Distributed and Cluster Computing

Papers filed under cs.DC on arXiv, each one already summarized by Paperlayer. Open any of them to read the summary beside the original PDF, with every point linked to the line, figure, or table it came from.

Search paper metadata (including unsummarized papers)

1,141 to 1,200 of 1,812

ATOMO: Communication-efficient Learning via Atomic Sparsification
Hongyi Wang, Scott Sievert, Zachary Charles +3
stat.MLcs.DCcs.LGarXiv:1806.04090v32018
Measurement-Driven Diagnosis and Mitigation of Host-CPU Co-location Interference in Single-GPU LLM Serving on a Multi-GPU Server
Guanjie Cheng, Guowei Li, Yingying Wen +3
cs.DCarXiv:2609.05425v12026
BurstGPT: A Real-world Workload Dataset to Optimize LLM Serving Systems
Yuxin Wang, Yuhan Chen, Zeyu Li +11
cs.DCcs.PFarXiv:2401.17644v52024
Exploring Collaborative Distributed Diffusion-Based AI-Generated Content (AIGC) in Wireless Networks
Hongyang Du, Ruichen Zhang, Dusit Niyato +6
cs.DCarXiv:2304.03446v22023
Exploring the Role of LLMs in HPC Programming: A Survey
Strahinja Ljaljevic, Josep Jorba, Sergio Iserte
cs.DCcs.AIarXiv:2608.26110v12026
SlackSwap: Bandwidth-Aware Activation Swapping and Recomputation for Memory-Efficient DNN Training
Hui Feng, Xun Zhou, Yuxin Wang
cs.DCarXiv:2610.13003v12026
Sparse Distributed Learning Based on Diffusion Adaptation
Paolo Di Lorenzo, Ali H. Sayed
cs.LGcs.DCarXiv:1206.3099v22012
Summaries:한국어
BASP: Communication-Efficient Batch-Aware Sequence Parallelism for LLM Training
Bigyan Ghimire, Jon C. Calhoun
cs.DCcs.LGarXiv:2609.03151v12026
MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems
Tianqi Chen, Mu Li, Yutian Li +7
cs.DCcs.LGcs.MSarXiv:1512.01274v12015
Efficient Block-Layer Parallel Inference for Vision-Language-Action on Hybrid Architectures
Haibo HU, Lianming Huang, Qiao Li +2
cs.DCcs.AIarXiv:2608.14586v12026
Towards Blockchain-based Auditable Storage and Sharing of IoT Data
Hossein Shafagh, Lukas Burkhalter, Anwar Hithnawi +1
cs.DCarXiv:1705.08230v22017
Capturing a Moving Target on Star Graphs by Two Communicating Mobile Agents
Khaled Jawhar, Evangelos Kranakis
cs.DCarXiv:2610.11955v12026
Graph-Structured Deep Learning Framework for Multi-task Contention Identification with High-dimensional Metrics
Xiao Yang, Yinan Ni, Yuqi Tang +3
cs.DCcs.LGarXiv:2601.20389v12026
LLM-42: Enabling Determinism in LLM Inference with Verified Speculation
Raja Gond, Aditya K Kamath, Ramachandran Ramjee +1
cs.LGcs.AIcs.DCarXiv:2601.17768v22026
Personalized Federated Learning for Generative AI-Assisted Semantic Communications
Yubo Peng, Feibo Jiang, Li Dong +2
cs.LGcs.DCcs.ITarXiv:2410.02450v12024
Verified Detection and Prevention of Concurrency Anomalies in Multi-Agent Large Language Model Systems
Sajjad Khan
cs.LGcs.DCcs.LOarXiv:2606.17182v12026
FRESHLATENT: Channel-Aware Latent Adaptation for Resource-Constrained Embodied VLM Perception
Rajat Bhattacharjya, Minwoo Kim, Arnab Sarkar +5
eess.SPcs.CVcs.DCarXiv:2609.30629v12026
Network Topology and Communication-Computation Tradeoffs in Decentralized Optimization
Angelia Nedić, Alex Olshevsky, Michael G. Rabbat
math.OCcs.DCcs.MAarXiv:1709.08765v22017
