Predicting the Computational Cost of Deep Learning Models

Predicting the Computational Cost of Deep Learning Models

28 November 2018

Papers citing "Predicting the Computational Cost of Deep Learning Models"

18 / 18 papers shown

Title
Phantora: Live GPU Cluster Simulation for Machine Learning System Performance Estimation Jianxing Qin Jingrong Chen Xinhao Kong Yongji Wu Liang Luo Ziyi Wang Ying Zhang Tingjun Chen Alvin R. Lebeck Danyang Zhuo 175 0 0 02 May 2025
Pretraining Decision Transformers with Reward Prediction for In-Context Multi-task Structured Bandit Learning Subhojyoti Mukherjee Josiah P. Hanna Qiaomin Xie Robert Nowak 89 2 0 07 Jun 2024
On Replacing Cryptopuzzles with Useful Computation in Blockchain Proof-of-Work Protocols Andrea Merlina Thiago Garrett Roman Vitenberg 33 0 0 24 Apr 2024
Self-Expansion of Pre-trained Models with Mixture of Adapters for Continual Learning Huiyi Wang Haodong Lu Lina Yao Dong Gong KELM CLL 53 9 0 27 Mar 2024
Using Cooperative Game Theory to Prune Neural Networks M. Diaz-Ortiz Benjamin Kempinski Daphne Cornelisse Yoram Bachrach Tal Kachman 46 2 0 17 Nov 2023
Low-latency Federated Learning with DNN Partition in Distributed Industrial IoT Networks Xiumei Deng Jun Li Chuan Ma Kang Wei Long Shi Ming Ding Wen Chen FedML 41 36 0 26 Oct 2022
DNNAbacus: Toward Accurate Computational Cost Prediction for Deep Neural Networks Lu Bai Weixing Ji Qinyuan Li Xi Yao Wei Xin Wanyi Zhu 15 6 0 24 May 2022
Towards Optimal VPU Compiler Cost Modeling by using Neural Networks to Infer Hardware Performances Ian Frederick Vigogne Goodbody Hunter Alessandro Palla Sebastian Eusebiu Nagy R. Richmond Kyle McAdoo 25 2 0 09 May 2022
A Closer Look at Rehearsal-Free Continual Learning James Smith Junjiao Tian Shaunak Halbe Yen-Chang Hsu Z. Kira VLM CLL 26 60 0 31 Mar 2022
Perception Over Time: Temporal Dynamics for Robust Image Understanding Maryam Daniali Edward J. Kim AI4TS 25 5 0 11 Mar 2022
Benchmarking Resource Usage for Efficient Distributed Deep Learning Nathan C. Frey Baolin Li Joseph McDonald Dan Zhao Michael Jones David Bestor Devesh Tiwari V. Gadepally S. Samsi 37 9 0 28 Jan 2022
Building a Performance Model for Deep Learning Recommendation Model Training on GPUs Zhongyi Lin Louis Feng E. K. Ardestani Jaewon Lee J. Lundell Changkyu Kim A. Kejariwal John Douglas Owens 30 19 0 19 Jan 2022
Visual Sensation and Perception Computational Models for Deep Learning: State of the art, Challenges and Prospects Bing Wei Yudi Zhao K. Hao Lei Gao 42 5 0 08 Sep 2021
A Runtime-Based Computational Performance Predictor for Deep Neural Network Training Geoffrey X. Yu Yubo Gao P. Golikov Gennady Pekhimenko 3DH 36 67 0 31 Jan 2021
Predicting Training Time Without Training L. Zancato Alessandro Achille Avinash Ravichandran Rahul Bhotika Stefano Soatto 26 24 0 28 Aug 2020
A Learned Performance Model for Tensor Processing Units Samuel J. Kaufman P. Phothilimthana Yanqi Zhou Charith Mendis Sudip Roy Amit Sabne Mike Burrows 26 8 0 03 Aug 2020
Characterizing Deep Learning Training Workloads on Alibaba-PAI Mengdi Wang Chen Meng Guoping Long Chuan Wu Jun Yang Wei Lin Yangqing Jia 25 54 0 14 Oct 2019
A Survey of the Recent Architectures of Deep Convolutional Neural Networks Asifullah Khan A. Sohail Umme Zahoora Aqsa Saeed Qureshi OOD 72 2,273 0 17 Jan 2019