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.

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421 to 480 of 1,072

Turbo-Aggregate: Breaking the Quadratic Aggregation Barrier in Secure Federated Learning
Jinhyun So, Basak Guler, A. Salman Avestimehr
cs.LGcs.CRcs.DCarXiv:2002.04156v32020
5G network slicing using SDN and NFV- A survey of taxonomy, architectures and future challenges
Alcardo Alex Barakabitze, Arslan Ahmad, Rashid Mijumbi +1
cs.NIcs.DCcs.MMarXiv:1912.02802v12019
SAFA: a Semi-Asynchronous Protocol for Fast Federated Learning with Low Overhead
Wentai Wu, Ligang He, Weiwei Lin +3
cs.DCcs.LGarXiv:1910.01355v42019
Model Pruning Enables Efficient Federated Learning on Edge Devices
Yuang Jiang, Shiqiang Wang, Victor Valls +4
cs.LGcs.DCstat.MLarXiv:1909.12326v52019
Alpaca: Intermittent Execution without Checkpoints
Kiwan Maeng, Alexei Colin, Brandon Lucia
cs.DCarXiv:1909.06951v12019
Characterizing the Scalability and Performance of Large-Scale AI Training Under Multi-Tenancy
Jacopo Raffi, Thomas Pasquali, Lorenzo Piarulli +6
cs.DCarXiv:2609.00817v22026
Customer churn prediction in telecom using machine learning and social network analysis in big data platform
Abdelrahim Kasem Ahmad, Assef Jafar, Kadan Aljoumaa
cs.CYcs.DCcs.LGarXiv:1904.00690v12019
Scaling Inference Prefill with High-Radix Photonic Interconnects
Arulselvan Madhavan, Peter Carson, Taylor Groves +1
cs.DCcs.ARarXiv:2609.01821v12026
Intelligence Beyond the Edge: Inference on Intermittent Embedded Systems
Graham Gobieski, Nathan Beckmann, Brandon Lucia
cs.DCarXiv:1810.07751v22018
Decentralized Applications: The Blockchain-Empowered Software System
Wei Cai, Zehua Wang, Jason B. Ernst +3
cs.DCcs.CRcs.CYarXiv:1810.05365v12018
Federated Quantum Machine Learning
Samuel Yen-Chi Chen, Shinjae Yoo
quant-phcs.AIcs.CRarXiv:2103.12010v12021
Fog Computing: Survey of Trends, Architectures, Requirements, and Research Directions
Ranesh Kumar Naha, Saurabh Garg, Dimitrios Georgakopoulos +4
cs.DCarXiv:1807.00976v12018
Summaries:한국어
Limits of local algorithms over sparse random graphs
David Gamarnik, Madhu Sudan
math.PRcs.CCcs.DCarXiv:1304.1831v12013
Performance Evaluation of Container-based Virtualization for High Performance Computing Environments
Carlos Arango, Rémy Dernat, John Sanabria
cs.OScs.DCcs.PFarXiv:1709.10140v12017
A decentralized proximal-gradient method with network independent step-sizes and separated convergence rates
Zhi Li, Wei Shi, Ming Yan
math.OCcs.DCcs.LGarXiv:1704.07807v22017
Distributed Optimization Under Adversarial Nodes
Shreyas Sundaram, Bahman Gharesifard
eess.SYcs.DCmath.OCarXiv:1606.08939v12016
Dynamic Service Migration in Mobile Edge Computing Based on Markov Decision Process
Shiqiang Wang, Rahul Urgaonkar, Murtaza Zafer +3
cs.DCcs.NImath.OCarXiv:1506.05261v22015
Best bang for your buck: GPU nodes for GROMACS biomolecular simulations
Carsten Kutzner, Szilárd Páll, Martin Fechner +3
cs.DCcs.PFphysics.bio-pharXiv:1507.00898v12015
GraphMat: High performance graph analytics made productive
Narayanan Sundaram, Nadathur Rajagopalan Satish, Md Mostofa Ali Patwary +4
