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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601 to 660 of 1,071

FedMix: Approximation of Mixup under Mean Augmented Federated Learning
Tehrim Yoon, Sumin Shin, Sung Ju Hwang +1
cs.LGcs.AIcs.CVarXiv:2107.00233v12021
A unified sparse matrix data format for efficient general sparse matrix-vector multiply on modern processors with wide SIMD units
Moritz Kreutzer, Georg Hager, Gerhard Wellein +2
cs.MScs.DCarXiv:1307.6209v22013
OpenFedLLM: Training Large Language Models on Decentralized Private Data via Federated Learning
Rui Ye, Wenhao Wang, Jingyi Chai +6
cs.LGcs.CLcs.DCarXiv:2402.06954v12024
Scalable Byzantine Consensus via Hardware-assisted Secret Sharing
Jian Liu, Wenting Li, Ghassan O. Karame +1
cs.CRcs.DCarXiv:1612.04997v52016
DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression
Hanlin Tang, Xiangru Lian, Chen Yu +2
cs.DCcs.LGarXiv:1905.05957v32019
Massively Parallel Probabilistic Computing with Sparse Ising Machines
Navid Anjum Aadit, Andrea Grimaldi, Mario Carpentieri +4
cs.ETcond-mat.dis-nncs.DCarXiv:2110.02481v22021
Effective Extensible Programming: Unleashing Julia on GPUs
Tim Besard, Christophe Foket, Bjorn De Sutter
cs.PLcs.DCarXiv:1712.03112v12017
Mooncake: A KVCache-centric Disaggregated Architecture for LLM Serving
Ruoyu Qin, Zheming Li, Weiran He +4
cs.DCcs.AIcs.ARarXiv:2407.00079v42024
Dissecting GPU Memory Hierarchy through Microbenchmarking
Xinxin Mei, Xiaowen Chu
cs.ARcs.DCarXiv:1509.02308v22015
Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication
Felix Sattler, Simon Wiedemann, Klaus-Robert Müller +1
cs.LGcs.AIcs.DCarXiv:1805.08768v12018
Federated Learning with Partial Model Personalization
Krishna Pillutla, Kshitiz Malik, Abdelrahman Mohamed +3
cs.LGcs.DCmath.OCarXiv:2204.03809v22022
A Review on the Application of Blockchain for the Next Generation of Cybersecure Industry 4.0 Smart Factories
Tiago M. Fernandez-Carames, Paula Fraga-Lamas
cs.DCcs.CRcs.CYarXiv:1902.09604v22019
On Biased Compression for Distributed Learning
Aleksandr Beznosikov, Samuel Horváth, Peter Richtárik +1
cs.LGcs.DCmath.OCarXiv:2002.12410v42020
Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning
Matias Mendieta, Taojiannan Yang, Pu Wang +3
cs.LGcs.CVcs.DCarXiv:2111.14213v32021
End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things
Yansong Gao, Minki Kim, Sharif Abuadbba +6
cs.CRcs.DCcs.LGarXiv:2003.13376v22020
A Multi-Threaded Version of MCFM
John M. Campbell, R. Keith Ellis, Walter T. Giele
physics.comp-phcs.DCcs.MSarXiv:1503.06182v12015
Coded Computation over Heterogeneous Clusters
Amirhossein Reisizadeh, Saurav Prakash, Ramtin Pedarsani +1
cs.DCcs.ITarXiv:1701.05973v52017
Astraea: Self-balancing Federated Learning for Improving Classification Accuracy of Mobile Deep Learning Applications
Moming Duan, Duo Liu, Xianzhang Chen +4
cs.LGcs.DCstat.MLarXiv:1907.01132v22019
A Distributed Algorithm for Solving a Linear Algebraic Equation
Shaoshuai Mou, Ji Liu, A. Stephen Morse
eess.SYcs.DCcs.MAarXiv:1503.00808v12015
Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization
Paras Jain, Ajay Jain, Aniruddha Nrusimha +5
cs.LGcs.CVcs.DCarXiv:1910.02653v32019
When the Curious Abandon Honesty: Federated Learning Is Not Private
Franziska Boenisch, Adam Dziedzic, Roei Schuster +3
cs.LGcs.CRcs.DCarXiv:2112.02918v22021
On the convergence properties of a $K$-step averaging stochastic gradient descent algorithm for nonconvex optimization
Fan Zhou, Guojing Cong
cs.LGcs.DCstat.MLarXiv:1708.01012v32017
Fast O(1) bilateral filtering using trigonometric range kernels
Kunal Narayan Chaudhury, Daniel Sage, Michael Unser
cs.CVcs.CEcs.DCarXiv:1105.4204v32011
DMRO:A Deep Meta Reinforcement Learning-based Task Offloading Framework for Edge-Cloud Computing
Guanjin Qu, Huaming Wu
cs.DCeess.SParXiv:2008.09930v12020
Optimal Client Sampling for Federated Learning
Wenlin Chen, Samuel Horvath, Peter Richtarik
cs.LGcs.DCarXiv:2010.13723v32020
Benchmarking, Analysis, and Optimization of Serverless Function Snapshots
Dmitrii Ustiugov, Plamen Petrov, Marios Kogias +2
cs.DCarXiv:2101.09355v32021
Perturbed Iterate Analysis for Asynchronous Stochastic Optimization
Horia Mania, Xinghao Pan, Dimitris Papailiopoulos +3
stat.MLcs.DCcs.DSarXiv:1507.06970v22015
Decentralized Collaborative Learning of Personalized Models over Networks
Paul Vanhaesebrouck, Aurélien Bellet, Marc Tommasi
cs.LGcs.AIcs.DCarXiv:1610.05202v22016
MegaBlocks: Efficient Sparse Training with Mixture-of-Experts
Trevor Gale, Deepak Narayanan, Cliff Young +1
cs.LGcs.AIcs.DCarXiv:2211.15841v12022
FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction
Samiul Alam, Luyang Liu, Ming Yan +1
cs.LGcs.CRcs.CVarXiv:2212.01548v22022
Settling Payments Fast and Private: Efficient Decentralized Routing for Path-Based Transactions
Stefanie Roos, Pedro Moreno-Sanchez, Aniket Kate +1
cs.CRcs.DCarXiv:1709.05748v22017
Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning
Sai Praneeth Karimireddy, Martin Jaggi, Satyen Kale +4
cs.LGcs.DCmath.OCarXiv:2008.03606v22020
PatDNN: Achieving Real-Time DNN Execution on Mobile Devices with Pattern-based Weight Pruning
Wei Niu, Xiaolong Ma, Sheng Lin +5
cs.LGcs.CVcs.DCarXiv:2001.00138v42020
SCARFF: a Scalable Framework for Streaming Credit Card Fraud Detection with Spark
Fabrizio Carcillo, Andrea Dal Pozzolo, Yann-Aël Le Borgne +3
cs.DCarXiv:1709.08920v12017
Self-repairing Homomorphic Codes for Distributed Storage Systems
Frederique Oggier, Anwitaman Datta
cs.DCarXiv:1008.0064v12010
The Deep Learning Compiler: A Comprehensive Survey
Mingzhen Li, Yi Liu, Xiaoyan Liu +7
cs.DCcs.LGcs.PFarXiv:2002.03794v42020
No Silver Bullet: Boosting GaussDB Performance on the 30TB TPC-H Workload
Tim Zeyl, Jason Lam, Shu Lin +15
cs.DBcs.DCarXiv:2608.28352v12026
Relaxed Sender Anonymity for CBDC Interbank Settlement: A Zero-Knowledge Approach on Permissioned EVM
Pietro Tiberi, Gabriele Marcelli, Vitangelo Lasorella
cs.CRcs.DCarXiv:2608.28529v12026
An OpenCL(TM) Deep Learning Accelerator on Arria 10
Utku Aydonat, Shane O'Connell, Davor Capalija +2
