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ORCIDNAIC 2025: Coimbra, Portugal
- Proceedings of the 2nd Workshop on Networks for AI Computing, NAIC 2025, Coimbra, Portugal, September 8-11, 2025. ACM 2025, ISBN 979-8-4007-2082-6
- Shengnan Yue
, Mowei Wang, Yu Yan, Weiqiang Cheng, Zihan Jiang, Zhenhui Zhang:
RTT- or Bandwidth-Bound? Demystifying the KV Cache Transfer in Large Language Model Serving. 5-7 - Revant Teotia, Muhammad Haseeb:
Codesign of Tensors Encoding And Transcoding: A Building Block For Decentralized AI. 8-10 - Ying Wan, Haoyu Song, Yu Jia, Yunhui Yang, Tao Huang, Zhikang Chen:
LAPS: Joint Load Balancing and Congestion Control on Unequal-cost Multi-path Data Center Networks. 11-18 - Sajy Khashab, Hariharan Sezhiyan, Rani Abboud, Alex Normatov, Stefan Kaestle, Eliav Bar-Ilan, Mohammad Nassar, Omer Shabtai, Wei Bai, Matty Kadosh, Jiarong Xing, Mark Silberstein, T. S. Eugene Ng, Ang Chen:
NSX: Large-Scale Network Simulation on an AI Server. 19-25 - Chris Misa, Matthew Nance Hall, Reza Rejaie, Walter Willinger, Ramakrishnan Durairajan:
Why choose when you can have both: Programmable data planes meet programmable optics. 26-33 - Yunxiao Ma, Peilong Zhang, Hua Li, Yufeng Zhao, Yintan Ai, Hanlin Liu:
Intent Fuel Station: A RAG-Enhanced Agent Hub for Realizing Networking Intents. 34-36 - Ruoxi Wang, Kun Li, Minghui Xu, Yue Zhang, Kaidi Xu, Chunchi Liu, Yinhao Xiao, Xiuzhen Cheng:
LIFT: Automating Symbolic Execution Optimization with Large Language Models for AI Networks. 37-42 - Rukshani Athapathu, George Porter:
Reconfigurability within Collective Communication Algorithms. 43-49 - Kaile Zhu, Shihao Shen, Tuo Zhang, Xiaofei Wang, Xiaoliang Wang, Xin Jiang, Wenyu Wang, Hai Jin:
Sparkle: Optimizing the Serverless AIGC Deployment over Crowdsourced Edge Environments. 50-56 - Wenjie Chu, Yunfeng Shao, Chunhui Du:
A Cloud-Edge Collaborative Inference System for Data-secure LLM Serving. 57-63 - Dhananjaya Wijerathne, Haris Javaid, Guanwen Zhong, Dan Wu, Xing Yuan Kom, Mario Baldi:
Sparse Collectives: Exploiting Data Sparsity to Improve Communication Efficiency. 64-66 - Yuqi Li, Tianyu Chen, Vladimir M. Ciric, Changda Wang:
AMSO-INT: Reinforcement Learning-Driven Dynamic Adaptive In-Band Telemetry. 67-73 - Dante Van Poucke, Didier Colle, Mario Pickavet, Wouter Tavernier:
Quantifying the Impact of Job Placement and Routing on Network Efficiency in AI Clusters. 74-80 - Saar Ben Yochana, Chen Avin, Gabriel Scalosub:
T3P: Topology-Tailored Tensor Parallelism. 81-88 - Sundararajan Renganathan, Nick McKeown:
Chronos: Prescheduled circuit switching for LLM training. 89-97 - Adel Sefiane, Alireza Farshin, Marios Kogias:
MLSynth: Towards Synthetic ML Traces. 98-104 - Sumit Kumar, Arjun Temura, Naman Sharma, Ramanjeet Singh, Meet Dadhania, Praveen Tammana, Satananda Burla, Abed Mohammad Kamaluddin, Rinku Shah:
Simulating LLM training workloads for heterogeneous compute and network infrastructure. 105-107 - Philippe Buschmann, Arne Broering, Georg Carle, Andreas Blenk:
LLMs on Edge: Network Traffic Characteristics of Distributed Inference under the Loupe. 108-114
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