FireCaffe: near-linear acceleration of deep neural network training on compute clusters

31 October 2015

Papers citing "FireCaffe: near-linear acceleration of deep neural network training on compute clusters"

28 / 28 papers shown

Title
Analysing the Influence of Attack Configurations on the Reconstruction of Medical Images in Federated Learning M. Dahlgaard Morten Wehlast Jorgensen N. Fuglsang Hiba Nassar FedML AAML 28 2 0 25 Apr 2022
FedDC: Federated Learning with Non-IID Data via Local Drift Decoupling and Correction Liang Gao H. Fu Li Li Yingwen Chen Minghua Xu Chengzhong Xu FedML 21 242 0 22 Mar 2022
FA-GAN: Fused Attentive Generative Adversarial Networks for MRI Image Super-Resolution M. Jiang Min Zhi Liying Wei Xiaocheng Yang Jucheng Zhang Yongming Li Pin Wang Jiahao Huang Guang Yang MedIm 17 83 0 09 Aug 2021
Concurrent Adversarial Learning for Large-Batch Training Yong Liu Xiangning Chen Minhao Cheng Cho-Jui Hsieh Yang You ODL 28 13 0 01 Jun 2021
Partitioning sparse deep neural networks for scalable training and inference G. Demirci Hakan Ferhatosmanoglu 18 11 0 23 Apr 2021
See through Gradients: Image Batch Recovery via GradInversion Hongxu Yin Arun Mallya Arash Vahdat J. Álvarez Jan Kautz Pavlo Molchanov FedML 23 459 0 15 Apr 2021
Towards a Scalable and Distributed Infrastructure for Deep Learning Applications Bita Hasheminezhad S. Shirzad Nanmiao Wu Patrick Diehl Hannes Schulz Hartmut Kaiser GNN AI4CE 11 4 0 06 Oct 2020
PSO-PS: Parameter Synchronization with Particle Swarm Optimization for Distributed Training of Deep Neural Networks Qing Ye Y. Han Yanan Sun Jiancheng Lv 23 3 0 06 Sep 2020
CLAN: Continuous Learning using Asynchronous Neuroevolution on Commodity Edge Devices Parth Mannan A. Samajdar T. Krishna 15 2 0 27 Aug 2020
ZynqNet: An FPGA-Accelerated Embedded Convolutional Neural Network David Gschwend 13 64 0 14 May 2020
Characterizing and Modeling Distributed Training with Transient Cloud GPU Servers Shijian Li R. Walls Tian Guo 15 23 0 07 Apr 2020
Parallelizing Training of Deep Generative Models on Massive Scientific Datasets S. A. Jacobs B. Van Essen D. Hysom Jae-Seung Yeom Tim Moon ... J. Gaffney Tom Benson Peter B. Robinson L. Peterson B. Spears BDL AI4CE 14 17 0 05 Oct 2019
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization Thijs Vogels Sai Praneeth Karimireddy Martin Jaggi 17 316 0 31 May 2019
MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling Jianyu Wang Anit Kumar Sahu Zhouyi Yang Gauri Joshi S. Kar 13 159 0 23 May 2019
Large Batch Optimization for Deep Learning: Training BERT in 76 minutes Yang You Jing Li Sashank J. Reddi Jonathan Hseu Sanjiv Kumar Srinadh Bhojanapalli Xiaodan Song J. Demmel Kurt Keutzer Cho-Jui Hsieh ODL 28 978 0 01 Apr 2019
swCaffe: a Parallel Framework for Accelerating Deep Learning Applications on Sunway TaihuLight Jiarui Fang Liandeng Li H. Fu Jinlei Jiang Wenlai Zhao Conghui He Xin You Guangwen Yang 21 30 0 16 Mar 2019
Pipe-SGD: A Decentralized Pipelined SGD Framework for Distributed Deep Net Training Youjie Li Hang Qiu Songze Li A. Avestimehr N. Kim A. Schwing FedML 16 103 0 08 Nov 2018
Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks Kang Liu Brendan Dolan-Gavitt S. Garg AAML 4 1,017 0 30 May 2018
Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis Tal Ben-Nun Torsten Hoefler GNN 22 701 0 26 Feb 2018
Efficient Training of Convolutional Neural Nets on Large Distributed Systems Sameer Kumar D. Sreedhar Vaibhav Saxena Yogish Sabharwal Ashish Verma 25 4 0 02 Nov 2017
Distributed Training Large-Scale Deep Architectures Shang-Xuan Zou Chun-Yen Chen Jui-Lin Wu Chun-Nan Chou Chia-Chin Tsao Kuan-Chieh Tung Ting-Wei Lin Cheng-Lung Sung Edward Y. Chang 16 22 0 10 Aug 2017
Scaling Deep Learning on GPU and Knights Landing clusters Yang You A. Buluç J. Demmel GNN 15 75 0 09 Aug 2017
Optimized Broadcast for Deep Learning Workloads on Dense-GPU InfiniBand Clusters: MPI or NCCL? A. A. Awan Ching-Hsiang Chu Hari Subramoni D. Panda GNN 33 46 0 28 Jul 2017
How to scale distributed deep learning? Peter H. Jin Qiaochu Yuan F. Iandola Kurt Keutzer 3DH 16 136 0 14 Nov 2016
Distributed Training of Deep Neural Networks: Theoretical and Practical Limits of Parallel Scalability J. Keuper Franz-Josef Pfreundt GNN 47 97 0 22 Sep 2016
A Convolutional Autoencoder for Multi-Subject fMRI Data Aggregation Po-Hsuan Chen Xia Zhu Hejia Zhang Javier S. Turek Janice Chen Theodore L. Willke Uri Hasson Peter J. Ramadge 16 24 0 17 Aug 2016
Omnivore: An Optimizer for Multi-device Deep Learning on CPUs and GPUs Stefan Hadjis Ce Zhang Ioannis Mitliagkas Dan Iter Christopher Ré 11 65 0 14 Jun 2016
The Effects of Hyperparameters on SGD Training of Neural Networks Thomas Breuel 64 63 0 12 Aug 2015