Device Placement Optimization with Reinforcement Learning

13 June 2017

Papers citing "Device Placement Optimization with Reinforcement Learning"

50 / 56 papers shown

Title
Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition Zhong Zheng Haochen Zhang Lingzhou Xue OffRL 75 2 0 10 Oct 2024
To Switch or Not to Switch? Balanced Policy Switching in Offline Reinforcement Learning Tao Ma Xuzhi Yang Zoltan Szabo OffRL 70 0 0 01 Jul 2024
A Structure-Aware Framework for Learning Device Placements on Computation Graphs Shukai Duan Heng Ping Nikos Kanakaris Xiongye Xiao Panagiotis Kyriakis ... Guixiang Ma Mihai Capota Shahin Nazarian Theodore L. Willke Paul Bogdan 45 2 0 23 May 2024
Workload-Aware Hardware Accelerator Mining for Distributed Deep Learning Training Muhammad Adnan Amar Phanishayee Janardhan Kulkarni Prashant J. Nair Divyat Mahajan 45 0 0 23 Apr 2024
Moirai: Towards Optimal Placement for Distributed Inference on Heterogeneous Devices Beibei Zhang Hongwei Zhu Feng Gao Zhihui Yang Xiaoyang Sean Wang 29 1 0 07 Dec 2023
A Survey From Distributed Machine Learning to Distributed Deep Learning Mohammad Dehghani Zahra Yazdanparast 23 0 0 11 Jul 2023
Optimizing Memory Mapping Using Deep Reinforcement Learning Pengming Wang Mikita Sazanovich Berkin Ilbeyi P. Phothilimthana Manish Purohit ... R. Tung Paula Kurylowicz Kieran Milan Oriol Vinyals D. Mankowitz 14 4 0 11 May 2023
Expediting Distributed DNN Training with Device Topology-Aware Graph Deployment Shiwei Zhang Xiaodong Yi Lansong Diao Chuan Wu Siyu Wang W. Lin GNN 22 5 0 13 Feb 2023
Task Placement and Resource Allocation for Edge Machine Learning: A GNN-based Multi-Agent Reinforcement Learning Paradigm Yihong Li Xiaoxi Zhang Tian Zeng Jingpu Duan Chuanxi Wu Di Wu Xu Chen 23 15 0 01 Feb 2023
AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness Dacheng Li Hongyi Wang Eric P. Xing Haotong Zhang MoE 22 20 0 13 Oct 2022
DreamShard: Generalizable Embedding Table Placement for Recommender Systems Daochen Zha Louis Feng Qiaoyu Tan Zirui Liu Kwei-Herng Lai Bhargav Bhushanam Yuandong Tian A. Kejariwal Xia Hu LMTD OffRL 30 28 0 05 Oct 2022
Celeritas: Fast Optimizer for Large Dataflow Graphs Hengwei Xu Yong Liao Haiyong Xie Pengyuan Zhou GNN 17 1 0 30 Jul 2022
Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization Minsu Kim Junyoung Park Jinkyoo Park 76 80 0 26 May 2022
MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud Zhen Zhang Shuai Zheng Yida Wang Justin Chiu George Karypis Trishul Chilimbi Mu Li Xin Jin 19 39 0 30 Apr 2022
FuncPipe: A Pipelined Serverless Framework for Fast and Cost-efficient Training of Deep Learning Models Yunzhuo Liu Bo Jiang Tian Guo Zimeng Huang Wen-ping Ma Xinbing Wang Chenghu Zhou 24 9 0 28 Apr 2022
Efficient Pipeline Planning for Expedited Distributed DNN Training Ziyue Luo Xiaodong Yi Guoping Long Shiqing Fan Chuan Wu Jun Yang Wei Lin 28 16 0 22 Apr 2022
Reinforcement Learning in Practice: Opportunities and Challenges Yuxi Li OffRL 36 9 0 23 Feb 2022
TopoOpt: Co-optimizing Network Topology and Parallelization Strategy for Distributed Training Jobs Weiyang Wang Moein Khazraee Zhizhen Zhong M. Ghobadi Zhihao Jia Dheevatsa Mudigere Ying Zhang A. Kewitsch 39 81 0 01 Feb 2022
Accelerate Model Parallel Training by Using Efficient Graph Traversal Order in Device Placement Tianze Wang A. H. Payberah D. Hagos Vladimir Vlassov GNN 25 0 0 21 Jan 2022
Automated Deep Learning: Neural Architecture Search Is Not the End Xuanyi Dong D. Kedziora Katarzyna Musial Bogdan Gabrys 25 26 0 16 Dec 2021
HeterPS: Distributed Deep Learning With Reinforcement Learning Based Scheduling in Heterogeneous Environments Ji Liu Zhihua Wu Dianhai Yu Yanjun Ma Danlei Feng Minxu Zhang Xinxuan Wu Xuefeng Yao Dejing Dou 16 44 0 20 Nov 2021
FTPipeHD: A Fault-Tolerant Pipeline-Parallel Distributed Training Framework for Heterogeneous Edge Devices Yuhao Chen Qianqian Yang Shibo He Zhiguo Shi Jiming Chen 16 3 0 06 Oct 2021
Toward Efficient Online Scheduling for Distributed Machine Learning Systems Menglu Yu Jia Liu Chuan Wu Bo Ji Elizabeth S. Bentley 16 6 0 06 Aug 2021
High-Dimensional Bayesian Optimization with Multi-Task Learning for RocksDB Sami Alabed Eiko Yoneki 13 17 0 30 Mar 2021
