Understanding Capacity-Driven Scale-Out Neural Recommendation Inference

4 November 2020

Papers citing "Understanding Capacity-Driven Scale-Out Neural Recommendation Inference"

35 / 35 papers shown

Title
RBFleX-NAS: Training-Free Neural Architecture Search Using Radial Basis Function Kernel and Hyperparameter Detection Tomomasa Yamasaki Zhehui Wang Tao Luo Niangjun Chen Bo Wang 32 0 0 26 Mar 2025
Pushing the Performance Envelope of DNN-based Recommendation Systems Inference on GPUs Rishabh Jain Vivek M. Bhasi Adwait Jog A. Sivasubramaniam M. Kandemir Chita R. Das 21 2 0 29 Oct 2024
The Unseen AI Disruptions for Power Grids: LLM-Induced Transients Yuzhuo Li Mariam Mughees Yize Chen Yunwei Ryan Li 20 9 0 09 Sep 2024
CADC: Encoding User-Item Interactions for Compressing Recommendation Model Training Data Hossein Entezari Zarch Abdulla Alshabanah Chaoyi Jiang Murali Annavaram 23 1 0 11 Jul 2024
ElasticRec: A Microservice-based Model Serving Architecture Enabling Elastic Resource Scaling for Recommendation Models Yujeong Choi Jiin Kim Minsoo Rhu 32 1 0 11 Jun 2024
Towards Universal Performance Modeling for Machine Learning Training on Multi-GPU Platforms Zhongyi Lin Ning Sun Pallab Bhattacharya Xizhou Feng Louis Feng John Douglas Owens 32 1 0 19 Apr 2024
Evaluating and Enhancing Robustness of Deep Recommendation Systems Against Hardware Errors Dongning Ma Xun Jiao Fred Lin Mengshi Zhang Alban Desmaison Thomas Sellinger Daniel Moore Sriram Sankar 19 2 0 17 Jul 2023
Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Models Daochen Zha Louis Feng Liangchen Luo Bhargav Bhushanam Zirui Liu ... J. McMahon Yuzhen Huang Bryan Clarke A. Kejariwal Xia Hu 50 7 0 03 May 2023
Hera: A Heterogeneity-Aware Multi-Tenant Inference Server for Personalized Recommendations Yujeong Choi John Kim Minsoo Rhu 13 1 0 23 Feb 2023
MP-Rec: Hardware-Software Co-Design to Enable Multi-Path Recommendation Samuel Hsia Udit Gupta Bilge Acun Newsha Ardalani Pan Zhong Gu-Yeon Wei David Brooks Carole-Jean Wu 33 17 0 21 Feb 2023
FlexShard: Flexible Sharding for Industry-Scale Sequence Recommendation Models Geet Sethi Pallab Bhattacharya Dhruv Choudhary Carole-Jean Wu Christos Kozyrakis 11 5 0 08 Jan 2023
Data Leakage via Access Patterns of Sparse Features in Deep Learning-based Recommendation Systems H. Hashemi Wenjie Xiong Liu Ke Kiwan Maeng M. Annavaram G. E. Suh Hsien-Hsin S. Lee 21 6 0 12 Dec 2022
DisaggRec: Architecting Disaggregated Systems for Large-Scale Personalized Recommendation Liu Ke Xuan Zhang Benjamin C. Lee G. E. Suh Hsien-Hsin S. Lee 41 8 0 02 Dec 2022
A GPU-specialized Inference Parameter Server for Large-Scale Deep Recommendation Models Yingcan Wei Matthias Langer F. Yu Minseok Lee Kingsley Liu Ji Shi Zehuan Wang BDL 24 17 0 17 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 15 28 0 05 Oct 2022
A Comprehensive Survey on Trustworthy Recommender Systems Wenqi Fan Xiangyu Zhao Xiao Chen Jingran Su Jingtong Gao ... Qidong Liu Yiqi Wang Hanfeng Xu Lei Chen Qing Li FaML 40 46 0 21 Sep 2022
Understanding Scaling Laws for Recommendation Models Newsha Ardalani Carole-Jean Wu Zeliang Chen Bhargav Bhushanam Adnan Aziz 29 28 0 17 Aug 2022
FEL: High Capacity Learning for Recommendation and Ranking via Federated Ensemble Learning Meisam Hejazinia Dzmitry Huba Ilias Leontiadis Kiwan Maeng Mani Malek Luca Melis Ilya Mironov Milad Nasr Kaikai Wang Carole-Jean Wu FedML 9 5 0 07 Jun 2022