Spread of Misinformation in Social Networks
Daron Acemoglu, Asuman Ozdaglar, Ali ParandehGheibi
cs.ITcs.DCmath.PRarXiv:0906.5007v12009
Adaptive Federated Learning and Digital Twin for Industrial Internet of Things
Wen Sun, Shiyu Lei, Lu Wang +2
cs.LGcs.DCarXiv:2010.13058v22020
Scaling Inference Prefill with High-Radix Photonic Interconnects
Arulselvan Madhavan, Peter Carson, Taylor Groves +1
cs.DCcs.ARarXiv:2609.01821v12026
Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures
Chenggang Zhao, Chengqi Deng, Chong Ruan +12
cs.DCcs.AIcs.ARarXiv:2505.09343v22025
MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs
Ziheng Jiang, Haibin Lin, Yinmin Zhong +29
cs.LGcs.DCarXiv:2402.15627v12024
LayerCheck: Adaptive Layer-wise Checkpointing for Large Language Model Post-training
Minqiu Sun, Xin Huang, Luanzheng Guo +3
cs.DCarXiv:2609.27193v12026
Personalized Federated Learning with Moreau Envelopes
Canh T. Dinh, Nguyen H. Tran, Tuan Dung Nguyen
cs.LGcs.DCstat.MLarXiv:2006.08848v32020
SAFA: a Semi-Asynchronous Protocol for Fast Federated Learning with Low Overhead
Wentai Wu, Ligang He, Weiwei Lin +3
cs.DCcs.LGarXiv:1910.01355v42019
Semi-Decentralized Federated Learning with Cooperative D2D Local Model Aggregations
Frank Po-Chen Lin, Seyyedali Hosseinalipour, Sheikh Shams Azam +2
cs.LGcs.DCstat.MLarXiv:2103.10481v32021
Distributed Deep Learning Using Synchronous Stochastic Gradient Descent
Dipankar Das, Sasikanth Avancha, Dheevatsa Mudigere +5
cs.DCcs.LGarXiv:1602.06709v12016
Hierarchical Federated Learning Across Heterogeneous Cellular Networks
Mehdi Salehi Heydar Abad, Emre Ozfatura, Deniz Gunduz +1
cs.LGcs.DCcs.ITarXiv:1909.02362v12019
KMC 3: counting and manipulating k-mer statistics
Marek Kokot, Maciej Długosz, Sebastian Deorowicz
q-bio.GNcs.DCcs.DSarXiv:1701.08022v12017
Accelerating CNN inference on FPGAs: A Survey
Kamel Abdelouahab, Maxime Pelcat, Jocelyn Serot +1
cs.DCcs.ARcs.CVarXiv:1806.01683v12018
FedMix: Approximation of Mixup under Mean Augmented Federated Learning
Tehrim Yoon, Sumin Shin, Sung Ju Hwang +1
cs.LGcs.AIcs.CVarXiv:2107.00233v12021
Redundancy Meets Synergy: Dependency-aware Expert Selection for MoE via Submodular Optimization
Zheng Lin, Shaoke Fang, Yuxin Zhang +6
cs.LGcs.DCarXiv:2610.00558v12026
RT-HiSS: Ray Tracing Accelerated High Dimensional Vector Similarity Searches
Revanth Reddy Munugala, Michael Gowanlock
cs.DCcs.DBarXiv:2609.01975v12026
Parallel Sparse Matrix-Matrix Multiplication and Indexing: Implementation and Experiments
Aydin Buluc, John Gilbert
cs.DCcs.MScs.PFarXiv:1109.3739v22011
Scalable Multi-GPU Simulation of 3D Multicellular Growth with RNN-Based Workload Balancing
Matvey Moisseyev, Huijing Du, Dandan Zheng +2
cs.DCcs.CEcs.LGarXiv:2608.25890v12026
GE-SpMM: General-purpose Sparse Matrix-Matrix Multiplication on GPUs for Graph Neural Networks
Guyue Huang, Guohao Dai, Yu Wang +1
cs.DCarXiv:2007.03179v12020
OneLA: Scaling Linear-Attention Decoding to Large Beams in Generative Recommendation
Xiangrui Yang, Cheng Peng, Yunfeng Zhao +9
cs.AIcs.DCcs.IRarXiv:2609.12399v12026
MinT: Managed Infrastructure for Training and Serving Millions of LLMs
Mind Lab, :, Song Cao +60
