Flexible Coded Distributed Convolution Computing for Enhanced Straggler Resilience and Numerical Stability in Distributed CNNs
Fuente:
arXiv
Guardado en:
| Autores principales: | Tan, Shuo, Liu, Rui, Han, Xuesong, Long, XianLei, Wan, Kai, Song, Linqi, Li, Yong |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
dSTAR: Straggler Tolerant and Byzantine Resilient Distributed SGD
por: Yan, Jiahe, et al.
Publicado: (2024)
por: Yan, Jiahe, et al.
Publicado: (2024)
Exploiting Stragglers in Distributed Computing Systems with Task Grouping
por: Adikari, Tharindu, et al.
Publicado: (2024)
por: Adikari, Tharindu, et al.
Publicado: (2024)
CoCoI: Distributed Coded Inference System for Straggler Mitigation
por: Liu, Xing, et al.
Publicado: (2025)
por: Liu, Xing, et al.
Publicado: (2025)
Sparsity-Preserving Encodings for Straggler-Optimal Distributed Matrix Computations at the Edge
por: Das, Anindya Bijoy, et al.
Publicado: (2024)
por: Das, Anindya Bijoy, et al.
Publicado: (2024)
Straggler Tolerant and Resilient DL Training on Homogeneous GPUs
por: Zhang, Zeyu, et al.
Publicado: (2025)
por: Zhang, Zeyu, et al.
Publicado: (2025)
Adaptra: Straggler-Resilient Hybrid-Parallel Training with Pipeline Adaptation
por: Wu, Tianyuan, et al.
Publicado: (2025)
por: Wu, Tianyuan, et al.
Publicado: (2025)
Barycentric Coded Distributed Computing with Flexible Recovery Threshold for Collaborative Mobile Edge Computing
por: Qiu, Houming, et al.
Publicado: (2025)
por: Qiu, Houming, et al.
Publicado: (2025)
Distributed Learning based on 1-Bit Gradient Coding in the Presence of Stragglers
por: Li, Chengxi, et al.
Publicado: (2024)
por: Li, Chengxi, et al.
Publicado: (2024)
General Coded Computing in a Probabilistic Straggler Regime
por: Moradi, Parsa, et al.
Publicado: (2025)
por: Moradi, Parsa, et al.
Publicado: (2025)
Uncoded Download in Lagrange-Coded Elastic Computing with Straggler Tolerance
por: Zhong, Xi, et al.
Publicado: (2025)
por: Zhong, Xi, et al.
Publicado: (2025)
Distributed Linearly Separable Computation with Arbitrary Heterogeneous Data Assignment
por: Zhang, Ziting, et al.
Publicado: (2026)
por: Zhang, Ziting, et al.
Publicado: (2026)
Malleus: Straggler-Resilient Hybrid Parallel Training of Large-scale Models via Malleable Data and Model Parallelization
por: Li, Haoyang, et al.
Publicado: (2024)
por: Li, Haoyang, et al.
Publicado: (2024)
Lightweight Federated Learning with Differential Privacy and Straggler Resilience
por: Hong, Shu, et al.
Publicado: (2024)
por: Hong, Shu, et al.
Publicado: (2024)
Straggler-Resilient Decentralized Learning via Adaptive Asynchronous Updates
por: Xiong, Guojun, et al.
Publicado: (2023)
por: Xiong, Guojun, et al.
Publicado: (2023)
Privacy-Preserving Coding Schemes for Multi-Access Distributed Computing Models
por: Sasi, Shanuja
Publicado: (2026)
por: Sasi, Shanuja
Publicado: (2026)
Truncated Non-Uniform Quantization for Distributed SGD
por: Yan, Guangfeng, et al.
Publicado: (2024)
por: Yan, Guangfeng, et al.
Publicado: (2024)
Distributed Speculative Execution for Resilient Cloud Applications
por: Li, Tianyu, et al.
Publicado: (2024)
por: Li, Tianyu, et al.
Publicado: (2024)
Distributed On-Device LLM Inference With Over-the-Air Computation
por: Zhang, Kai, et al.
Publicado: (2025)
por: Zhang, Kai, et al.
Publicado: (2025)
Approximated Coded Computing: Towards Fast, Private and Secure Distributed Machine Learning
por: Qiu, Houming, et al.
Publicado: (2024)
por: Qiu, Houming, et al.
Publicado: (2024)
AntDT: A Self-Adaptive Distributed Training Framework for Leader and Straggler Nodes
por: Xiao, Youshao, et al.
Publicado: (2024)
por: Xiao, Youshao, et al.
Publicado: (2024)
Supervised Distributed Computing
por: Augustine, John, et al.
Publicado: (2025)
por: Augustine, John, et al.
