36 citations · 39 across the 8 of their papers we have counts for
8 papers
Janus: An Algorithm-Evaluator Co-Evolution Framework for LLM-Driven Discovery under Expensive Evaluation Budgets
Ximeng Liu, Qianlong Wang, Yingming Mao +6
LLM-driven program discovery relies on rapid evaluator feedback, but many scientific and engineering tasks require high-fidelity simulations, hardware execution, or physical experi…
NeuroRisk: Physics-Informed Neural Optimization for Risk-Aware Traffic Engineering
Yingming Mao, Ximeng Liu, Jingyi Cheng +8
In production Wide-Area Networks (WANs), correlated failures dominate availability losses, forcing operators to reserve large safety margins that leave substantial capacity underut…
Leaf-centric Logical Topology Design for OCS-based GPU Clusters
Xinchi Han, Weihao Jiang, Yingming Mao +14
Recent years have witnessed the growing deployment of optical circuit switches (OCS) in commercial GPU clusters (e.g., Google A3 GPU cluster) optimized for machine learning (ML) wo…
ATRO: A Fast Algorithm for Topology Engineering of Reconfigurable Datacenter Networks
Yingming Mao, Qiaozhu Zhai, Ximeng Liu +6
Reconfigurable data center networks (DCNs) enhance traditional architectures with optical circuit switches (OCSs), enabling dynamic reconfiguration of inter-pod links, i.e., the lo…
Geminet: Learning the Duality-based Iterative Process for Lightweight Traffic Engineering in Changing Topologies
Ximeng Liu, Zhuoran Liu, Yingming Mao +3
Recently, researchers have explored ML-based Traffic Engineering (TE), leveraging neural networks to solve TE problems traditionally addressed by optimization. However, existing ML…
A Fast Solver-Free Algorithm for Traffic Engineering in Large-Scale Data Center Network
Yingming Mao, Qiaozhu Zhai, Ximeng Liu +3
Rapid growth of data center networks (DCNs) poses significant challenges for large-scale traffic engineering (TE). Existing acceleration strategies, which rely on commercial solver…
FIGRET: Fine-Grained Robustness-Enhanced Traffic Engineering
Ximeng Liu, Shizhen Zhao, Yong Cui +1
Traffic Engineering (TE) is critical for improving network performance and reliability. A key challenge in TE is the management of sudden traffic bursts. Existing TE schemes either…
Efficient Routing Algorithm Design for Large DetNet
Shizhen Zhao, Tianyu Zhu, Ximeng Liu
Deterministic Networking (DetNet) is a rising technology that offers deterministic delay \& jitter and zero packet loss regardless of failures in large IP networks. In order to sup…