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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721 to 780 of 1,072

An Efficiency-boosting Client Selection Scheme for Federated Learning with Fairness Guarantee
Tiansheng Huang, Weiwei Lin, Wentai Wu +3
cs.LGcs.DCarXiv:2011.01783v52020
SpArch: Efficient Architecture for Sparse Matrix Multiplication
Zhekai Zhang, Hanrui Wang, Song Han +1
cs.ARcs.DCarXiv:2002.08947v12020
Generalized Byzantine-tolerant SGD
Cong Xie, Oluwasanmi Koyejo, Indranil Gupta
cs.DCstat.MLarXiv:1802.10116v32018
Memory-Efficient Pipeline-Parallel DNN Training
Deepak Narayanan, Amar Phanishayee, Kaiyu Shi +2
cs.LGcs.DCstat.MLarXiv:2006.09503v32020
Focus: Querying Large Video Datasets with Low Latency and Low Cost
Kevin Hsieh, Ganesh Ananthanarayanan, Peter Bodik +4
cs.DBcs.CVcs.DCarXiv:1801.03493v12018
The blockchain: a new framework for robotic swarm systems
Eduardo Castelló Ferrer
cs.ROcs.DCcs.ETarXiv:1608.00695v42016
PINT: Probabilistic In-band Network Telemetry
Ran Ben Basat, Sivaramakrishnan Ramanathan, Yuliang Li +3
cs.NIcs.DCarXiv:2007.03731v12020
Parallel and Distributed Methods for Nonconvex Optimization--Part II: Applications
Gesualdo Scutari, Francisco Facchinei, Lorenzo Lampariello +2
cs.ITcs.DCarXiv:1601.04059v12016
Differentially Private Distributed Optimization
Zhenqi Huang, Sayan Mitra, Nitin Vaidya
cs.CRcs.DCarXiv:1401.2596v12014
Optimal Edge User Allocation in Edge Computing with Variable Sized Vector Bin Packing
Phu Lai, Qiang He, Mohamed Abdelrazek +4
cs.DCarXiv:1904.05553v12019
All You Need is DAG
Idit Keidar, Eleftherios Kokoris-Kogias, Oded Naor +1
cs.DCarXiv:2102.08325v22021
A$^3$: Accelerating Attention Mechanisms in Neural Networks with Approximation
Tae Jun Ham, Sung Jun Jung, Seonghak Kim +8
cs.DCcs.LGarXiv:2002.10941v12020
JointDNN: An Efficient Training and Inference Engine for Intelligent Mobile Cloud Computing Services
Amir Erfan Eshratifar, Mohammad Saeed Abrishami, Massoud Pedram
cs.DCcs.AIcs.LGarXiv:1801.08618v22018
Communication Compression for Decentralized Training
Hanlin Tang, Shaoduo Gan, Ce Zhang +2
cs.LGcs.DCeess.SYarXiv:1803.06443v52018
The Locality of Distributed Symmetry Breaking
Leonid Barenboim, Michael Elkin, Seth Pettie +1
cs.DCarXiv:1202.1983v32012
Deep Rewiring: Training very sparse deep networks
Guillaume Bellec, David Kappel, Wolfgang Maass +1
cs.NEcs.AIcs.DCarXiv:1711.05136v52017
Tiramisu: A Polyhedral Compiler for Expressing Fast and Portable Code
Riyadh Baghdadi, Jessica Ray, Malek Ben Romdhane +6
cs.PLcs.DCcs.MSarXiv:1804.10694v52018
Salvaging Federated Learning by Local Adaptation
Tao Yu, Eugene Bagdasaryan, Vitaly Shmatikov
cs.LGcs.AIcs.DCarXiv:2002.04758v32020
DFINITY Technology Overview Series, Consensus System
Timo Hanke, Mahnush Movahedi, Dominic Williams
cs.DCarXiv:1805.04548v12018
Carbon-Aware Computing for Datacenters
Ana Radovanovic, Ross Koningstein, Ian Schneider +12
cs.DCeess.SYarXiv:2106.11750v12021