Publicado: (2025)
Resilience through Automated Adaptive Configuration for Distribution and Replication
por: Stoller, Scott D., et al.
Publicado: (2025)
por: Stoller, Scott D., et al.
Publicado: (2025)
Improved Quantization Strategies for Managing Heavy-tailed Gradients in Distributed Learning
por: Yan, Guangfeng, et al.
Publicado: (2024)
por: Yan, Guangfeng, et al.
Publicado: (2024)
Data Augmentation and Convolutional Network Architecture Influence on Distributed Learning
por: Jansen, Victor Forattini, et al.
Publicado: (2026)
por: Jansen, Victor Forattini, et al.
Publicado: (2026)
Distributed Computation with Local Advice
por: Balliu, Alkida, et al.
Publicado: (2024)
por: Balliu, Alkida, et al.
Publicado: (2024)
Approximate Byzantine Fault-Tolerance in Distributed Optimization
por: Liu, Shuo, et al.
Publicado: (2021)
por: Liu, Shuo, et al.
Publicado: (2021)
Fully-Distributed Construction of Byzantine-Resilient Dynamic Peer-to-Peer Networks
por: Gupta, Aayush, et al.
Publicado: (2025)
por: Gupta, Aayush, et al.
Publicado: (2025)
COoL-TEE: Client-TEE Collaboration for Resilient Distributed Search
por: Bettinger, Matthieu, et al.
Publicado: (2025)
por: Bettinger, Matthieu, et al.
Publicado: (2025)
Biased Compression in Gradient Coding for Distributed Learning
por: Li, Chengxi, et al.
Publicado: (2026)
por: Li, Chengxi, et al.
Publicado: (2026)
The Singular Optimality of Distributed Computation in LOCAL
por: Dufoulon, Fabien, et al.
Publicado: (2024)
por: Dufoulon, Fabien, et al.
Publicado: (2024)
Byzantine-Resilient Distributed Computation via Task Replication and Local Computations
por: Rajesh, Aayush, et al.
Publicado: (2025)
por: Rajesh, Aayush, et al.
Publicado: (2025)
Coded Computing for Resilient Distributed Computing: A Learning-Theoretic Framework
por: Moradi, Parsa, et al.
Publicado: (2024)
por: Moradi, Parsa, et al.
Publicado: (2024)
Towards Straggler-Resilient Split Federated Learning: An Unbalanced Update Approach
por: Liang, Dandan, et al.
Publicado: (2025)
por: Liang, Dandan, et al.
Publicado: (2025)
SHEATH: Defending Horizontal Collaboration for Distributed CNNs against Adversarial Noise
por: Asif, Muneeba, et al.
Publicado: (2024)
por: Asif, Muneeba, et al.
Publicado: (2024)
AI Surrogate Model for Distributed Computing Workloads
por: Park, David K., et al.
Publicado: (2024)
por: Park, David K., et al.
Publicado: (2024)
FedCore: Straggler-Free Federated Learning with Distributed Coresets
por: Guo, Hongpeng, et al.
Publicado: (2024)
por: Guo, Hongpeng, et al.
Publicado: (2024)
DeFT: Mitigating Data Dependencies for Flexible Communication Scheduling in Distributed Training
por: Meng, Lin, et al.
Publicado: (2025)
por: Meng, Lin, et al.
Publicado: (2025)
Distributed Load Orchestration for Vision Computing in Multi-Access Edge Computing
por: Boing, Ricardo N., et al.
Publicado: (2022)
por: Boing, Ricardo N., et al.
Publicado: (2022)
FuxiShuffle: An Adaptive and Resilient Shuffle Service for Distributed Data Processing on Alibaba Cloud
por: Lin, Yuhao, et al.
Publicado: (2026)
por: Lin, Yuhao, et al.
Publicado: (2026)
Efficient AllReduce with Stragglers
por: Devraj, Arjun, et al.
Publicado: (2025)
por: Devraj, Arjun, et al.
Publicado: (2025)
Ejemplares similares
-
dSTAR: Straggler Tolerant and Byzantine Resilient Distributed SGD
por: Yan, Jiahe, et al.
Publicado: (2024) -
Exploiting Stragglers in Distributed Computing Systems with Task Grouping
por: Adikari, Tharindu, et al.
Publicado: (2024) -
CoCoI: Distributed Coded Inference System for Straggler Mitigation
por: Liu, Xing, et al.
Publicado: (2025) -
Sparsity-Preserving Encodings for Straggler-Optimal Distributed Matrix Computations at the Edge
por: Das, Anindya Bijoy, et al.
Publicado: (2024) -
Straggler Tolerant and Resilient DL Training on Homogeneous GPUs
por: Zhang, Zeyu, et al.
Publicado: (2025)