arXiv cs.DC Distributed, Parallel, and Cluster Computing
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Reposted by arXiv cs.DC Distributed, Parallel, and Cluster Computing
Mincheol Jeon, Euinam Huh: Federated style aware transformer aggregation of representations https://arxiv.org/abs/2511.18841 https://arxiv.org/pdf/2511.18841 https://arxiv.org/html/2511.18841
November 25, 2025 at 6:35 AM
Mincheol Jeon, Euinam Huh: Federated style aware transformer aggregation of representations https://arxiv.org/abs/2511.18841 https://arxiv.org/pdf/2511.18841 https://arxiv.org/html/2511.18841
Reposted by arXiv cs.DC Distributed, Parallel, and Cluster Computing
Longfei Wang, Junyan Liu, Fan Zhang, Jiangwen Wei, Yuanhua Tang, Jie Sun, Xiaodong Luo: N2N: A Parallel Framework for Large-Scale MILP under Distributed Memory https://arxiv.org/abs/2511.18723 https://arxiv.org/pdf/2511.18723 https://arxiv.org/html/2511.18723
November 25, 2025 at 6:29 AM
Longfei Wang, Junyan Liu, Fan Zhang, Jiangwen Wei, Yuanhua Tang, Jie Sun, Xiaodong Luo: N2N: A Parallel Framework for Large-Scale MILP under Distributed Memory https://arxiv.org/abs/2511.18723 https://arxiv.org/pdf/2511.18723 https://arxiv.org/html/2511.18723
Reposted by arXiv cs.DC Distributed, Parallel, and Cluster Computing
Alfredo Metere: Low-Rank GEMM: Efficient Matrix Multiplication via Low-Rank Approximation with FP8 Acceleration https://arxiv.org/abs/2511.18674 https://arxiv.org/pdf/2511.18674 https://arxiv.org/html/2511.18674
November 25, 2025 at 6:33 AM
Alfredo Metere: Low-Rank GEMM: Efficient Matrix Multiplication via Low-Rank Approximation with FP8 Acceleration https://arxiv.org/abs/2511.18674 https://arxiv.org/pdf/2511.18674 https://arxiv.org/html/2511.18674
Reposted by arXiv cs.DC Distributed, Parallel, and Cluster Computing
Mengdi Wang, Efe Bozkir, Enkelejda Kasneci: CycleSL: Server-Client Cyclical Update Driven Scalable Split Learning https://arxiv.org/abs/2511.18611 https://arxiv.org/pdf/2511.18611 https://arxiv.org/html/2511.18611
November 25, 2025 at 6:34 AM
Mengdi Wang, Efe Bozkir, Enkelejda Kasneci: CycleSL: Server-Client Cyclical Update Driven Scalable Split Learning https://arxiv.org/abs/2511.18611 https://arxiv.org/pdf/2511.18611 https://arxiv.org/html/2511.18611
Reposted by arXiv cs.DC Distributed, Parallel, and Cluster Computing
Xiaoyu Wang, Xiaotian Li, Zhixiang Zhou, Chen Li, Yong Liu: ADF-LoRA: Alternating Low-Rank Aggregation for Decentralized Federated Fine-Tuning https://arxiv.org/abs/2511.18291 https://arxiv.org/pdf/2511.18291 https://arxiv.org/html/2511.18291
November 25, 2025 at 6:34 AM
Xiaoyu Wang, Xiaotian Li, Zhixiang Zhou, Chen Li, Yong Liu: ADF-LoRA: Alternating Low-Rank Aggregation for Decentralized Federated Fine-Tuning https://arxiv.org/abs/2511.18291 https://arxiv.org/pdf/2511.18291 https://arxiv.org/html/2511.18291
Reposted by arXiv cs.DC Distributed, Parallel, and Cluster Computing
Saicharan Kolluru: Comparative Analysis of Large Language Model Inference Serving Systems: A Performance Study of vLLM and HuggingFace TGI https://arxiv.org/abs/2511.17593 https://arxiv.org/pdf/2511.17593 https://arxiv.org/html/2511.17593
November 25, 2025 at 6:32 AM