Stochastic Controlled Averaging for Federated Learning with Communication Compression
Xinmeng Huang, Ping Li, Xiaoyun Li
math.OCcs.DCcs.LGarXiv:2308.08165v22023
Heterogeneity-Aware Cluster Scheduling Policies for Deep Learning Workloads
Deepak Narayanan, Keshav Santhanam, Fiodar Kazhamiaka +2
cs.DCarXiv:2008.09213v12020
On the Optimal Recovery Threshold of Coded Matrix Multiplication
Sanghamitra Dutta, Mohammad Fahim, Farzin Haddadpour +3
cs.ITcs.DCarXiv:1801.10292v22018
Extremely Large Minibatch SGD: Training ResNet-50 on ImageNet in 15 Minutes
Takuya Akiba, Shuji Suzuki, Keisuke Fukuda
cs.DCcs.CVcs.LGarXiv:1711.04325v12017
Semantic Gateway as a Service architecture for IoT Interoperability
Pratikkumar Desai, Amit Sheth, Pramod Anantharam
cs.NIcs.DCarXiv:1410.4977v12014
Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect
Ang Li, Shuaiwen Leon Song, Jieyang Chen +4
cs.ARcs.DCcs.NIarXiv:1903.04611v12019
DLAU: A Scalable Deep Learning Accelerator Unit on FPGA
Chao Wang, Qi Yu, Lei Gong +3
cs.LGcs.DCcs.NEarXiv:1605.06894v12016
On the Convergence of Local Descent Methods in Federated Learning
Farzin Haddadpour, Mehrdad Mahdavi
cs.LGcs.DCstat.MLarXiv:1910.14425v22019
PipeDream: Fast and Efficient Pipeline Parallel DNN Training
Aaron Harlap, Deepak Narayanan, Amar Phanishayee +4
cs.DCarXiv:1806.03377v12018
Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning
Haibo Yang, Minghong Fang, Jia Liu
cs.LGcs.DCarXiv:2101.11203v32021
PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments
Fan Mo, Hamed Haddadi, Kleomenis Katevas +3
cs.CRcs.DCcs.LGarXiv:2104.14380v22021
CoEdge: Cooperative DNN Inference with Adaptive Workload Partitioning over Heterogeneous Edge Devices
Liekang Zeng, Xu Chen, Zhi Zhou +2
cs.NIcs.CVcs.DCarXiv:2012.03257v12020
Byzantine Stochastic Gradient Descent
Dan Alistarh, Zeyuan Allen-Zhu, Jerry Li
cs.LGcs.DCcs.DSarXiv:1803.08917v12018
CSR5: An Efficient Storage Format for Cross-Platform Sparse Matrix-Vector Multiplication
Weifeng Liu, Brian Vinter
cs.MScs.DCmath.NAarXiv:1503.05032v22015
Intent Engine: Natural-Language Intent Translation for Intent-Driven Orchestration in the Compute Continuum
Koushikur Islam, Rodrigo N. Calheiros
cs.CLcs.DCarXiv:2608.20388v12026
Verified Detection and Prevention of Concurrency Anomalies in Multi-Agent Large Language Model Systems
Sajjad Khan
cs.LGcs.DCcs.LOarXiv:2606.17182v12026
HybridFlow: A Flexible and Efficient RLHF Framework
Guangming Sheng, Chi Zhang, Zilingfeng Ye +6
cs.LGcs.DCarXiv:2409.19256v22024
A Solution to the Network Challenges of Data Recovery in Erasure-coded Distributed Storage Systems: A Study on the Facebook Warehouse Cluster
K. V. Rashmi, Nihar B. Shah, Dikang Gu +3
cs.NIcs.DCcs.ITarXiv:1309.0186v12013
Byzantine-Resilient Secure Federated Learning
Jinhyun So, Basak Guler, A. Salman Avestimehr
cs.CRcs.DCcs.LGarXiv:2007.11115v22020
LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning
Tianyi Chen, Georgios B. Giannakis, Tao Sun +1
stat.MLcs.DCcs.LGarXiv:1805.09965v22018