cs.LGcs.AIcs.DCarXiv:2605.13779v22026
Transformative effects of IoT, Blockchain and Artificial Intelligence on cloud computing: Evolution, vision, trends and open challenges
Sukhpal Singh Gill, Shreshth Tuli, Minxian Xu +15
cs.DCarXiv:1911.01941v12019
Dynamic Service Placement for Mobile Micro-Clouds with Predicted Future Costs
Shiqiang Wang, Rahul Urgaonkar, Ting He +3
cs.DCcs.NImath.OCarXiv:1503.02735v22015
FusionLLM: A Decentralized LLM Training System on Geo-distributed GPUs with Adaptive Compression
Zhenheng Tang, Xueze Kang, Yiming Yin +11
cs.DCcs.AIcs.LGarXiv:2410.12707v12024
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization
Amirhossein Reisizadeh, Aryan Mokhtari, Hamed Hassani +2
cs.LGcs.DCmath.OCarXiv:1909.13014v42019
New Contraction Bounds for Multidimensional Asymptotic Consensus in Dynamic Networks
Zeremonienmeister Berber Aab, Darya Melnyk, Stefan Schmid
cs.DCarXiv:2610.11805v12026
XFT: Practical Fault Tolerance Beyond Crashes
Shengyun Liu, Paolo Viotti, Christian Cachin +2
cs.DCarXiv:1502.05831v32015
A Lower Bound for the Distributed Lovász Local Lemma
Sebastian Brandt, Orr Fischer, Juho Hirvonen +5
cs.DCcs.CCarXiv:1511.00900v12015
On the Capacity of Secure Distributed Matrix Multiplication
Wei-Ting Chang, Ravi Tandon
cs.ITcs.CRcs.DCarXiv:1806.00469v12018
AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networks
Zheng Lin, Guanqiao Qu, Wei Wei +2
cs.LGcs.AIcs.DCarXiv:2403.13101v42024
Performance Evaluation of Fast Fourier Transforms on Emerging RISC-V Hardware with Vector Extension Support
Daniel Seibel, Kaveh Haghighi Mood, Jayesh Badwaik +3
cs.MScs.DCmath.NAarXiv:2608.28076v12026
EnGN: A High-Throughput and Energy-Efficient Accelerator for Large Graph Neural Networks
Shengwen Liang, Ying Wang, Cheng Liu +3
cs.DCarXiv:1909.00155v32019
Towards Loosely-Coupled Programming on Petascale Systems
Ioan Raicu, Zhao Zhang, Mike Wilde +4
cs.DCarXiv:0808.3540v22008
Fast Clustering using MapReduce
Alina Ene, Sungjin Im, Benjamin Moseley
cs.DCcs.DSarXiv:1109.1579v12011
Quantum Reinforcement Learning for Cost and Delay Tradeoffs in Quantum Cloud Orchestration
An N. H. Phan, Dang Van Huynh, Muhammad Usman +1
cs.LGcs.AIcs.DCarXiv:2609.27446v12026
Gunrock: GPU Graph Analytics
Yangzihao Wang, Yuechao Pan, Andrew Davidson +8
cs.DCarXiv:1701.01170v12017
Improving LoRA in Privacy-preserving Federated Learning
Youbang Sun, Zitao Li, Yaliang Li +1
cs.LGcs.CRcs.DCarXiv:2403.12313v12024
FDLoRA: Personalized Federated Learning of Large Language Model via Dual LoRA Tuning
Yao Lu, Jiaxing QI, Zhongzhi Luan +4
cs.DCarXiv:2406.07925v22024
EPR Count for Runtime Prediction in Distributed Quantum Computing
Fatih E. Bilgen, Ozgur B. Akan
cs.DCquant-pharXiv:2609.39851v12026
Federated Asymptotics: a model to compare federated learning algorithms
Gary Cheng, Karan Chadha, John Duchi
cs.LGcs.DCmath.OCarXiv:2108.07313v32021
Confidant: Customizing Transformer-based LLMs via Collaborative Edge Training
Yuhao Chen, Yuxuan Yan, Qianqian Yang +3
cs.LGcs.AIcs.DCarXiv:2311.13381v12023
AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving
Zhuohan Li, Lianmin Zheng, Yinmin Zhong +8
cs.LGcs.DCcs.NIarXiv:2302.11665v22023

