Title
Learning to Collide: Recommendation System Model Compression with Learned Hash Functions Benjamin Ghaemmaghami Mustafa Ozdal Rakesh Komuravelli D. Korchev Dheevatsa Mudigere Krishnakumar Nair Maxim Naumov 34 6 0 28 Mar 2022
Learning Compressed Embeddings for On-Device Inference Niketan Pansare J. Katukuri Aditya Arora F. Cipollone R. Shaik Noyan Tokgozoglu Chandru Venkataraman 29 14 0 18 Mar 2022
ORCA: A Network and Architecture Co-design for Offloading us-scale Datacenter Applications Yifan Yuan Jing-yu Huang Yan Sun Tianchen Wang Jacob Nelson Dan R. K. Ports Yipeng Wang Ren Wang Charlie Tai N. Kim 32 2 0 16 Mar 2022
Hercules: Heterogeneity-Aware Inference Serving for At-Scale Personalized Recommendation Liu Ke Udit Gupta Mark Hempstead Carole-Jean Wu Hsien-Hsin S. Lee Xuan Zhang 24 21 0 14 Mar 2022
GPU-Initiated On-Demand High-Throughput Storage Access in the BaM System Architecture Zaid Qureshi Vikram Sharma Mailthody Isaac Gelado S. Min Amna Masood ... Dmitri Vainbrand I-Hsin Chung M. Garland W. Dally Wen-mei W. Hwu GNN 31 21 0 09 Mar 2022
PARIS and ELSA: An Elastic Scheduling Algorithm for Reconfigurable Multi-GPU Inference Servers Yunseong Kim Yujeong Choi Minsoo Rhu 18 15 0 27 Feb 2022
BagPipe: Accelerating Deep Recommendation Model Training Saurabh Agarwal Chengpo Yan Ziyi Zhang Shivaram Venkataraman 29 17 0 24 Feb 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
SparseP: Towards Efficient Sparse Matrix Vector Multiplication on Real Processing-In-Memory Systems Christina Giannoula Ivan Fernandez Juan Gómez Luna N. Koziris G. Goumas O. Mutlu MoE 16 26 0 13 Jan 2022
Synthetic Data and Simulators for Recommendation Systems: Current State and Future Directions Adam Lesnikowski G. D. S. P. Moreira Sara Rabhi K. Byleen-Higley ELM 15 2 0 21 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
GNNear: Accelerating Full-Batch Training of Graph Neural Networks with Near-Memory Processing Zhe Zhou Cong Li Xuechao Wei Xiaoyang Wang Guangyu Sun GNN 16 24 0 01 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 45 381 0 30 Oct 2021
Differentiable NAS Framework and Application to Ads CTR Prediction Ravi Krishna Aravind Kalaiah Bichen Wu Maxim Naumov Dheevatsa Mudigere M. Smelyanskiy Kurt Keutzer 20 8 0 25 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
Looper: An end-to-end ML platform for product decisions I. Markov Hanson Wang Nitya Kasturi Shaun Singh Szeto Wai Yuen ... Michael Belkin Sal Uryasev Sam Howie E. Bakshy Norm Zhou OffRL 33 15 0 14 Oct 2021
Understanding Data Storage and Ingestion for Large-Scale Deep Recommendation Model Training Mark Zhao Niket Agarwal Aarti Basant B. Gedik Satadru Pan ... Kevin Wilfong Harsha Rastogi Carole-Jean Wu Christos Kozyrakis Parikshit Pol GNN 26 70 0 20 Aug 2021
$Random Offset Block Embedding Array (ROBE) for CriteoTB Benchmark MLPerf DLRM Model : 1000$\times$ Compression and 3.1$\times$ Faster Inference$ Random Offset Block Embedding Array (ROBE) for CriteoTB Benchmark MLPerf DLRM Model : 1000 $\times$ Compression and 3.1 $\times$ Faster Inference Aditya Desai Li Chou Anshumali Shrivastava AI4CE 25 6 0 04 Aug 2021
Leaf-FM: A Learnable Feature Generation Factorization Machine for Click-Through Rate Prediction Qingyun She Zhiqiang Wang Junlin Zhang 26 1 0 26 Jul 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 21 11 0 26 May 2021
Post-Training Sparsity-Aware Quantization Gil Shomron F. Gabbay Samer Kurzum U. Weiser MQ 36 33 0 23 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 41 32 0 18 May 2021
DAMOV: A New Methodology and Benchmark Suite for Evaluating Data Movement Bottlenecks Geraldo F. Oliveira Juan Gómez Luna Lois Orosa Saugata Ghose Nandita Vijaykumar Ivan Fernandez Mohammad Sadrosadati O. Mutlu 36 82 0 08 May 2021
CoSA: Scheduling by Constrained Optimization for Spatial Accelerators Qijing Huang Minwoo Kang Grace Dinh Thomas Norell Aravind Kalaiah J. Demmel J. Wawrzynek Y. Shao 15 105 0 05 May 2021
Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems Xiaocong Du Bhargav Bhushanam Jiecao Yu Dhruv Choudhary Tianxiang Gao Sherman Wong Louis Feng Jongsoo Park Yu Cao A. Kejariwal 26 5 0 04 May 2021