Dynamic scheduling of virtual machines running hpc workloads in scientific grids
Omer Khalid, Ivo Maljevic, Richard Anthony +3
cs.DCcs.DScs.PFarXiv:1009.4841v12010
The Internet of Things, Fog and Cloud Continuum: Integration and Challenges
Luiz F. Bittencourt, Roger Immich, Rizos Sakellariou +7
cs.DCarXiv:1809.09972v12018
The Cloud Adoption Toolkit: Supporting Cloud Adoption Decisions in the Enterprise
Ali Khajeh-Hosseini, David Greenwood, James W. Smith +1
cs.DCarXiv:1008.1900v12010
DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs
Da Zheng, Chao Ma, Minjie Wang +6
cs.LGcs.DCarXiv:2010.05337v32020
Parsl: Pervasive Parallel Programming in Python
Yadu Babuji, Anna Woodard, Zhuozhao Li +9
cs.DCcs.PLarXiv:1905.02158v22019
Interactive Supercomputing on 40,000 Cores for Machine Learning and Data Analysis
Albert Reuther, Jeremy Kepner, Chansup Byun +15
cs.DCarXiv:1807.07814v12018
Benchmarking State-of-the-Art Deep Learning Software Tools
Shaohuai Shi, Qiang Wang, Pengfei Xu +1
cs.DCcs.LGarXiv:1608.07249v72016
A Review on Industrial Augmented Reality Systems for the Industry 4.0 Shipyard
Paula Fraga-Lamas, Tiago M Fernandez-Carames, Oscar Blanco-Novoa +1
cs.DCcs.HCarXiv:2405.00010v12024
Federated Learning with Compression: Unified Analysis and Sharp Guarantees
Farzin Haddadpour, Mohammad Mahdi Kamani, Aryan Mokhtari +1
cs.LGcs.DCstat.MLarXiv:2007.01154v22020
Decentralized Federated Learning: A Survey and Perspective
Liangqi Yuan, Ziran Wang, Lichao Sun +2
cs.LGcs.CYcs.DCarXiv:2306.01603v22023
Distributed Online Optimization in Dynamic Environments Using Mirror Descent
Shahin Shahrampour, Ali Jadbabaie
math.OCcs.DCcs.LGarXiv:1609.02845v12016
Asymptotically Exact, Embarrassingly Parallel MCMC
Willie Neiswanger, Chong Wang, Eric Xing
stat.MLcs.DCcs.LGarXiv:1311.4780v22013
DMTCP: Transparent Checkpointing for Cluster Computations and the Desktop
Jason Ansel, Kapil Arya, Gene Cooperman
cs.DCcs.OSarXiv:cs/0701037v32007
TPP: Transparent Page Placement for CXL-Enabled Tiered-Memory
Hasan Al Maruf, Hao Wang, Abhishek Dhanotia +7
cs.DCcs.OSarXiv:2206.02878v22022
Fast Adaptive Task Offloading in Edge Computing based on Meta Reinforcement Learning
Jin Wang, Jia Hu, Geyong Min +2
cs.DCcs.LGarXiv:2008.02033v52020
Personalized Federated Learning for Intelligent IoT Applications: A Cloud-Edge based Framework
Qiong Wu, Kaiwen He, Xu Chen
cs.NIcs.DCcs.LGarXiv:2002.10671v32020
FogBus: A Blockchain-based Lightweight Framework for Edge and Fog Computing
Shreshth Tuli, Redowan Mahmud, Shikhar Tuli +1
cs.DCarXiv:1811.11978v12018
DAPPLE: A Pipelined Data Parallel Approach for Training Large Models
Shiqing Fan, Yi Rong, Chen Meng +10
cs.DCarXiv:2007.01045v12020
From Words to Watts: Benchmarking the Energy Costs of Large Language Model Inference
Siddharth Samsi, Dan Zhao, Joseph McDonald +7
cs.CLcs.DCarXiv:2310.03003v12023
HyGCN: A GCN Accelerator with Hybrid Architecture
Mingyu Yan, Lei Deng, Xing Hu +6
cs.DCarXiv:2001.02514v12020