cs.PFcs.DBcs.DCarXiv:1503.07241v12015
Dynamic Service Placement for Mobile Micro-Clouds with Predicted Future Costs
Shiqiang Wang, Rahul Urgaonkar, Ting He +3
cs.DCcs.NImath.OCarXiv:1503.02735v22015
Thermo-FL: Thermal-Aware Robust Federated Fine-Tuning of Large Language Models for Edge AI
Shiva Shrestha, Kazi Shaharair Sharif, Zongxing Xie +3
cs.LGcs.DCarXiv:2608.21172v12026
Orbital AI Computing: Carbon Tradeoffs Across Satellite Scale
Nisha Sarwar, Lei Jiang, Fan Chen
cs.DCcs.AIarXiv:2608.14557v12026
InfiniGen: Efficient Generative Inference of Large Language Models with Dynamic KV Cache Management
Wonbeom Lee, Jungi Lee, Junghwan Seo +1
cs.LGcs.DCarXiv:2406.19707v12024
Efficient Memory Management for Large Language Model Serving with PagedAttention
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang +6
cs.LGcs.DCarXiv:2309.06180v12023
FedProto: Federated Prototype Learning across Heterogeneous Clients
Yue Tan, Guodong Long, Lu Liu +4
cs.LGcs.DCarXiv:2105.00243v42021
Personalized Federated Learning with Moreau Envelopes
Canh T. Dinh, Nguyen H. Tran, Tuan Dung Nguyen
cs.LGcs.DCstat.MLarXiv:2006.08848v32020
Adaptive Personalized Federated Learning
Yuyang Deng, Mohammad Mahdi Kamani, Mehrdad Mahdavi
cs.LGcs.DCstat.MLarXiv:2003.13461v32020
Serving DNNs like Clockwork: Performance Predictability from the Bottom Up
Arpan Gujarati, Reza Karimi, Safya Alzayat +4
cs.DCcs.LGarXiv:2006.02464v22020
Faasm: Lightweight Isolation for Efficient Stateful Serverless Computing
Simon Shillaker, Peter Pietzuch
cs.DCarXiv:2002.09344v22020
Think Locally, Act Globally: Federated Learning with Local and Global Representations
Paul Pu Liang, Terrance Liu, Liu Ziyin +5
cs.LGcs.DCstat.MLarXiv:2001.01523v32020
Tighter Theory for Local SGD on Identical and Heterogeneous Data
Ahmed Khaled, Konstantin Mishchenko, Peter Richtárik
cs.LGcs.DCmath.NAarXiv:1909.04746v42019
Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning
Hao Yu, Sen Yang, Shenghuo Zhu
math.OCcs.DCcs.LGarXiv:1807.06629v32018
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates
Dong Yin, Yudong Chen, Kannan Ramchandran +1
cs.LGcs.CRcs.DCarXiv:1803.01498v22018
BestConfig: Tapping the Performance Potential of Systems via Automatic Configuration Tuning
Yuqing Zhu, Jianxun Liu, Mengying Guo +5
cs.PFcs.DBcs.DCarXiv:1710.03439v12017
TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning
Wei Wen, Cong Xu, Feng Yan +4
cs.LGcs.DCcs.NEarXiv:1705.07878v62017
Iterative Approximate Byzantine Consensus in Arbitrary Directed Graphs
Nitin Vaidya, Lewis Tseng, Guanfeng Liang
cs.DCarXiv:1201.4183v22012
Distributed Private Data Analysis: On Simultaneously Solving How and What
Amos Beimel, Kobbi Nissim, Eran Omri
cs.CRcs.DCarXiv:1103.2626v12011
Optimal Exact-Regenerating Codes for Distributed Storage at the MSR and MBR Points via a Product-Matrix Construction
K. V. Rashmi, Nihar B. Shah, P. Vijay Kumar
cs.ITcs.DCcs.NIarXiv:1005.4178v22010
A Manifesto for Future Generation Cloud Computing: Research Directions for the Next Decade
Rajkumar Buyya, Satish Narayana Srirama, Giuliano Casale +22