Distributed and Cluster Computing

ATOMO: Communication-efficient Learning via Atomic Sparsification

Measurement-Driven Diagnosis and Mitigation of Host-CPU Co-location Interference in Single-GPU LLM Serving on a Multi-GPU Server

BurstGPT: A Real-world Workload Dataset to Optimize LLM Serving Systems

Exploring Collaborative Distributed Diffusion-Based AI-Generated Content (AIGC) in Wireless Networks

Exploring the Role of LLMs in HPC Programming: A Survey

SlackSwap: Bandwidth-Aware Activation Swapping and Recomputation for Memory-Efficient DNN Training

Sparse Distributed Learning Based on Diffusion Adaptation

BASP: Communication-Efficient Batch-Aware Sequence Parallelism for LLM Training

MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems

Efficient Block-Layer Parallel Inference for Vision-Language-Action on Hybrid Architectures

Towards Blockchain-based Auditable Storage and Sharing of IoT Data

Capturing a Moving Target on Star Graphs by Two Communicating Mobile Agents

Graph-Structured Deep Learning Framework for Multi-task Contention Identification with High-dimensional Metrics

LLM-42: Enabling Determinism in LLM Inference with Verified Speculation

Personalized Federated Learning for Generative AI-Assisted Semantic Communications

Verified Detection and Prevention of Concurrency Anomalies in Multi-Agent Large Language Model Systems

FRESHLATENT: Channel-Aware Latent Adaptation for Resource-Constrained Embodied VLM Perception

Network Topology and Communication-Computation Tradeoffs in Decentralized Optimization

Spread of Misinformation in Social Networks

Adaptive Federated Learning and Digital Twin for Industrial Internet of Things

Scaling Inference Prefill with High-Radix Photonic Interconnects

Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures

MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs

LayerCheck: Adaptive Layer-wise Checkpointing for Large Language Model Post-training

Personalized Federated Learning with Moreau Envelopes

SAFA: a Semi-Asynchronous Protocol for Fast Federated Learning with Low Overhead

Semi-Decentralized Federated Learning with Cooperative D2D Local Model Aggregations

Distributed Deep Learning Using Synchronous Stochastic Gradient Descent

Hierarchical Federated Learning Across Heterogeneous Cellular Networks

KMC 3: counting and manipulating k-mer statistics

Accelerating CNN inference on FPGAs: A Survey

FedMix: Approximation of Mixup under Mean Augmented Federated Learning

Redundancy Meets Synergy: Dependency-aware Expert Selection for MoE via Submodular Optimization

RT-HiSS: Ray Tracing Accelerated High Dimensional Vector Similarity Searches

Parallel Sparse Matrix-Matrix Multiplication and Indexing: Implementation and Experiments

Scalable Multi-GPU Simulation of 3D Multicellular Growth with RNN-Based Workload Balancing

GE-SpMM: General-purpose Sparse Matrix-Matrix Multiplication on GPUs for Graph Neural Networks

OneLA: Scaling Linear-Attention Decoding to Large Beams in Generative Recommendation

MinT: Managed Infrastructure for Training and Serving Millions of LLMs

Transformative effects of IoT, Blockchain and Artificial Intelligence on cloud computing: Evolution, vision, trends and open challenges

Dynamic Service Placement for Mobile Micro-Clouds with Predicted Future Costs

FusionLLM: A Decentralized LLM Training System on Geo-distributed GPUs with Adaptive Compression

FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization

New Contraction Bounds for Multidimensional Asymptotic Consensus in Dynamic Networks

XFT: Practical Fault Tolerance Beyond Crashes

A Lower Bound for the Distributed Lovász Local Lemma

On the Capacity of Secure Distributed Matrix Multiplication

AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networks

Performance Evaluation of Fast Fourier Transforms on Emerging RISC-V Hardware with Vector Extension Support

EnGN: A High-Throughput and Energy-Efficient Accelerator for Large Graph Neural Networks

Towards Loosely-Coupled Programming on Petascale Systems

Fast Clustering using MapReduce

Quantum Reinforcement Learning for Cost and Delay Tradeoffs in Quantum Cloud Orchestration

Gunrock: GPU Graph Analytics

Improving LoRA in Privacy-preserving Federated Learning

FDLoRA: Personalized Federated Learning of Large Language Model via Dual LoRA Tuning

EPR Count for Runtime Prediction in Distributed Quantum Computing

Federated Asymptotics: a model to compare federated learning algorithms

Confidant: Customizing Transformer-based LLMs via Collaborative Edge Training

AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving