Machine Learning · Computer Science
Multi-GPU Training of ConvNets
Omry Yadan, Keith Adams, Yaniv Taigman, Marc'Aurelio Ranzato
2014-02-20
Machine Learning · Computer Science
Exploring Hidden Dimensions in Parallelizing Convolutional Neural Networks
Zhihao Jia, Sina Lin, Charles R. Qi, Alex Aiken
2018-06-12
Distributed, Parallel, and Cluster Computing · Computer Science
A Multi-signal Variant for the GPU-based Parallelization of Growing Self-Organizing Networks
Giacomo Parigi, Angelo Stramieri, Danilo Pau, Marco Piastra
2015-03-31
Machine Learning · Computer Science
Layer-Parallel Training with GPU Concurrency of Deep Residual Neural Networks via Nonlinear Multigrid
Andrew C. Kirby, Siddharth Samsi, Michael Jones, Albert Reuther +2
2020-09-01
Distributed, Parallel, and Cluster Computing · Computer Science
Brief Announcement: On the Limits of Parallelizing Convolutional Neural Networks on GPUs
Behnam Pourghassemi, Chenghao Zhang, Joo Hwan Lee, Aparna Chandramowlishwaran
2020-05-29
Machine Learning · Computer Science
Gear Training: A new way to implement high-performance model-parallel training
Hao Dong, Shuai Li, Dongchang Xu, Yi Ren +1
2018-06-12
Computer Vision and Pattern Recognition · Computer Science
GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network Training
Thomas Paine, Hailin Jin, Jianchao Yang, Zhe Lin +1
2013-12-24
Distributed, Parallel, and Cluster Computing · Computer Science
Characterizing and Understanding Distributed GNN Training on GPUs
Haiyang Lin, Mingyu Yan, Xiaocheng Yang, Mo Zou +3
2022-04-19
Distributed, Parallel, and Cluster Computing · Computer Science
Distributed learning of CNNs on heterogeneous CPU/GPU architectures
Jose Marques, Gabriel Falcao, Luís A. Alexandre
2017-12-08
Distributed, Parallel, and Cluster Computing · Computer Science
Using Hierarchical Parallelism to Accelerate the Solution of Many Small Partial Differential Equations
Jacob Merson, Mark S. Shephard
2023-05-15
Distributed, Parallel, and Cluster Computing · Computer Science
The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs with Hybrid Parallelism
Yosuke Oyama, Naoya Maruyama, Nikoli Dryden, Erin McCarthy +5
2020-07-28
Machine Learning · Computer Science
Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training
Shenggui Li, Hongxin Liu, Zhengda Bian, Jiarui Fang +4
2023-10-06
Machine Learning · Computer Science
Large-Scale Stochastic Learning using GPUs
Thomas Parnell, Celestine Dünner, Kubilay Atasu, Manolis Sifalakis +1
2017-02-24
Machine Learning · Computer Science
Parallel training of linear models without compromising convergence
Nikolas Ioannou, Celestine Dünner, Kornilios Kourtis, Thomas Parnell
2018-12-20
Distributed, Parallel, and Cluster Computing · Computer Science
GSplit: Scaling Graph Neural Network Training on Large Graphs via Split-Parallelism
Sandeep Polisetty, Juelin Liu, Kobi Falus, Yi Ren Fung +3
2025-12-15
Distributed, Parallel, and Cluster Computing · Computer Science
Large Scale Artificial Neural Network Training Using Multi-GPUs
Linnan Wang, Wei Wu, Jianxiong Xiao, Yang Yi
2015-11-16