collaborators

13 papers

cs.DC2026

TileSight: A First-Principles Tile-Centric Analytical GPU Performance Model from Cores to Clusters

Zhiwen Mo, Yu Cheng, Lei Wang +12

Recent GPU programming frameworks such as Triton, TileLang, and CUDA Tile adopt tiles as first-class primitives, making tile-centric programming the prevailing approach for high-pe…

cs.GR2026

Efficient 3D Gaussian Splatting with Axis-Shared Rasterization and Order-independent Transmittance

Zhican Wang, Guanghui He, Lingjun Gao +6

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for novel view synthesis, combining high-quality reconstruction with efficient rendering. It has been widely adopte…

cs.AR2026

Coset Ensemble Decoder for Quantum Error Correction with Algorithm-Hardware Co-Design

Shuang Liang, Jubo Xu, Giulio Bassanino +8

Reliable large-scale quantum computation relies on fault-tolerant architectures, where quantum error correction (QEC) continuously extracts and decodes error syndromes in real time…

cs.NI2026

SPAC: Automating FPGA-based Network Switches with Protocol Adaptive Customization

Guoyu Li, Yang Cao, Lucas H L Ng +9

With network requirements diverging across emerging applications, latency-critical services demand minimal logic delay, while hyperscale training and collectives require sustained…

cs.AR2026

Combating the Memory Walls: Optimization Pathways for Long-Context Agentic LLM Inference

Haoran Wu, Can Xiao, Jiayi Nie +15

LLMs now form the backbone of AI agents across a diverse range of applications, including tool use, command-line interfaces, and web or computer interaction. These agentic LLM infe…

cs.AR2026

DeepStack: Facilitating Co-Design Exploration of 3D DRAM-Stacked Accelerators for Distributed LLM Inference

Zhiwen Mo, Guoyu Li, Hao Mark Chen +11

Advances in hybrid bonding and packaging have driven growing interest in 3D DRAM-stacked AI accelerators. As large language models (LLMs) scale to hundreds of billions or trillions…