Distributed and Cluster Computing

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781 to 840 of 1,072

Federated Learning: Opportunities and Challenges
Priyanka Mary Mammen
cs.LGcs.DCarXiv:2101.05428v12021
Asynchronous Stochastic Gradient Descent with Delay Compensation
Shuxin Zheng, Qi Meng, Taifeng Wang +4
cs.LGcs.DCarXiv:1609.08326v62016
From Distributed Machine Learning to Federated Learning: A Survey
Ji Liu, Jizhou Huang, Yang Zhou +4
cs.DCcs.AIcs.LGarXiv:2104.14362v42021
Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms
Jianyu Wang, Gauri Joshi
cs.LGcs.DCstat.MLarXiv:1808.07576v32018
Fast Convolutional Nets With fbfft: A GPU Performance Evaluation
Nicolas Vasilache, Jeff Johnson, Michael Mathieu +3
cs.LGcs.DCcs.NEarXiv:1412.7580v32014
Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation
Cong Xie, Sanmi Koyejo, Indranil Gupta
cs.LGcs.CRcs.DCarXiv:1903.03936v12019
More Bang for Your Buck: Improved use of GPU Nodes for GROMACS 2018
Carsten Kutzner, Szilárd Páll, Martin Fechner +3
cs.DCcs.PFphysics.bio-pharXiv:1903.05918v22019
TensorFlow-Serving: Flexible, High-Performance ML Serving
Christopher Olston, Noah Fiedel, Kiril Gorovoy +6
cs.DCcs.LGarXiv:1712.06139v22017
SPINN: Synergistic Progressive Inference of Neural Networks over Device and Cloud
Stefanos Laskaridis, Stylianos I. Venieris, Mario Almeida +2
cs.LGcs.CVcs.DCarXiv:2008.06402v22020
Federated Learning with Cooperating Devices: A Consensus Approach for Massive IoT Networks
Stefano Savazzi, Monica Nicoli, Vittorio Rampa
eess.SPcs.DCcs.LGarXiv:1912.13163v12019
Federated Learning for Open Banking
Guodong Long, Yue Tan, Jing Jiang +1
cs.DCcs.LGarXiv:2108.10749v12021
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout
Samuel Horvath, Stefanos Laskaridis, Mario Almeida +3
cs.LGcs.DCarXiv:2102.13451v52021
Gemmini: Enabling Systematic Deep-Learning Architecture Evaluation via Full-Stack Integration
Hasan Genc, Seah Kim, Alon Amid +16
cs.DCcs.ARcs.LGarXiv:1911.09925v32019
Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking
Zhe Jia, Marco Maggioni, Benjamin Staiger +1
cs.DCcs.PFarXiv:1804.06826v12018
Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters
Hao Zhang, Zeyu Zheng, Shizhen Xu +7
cs.LGcs.CVcs.DCarXiv:1706.03292v12017
MeshReduce-U: Compiler-Guided Communication Reduction for Irregular Neural Reductions on Mesh NoCs
Amirreza Khorasanian
cs.ARcs.DCarXiv:2608.26220v12026
Benchmarking Confidential Computing Performance on NVIDIA Blackwell GPUs
Daniyal Khan, Amean Asad, Ansgar Grunseid
cs.DCcs.CRarXiv:2608.26575v12026
MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs
Ziheng Jiang, Haibin Lin, Yinmin Zhong +29
cs.LGcs.DCarXiv:2402.15627v12024
Distributed Stochastic Gradient Tracking Methods
Shi Pu, Angelia Nedić
math.OCcs.DCcs.SIarXiv:1805.11454v52018
Decentralized Federated Averaging
Tao Sun, Dongsheng Li, Bao Wang
cs.DCstat.MLarXiv:2104.11375v12021
Distillation-Based Semi-Supervised Federated Learning for Communication-Efficient Collaborative Training with Non-IID Private Data