Saicharan Kolluru: Comparative Analysis of Large Language Model Inference Serving Systems: A Performance Study of vLLM and HuggingFace TGI https://arxiv.org/abs/2511.17593 https://arxiv.org/pdf/2511.17593 https://arxiv.org/html/2511.17593
Reposted by arXiv cs.DC Distributed, Parallel, and Cluster Computing
Leszek Sliwko, Aleksander Zgrzywa: A novel strategy for multi-resource load balancing in agent-based systems https://arxiv.org/abs/2511.17580 https://arxiv.org/pdf/2511.17580 https://arxiv.org/html/2511.17580
November 25, 2025 at 6:32 AM
Leszek Sliwko, Aleksander Zgrzywa: A novel strategy for multi-resource load balancing in agent-based systems https://arxiv.org/abs/2511.17580 https://arxiv.org/pdf/2511.17580 https://arxiv.org/html/2511.17580
Reposted by arXiv cs.DC Distributed, Parallel, and Cluster Computing
Shuaiyu Xie, Hanbin He, Jian Wang, Bing Li: Root Cause Analysis for Microservice Systems via Cascaded Conditional Learning with Hypergraphs https://arxiv.org/abs/2511.17566 https://arxiv.org/pdf/2511.17566 https://arxiv.org/html/2511.17566
November 25, 2025 at 6:32 AM
Shuaiyu Xie, Hanbin He, Jian Wang, Bing Li: Root Cause Analysis for Microservice Systems via Cascaded Conditional Learning with Hypergraphs https://arxiv.org/abs/2511.17566 https://arxiv.org/pdf/2511.17566 https://arxiv.org/html/2511.17566
Antonis Psistakis: IOMMU Support for Virtual-Address Remote DMA in an ARMv8 environment https://arxiv.org/abs/2511.19258 https://arxiv.org/pdf/2511.19258 https://arxiv.org/html/2511.19258
November 25, 2025 at 6:30 AM
Antonis Psistakis: IOMMU Support for Virtual-Address Remote DMA in an ARMv8 environment https://arxiv.org/abs/2511.19258 https://arxiv.org/pdf/2511.19258 https://arxiv.org/html/2511.19258
J\'er\'emie Chalopin, Maria Kokkou: Constant-Size Certificates for Leader Election in Chordal Graphs and Related Classes https://arxiv.org/abs/2511.19208 https://arxiv.org/pdf/2511.19208 https://arxiv.org/html/2511.19208
November 25, 2025 at 6:30 AM
J\'er\'emie Chalopin, Maria Kokkou: Constant-Size Certificates for Leader Election in Chordal Graphs and Related Classes https://arxiv.org/abs/2511.19208 https://arxiv.org/pdf/2511.19208 https://arxiv.org/html/2511.19208
Xinkui Zhao, Qingyu Ma, Yifan Zhang, Hengxuan Lou, Guanjie Cheng, Shuiguang Deng, Jianwei Yin: AME: An Efficient Heterogeneous Agentic Memory Engine for Smartphones https://arxiv.org/abs/2511.19192 https://arxiv.org/pdf/2511.19192 https://arxiv.org/html/2511.19192
November 25, 2025 at 6:30 AM
Xinkui Zhao, Qingyu Ma, Yifan Zhang, Hengxuan Lou, Guanjie Cheng, Shuiguang Deng, Jianwei Yin: AME: An Efficient Heterogeneous Agentic Memory Engine for Smartphones https://arxiv.org/abs/2511.19192 https://arxiv.org/pdf/2511.19192 https://arxiv.org/html/2511.19192
Marco Zambianco, Lorenzo Fasol, Roberto Doriguzzi-Corin: An Online Fragmentation-Aware GPU Scheduler for Multi-Tenant MIG-based Clouds https://arxiv.org/abs/2511.18906 https://arxiv.org/pdf/2511.18906 https://arxiv.org/html/2511.18906
November 25, 2025 at 6:30 AM
Marco Zambianco, Lorenzo Fasol, Roberto Doriguzzi-Corin: An Online Fragmentation-Aware GPU Scheduler for Multi-Tenant MIG-based Clouds https://arxiv.org/abs/2511.18906 https://arxiv.org/pdf/2511.18906 https://arxiv.org/html/2511.18906
