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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1,561 to 1,620 of 1,781

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
AI and Memory Wall
Amir Gholami, Zhewei Yao, Sehoon Kim +3
cs.LGcs.ARcs.DCarXiv:2403.14123v12024
Pathways: Asynchronous Distributed Dataflow for ML
Paul Barham, Aakanksha Chowdhery, Jeff Dean +13
cs.DCcs.LGarXiv:2203.12533v12022
MegaBlocks: Efficient Sparse Training with Mixture-of-Experts
Trevor Gale, Deepak Narayanan, Cliff Young +1
cs.LGcs.AIcs.DCarXiv:2211.15841v12022
Split Learning in 6G Edge Networks
Zheng Lin, Guanqiao Qu, Xianhao Chen +1
cs.LGcs.DCcs.NIarXiv:2306.12194v32023
An Overview on Generative AI at Scale with Edge-Cloud Computing
Yun-Cheng Wang, Jintang Xue, Chengwei Wei +1
cs.DCcs.AIcs.SYarXiv:2306.17170v22023
Fast Distributed Inference Serving for Large Language Models
Bingyang Wu, Yinmin Zhong, Zili Zhang +6
cs.LGcs.DCarXiv:2305.05920v32023
Accelerating Distributed MoE Training and Inference with Lina
Jiamin Li, Yimin Jiang, Yibo Zhu +2
cs.DCarXiv:2210.17223v22022
Carbon-Aware Computing for Datacenters
Ana Radovanovic, Ross Koningstein, Ian Schneider +12
cs.DCeess.SYarXiv:2106.11750v12021
SZ3: A Modular Framework for Composing Prediction-Based Error-Bounded Lossy Compressors
Xin Liang, Kai Zhao, Sheng Di +9
cs.DCarXiv:2111.02925v22021
TinyOL: TinyML with Online-Learning on Microcontrollers
Haoyu Ren, Darko Anicic, Thomas Runkler
cs.LGcs.DCeess.SYarXiv:2103.08295v32021
Blockchain for Edge of Things: Applications, Opportunities, and Challenges
Thippa Reddy Gadekallu, Quoc-Viet Pham, Dinh C. Nguyen +6
cs.CRcs.DCarXiv:2110.05022v12021
FaaSNet: Scalable and Fast Provisioning of Custom Serverless Container Runtimes at Alibaba Cloud Function Compute
Ao Wang, Shuai Chang, Huangshi Tian +5
cs.DCarXiv:2105.11229v32021
From Federated Learning to Federated Neural Architecture Search: A Survey
Hangyu Zhu, Haoyu Zhang, Yaochu Jin
cs.DCarXiv:2009.05868v12020
Computing Systems for Autonomous Driving: State-of-the-Art and Challenges
Liangkai Liu, Sidi Lu, Ren Zhong +4
cs.DCcs.ROarXiv:2009.14349v32020
SeBS: A Serverless Benchmark Suite for Function-as-a-Service Computing
Marcin Copik, Grzegorz Kwasniewski, Maciej Besta +2
cs.DCarXiv:2012.14132v22020
Collaborative Federated Learning For Healthcare: Multi-Modal COVID-19 Diagnosis at the Edge
Adnan Qayyum, Kashif Ahmad, Muhammad Ahtazaz Ahsan +2
cs.LGcs.DCarXiv:2101.07511v12021
Dynamic Fusion based Federated Learning for COVID-19 Detection
Weishan Zhang, Tao Zhou, Qinghua Lu +6
cs.DCcs.LGarXiv:2009.10401v42020
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
Survey of Machine Learning Accelerators
Albert Reuther, Peter Michaleas, Michael Jones +3
cs.DCcs.LGarXiv:2009.00993v12020
A Survey on the Evolution of Stream Processing Systems
Marios Fragkoulis, Paris Carbone, Vasiliki Kalavri +1
cs.DCcs.CLcs.DBarXiv:2008.00842v22020
RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing
Liu Ke, Udit Gupta, Carole-Jean Wu +18
cs.DCcs.ARarXiv:1912.12953v12019
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
Samyam Rajbhandari, Jeff Rasley, Olatunji Ruwase +1
cs.LGcs.DCstat.MLarXiv:1910.02054v32019
DeepRecSys: A System for Optimizing End-To-End At-scale Neural Recommendation Inference
Udit Gupta, Samuel Hsia, Vikram Saraph +6
cs.DCarXiv:2001.02772v12020
Serverless in the Wild: Characterizing and Optimizing the Serverless Workload at a Large Cloud Provider
Mohammad Shahrad, Rodrigo Fonseca, Íñigo Goiri +7
cs.DCarXiv:2003.03423v32020
Gemmini: Enabling Systematic Deep-Learning Architecture Evaluation via Full-Stack Integration
Hasan Genc, Seah Kim, Alon Amid +16
cs.DCcs.ARcs.LGarXiv:1911.09925v32019
Edge Intelligence: Paving the Last Mile of Artificial Intelligence with Edge Computing
Zhi Zhou, Xu Chen, En Li +3
cs.DCcs.AIcs.NIarXiv:1905.10083v12019
The Architectural Implications of Facebook's DNN-based Personalized Recommendation
Udit Gupta, Carole-Jean Wu, Xiaodong Wang +12
cs.DCcs.LGarXiv:1906.03109v42019
Federated Learning: Challenges, Methods, and Future Directions
Tian Li, Anit Kumar Sahu, Ameet Talwalkar +1
cs.LGcs.DCstat.MLarXiv:1908.07873v12019
Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing
En Li, Liekang Zeng, Zhi Zhou +1
cs.NIcs.CVcs.DCarXiv:1910.05316v12019
MediaPipe: A Framework for Building Perception Pipelines
Camillo Lugaresi, Jiuqiang Tang, Hadon Nash +11
cs.DCarXiv:1906.08172v12019
Blockchain for Internet of Things: A Survey
Hong-Ning Dai, Zibin Zheng, Yan Zhang
cs.NIcs.DCcs.SEarXiv:1906.00245v52019
Effective Extensible Programming: Unleashing Julia on GPUs
Tim Besard, Christophe Foket, Bjorn De Sutter
cs.PLcs.DCarXiv:1712.03112v12017
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
Database Meets Deep Learning: Challenges and Opportunities
Wei Wang, Meihui Zhang, Gang Chen +3
cs.DBcs.DCcs.LGarXiv:1906.08986v22019
Basic Performance Measurements of the Intel Optane DC Persistent Memory Module
Joseph Izraelevitz, Jian Yang, Lu Zhang +9
cs.DCcs.PFarXiv:1903.05714v32019
Priority-based Parameter Propagation for Distributed DNN Training
Anand Jayarajan, Jinliang Wei, Garth Gibson +2
cs.DCcs.LGarXiv:1905.03960v12019
Rucio - Scientific data management
Martin Barisits, Thomas Beermann, Frank Berghaus +27
cs.DCarXiv:1902.09857v22019
FastFabric: Scaling Hyperledger Fabric to 20,000 Transactions per Second
Christian Gorenflo, Stephen Lee, Lukasz Golab +1
cs.DCarXiv:1901.00910v22019
High-Throughput CNN Inference on Embedded ARM big.LITTLE Multi-Core Processors
Siqi Wang, Gayathri Ananthanarayanan, Yifan Zeng +3
cs.LGcs.DCcs.PFarXiv:1903.05898v32019
Summaries:한국어
PipeDream: Fast and Efficient Pipeline Parallel DNN Training
Aaron Harlap, Deepak Narayanan, Amar Phanishayee +4
cs.DCarXiv:1806.03377v12018
Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training Workloads
Myeongjae Jeon, Shivaram Venkataraman, Amar Phanishayee +3
cs.DCarXiv:1901.05758v22019
An OpenCL(TM) Deep Learning Accelerator on Arria 10
Utku Aydonat, Shane O'Connell, Davor Capalija +2
cs.DCcs.ARcs.CVarXiv:1701.03534v12017
Machine Learning at the Wireless Edge: Distributed Stochastic Gradient Descent Over-the-Air
Mohammad Mohammadi Amiri, Deniz Gunduz
cs.DCcs.ITcs.LGarXiv:1901.00844v32019
Exascale Deep Learning for Climate Analytics
Thorsten Kurth, Sean Treichler, Joshua Romero +9
cs.DCarXiv:1810.01993v12018
AInfer-PD: Communication-Safe In-Place Prefill-Decode Multiplexing for Distributed MoE Rollouts
Guowei Wang, Chaokun Yang, Zhenxuan Pan +5
cs.DCarXiv:2609.00993v12026
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
Resource Management in Fog/Edge Computing: A Survey
Cheol-Ho Hong, Blesson Varghese
cs.DCarXiv:1810.00305v12018
TensorFlow: A system for large-scale machine learning
Martín Abadi, Paul Barham, Jianmin Chen +19
cs.DCcs.AIarXiv:1605.08695v22016
MUC-FL: Block-Wise Marginal Utility Contribution for Communication-Efficient Federated Learning
Akshay Mhatre, Vikram Karthick, Deepti Gupta +1
cs.DCcs.LGarXiv:2609.10545v12026
BlendCAC: A BLockchain-ENabled Decentralized Capability-based Access Control for IoTs
Ronghua Xu, Yu Chen, Erik Blasch +1
cs.NIcs.CRcs.DCarXiv:1804.09267v12018
Ray: A Distributed Framework for Emerging AI Applications
Philipp Moritz, Robert Nishihara, Stephanie Wang +8
cs.DCcs.AIcs.LGarXiv:1712.05889v22017
Hyperledger Fabric: A Distributed Operating System for Permissioned Blockchains
Elli Androulaki, Artem Barger, Vita Bortnikov +18
cs.DCcs.CRarXiv:1801.10228v22018
Focus: Querying Large Video Datasets with Low Latency and Low Cost
Kevin Hsieh, Ganesh Ananthanarayanan, Peter Bodik +4
cs.DBcs.CVcs.DCarXiv:1801.03493v12018
NVIDIA Tensor Core Programmability, Performance & Precision
Stefano Markidis, Steven Wei Der Chien, Erwin Laure +2
cs.DCcs.PFarXiv:1803.04014v12018
Deep Learning on FPGAs: Past, Present, and Future
Griffin Lacey, Graham W. Taylor, Shawki Areibi
cs.DCcs.LGstat.MLarXiv:1602.04283v12016
Prefill-as-a-Service: KVCache of Next-Generation Models Could Go Cross-Datacenter
Ruoyu Qin, Weiran He, Yaoyu Wang +5
cs.DCarXiv:2604.15039v22026
Serving deep learning models in a serverless platform
Vatche Ishakian, Vinod Muthusamy, Aleksander Slominski
cs.DCarXiv:1710.08460v22017
Model Extraction Warning in MLaaS Paradigm
Manish Kesarwani, Bhaskar Mukhoty, Vijay Arya +1
cs.LGcs.CRcs.DCarXiv:1711.07221v12017
Sparse Communication for Distributed Gradient Descent
Alham Fikri Aji, Kenneth Heafield
cs.CLcs.DCcs.LGarXiv:1704.05021v22017