Faa $T: A Transparent Auto-Scaling Cache for Serverless Applications$ Francisco Romero G. Chaudhry Íñigo Goiri Pragna Gopa Paul Batum N. Yadwadkar Rodrigo Fonseca Christos Kozyrakis Ricardo Bianchini 60 111 0 28 Apr 2021
Software-Hardware Co-design for Fast and Scalable Training of Deep Learning Recommendation Models Dheevatsa Mudigere Y. Hao Jianyu Huang Zhihao Jia Andrew Tulloch ... Ajit Mathews Lin Qiao M. Smelyanskiy Bill Jia Vijay Rao 32 149 0 12 Apr 2021
ECRM: Efficient Fault Tolerance for Recommendation Model Training via Erasure Coding Kaige Liu J. Kosaian K. V. Rashmi 22 4 0 05 Apr 2021
Accelerating Recommendation System Training by Leveraging Popular Choices Muhammad Adnan Yassaman Ebrahimzadeh Maboud Divyat Mahajan Prashant J. Nair 17 55 0 01 Mar 2021
Semantically Constrained Memory Allocation (SCMA) for Embedding in Efficient Recommendation Systems Aditya Desai Yanzhou Pan K. Sun Li Chou Anshumali Shrivastava 20 9 0 24 Feb 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 14 114 0 29 Jan 2021
TT-Rec: Tensor Train Compression for Deep Learning Recommendation Models Chunxing Yin Bilge Acun Xing Liu Carole-Jean Wu 42 102 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 23 109 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 18 31 0 05 Nov 2020
Understanding Capacity-Driven Scale-Out Neural Recommendation Inference Michael Lui Yavuz Yetim Özgür Özkan Zhuoran Zhao Shin-Yeh Tsai Carole-Jean Wu Mark Hempstead GNN BDL LRM 22 51 0 04 Nov 2020
Tensor Casting: Co-Designing Algorithm-Architecture for Personalized Recommendation Training Youngeun Kwon Yunjae Lee Minsoo Rhu 19 39 0 25 Oct 2020
Adaptive Dense-to-Sparse Paradigm for Pruning Online Recommendation System with Non-Stationary Data Mao Ye Dhruv Choudhary Jiecao Yu Ellie Wen Zeliang Chen Jiyan Yang Jongsoo Park Qiang Liu A. Kejariwal 13 9 0 16 Oct 2020
MicroRec: Efficient Recommendation Inference by Hardware and Data Structure Solutions Wenqi Jiang Zhen He Shuai Zhang Thomas B. Preußer Kai Zeng ... Tongxuan Liu Yong Li Jingren Zhou Ce Zhang Gustavo Alonso 34 7 0 12 Oct 2020
Cross-Stack Workload Characterization of Deep Recommendation Systems Samuel Hsia Udit Gupta Mark Wilkening Carole-Jean Wu Gu-Yeon Wei David Brooks BDL GNN HAI 20 32 0 10 Oct 2020
Accelerating Recommender Systems via Hardware "scale-in" S. Krishna Ravi Krishna GNN LRM 19 6 0 11 Sep 2020
Model Size Reduction Using Frequency Based Double Hashing for Recommender Systems Caojin Zhang Yicun Liu Yuanpu Xie S. Ktena Alykhan Tejani ... Suvadip Paul Ikuhiro Ihara P. Upadhyaya Ferenc Huszár Wenzhe Shi 28 53 0 28 Jul 2020
AI Tax: The Hidden Cost of AI Data Center Applications Daniel Richins Dharmisha Doshi Matthew Blackmore A. Nair Neha Pathapati ... Daniel Dobrijalowski R. Illikkal Kevin Long David Zimmerman Vijay Janapa Reddi 10 5 0 21 Jul 2020
Optimizing Prediction Serving on Low-Latency Serverless Dataflow Vikram Sreekanti Harikaran Subbaraj Chenggang Wu Joseph E. Gonzalez J. M. Hellerstein 20 21 0 11 Jul 2020
Centaur: A Chiplet-based, Hybrid Sparse-Dense Accelerator for Personalized Recommendations Ranggi Hwang Taehun Kim Youngeun Kwon Minsoo Rhu 18 103 0 12 May 2020
Optimizing Deep Learning Recommender Systems' Training On CPU Cluster Architectures Dhiraj D. Kalamkar E. Georganas Sudarshan Srinivasan Jianping Chen Mikhail Shiryaev A. Heinecke 48 47 0 10 May 2020
A Social Search Model for Large Scale Social Networks Yunzhong He Wenyuan Li Liangxing Chen Gabriel Forgues Xunlong Gui Sui Liang Bo Hou GNN 26 2 0 09 May 2020
Developing a Recommendation Benchmark for MLPerf Training and Inference Carole-Jean Wu Robin Burke Ed H. Chi Joseph Konstan Julian McAuley Yves Raimond Hao Zhang VLM 8 29 0 16 Mar 2020
DeepRecSys: A System for Optimizing End-To-End At-scale Neural Recommendation Inference Udit Gupta Samuel Hsia V. Saraph Xiaodong Wang Brandon Reagen Gu-Yeon Wei Hsien-Hsin S. Lee David Brooks Carole-Jean Wu GNN 25 188 0 08 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 46 213 0 30 Dec 2019
NeuMMU: Architectural Support for Efficient Address Translations in Neural Processing Units Bongjoon Hyun Youngeun Kwon Yujeong Choi John Kim Minsoo Rhu 17 28 0 15 Nov 2019