Rajashree Bar, Daibik Barik, Adri Bhattacharya, Partha Sarathi Mandal: Monotone Decontamination of Arbitrary Dynamic Graphs with Mobile Agents https://arxiv.org/abs/2511.18315 https://arxiv.org/pdf/2511.18315 https://arxiv.org/html/2511.18315
November 25, 2025 at 6:30 AM
Rajashree Bar, Daibik Barik, Adri Bhattacharya, Partha Sarathi Mandal: Monotone Decontamination of Arbitrary Dynamic Graphs with Mobile Agents https://arxiv.org/abs/2511.18315 https://arxiv.org/pdf/2511.18315 https://arxiv.org/html/2511.18315
Bhattacharjya, Wu, Oh, Nam, Koo, Imani, Bozorgzadeh, Dutt: AVERY: Adaptive VLM Split Computing through Embodied Self-Awareness for Efficient Disaster Response Systems https://arxiv.org/abs/2511.18151 https://arxiv.org/pdf/2511.18151 https://arxiv.org/html/2511.18151
November 25, 2025 at 6:30 AM
Bhattacharjya, Wu, Oh, Nam, Koo, Imani, Bozorgzadeh, Dutt: AVERY: Adaptive VLM Split Computing through Embodied Self-Awareness for Efficient Disaster Response Systems https://arxiv.org/abs/2511.18151 https://arxiv.org/pdf/2511.18151 https://arxiv.org/html/2511.18151
Christoph Goldgruber, Benedikt Pittl, Erich Schikuta: Simulating Dynamic Cloud Marketspaces: Modeling Spot Instance Behavior and Scheduling with CloudSim Plus https://arxiv.org/abs/2511.18137 https://arxiv.org/pdf/2511.18137 https://arxiv.org/html/2511.18137
November 25, 2025 at 6:30 AM
Christoph Goldgruber, Benedikt Pittl, Erich Schikuta: Simulating Dynamic Cloud Marketspaces: Modeling Spot Instance Behavior and Scheduling with CloudSim Plus https://arxiv.org/abs/2511.18137 https://arxiv.org/pdf/2511.18137 https://arxiv.org/html/2511.18137
Ghimire, Niraula, Bhurtel, Timalsina, Neupane, Bhattarai, Jha: MIDAS: Adaptive Proxy Middleware for Mitigating Metadata Hotspots in HPC I/O at Scale https://arxiv.org/abs/2511.18124 https://arxiv.org/pdf/2511.18124 https://arxiv.org/html/2511.18124
November 25, 2025 at 6:30 AM
Ghimire, Niraula, Bhurtel, Timalsina, Neupane, Bhattarai, Jha: MIDAS: Adaptive Proxy Middleware for Mitigating Metadata Hotspots in HPC I/O at Scale https://arxiv.org/abs/2511.18124 https://arxiv.org/pdf/2511.18124 https://arxiv.org/html/2511.18124
Ruide Cao, Zhuyun Qi, Qinyang He, Chenxi Ling, Yi Wang, Guoming Tang: SAGkit: A Python SAG Toolkit for Response Time Analysis of Hybrid-Triggered Jobs https://arxiv.org/abs/2511.17882 https://arxiv.org/pdf/2511.17882 https://arxiv.org/html/2511.17882
November 25, 2025 at 6:30 AM
Ruide Cao, Zhuyun Qi, Qinyang He, Chenxi Ling, Yi Wang, Guoming Tang: SAGkit: A Python SAG Toolkit for Response Time Analysis of Hybrid-Triggered Jobs https://arxiv.org/abs/2511.17882 https://arxiv.org/pdf/2511.17882 https://arxiv.org/html/2511.17882
Shuyuan Fan, Zhao Zhang: Pier: Efficient Large Language Model pretraining with Relaxed Global Communication https://arxiv.org/abs/2511.17849 https://arxiv.org/pdf/2511.17849 https://arxiv.org/html/2511.17849
November 25, 2025 at 6:30 AM
Shuyuan Fan, Zhao Zhang: Pier: Efficient Large Language Model pretraining with Relaxed Global Communication https://arxiv.org/abs/2511.17849 https://arxiv.org/pdf/2511.17849 https://arxiv.org/html/2511.17849
[2025-11-25 Tue (UTC), 10 new articles found for csDC Distributed, Parallel, and Cluster Computing]