cs.DCarXiv:1711.09123v22017
Ready Cohorts: Bounding GPU Opportunity and Avoiding Host Round Trips in LLM-Agent Control
Josef Liyanjun Chen
cs.DCcs.AIcs.OSarXiv:2608.12123v12026
LongStraw: Long-Context RL Beyond 2M Tokens under a Fixed GPU Budget
Changhai Zhou, Kieran Liu, Yuhua Zhou +17
cs.LGcs.DCarXiv:2607.14952v12026
Contribution-Aware Bandwidth Allocation for Multimodal Split Learning
Iason Ofeidis, Leandros Tassiulas
cs.LGcs.DCcs.NIarXiv:2609.01406v12026
TurboServe: Serving Streaming Video Generation Efficiently and Economically
Youhe Jiang, Haoxu Wang, Haotong Bao +5
cs.DCarXiv:2606.19271v12026
Simple Regenerating Codes: Network Coding for Cloud Storage
Dimitris S. Papailiopoulos, Jianqiang Luo, Alexandros G. Dimakis +2
cs.ITcs.DCcs.NIarXiv:1109.0264v12011
Federated Learning on Non-IID Data Silos: An Experimental Study
Qinbin Li, Yiqun Diao, Quan Chen +1
cs.LGcs.DCarXiv:2102.02079v42021
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping
Xiaoyu Cao, Minghong Fang, Jia Liu +1
cs.CRcs.AIcs.DCarXiv:2012.13995v32020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization
Jianyu Wang, Qinghua Liu, Hao Liang +2
cs.LGcs.DCstat.MLarXiv:2007.07481v12020
Adaptive Federated Optimization
Sashank Reddi, Zachary Charles, Manzil Zaheer +5
cs.LGcs.DCmath.OCarXiv:2003.00295v52020
Federated Learning with Personalization Layers
Manoj Ghuhan Arivazhagan, Vinay Aggarwal, Aaditya Kumar Singh +1
cs.LGcs.DCstat.MLarXiv:1912.00818v12019
Distributed Nonconvex Constrained Optimization over Time-Varying Digraphs
Gesualdo Scutari, Ying Sun
math.OCcs.DCcs.MAarXiv:1809.01106v12018
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints
Felix Sattler, Klaus-Robert Müller, Wojciech Samek
cs.LGcs.DCstat.MLarXiv:1910.01991v12019
Robust and Communication-Efficient Federated Learning from Non-IID Data
Felix Sattler, Simon Wiedemann, Klaus-Robert Müller +1
cs.LGcs.AIcs.DCarXiv:1903.02891v12019
Performance Benchmarking and Optimizing Hyperledger Fabric Blockchain Platform
Parth Thakkar, Senthil Nathan, Balaji Vishwanathan
cs.DCarXiv:1805.11390v12018
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
Shiqiang Wang, Tiffany Tuor, Theodoros Salonidis +4
cs.DCcs.LGmath.OCarXiv:1804.05271v32018
Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis
Tal Ben-Nun, Torsten Hoefler
cs.LGcs.CVcs.DCarXiv:1802.09941v22018
Computation Rate Maximization for Wireless Powered Mobile-Edge Computing with Binary Computation Offloading
Suzhi Bi, Ying-Jun Angela Zhang
cs.DCcs.ITarXiv:1708.08810v42017
Internet of Things: An Overview
Farzad Khodadadi, Amir Vahid Dastjerdi, Rajkumar Buyya
cs.DCcs.NIarXiv:1703.06409v12017
Computation Peer Offloading for Energy-Constrained Mobile Edge Computing in Small-Cell Networks
Lixing Chen, Sheng Zhou, Jie Xu
cs.GTcs.DCarXiv:1703.06058v22017
Using Battery Storage for Peak Shaving and Frequency Regulation: Joint Optimization for Superlinear Gains
Yuanyuan Shi, Bolun Xu, Di Wang +1
eess.SYcs.DCmath.OCarXiv:1702.08065v32017
Distributed optimization over time-varying directed graphs
Angelia Nedic, Alex Olshevsky
math.OCcs.DCeess.SYarXiv:1303.2289v22013