cs.DCcs.ARcs.CVarXiv:1701.03534v12017
Mathematical Foundations of the GraphBLAS
Jeremy Kepner, Peter Aaltonen, David Bader +13
cs.MSastro-ph.IMcs.DCarXiv:1606.05790v22016
Parallel Breadth-First Search on Distributed Memory Systems
Aydin Buluc, Kamesh Madduri
cs.DCcs.MScs.PFarXiv:1104.4518v22011
A Performance Comparison of CUDA and OpenCL
Kamran Karimi, Neil G. Dickson, Firas Hamze
cs.PFcs.DCphysics.comp-pharXiv:1005.2581v32010
AI Hardware Accelerators for Large Language Models: Architectures and the Memory Wall
Siddharth Patel, Rohit Singh
cs.ARcs.DCarXiv:2608.28048v12026
TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning
Youngeun Kwon, Yunjae Lee, Minsoo Rhu
cs.LGcs.ARcs.DCarXiv:1908.03072v22019
Fast-Convergent Federated Learning
Hung T. Nguyen, Vikash Sehwag, Seyyedali Hosseinalipour +3
cs.LGcs.DCarXiv:2007.13137v22020
Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization
Jiaxiang Wu, Weidong Huang, Junzhou Huang +1
cs.CVcs.DCarXiv:1806.08054v12018
Adaptive Communication Strategies to Achieve the Best Error-Runtime Trade-off in Local-Update SGD
Jianyu Wang, Gauri Joshi
cs.LGcs.DCstat.MLarXiv:1810.08313v22018
HARTS: Efficient Agentic Reinforcement Learning for Hybrid-Attention Models over Arbitrary Rollout Trees
Boyuan Meng, Peihua Bao, Hong Liu +4
cs.LGcs.DCarXiv:2608.28158v12026
Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling
Bing Luo, Wenli Xiao, Shiqiang Wang +2
cs.LGcs.AIcs.DCarXiv:2112.11256v12021
Themis: Fair and Efficient GPU Cluster Scheduling
Kshiteej Mahajan, Arjun Balasubramanian, Arjun Singhvi +4
cs.DCarXiv:1907.01484v22019
Great Expectations: Benchmarking the Real-World Performance of RVV 1.0 in HPC
Stepan Nassyr, Prateek Chawla, Daniel Seibel +3
cs.DCcs.ARcs.ETarXiv:2608.28097v12026
Exact Gaussian Processes on a Million Data Points
Ke Alexander Wang, Geoff Pleiss, Jacob R. Gardner +3
cs.LGcs.DCstat.MLarXiv:1903.08114v22019
Distributed Coordinate Descent Method for Learning with Big Data
Peter Richtárik, Martin Takáč
stat.MLcs.DCcs.LGarXiv:1310.2059v12013
P3DFFT: a framework for parallel computations of Fourier transforms in three dimensions
Dmitry Pekurovsky
cs.DCcs.MSarXiv:1905.02803v12019
Dynamic Fusion based Federated Learning for COVID-19 Detection
Weishan Zhang, Tao Zhou, Qinghua Lu +6
cs.DCcs.LGarXiv:2009.10401v42020
Proof of Luck: an Efficient Blockchain Consensus Protocol
Mitar Milutinovic, Warren He, Howard Wu +1
cs.CRcs.DCarXiv:1703.05435v12017
Parameterized Knowledge Transfer for Personalized Federated Learning
Jie Zhang, Song Guo, Xiaosong Ma +3
cs.LGcs.DCarXiv:2111.02862v12021
Survey of clustering algorithms for MANET
Ratish Agarwal, Dr. Mahesh Motwani
cs.DCcs.NIarXiv:0912.2303v12009
Live Service Migration in Mobile Edge Clouds
Andrew Machen, Shiqiang Wang, Kin K. Leung +2
cs.DCcs.NIarXiv:1706.04118v22017
Distributed Storage Codes with Repair-by-Transfer and Non-achievability of Interior Points on the Storage-Bandwidth Tradeoff
Nihar B. Shah, K. V. Rashmi, P. Vijay Kumar +1
cs.ITcs.DCcs.NIarXiv:1011.2361v22010