November 25, 2025 at 6:30 AM
[2025-11-25 Tue (UTC), 10 new articles found for csDC Distributed, Parallel, and Cluster Computing]
Reposted by arXiv cs.DC Distributed, Parallel, and Cluster Computing
Quentin Anthony, et al.: Training Foundation Models on a Full-Stack AMD Platform: Compute, Networking, and System Design https://arxiv.org/abs/2511.17127 https://arxiv.org/pdf/2511.17127 https://arxiv.org/html/2511.17127
November 24, 2025 at 6:30 AM
Quentin Anthony, et al.: Training Foundation Models on a Full-Stack AMD Platform: Compute, Networking, and System Design https://arxiv.org/abs/2511.17127 https://arxiv.org/pdf/2511.17127 https://arxiv.org/html/2511.17127
Reposted by arXiv cs.DC Distributed, Parallel, and Cluster Computing
Kirill Nagaitsev, Luka Grbcic, Samuel Williams, Costin Iancu: Optimizing PyTorch Inference with LLM-Based Multi-Agent Systems https://arxiv.org/abs/2511.16964 https://arxiv.org/pdf/2511.16964 https://arxiv.org/html/2511.16964
November 24, 2025 at 6:32 AM
Kirill Nagaitsev, Luka Grbcic, Samuel Williams, Costin Iancu: Optimizing PyTorch Inference with LLM-Based Multi-Agent Systems https://arxiv.org/abs/2511.16964 https://arxiv.org/pdf/2511.16964 https://arxiv.org/html/2511.16964
Gabriel Job Antunes Grabher, Fumio Machida, Thomas Ropars: Modeling Anomaly Detection in Cloud Services: Analysis of the Properties that Impact Latency and Resource Consumption https://arxiv.org/abs/2511.17119 https://arxiv.org/pdf/2511.17119 https://arxiv.org/html/2511.17119
November 24, 2025 at 6:30 AM
Gabriel Job Antunes Grabher, Fumio Machida, Thomas Ropars: Modeling Anomaly Detection in Cloud Services: Analysis of the Properties that Impact Latency and Resource Consumption https://arxiv.org/abs/2511.17119 https://arxiv.org/pdf/2511.17119 https://arxiv.org/html/2511.17119
Chenqi Zhao, Wenfei Wu, Linhai Song, Yuchen Xu: MicroMoE: Fine-Grained Load Balancing for Mixture-of-Experts with Token Scheduling https://arxiv.org/abs/2511.16947 https://arxiv.org/pdf/2511.16947 https://arxiv.org/html/2511.16947
November 24, 2025 at 6:30 AM
Chenqi Zhao, Wenfei Wu, Linhai Song, Yuchen Xu: MicroMoE: Fine-Grained Load Balancing for Mixture-of-Experts with Token Scheduling https://arxiv.org/abs/2511.16947 https://arxiv.org/pdf/2511.16947 https://arxiv.org/html/2511.16947
[2025-11-24 Mon (UTC), 2 new articles found for csDC Distributed, Parallel, and Cluster Computing]
November 24, 2025 at 6:30 AM
[2025-11-24 Mon (UTC), 2 new articles found for csDC Distributed, Parallel, and Cluster Computing]
Reposted by arXiv cs.DC Distributed, Parallel, and Cluster Computing
Qinghao Hu, Shang Yang, Junxian Guo, Xiaozhe Yao, Yujun Lin, Yuxian Gu, Han Cai, Chuang Gan, Ana Klimovic, Song Han: Taming the Long-Tail: Efficient Reasoning RL Training with Adaptive Drafter https://arxiv.org/abs/2511.16665 https://arxiv.org/pdf/2511.16665 https://arxiv.org/html/2511.16665
November 21, 2025 at 6:33 AM
Qinghao Hu, Shang Yang, Junxian Guo, Xiaozhe Yao, Yujun Lin, Yuxian Gu, Han Cai, Chuang Gan, Ana Klimovic, Song Han: Taming the Long-Tail: Efficient Reasoning RL Training with Adaptive Drafter https://arxiv.org/abs/2511.16665 https://arxiv.org/pdf/2511.16665 https://arxiv.org/html/2511.16665