Distributed and Cluster Computing

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

AI and Memory Wall

Pathways: Asynchronous Distributed Dataflow for ML

MegaBlocks: Efficient Sparse Training with Mixture-of-Experts

Split Learning in 6G Edge Networks

An Overview on Generative AI at Scale with Edge-Cloud Computing

Fast Distributed Inference Serving for Large Language Models

Accelerating Distributed MoE Training and Inference with Lina

Carbon-Aware Computing for Datacenters

SZ3: A Modular Framework for Composing Prediction-Based Error-Bounded Lossy Compressors

TinyOL: TinyML with Online-Learning on Microcontrollers

Blockchain for Edge of Things: Applications, Opportunities, and Challenges

FaaSNet: Scalable and Fast Provisioning of Custom Serverless Container Runtimes at Alibaba Cloud Function Compute

From Federated Learning to Federated Neural Architecture Search: A Survey

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

SeBS: A Serverless Benchmark Suite for Function-as-a-Service Computing

Collaborative Federated Learning For Healthcare: Multi-Modal COVID-19 Diagnosis at the Edge

Dynamic Fusion based Federated Learning for COVID-19 Detection

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

Survey of Machine Learning Accelerators

A Survey on the Evolution of Stream Processing Systems

RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing

ZeRO: Memory Optimizations Toward Training Trillion Parameter Models

DeepRecSys: A System for Optimizing End-To-End At-scale Neural Recommendation Inference

Serverless in the Wild: Characterizing and Optimizing the Serverless Workload at a Large Cloud Provider

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

Edge Intelligence: Paving the Last Mile of Artificial Intelligence with Edge Computing

The Architectural Implications of Facebook's DNN-based Personalized Recommendation

Federated Learning: Challenges, Methods, and Future Directions

Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing

MediaPipe: A Framework for Building Perception Pipelines

Blockchain for Internet of Things: A Survey

Effective Extensible Programming: Unleashing Julia on GPUs

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

Database Meets Deep Learning: Challenges and Opportunities

Basic Performance Measurements of the Intel Optane DC Persistent Memory Module

Priority-based Parameter Propagation for Distributed DNN Training

Rucio - Scientific data management

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

High-Throughput CNN Inference on Embedded ARM big.LITTLE Multi-Core Processors

PipeDream: Fast and Efficient Pipeline Parallel DNN Training

Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training Workloads

An OpenCL(TM) Deep Learning Accelerator on Arria 10

Machine Learning at the Wireless Edge: Distributed Stochastic Gradient Descent Over-the-Air

Exascale Deep Learning for Climate Analytics

AInfer-PD: Communication-Safe In-Place Prefill-Decode Multiplexing for Distributed MoE Rollouts

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

Resource Management in Fog/Edge Computing: A Survey

TensorFlow: A system for large-scale machine learning

MUC-FL: Block-Wise Marginal Utility Contribution for Communication-Efficient Federated Learning

BlendCAC: A BLockchain-ENabled Decentralized Capability-based Access Control for IoTs

Ray: A Distributed Framework for Emerging AI Applications

Hyperledger Fabric: A Distributed Operating System for Permissioned Blockchains

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

NVIDIA Tensor Core Programmability, Performance & Precision

Deep Learning on FPGAs: Past, Present, and Future

Prefill-as-a-Service: KVCache of Next-Generation Models Could Go Cross-Datacenter

Serving deep learning models in a serverless platform

Model Extraction Warning in MLaaS Paradigm

Sparse Communication for Distributed Gradient Descent