Distributed and Cluster Computing

An Efficiency-boosting Client Selection Scheme for Federated Learning with Fairness Guarantee

SpArch: Efficient Architecture for Sparse Matrix Multiplication

Generalized Byzantine-tolerant SGD

Memory-Efficient Pipeline-Parallel DNN Training

Focus: Querying Large Video Datasets with Low Latency and Low Cost

The blockchain: a new framework for robotic swarm systems

PINT: Probabilistic In-band Network Telemetry

Parallel and Distributed Methods for Nonconvex Optimization--Part II: Applications

Differentially Private Distributed Optimization

Optimal Edge User Allocation in Edge Computing with Variable Sized Vector Bin Packing

All You Need is DAG

A$^3$: Accelerating Attention Mechanisms in Neural Networks with Approximation

JointDNN: An Efficient Training and Inference Engine for Intelligent Mobile Cloud Computing Services

Communication Compression for Decentralized Training

The Locality of Distributed Symmetry Breaking

Deep Rewiring: Training very sparse deep networks

Tiramisu: A Polyhedral Compiler for Expressing Fast and Portable Code

Salvaging Federated Learning by Local Adaptation

DFINITY Technology Overview Series, Consensus System

Carbon-Aware Computing for Datacenters

Stochastic Controlled Averaging for Federated Learning with Communication Compression

Heterogeneity-Aware Cluster Scheduling Policies for Deep Learning Workloads

On the Optimal Recovery Threshold of Coded Matrix Multiplication

Extremely Large Minibatch SGD: Training ResNet-50 on ImageNet in 15 Minutes

Semantic Gateway as a Service architecture for IoT Interoperability

Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect

DLAU: A Scalable Deep Learning Accelerator Unit on FPGA

On the Convergence of Local Descent Methods in Federated Learning

PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning

PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments

CoEdge: Cooperative DNN Inference with Adaptive Workload Partitioning over Heterogeneous Edge Devices

Byzantine Stochastic Gradient Descent

CSR5: An Efficient Storage Format for Cross-Platform Sparse Matrix-Vector Multiplication

Intent Engine: Natural-Language Intent Translation for Intent-Driven Orchestration in the Compute Continuum

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

HybridFlow: A Flexible and Efficient RLHF Framework

A Solution to the Network Challenges of Data Recovery in Erasure-coded Distributed Storage Systems: A Study on the Facebook Warehouse Cluster

Byzantine-Resilient Secure Federated Learning

LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning

Dynamic scheduling of virtual machines running hpc workloads in scientific grids

The Internet of Things, Fog and Cloud Continuum: Integration and Challenges

The Cloud Adoption Toolkit: Supporting Cloud Adoption Decisions in the Enterprise

DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs

Parsl: Pervasive Parallel Programming in Python

Interactive Supercomputing on 40,000 Cores for Machine Learning and Data Analysis

Benchmarking State-of-the-Art Deep Learning Software Tools

A Review on Industrial Augmented Reality Systems for the Industry 4.0 Shipyard

Federated Learning with Compression: Unified Analysis and Sharp Guarantees

Decentralized Federated Learning: A Survey and Perspective

Distributed Online Optimization in Dynamic Environments Using Mirror Descent

Asymptotically Exact, Embarrassingly Parallel MCMC

DMTCP: Transparent Checkpointing for Cluster Computations and the Desktop

TPP: Transparent Page Placement for CXL-Enabled Tiered-Memory

Fast Adaptive Task Offloading in Edge Computing based on Meta Reinforcement Learning

Personalized Federated Learning for Intelligent IoT Applications: A Cloud-Edge based Framework

FogBus: A Blockchain-based Lightweight Framework for Edge and Fog Computing

DAPPLE: A Pipelined Data Parallel Approach for Training Large Models

From Words to Watts: Benchmarking the Energy Costs of Large Language Model Inference

HyGCN: A GCN Accelerator with Hybrid Architecture