21 citations · 22 across the 12 of their papers we have counts for
15 papers
Algorithm-Architecture Co-Design for Efficient VLA Inference via Speculative Inference and Verification
Chunyu Qi, Zhuoran Song, Jian Weng +6
Vision-Language-Action (VLA) models have demonstrated remarkable capabilities in the field of embodied AI, but their high computational cost and limited predicted action length hin…
DeGS: A Scalable 3DGS Architecture via Decoupled Workload Parsing and Reorganization
Minnan Pei, Gang Li, Zeyu Zhu +7
3D Gaussian Splatting (3DGS) has emerged as a leading technique for real-time novel view synthesis, yet existing 3DGS accelerators suffer from poor architectural scalability: incre…
A Motion-Aware Vector Quantization Framework with Centroid Reuse for Efficient VLA Inference
Zhuoran Song, Haozhe Jiang, Chunyu Qi +4
Vision-Language-Action (VLA) models have demonstrated strong potential for embodied AI, yet their high inference latency on GPUs limits real-time deployment. Existing accelerators,…
Accelerating 3D Gaussian Splatting using Tensor Cores
Sheng Li, Yang Sui, Yue Wu +4
3D Gaussian Splatting (3DGS) has become a leading technique for real-time neural rendering and 3D scene reconstruction, but its rendering cost remains too high for many latency-sen…
Towards Compute-Aware In-Switch Computing for LLMs Tensor-Parallelism on Multi-GPU Systems
Chen Zhang, Qijun Zhang, Zhuoshan Zhou +10
Tensor parallelism (TP) in large-scale LLM inference and training introduces frequent collective operations that dominate inter-GPU communication. While in-switch computing, exempl…
DALI: A Workload-Aware Offloading Framework for Efficient MoE Inference on Local PCs
Zeyu Zhu, Gang Li, Peisong Wang +5
Mixture of Experts (MoE) architectures significantly enhance the capacity of LLMs without proportional increases in computation, but at the cost of a vast parameter size. Offloadin…