works on

From the 1 of 31 linked papers with an AI index.

activity
20242026
collaborators

31 papers

cs.AR2026

A Thread-Register Decoupled GPU Execution Model for Efficient Tensor Computation

Zihan Liu, Jingwen Leng, Yangjie Zhou +12

Modern GPUs increasingly integrate Tensor Cores into the execution pipeline. Although aggregate tensor throughput continues to grow, aided by an operand supply that has evolved fro…

cs.AR2026

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

Zheng Liu, Zeyu Guo, Zihan Liu +9

Vision-language-action (VLA) models have emerged as a key component in embodied AI. Among existing approaches, diffusion-based VLA models achieve superior motion quality and genera…

cs.AR2026

DSTAR: Accelerating Diffusion Transformers via Spatial and Temporal Redundancy Reduction

Chi Zhang, Jieru Zhao, Yu Feng +3

Diffusion Transformers (DiTs) have been widely used in many tasks, including image synthesis, video generation, and content editing. However, their multi-iteration inference proces…

cs.AR2026

Kaleido: Algorithm-Hardware Co-Design for Video Diffusion Transformers by Exploiting Latent Space Correlations

Wenxuan Miao, Haosong Liu, Weiming Hu +9

Kaleido introduces a hardware‑software co‑design that speeds up video diffusion transformers by reusing channel‑wise spatiotemporal information in the latent space, achieving large…

cs.DC2026

GF-DiT: Scheduling Parallelism for Diffusion Transformer Serving

Xinwei Qiang, Yifan Hu, Shixuan Sun +6

Diffusion Transformers (DiTs) have become the dominant architecture for image and video generation, creating growing demand for efficient DiT serving. Existing systems assign each…

cs.AR2026

MoE-Hub: Taming Software Complexity for Seamless MoE Overlap with Hardware-Accelerated Communication on Multi-GPU Systems

Zhuoshan Zhou, Chen Zhang, Shuyi Zhang +10

The Mixture-of-Experts (MoE) architecture is crucial for scaling large language models, but its scalability is severely limited by inter-GPU communication bottlenecks in multi-GPU…