Papers citing 'A Graph Theoretic Framework of Recomputation Algorithms for Memory-Efficient Backpropagation'

Title
End-to-End Training Induces Information Bottleneck through Layer-Role Differentiation: A Comparative Analysis with Layer-wise Training Keitaro Sakamoto Issei Sato 294 9 0 14 Feb 2024
GMLake: Efficient and Transparent GPU Memory Defragmentation for Large-scale DNN Training with Virtual Memory StitchingInternational Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2024 Cong Guo Rui Zhang Jiale Xu Jingwen Leng Zihan Liu ... Minyi Guo Hao Wu Shouren Zhao Junping Zhao Ke Zhang VLM 167 24 0 16 Jan 2024
FlashFFTConv: Efficient Convolutions for Long Sequences with Tensor CoresInternational Conference on Learning Representations (ICLR), 2023 Daniel Y. Fu Hermann Kumbong Eric N. D. Nguyen Christopher Ré VLM 224 38 0 10 Nov 2023
FetusMapV2: Enhanced Fetal Pose Estimation in 3D Ultrasound Chaoyu Chen Xin Yang Yuhao Huang Wenlong Shi Yan Cao ... Kejuan Yue Yuanji Zhang Yi Xiong Dong Ni Weijun Huang 3DH 114 0 0 30 Oct 2023
Rockmate: an Efficient, Fast, Automatic and Generic Tool for Re-materialization in PyTorchInternational Conference on Machine Learning (ICML), 2023 Xunyi Zhao Théotime Le Hellard Lionel Eyraud Julia Gusak Olivier Beaumont 249 10 0 03 Jul 2023
Moccasin: Efficient Tensor Rematerialization for Neural NetworksInternational Conference on Machine Learning (ICML), 2023 Burak Bartan Haoming Li Harris Teague Chris Lott B. Dilkina 124 3 0 27 Apr 2023
XEngine: Optimal Tensor Rematerialization for Neural Networks in Heterogeneous EnvironmentsACM Transactions on Architecture and Code Optimization (TACO) (TACO), 2022 Manuela Schuler Richard Membarth P. Slusallek 225 4 0 19 Dec 2022
On-device Training: A First Overview on Existing Systems Shuai Zhu Thiemo Voigt Jeonggil Ko Fatemeh Rahimian 383 30 0 01 Dec 2022
FedDCT: Federated Learning of Large Convolutional Neural Networks on Resource Constrained Devices using Divide and Collaborative TrainingIEEE Transactions on Network and Service Management (IEEE TNSM), 2022 Quan Nguyen Hieu H. Pham Kok-Seng Wong Phi Le Nguyen Truong Thao Nguyen Minh N. Do FedML 202 9 0 20 Nov 2022
Survey on Large Scale Neural Network Training Julia Gusak Daria Cherniuk Alena Shilova A. Katrutsa Daniel Bershatsky ... Lionel Eyraud-Dubois Oleg Shlyazhko Denis Dimitrov Ivan Oseledets Olivier Beaumont 193 13 0 21 Feb 2022
Front Contribution instead of Back Propagation Swaroop Mishra Anjana Arunkumar 143 0 0 10 Jun 2021
Classifying Sequences of Extreme Length with Constant Memory Applied to Malware DetectionAAAI Conference on Artificial Intelligence (AAAI), 2020 Edward Raff William Fleshman Richard Zak Hyrum S. Anderson Bobby Filar Mark McLean AAML 143 65 0 17 Dec 2020
Scaling Distributed Deep Learning Workloads beyond the Memory Capacity with KARMAInternational Conference for High Performance Computing, Networking, Storage and Analysis (SC), 2020 Mohamed Wahib Haoyu Zhang Truong Thao Nguyen Aleksandr Drozd Jens Domke Lingqi Zhang Ryousei Takano Satoshi Matsuoka OODD 176 24 0 26 Aug 2020
Dynamic Tensor Rematerialization Marisa Kirisame Steven Lyubomirsky Altan Haan Jennifer Brennan Mike He Jared Roesch Tianqi Chen Zachary Tatlock 309 108 0 17 Jun 2020
Optimal checkpointing for heterogeneous chains: how to train deep neural networks with limited memory Julien Herrmann Olivier Beaumont Lionel Eyraud-Dubois J. Herrmann Alexis Joly Alena Shilova BDL 174 44 0 27 Nov 2019