accelerates DiT and PixArt-Sigma diffusion models 3.47-4.74x over A100 GPUs by reusing cached tokens across denoising steps and reusing sparsity masks in attention, using hash-based bank distribution to run sparse workloads on standard compute units.