Training Personalized Recommendation Systems from (GPU) Scratch: Look Forward not Backwards Youngeun Kwon Minsoo Rhu 16 27 0 10 May 2022
A Survey of Multi-Tenant Deep Learning Inference on GPU Fuxun Yu Di Wang Longfei Shangguan Minjia Zhang Chenchen Liu Xiang Chen BDL AI4CE 11 32 0 17 Mar 2022
RecShard: Statistical Feature-Based Memory Optimization for Industry-Scale Neural Recommendation Geet Sethi Bilge Acun Niket Agarwal Christos Kozyrakis Caroline Trippel Carole-Jean Wu 47 66 0 25 Jan 2022
A Survey of Large-Scale Deep Learning Serving System Optimization: Challenges and Opportunities Fuxun Yu Di Wang Longfei Shangguan Minjia Zhang Xulong Tang Chenchen Liu Xiang Chen 21 9 0 28 Nov 2021
Sustainable AI: Environmental Implications, Challenges and Opportunities Carole-Jean Wu Ramya Raghavendra Udit Gupta Bilge Acun Newsha Ardalani ... Maximilian Balandat Joe Spisak R. Jain Michael G. Rabbat K. Hazelwood 40 380 0 30 Oct 2021
Supporting Massive DLRM Inference Through Software Defined Memory E. K. Ardestani Changkyu Kim Seung Jae Lee Luoshang Pan Valmiki Rampersad ... Krishnakumar Nair Maxim Naumov Christopher Peterson M. Smelyanskiy Vijay Rao BDL 31 20 0 21 Oct 2021
Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale Zhaoxia Deng Deng Jongsoo Park P. T. P. Tang Haixin Liu ... S. Nadathur Changkyu Kim Maxim Naumov S. Naghshineh M. Smelyanskiy 15 11 0 26 May 2021
RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance Udit Gupta Samuel Hsia J. Zhang Mark Wilkening Javin Pombra Hsien-Hsin S. Lee Gu-Yeon Wei Carole-Jean Wu David Brooks 36 32 0 18 May 2021
ECRM: Efficient Fault Tolerance for Recommendation Model Training via Erasure Coding Kaige Liu J. Kosaian K. V. Rashmi 17 4 0 05 Apr 2021
RecSSD: Near Data Processing for Solid State Drive Based Recommendation Inference Mark Wilkening Udit Gupta Samuel Hsia Caroline Trippel Carole-Jean Wu David Brooks Gu-Yeon Wei 12 114 0 29 Jan 2021
TT-Rec: Tensor Train Compression for Deep Learning Recommendation Models Chunxing Yin Bilge Acun Xing Liu Carole-Jean Wu 28 102 0 25 Jan 2021
Understanding Training Efficiency of Deep Learning Recommendation Models at Scale Bilge Acun Matthew Murphy Xiaodong Wang Jade Nie Carole-Jean Wu K. Hazelwood 12 109 0 11 Nov 2020
CPR: Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery Kiwan Maeng Shivam Bharuka Isabel Gao M. C. Jeffrey V. Saraph ... Caroline Trippel Jiyan Yang Michael G. Rabbat Brandon Lucia Carole-Jean Wu OffRL 11 31 0 05 Nov 2020
Deep Learning Training in Facebook Data Centers: Design of Scale-up and Scale-out Systems Maxim Naumov John Kim Dheevatsa Mudigere Srinivas Sridharan Xiaodong Wang ... Krishnakumar Nair Isabel Gao Bor-Yiing Su Jiyan Yang M. Smelyanskiy GNN 41 83 0 20 Mar 2020
Distributed Hierarchical GPU Parameter Server for Massive Scale Deep Learning Ads Systems Weijie Zhao Deping Xie Ronglai Jia Yulei Qian Rui Ding Mingming Sun P. Li MoE 57 150 0 12 Mar 2020
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 231 4,469 0 23 Jan 2020
RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing Liu Ke Udit Gupta Carole-Jean Wu B. Cho Mark Hempstead ... Dheevatsa Mudigere Maxim Naumov Martin D. Schatz M. Smelyanskiy Xiaodong Wang 41 213 0 30 Dec 2019