4 papers
An Executable Benchmarking Suite for Tool-Using Agents
Zhiqing Zhong, Zhijing Ye, Jiamin Wang +1
Closed-loop tool-using agents are increasingly evaluated in executable web, code, and micro-task environments, but benchmark reports often conflate workloads, action-generating dri…
NCCLZ: Compression-Enabled GPU Collectives with Decoupled Quantization and Entropy Coding
Jiamin Wang, Zhijing Ye, Xiaodong Yu
Collective communication is a major bottleneck for multi-node GPU workloads in scientific computing and distributed deep learning, especially when inter-node bandwidth is limited.…
An Efficient Gradient-Aware Error-Bounded Lossy Compressor for Federated Learning
Zhijing Ye, Sheng Di, Jiamin Wang +3
Federated learning (FL) enables collaborative model training without exposing clients' private data, but its deployment is often constrained by the communication cost of transmitti…
DenseGNN: universal and scalable deeper graph neural networks for high-performance property prediction in crystals and molecules
Hongwei Du, Jiamin Wang, Jian Hui +2
Generative models generate vast numbers of hypothetical materials, necessitating fast, accurate models for property prediction. Graph Neural Networks (GNNs) excel in this domain bu…