Distributed and Cluster Computing

FedMix: Approximation of Mixup under Mean Augmented Federated Learning

A unified sparse matrix data format for efficient general sparse matrix-vector multiply on modern processors with wide SIMD units

OpenFedLLM: Training Large Language Models on Decentralized Private Data via Federated Learning

Scalable Byzantine Consensus via Hardware-assisted Secret Sharing

DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression

Massively Parallel Probabilistic Computing with Sparse Ising Machines

Effective Extensible Programming: Unleashing Julia on GPUs

Mooncake: A KVCache-centric Disaggregated Architecture for LLM Serving

Dissecting GPU Memory Hierarchy through Microbenchmarking

Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication

Federated Learning with Partial Model Personalization

A Review on the Application of Blockchain for the Next Generation of Cybersecure Industry 4.0 Smart Factories

On Biased Compression for Distributed Learning

Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning

End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things

A Multi-Threaded Version of MCFM

Coded Computation over Heterogeneous Clusters

Astraea: Self-balancing Federated Learning for Improving Classification Accuracy of Mobile Deep Learning Applications

A Distributed Algorithm for Solving a Linear Algebraic Equation

Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization

When the Curious Abandon Honesty: Federated Learning Is Not Private

On the convergence properties of a $K$-step averaging stochastic gradient descent algorithm for nonconvex optimization

Fast O(1) bilateral filtering using trigonometric range kernels

DMRO:A Deep Meta Reinforcement Learning-based Task Offloading Framework for Edge-Cloud Computing

Optimal Client Sampling for Federated Learning

Benchmarking, Analysis, and Optimization of Serverless Function Snapshots

Perturbed Iterate Analysis for Asynchronous Stochastic Optimization

Decentralized Collaborative Learning of Personalized Models over Networks

MegaBlocks: Efficient Sparse Training with Mixture-of-Experts

FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction

Settling Payments Fast and Private: Efficient Decentralized Routing for Path-Based Transactions

Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning

PatDNN: Achieving Real-Time DNN Execution on Mobile Devices with Pattern-based Weight Pruning

SCARFF: a Scalable Framework for Streaming Credit Card Fraud Detection with Spark

Self-repairing Homomorphic Codes for Distributed Storage Systems

The Deep Learning Compiler: A Comprehensive Survey

No Silver Bullet: Boosting GaussDB Performance on the 30TB TPC-H Workload

Relaxed Sender Anonymity for CBDC Interbank Settlement: A Zero-Knowledge Approach on Permissioned EVM

An OpenCL(TM) Deep Learning Accelerator on Arria 10

Mathematical Foundations of the GraphBLAS

Parallel Breadth-First Search on Distributed Memory Systems

A Performance Comparison of CUDA and OpenCL

AI Hardware Accelerators for Large Language Models: Architectures and the Memory Wall

TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning

Fast-Convergent Federated Learning

Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization

Adaptive Communication Strategies to Achieve the Best Error-Runtime Trade-off in Local-Update SGD

HARTS: Efficient Agentic Reinforcement Learning for Hybrid-Attention Models over Arbitrary Rollout Trees

Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling

Themis: Fair and Efficient GPU Cluster Scheduling

Great Expectations: Benchmarking the Real-World Performance of RVV 1.0 in HPC

Exact Gaussian Processes on a Million Data Points

Distributed Coordinate Descent Method for Learning with Big Data

P3DFFT: a framework for parallel computations of Fourier transforms in three dimensions

Dynamic Fusion based Federated Learning for COVID-19 Detection

Proof of Luck: an Efficient Blockchain Consensus Protocol

Parameterized Knowledge Transfer for Personalized Federated Learning

Survey of clustering algorithms for MANET

Live Service Migration in Mobile Edge Clouds

Distributed Storage Codes with Repair-by-Transfer and Non-achievability of Interior Points on the Storage-Bandwidth Tradeoff