GF-DiT: Scheduling Parallelism for Diffusion Transformer Serving
Diffusion Transformers (DiTs) have become the dominant architecture for image and video generation, creating growing demand for efficient DiT serving. Existing systems assign each request a fixed parallel configuration throughout its lifetime. However, DiT workloads exhibit substantial heterogeneity across requests, execution stages, and system conditions, making static parallelism inefficient and often leading to poor GPU utilization and degraded service quality. This paper argues that DiT serving should treat GPU parallelism as a first-class schedulable resource. We present GF-DiT, a policy-programmable runtime for elastic DiT serving that dynamically adapts the parallelism of running r...
| Authors | Xinwei Qiang, Yifan Hu, Shixuan Sun et al. |
|---|---|
| Primary category | cs.DC |
| Published | 11 June 2026 |
| Last updated at source | 2 July 2026 |
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