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Found 4 papers, 3 papers with code
Unveiling Redundancy in Diffusion Transformers (DiTs): A Systematic Study
Our experimental analysis reveals substantial variations in the distribution of redundancy across diffusion steps among different DiT models.
xDiT: an Inference Engine for Diffusion Transformers (DiTs) with Massive Parallelism
Parallel inference is essential for real-time DiTs deployments, but relying on a single parallel method is impractical due to poor scalability at large scales.
MAC Revivo: Artificial Intelligence Paves the Way
The vast adoption of Wi-Fi and/or Bluetooth capabilities in Internet of Things (IoT) devices, along with the rapid growth of deployed smart devices, has caused significant interference and congestion in the industrial, scientific, and medical (ISM) bands.
PipeFusion: Patch-level Pipeline Parallelism for Diffusion Transformers Inference
This paper presents PipeFusion, an innovative parallel methodology to tackle the high latency issues associated with generating high-resolution images using diffusion transformers (DiTs) models.