A Survey of Machine Learning for Computer Architecture and Systems Nan Wu Yuan Xie AI4TS AI4CE 20 145 0 16 Feb 2021
AutoDropout: Learning Dropout Patterns to Regularize Deep Networks Hieu H. Pham Quoc V. Le 76 56 0 05 Jan 2021
Scaling Distributed Deep Learning Workloads beyond the Memory Capacity with KARMA M. Wahib Haoyu Zhang Truong Thao Nguyen Aleksandr Drozd Jens Domke Lingqi Zhang Ryousei Takano Satoshi Matsuoka OODD 34 23 0 26 Aug 2020
Runtime Task Scheduling using Imitation Learning for Heterogeneous Many-Core Systems A. Krishnakumar Samet E. Arda A. Alper Goksoy Sumit K. Mandal Ümit Y. Ogras A. L. Sartor R. Marculescu 11 30 0 18 Jul 2020
Optimizing Memory Placement using Evolutionary Graph Reinforcement Learning Shauharda Khadka Estelle Aflalo Mattias Marder Avrech Ben-David Santiago Miret Shie Mannor Tamir Hazan Hanlin Tang Somdeb Majumdar GNN 27 11 0 14 Jul 2020
DAPPLE: A Pipelined Data Parallel Approach for Training Large Models Shiqing Fan Yi Rong Chen Meng Zongyan Cao Siyu Wang ... Jun Yang Lixue Xia Lansong Diao Xiaoyong Liu Wei Lin 21 232 0 02 Jul 2020
Hardware Acceleration of Sparse and Irregular Tensor Computations of ML Models: A Survey and Insights Shail Dave Riyadh Baghdadi Tony Nowatzki Sasikanth Avancha Aviral Shrivastava Baoxin Li 59 82 0 02 Jul 2020
Data Movement Is All You Need: A Case Study on Optimizing Transformers A. Ivanov Nikoli Dryden Tal Ben-Nun Shigang Li Torsten Hoefler 36 131 0 30 Jun 2020
Automated Optical Multi-layer Design via Deep Reinforcement Learning Haozhu Wang Zeyu Zheng Chengang Ji L. J. Guo 14 3 0 21 Jun 2020
DeepSoCS: A Neural Scheduler for Heterogeneous System-on-Chip (SoC) Resource Scheduling Tegg Taekyong Sung J. Ha Jeewoo Kim Alex Yahja Chae-Bong Sohn Bo Ryu 21 9 0 15 May 2020
ProGraML: Graph-based Deep Learning for Program Optimization and Analysis Chris Cummins Zacharias V. Fisches Tal Ben-Nun Torsten Hoefler Hugh Leather 88 56 0 23 Mar 2020
Communication-Efficient Edge AI: Algorithms and Systems Yuanming Shi Kai Yang Tao Jiang Jun Zhang Khaled B. Letaief GNN 17 326 0 22 Feb 2020
DL2: A Deep Learning-driven Scheduler for Deep Learning Clusters Size Zheng Yixin Bao Yangrui Chen Chuan Wu Chen Meng Wei Lin 18 79 0 13 Sep 2019
Optimizing Multi-GPU Parallelization Strategies for Deep Learning Training Saptadeep Pal Eiman Ebrahimi A. Zulfiqar Yaosheng Fu Victor Zhang Szymon Migacz D. Nellans Puneet Gupta 34 55 0 30 Jul 2019
DeepPlace: Learning to Place Applications in Multi-Tenant Clusters Subrata Mitra S. S. Mondal Nikhil Sheoran Neeraj Dhake Ravinder Nehra Ramanuja Simha 14 7 0 30 Jul 2019
Co-training for Policy Learning Jialin Song Ravi Lanka Yisong Yue M. Ono OffRL 12 19 0 03 Jul 2019
Database Meets Deep Learning: Challenges and Opportunities Wei Wang Meihui Zhang Gang Chen H. V. Jagadish Beng Chin Ooi K. Tan 11 147 0 21 Jun 2019
Reinforcement Learning Driven Heuristic Optimization Qingpeng Cai W. Hang Azalia Mirhoseini George Tucker Jingtao Wang Wei Wei 21 26 0 16 Jun 2019
HARK Side of Deep Learning -- From Grad Student Descent to Automated Machine Learning O. Gencoglu M. Gils E. Guldogan Chamin Morikawa Mehmet Süzen M. Gruber J. Leinonen H. Huttunen 11 36 0 16 Apr 2019
Improving Strong-Scaling of CNN Training by Exploiting Finer-Grained Parallelism Nikoli Dryden N. Maruyama Tom Benson Tim Moon M. Snir B. Van Essen 26 49 0 15 Mar 2019
AutoLoss: Learning Discrete Schedules for Alternate Optimization Haowen Xu Huan Zhang Zhiting Hu Xiaodan Liang Ruslan Salakhutdinov Eric P. Xing 24 30 0 04 Oct 2018
Learning Scheduling Algorithms for Data Processing Clusters Hongzi Mao Malte Schwarzkopf S. Venkatakrishnan Zili Meng Mohammad Alizadeh OffRL 20 636 0 03 Oct 2018
Supporting Very Large Models using Automatic Dataflow Graph Partitioning Minjie Wang Chien-chin Huang Jinyang Li 37 154 0 24 Jul 2018
Beyond Data and Model Parallelism for Deep Neural Networks Zhihao Jia Matei A. Zaharia A. Aiken GNN AI4CE 27 497 0 14 Jul 2018
Variance Reduction for Reinforcement Learning in Input-Driven Environments Hongzi Mao S. Venkatakrishnan Malte Schwarzkopf Mohammad Alizadeh OffRL 38 94 0 06 Jul 2018
Learning to Search via Retrospective Imitation Jialin Song Ravi Lanka Albert Zhao Aadyot Bhatnagar Yisong Yue M. Ono OffRL 8 31 0 03 Apr 2018