Sohei Itahara, Takayuki Nishio, Yusuke Koda +2
cs.DCcs.LGarXiv:2008.06180v22020
Analysis of Bitcoin Pooled Mining Reward Systems
Meni Rosenfeld
cs.DCarXiv:1112.4980v12011
FIRM: An Intelligent Fine-Grained Resource Management Framework for SLO-Oriented Microservices
Haoran Qiu, Subho S. Banerjee, Saurabh Jha +2
cs.DCcs.PFarXiv:2008.08509v22020
A Parallel Random Forest Algorithm for Big Data in a Spark Cloud Computing Environment
Jianguo Chen, Kenli Li, Zhuo Tang +4
cs.DCarXiv:1810.07748v12018
Multi-Dataset Inverse Problem Solving with Distributed Generative AI
Daniel Lersch, Steven Goldenberg, Johann Rudi +5
cs.DCcs.LGarXiv:2608.26283v12026
ATOMO: Communication-efficient Learning via Atomic Sparsification
Hongyi Wang, Scott Sievert, Zachary Charles +3
stat.MLcs.DCcs.LGarXiv:1806.04090v32018
VPP: Virtual Pipeline Parallelism for Efficient Chunked Prefill in Long-Context LLM Inference
Yan Shi, Xiaochao Wang, Jingchun Gao +7
cs.DCarXiv:2608.26523v12026
Towards Reproducible Evaluation of Distributed Quantum Circuit Partitioning Algorithms
Javier Vela-Tambo, Davud Azizov, Tian Guo
quant-phcs.DCarXiv:2608.27099v12026
Hierarchical Federated Learning Across Heterogeneous Cellular Networks
Mehdi Salehi Heydar Abad, Emre Ozfatura, Deniz Gunduz +1
cs.LGcs.DCcs.ITarXiv:1909.02362v12019
Accelerated, Parallel and Proximal Coordinate Descent
Olivier Fercoq, Peter Richtárik
math.OCcs.DCmath.NAarXiv:1312.5799v22013
Asynchronous Federated Learning on Heterogeneous Devices: A Survey
Chenhao Xu, Youyang Qu, Yong Xiang +1
cs.DCarXiv:2109.04269v52021
One-Bit Over-the-Air Aggregation for Communication-Efficient Federated Edge Learning: Design and Convergence Analysis
Guangxu Zhu, Yuqing Du, Deniz Gunduz +1
cs.ITcs.DCcs.NIarXiv:2001.05713v22020
Edge Intelligence: On-Demand Deep Learning Model Co-Inference with Device-Edge Synergy
En Li, Zhi Zhou, Xu Chen
cs.DCcs.AIcs.CVarXiv:1806.07840v42018
A Byzantine Fault-Tolerant Ordering Service for the Hyperledger Fabric Blockchain Platform
João Sousa, Alysson Bessani, Marko Vukolić
cs.CRcs.DCarXiv:1709.06921v12017
Community Cloud Computing
Alexandros Marinos, Gerard Briscoe
cs.NIcs.DCcs.SEarXiv:0907.2485v32009
FedHome: Cloud-Edge based Personalized Federated Learning for In-Home Health Monitoring
Qiong Wu, Xu Chen, Zhi Zhou +1
cs.NIcs.AIcs.DCarXiv:2012.07450v12020
Vertical Federated Learning: Concepts, Advances and Challenges
Yang Liu, Yan Kang, Tianyuan Zou +6
cs.LGcs.AIcs.CRarXiv:2211.12814v42022
D$^2$: Decentralized Training over Decentralized Data
Hanlin Tang, Xiangru Lian, Ming Yan +2
cs.DCcs.LGstat.MLarXiv:1803.07068v22018
Computing Systems for Autonomous Driving: State-of-the-Art and Challenges
Liangkai Liu, Sidi Lu, Ren Zhong +4
cs.DCcs.ROarXiv:2009.14349v32020
AI and Memory Wall
Amir Gholami, Zhewei Yao, Sehoon Kim +3
cs.LGcs.ARcs.DCarXiv:2403.14123v12024
Toward Cloud-based Vehicular Networks with Efficient Resource Management
