arXiv Computer Vision

Spatio-Temporal Parallelism for Diffusion Model Inference on Heterogeneous Multi-GPU Systems

arXiv Machine Learning

Jul 15

FlashDiff: Efficient Regional Execution and Scheduling for Diffusion Model Serving

arXiv:2607. 12121v1 Announce Type: cross Abstract: Diffusion models have become the central backbone for modern image, video, and audio generation, but their efficient service remains a challenge.

By Yaqi Qiao, Ping He, Songrun Xie, Ayush Barik, Chensong Zhang, Zhengzhong Tu, Fan Lai

diffusion efficiency

arXiv Machine Learning

Jun 19

TetriServe: Efficiently Serving Mixed DiT Workloads

arXiv:2510. 01565v4 Announce Type: replace Abstract: Diffusion Transformer (DiT) models excel at generating high-quality images through iterative denoising steps, but serving them under strict Service Level Objectives (SLOs) is challenging due to their high computational cost, particularly at larger resolutions.

By Runyu Lu, Shiqi He, Wenxuan Tan, Shenggui Li, Ruofan Wu, Jeff J. Ma, Ang Chen, Mosharaf Chowdhury

llms diffusion benchmarks

arXiv Machine Learning

Jul 10

Tessera: Unlocking Heterogeneous GPUs through Kernel-Granularity Disaggregation

arXiv:2604. 10180v2 Announce Type: replace-cross Abstract: Disaggregation maps parts of an AI workload to different types of GPUs, offering a path to utilize modern heterogeneous GPU clusters.

By Tiancheng Hu, Jin Qin, Zheng Wang, Junhao Hu, Yuzheng Wang, Lei Chen, Yizhou Shan, Mingxing Zhang, Ting Cao, Chunwei Xia, Huimin Cui, Tao Xie, Chenxi Wang

efficiency

arXiv Machine Learning

Jul 3

GF-DiT: Scheduling Parallelism for Diffusion Transformer Serving

arXiv:2606. 13501v2 Announce Type: replace-cross Abstract: Diffusion Transformers (DiTs) have become the dominant architecture for image and video generation, creating growing demand for efficient DiT serving.

By Xinwei Qiang, Yifan Hu, Shixuan Sun, Jing Yang, Han Zhao, Chen Chen, Yu Feng, Jingwen Leng, Minyi Guo

llms diffusion efficiency

arXiv Machine Learning

3d ago

Mira: Memory-Efficient MoE Inference Using Adaptive Caching and Predictive Expert Staging

arXiv:2609.38090v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models are a compelling architecture for scaling model capacity, making them especially attractive for deployment on resource-...

By Sanjali Yadav, Bahar Asgari

efficiency benchmarks

arXiv AI

Jul 28

MegaSlide-DiT: Memory-Centric Adaptation and Deformable Local Attention for Efficient Video Diffusion

arXiv:2607. 22696v1 Announce Type: cross Abstract: High-resolution video diffusion models built on Diffusion Transformers (DiTs) deliver strong fidelity but quickly exhaust the memory budget of a single workstation.

By Jiacheng Liu, Jason Liu

llms diffusion

arXiv Machine Learning

Aug 12

CARB: A Characterization-Guided Framework for CNN Inference Cost Prediction and Deployment Screening

arXiv:2608. 10506v1 Announce Type: cross Abstract: Accurate pre-deployment estimation of CNN inference cost--energy, latency, and peak memory--is increasingly critical as models are deployed on resource-constrained GPU platforms.

By Linh Nguyen, Zhixin Pan

arXiv AI

Jul 7

Data Driven Optimization of GPU efficiency for Distributed LLM-Adapter Serving

arXiv:2602. 24044v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) adapters enable low-cost model specialization, but introduce complex caching and scheduling challenges in distributed serving systems where hundreds of adapters must be hosted concurrently.

By Ferran Agullo, Joan Oliveras, Chen Wang, Alberto Gutierrez-Torre, Olivier Tardieu, Alaa Youssef, Jordi Torres, Josep Ll. Berral

llms efficiency benchmarks

arXiv Machine Learning

Aug 6

Deltoris: Enabling Real-time VLA Inference in Embodied AI via Bit-level Sparsity and Speculative Inference

arXiv:2608. 04428v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have emerged as a key component in embodied AI.

By Zheng Liu, Zeyu Guo, Zihan Liu, Anbang Wu, Han Zhao, Fangxin Liu, Zhezhi He, Yinhe Han, Jingwen Leng, Minyi Guo, Yiming Gan, Yu Feng

diffusion robotics efficiency multimodal

arXiv AI

Aug 3

Topology-Aware Data Movement for Disaggregated GPU Inference

arXiv:2607. 28633v1 Announce Type: cross Abstract: Disaggregated LLM inference creates a datacenter networking problem that no existing system solves correctly.

By Sanjeev Rao Ganjihal

llms efficiency

arXiv Machine Learning

Jul 28

Gleam: Adaptive Network-Efficient CUDA API Remoting for Cross-Device GPU Sharing over LANs

arXiv:2607. 23115v1 Announce Type: cross Abstract: This paper aims to enable computation- and communication-efficient GPU sharing across devices within local area networks (LANs), facilitating ubiquitous AI inference on heterogeneous personal devices.

By Zhihao Xu, Hao Zhong, Zeting Zhou, Yuhang Xu, Haoyu Tong, Wei Wang, Jinshan Chen, Keqiang He, Chong Zhu, Shengzhong Liu, Fan Wu, Guihai Chen

efficiency benchmarks

arXiv AI

Jul 28

X-Stage: An Overlooked Pipeline Stage for Communication-Computation Overlap in DiT Inference

arXiv:2607. 23264v1 Announce Type: cross Abstract: Fine-grained, device-initiated communication lets persistent GPU kernels in distributed diffusion transformer (DiT) inference issue remote stores and overlap data movement with Tensor Core computation.

By Jianwen Xian, Zhiyuan Xu, Yuchen Li, Ziliang Lai, Kang He, Zhen Huang, Aichen Feng, Jinyan Chen, Yilin Zhang, Qinqin Chen, Chengru Song

llms diffusion

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