Distributed and Cluster Computing

Turbo-Aggregate: Breaking the Quadratic Aggregation Barrier in Secure Federated Learning

5G network slicing using SDN and NFV- A survey of taxonomy, architectures and future challenges

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

Model Pruning Enables Efficient Federated Learning on Edge Devices

Alpaca: Intermittent Execution without Checkpoints

Characterizing the Scalability and Performance of Large-Scale AI Training Under Multi-Tenancy

Customer churn prediction in telecom using machine learning and social network analysis in big data platform

Scaling Inference Prefill with High-Radix Photonic Interconnects

Intelligence Beyond the Edge: Inference on Intermittent Embedded Systems

Decentralized Applications: The Blockchain-Empowered Software System

Federated Quantum Machine Learning

Fog Computing: Survey of Trends, Architectures, Requirements, and Research Directions

Limits of local algorithms over sparse random graphs

Performance Evaluation of Container-based Virtualization for High Performance Computing Environments

A decentralized proximal-gradient method with network independent step-sizes and separated convergence rates

Distributed Optimization Under Adversarial Nodes

Dynamic Service Migration in Mobile Edge Computing Based on Markov Decision Process

Best bang for your buck: GPU nodes for GROMACS biomolecular simulations

GraphMat: High performance graph analytics made productive

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

Thermo-FL: Thermal-Aware Robust Federated Fine-Tuning of Large Language Models for Edge AI

Orbital AI Computing: Carbon Tradeoffs Across Satellite Scale

InfiniGen: Efficient Generative Inference of Large Language Models with Dynamic KV Cache Management

Efficient Memory Management for Large Language Model Serving with PagedAttention

FedProto: Federated Prototype Learning across Heterogeneous Clients

Personalized Federated Learning with Moreau Envelopes

Adaptive Personalized Federated Learning

Serving DNNs like Clockwork: Performance Predictability from the Bottom Up

Faasm: Lightweight Isolation for Efficient Stateful Serverless Computing

Think Locally, Act Globally: Federated Learning with Local and Global Representations

Tighter Theory for Local SGD on Identical and Heterogeneous Data

Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning

Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates

BestConfig: Tapping the Performance Potential of Systems via Automatic Configuration Tuning

TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning

Iterative Approximate Byzantine Consensus in Arbitrary Directed Graphs

Distributed Private Data Analysis: On Simultaneously Solving How and What

Optimal Exact-Regenerating Codes for Distributed Storage at the MSR and MBR Points via a Product-Matrix Construction

A Manifesto for Future Generation Cloud Computing: Research Directions for the Next Decade

Ready Cohorts: Bounding GPU Opportunity and Avoiding Host Round Trips in LLM-Agent Control

LongStraw: Long-Context RL Beyond 2M Tokens under a Fixed GPU Budget

Contribution-Aware Bandwidth Allocation for Multimodal Split Learning

TurboServe: Serving Streaming Video Generation Efficiently and Economically

Simple Regenerating Codes: Network Coding for Cloud Storage

Federated Learning on Non-IID Data Silos: An Experimental Study

FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping

Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization

Adaptive Federated Optimization

Federated Learning with Personalization Layers

Distributed Nonconvex Constrained Optimization over Time-Varying Digraphs

Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints

Robust and Communication-Efficient Federated Learning from Non-IID Data

Performance Benchmarking and Optimizing Hyperledger Fabric Blockchain Platform

Adaptive Federated Learning in Resource Constrained Edge Computing Systems

Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis

Computation Rate Maximization for Wireless Powered Mobile-Edge Computing with Binary Computation Offloading

Internet of Things: An Overview

Computation Peer Offloading for Energy-Constrained Mobile Edge Computing in Small-Cell Networks

Using Battery Storage for Peak Shaving and Frequency Regulation: Joint Optimization for Superlinear Gains

Distributed optimization over time-varying directed graphs