Benchmarking State-of-the-Art Deep Learning Software Tools

25 August 2016

Papers citing "Benchmarking State-of-the-Art Deep Learning Software Tools"

22 / 22 papers shown

Title
Unveiling the frontiers of deep learning: innovations shaping diverse domains Shams Forruque Ahmed Md. Sakib Bin Alam Maliha Kabir Shaila Afrin Sabiha Jannat Rafa Aanushka Mehjabin Amir H. Gandomi AI4CE 42 2 0 06 Sep 2023
A Generic Performance Model for Deep Learning in a Distributed Environment Tulasi Kavarakuntla Liangxiu Han H. Lloyd Annabel Latham Anthony Kleerekoper S. Akintoye 39 0 0 19 May 2023
Deep Learning Models on CPUs: A Methodology for Efficient Training Quchen Fu Ramesh Chukka Keith Achorn Thomas Atta-fosu Deepak R. Canchi Zhongwei Teng Jules White Douglas C. Schmidt 21 1 0 20 Jun 2022
Physics-constrained Deep Learning for Robust Inverse ECG Modeling Jianxin Xie B. Yao 30 21 0 26 Jul 2021
Data Science Methodologies: Current Challenges and Future Approaches Iñigo Martinez E. Viles Igor García Olaizola AI4TS 14 64 0 14 Jun 2021
Generating Reliable Process Event Streams and Time Series Data based on Neural Networks T. Herbert Juergen Mangler Stefanie Rinderle-Ma AI4TS 18 3 0 09 Mar 2021
From WiscKey to Bourbon: A Learned Index for Log-Structured Merge Trees Yifan Dai Yien Xu Aishwarya Ganesan Ramnatthan Alagappan Brian Kroth Andrea C. Arpaci-Dusseau Remzi H. Arpaci-Dusseau 11 1 0 28 May 2020
Comparison and Benchmarking of AI Models and Frameworks on Mobile Devices Chunjie Luo Xiwen He Jianfeng Zhan Lei Wang Wanling Gao Jiahui Dai ELM 24 58 0 07 May 2020
MG-WFBP: Merging Gradients Wisely for Efficient Communication in Distributed Deep Learning S. Shi X. Chu Bo Li FedML 22 25 0 18 Dec 2019
Characterizing Deep Learning Training Workloads on Alibaba-PAI Mengdi Wang Chen Meng Guoping Long Chuan Wu Jun Yang Wei Lin Yangqing Jia 17 53 0 14 Oct 2019
An Empirical Study towards Characterizing Deep Learning Development and Deployment across Different Frameworks and Platforms Qianyu Guo Sen Chen Xiaofei Xie Lei Ma Q. Hu Hongtao Liu Yang Liu Jianjun Zhao Xiaohong Li 38 122 0 15 Sep 2019
pCAMP: Performance Comparison of Machine Learning Packages on the Edges Xingzhou Zhang Yifan Wang Weisong Shi 9 91 0 05 Jun 2019
Speeding up Deep Learning with Transient Servers Shijian Li R. Walls Lijie Xu Tian Guo 27 12 0 28 Feb 2019
Scalable Distributed DNN Training using TensorFlow and CUDA-Aware MPI: Characterization, Designs, and Performance Evaluation A. A. Awan Jeroen Bédorf Ching-Hsiang Chu Hari Subramoni D. Panda GNN 30 45 0 25 Oct 2018
Characterizing Deep-Learning I/O Workloads in TensorFlow Steven W. D. Chien Stefano Markidis C. Sishtla Luís Santos Pawel Herman Sai B. Narasimhamurthy Erwin Laure 15 50 0 06 Oct 2018
Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark Cody Coleman Daniel Kang Deepak Narayanan Luigi Nardi Tian Zhao Jian Zhang Peter Bailis K. Olukotun Christopher Ré Matei A. Zaharia 13 117 0 04 Jun 2018
TBD: Benchmarking and Analyzing Deep Neural Network Training Hongyu Zhu Mohamed Akrout Bojian Zheng Andrew Pelegris Amar Phanishayee Bianca Schroeder Gennady Pekhimenko 25 80 0 16 Mar 2018
A Survey on Deep Learning Toolkits and Libraries for Intelligent User Interfaces Jan Zacharias Michael Barz Daniel Sonntag VLM 19 33 0 13 Mar 2018
Performance Modeling and Evaluation of Distributed Deep Learning Frameworks on GPUs S. Shi Qiang-qiang Wang Xiaowen Chu 37 110 0 16 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 23 22 0 10 Aug 2017
Speeding up Convolutional Neural Networks By Exploiting the Sparsity of Rectifier Units S. Shi Xiaowen Chu 15 43 0 25 Apr 2017
CHAOS: A Parallelization Scheme for Training Convolutional Neural Networks on Intel Xeon Phi Andre Viebke Suejb Memeti Sabri Pllana Ajith Abraham 32 25 0 25 Feb 2017