Rong Yu, Yan Zhang, Stein Gjessing +2
cs.DCcs.NIarXiv:1308.6208v12013
Federated Learning over Wireless Networks: Convergence Analysis and Resource Allocation
Canh T. Dinh, Nguyen H. Tran, Minh N. H. Nguyen +4
cs.LGcs.DCcs.NIarXiv:1910.13067v42019
The latest gossip on BFT consensus
Ethan Buchman, Jae Kwon, Zarko Milosevic
cs.DCarXiv:1807.04938v32018
Stochastic Gradient Push for Distributed Deep Learning
Mahmoud Assran, Nicolas Loizou, Nicolas Ballas +1
cs.LGcs.AIcs.DCarXiv:1811.10792v32018
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning
Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri +3
cs.LGcs.DCmath.OCarXiv:1910.06378v42019
FastFabric: Scaling Hyperledger Fabric to 20,000 Transactions per Second
Christian Gorenflo, Stephen Lee, Lukasz Golab +1
cs.DCarXiv:1901.00910v22019
Perfect Reconstruction Two-Channel Wavelet Filter-Banks for Graph Structured Data
Sunil K. Narang, Antonio Ortega
cs.DCcs.SIarXiv:1106.3693v32011
Cloud Migration: A Case Study of Migrating an Enterprise IT System to IaaS
Ali Khajeh-Hosseini, David Greenwood, Ian Sommerville
cs.DCarXiv:1002.3492v12010
Distributed Training using an Intelligent Network
Nihar Shah, Ben Blier
cs.LGcs.DCcs.NIarXiv:2608.26453v12026
Narwhal and Tusk: A DAG-based Mempool and Efficient BFT Consensus
George Danezis, Eleftherios Kokoris Kogias, Alberto Sonnino +1
cs.CRcs.DCarXiv:2105.11827v42021
Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes
Xianyan Jia, Shutao Song, Wei He +11
cs.LGcs.DCstat.MLarXiv:1807.11205v12018
Quantum Computing: A Taxonomy, Systematic Review and Future Directions
Sukhpal Singh Gill, Adarsh Kumar, Harvinder Singh +4
cs.ETcs.DCarXiv:2010.15559v42020
Push-Pull Gradient Methods for Distributed Optimization in Networks
Shi Pu, Wei Shi, Jinming Xu +1
math.OCcs.DCcs.MAarXiv:1810.06653v42018
Peer-to-Peer Energy Systems for Connected Communities: A Review of Recent Advances and Emerging Challenges
Wayes Tushar, Chau Yuen, Tapan Saha +5
cs.DCarXiv:2011.11118v12020
Blockchain for Future Smart Grid: A Comprehensive Survey
Muhammad Baqer Mollah, Jun Zhao, Dusit Niyato +5
cs.CRcs.DCcs.NIarXiv:1911.03298v22019
HFEL: Joint Edge Association and Resource Allocation for Cost-Efficient Hierarchical Federated Edge Learning
Siqi Luo, Xu Chen, Qiong Wu +2
cs.DCarXiv:2002.11343v22020
SpecInfer: Accelerating Generative Large Language Model Serving with Tree-based Speculative Inference and Verification
Xupeng Miao, Gabriele Oliaro, Zhihao Zhang +12
cs.CLcs.DCcs.LGarXiv:2305.09781v42023
Parallel Physics-Informed Neural Networks via Domain Decomposition
Khemraj Shukla, Ameya D. Jagtap, George Em Karniadakis
cs.DCarXiv:2104.10013v32021
Follow Me at the Edge: Mobility-Aware Dynamic Service Placement for Mobile Edge Computing
Tao Ouyang, Zhi Zhou, Xu Chen
cs.NIcs.AIcs.DCarXiv:1809.05239v12018
Decoupled I/O-Dominant Pipelines for Large-Scale Whole-Slide Image Embedding Extraction
Mayanka Chandrashekar, Xi Zhang, Ethan Seefried +3
cs.DCcs.CVarXiv:2608.27278v12026

Distributed and Cluster Computing

Federated Learning: Opportunities and Challenges

Asynchronous Stochastic Gradient Descent with Delay Compensation

From Distributed Machine Learning to Federated Learning: A Survey

Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation

Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation

More Bang for Your Buck: Improved use of GPU Nodes for GROMACS 2018

TensorFlow-Serving: Flexible, High-Performance ML Serving

SPINN: Synergistic Progressive Inference of Neural Networks over Device and Cloud

Federated Learning with Cooperating Devices: A Consensus Approach for Massive IoT Networks

Federated Learning for Open Banking

FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout

Gemmini: Enabling Systematic Deep-Learning Architecture Evaluation via Full-Stack Integration

Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking

Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters

MeshReduce-U: Compiler-Guided Communication Reduction for Irregular Neural Reductions on Mesh NoCs

Benchmarking Confidential Computing Performance on NVIDIA Blackwell GPUs

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

Distributed Stochastic Gradient Tracking Methods

Decentralized Federated Averaging

Distillation-Based Semi-Supervised Federated Learning for Communication-Efficient Collaborative Training with Non-IID Private Data

Analysis of Bitcoin Pooled Mining Reward Systems

FIRM: An Intelligent Fine-Grained Resource Management Framework for SLO-Oriented Microservices

A Parallel Random Forest Algorithm for Big Data in a Spark Cloud Computing Environment

Multi-Dataset Inverse Problem Solving with Distributed Generative AI

ATOMO: Communication-efficient Learning via Atomic Sparsification

VPP: Virtual Pipeline Parallelism for Efficient Chunked Prefill in Long-Context LLM Inference

Towards Reproducible Evaluation of Distributed Quantum Circuit Partitioning Algorithms

Hierarchical Federated Learning Across Heterogeneous Cellular Networks

Accelerated, Parallel and Proximal Coordinate Descent

Asynchronous Federated Learning on Heterogeneous Devices: A Survey

One-Bit Over-the-Air Aggregation for Communication-Efficient Federated Edge Learning: Design and Convergence Analysis

Edge Intelligence: On-Demand Deep Learning Model Co-Inference with Device-Edge Synergy

A Byzantine Fault-Tolerant Ordering Service for the Hyperledger Fabric Blockchain Platform

Community Cloud Computing

FedHome: Cloud-Edge based Personalized Federated Learning for In-Home Health Monitoring

Vertical Federated Learning: Concepts, Advances and Challenges

D$^2$: Decentralized Training over Decentralized Data

Computing Systems for Autonomous Driving: State-of-the-Art and Challenges

AI and Memory Wall

Toward Cloud-based Vehicular Networks with Efficient Resource Management

Federated Learning over Wireless Networks: Convergence Analysis and Resource Allocation

The latest gossip on BFT consensus

Stochastic Gradient Push for Distributed Deep Learning

SCAFFOLD: Stochastic Controlled Averaging for Federated Learning

FastFabric: Scaling Hyperledger Fabric to 20,000 Transactions per Second

Perfect Reconstruction Two-Channel Wavelet Filter-Banks for Graph Structured Data

Cloud Migration: A Case Study of Migrating an Enterprise IT System to IaaS

Distributed Training using an Intelligent Network

Narwhal and Tusk: A DAG-based Mempool and Efficient BFT Consensus

Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes

Quantum Computing: A Taxonomy, Systematic Review and Future Directions

Push-Pull Gradient Methods for Distributed Optimization in Networks

Peer-to-Peer Energy Systems for Connected Communities: A Review of Recent Advances and Emerging Challenges

Blockchain for Future Smart Grid: A Comprehensive Survey

HFEL: Joint Edge Association and Resource Allocation for Cost-Efficient Hierarchical Federated Edge Learning

SpecInfer: Accelerating Generative Large Language Model Serving with Tree-based Speculative Inference and Verification

Parallel Physics-Informed Neural Networks via Domain Decomposition

Follow Me at the Edge: Mobility-Aware Dynamic Service Placement for Mobile Edge Computing

Decoupled I/O-Dominant Pipelines for Large-Scale Whole-Slide Image Embedding Extraction