ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2205.04702
  4. Cited By
Training Personalized Recommendation Systems from (GPU) Scratch: Look
  Forward not Backwards

Training Personalized Recommendation Systems from (GPU) Scratch: Look Forward not Backwards

10 May 2022
Youngeun Kwon
Minsoo Rhu
ArXivPDFHTML

Papers citing "Training Personalized Recommendation Systems from (GPU) Scratch: Look Forward not Backwards"

13 / 13 papers shown
Title
SCRec: A Scalable Computational Storage System with Statistical Sharding and Tensor-train Decomposition for Recommendation Models
SCRec: A Scalable Computational Storage System with Statistical Sharding and Tensor-train Decomposition for Recommendation Models
Jinho Yang
Ji-Hoon Kim
Joo-Young Kim
44
0
0
01 Apr 2025
Pushing the Performance Envelope of DNN-based Recommendation Systems
  Inference on GPUs
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
33
2
0
29 Oct 2024
PreSto: An In-Storage Data Preprocessing System for Training
  Recommendation Models
PreSto: An In-Storage Data Preprocessing System for Training Recommendation Models
Yunjae Lee
Hyeseong Kim
Minsoo Rhu
42
3
0
11 Jun 2024
ElasticRec: A Microservice-based Model Serving Architecture Enabling
  Elastic Resource Scaling for Recommendation Models
ElasticRec: A Microservice-based Model Serving Architecture Enabling Elastic Resource Scaling for Recommendation Models
Yujeong Choi
Jiin Kim
Minsoo Rhu
39
1
0
11 Jun 2024
LazyDP: Co-Designing Algorithm-Software for Scalable Training of
  Differentially Private Recommendation Models
LazyDP: Co-Designing Algorithm-Software for Scalable Training of Differentially Private Recommendation Models
Juntaek Lim
Youngeun Kwon
Ranggi Hwang
Kiwan Maeng
Edward Suh
Minsoo Rhu
SyDa
33
0
0
12 Apr 2024
Failure Tolerant Training with Persistent Memory Disaggregation over CXL
Failure Tolerant Training with Persistent Memory Disaggregation over CXL
Miryeong Kwon
Junhyeok Jang
Hanjin Choi
Sangwon Lee
Myoungsoo Jung
32
8
0
14 Jan 2023
FlexShard: Flexible Sharding for Industry-Scale Sequence Recommendation
  Models
FlexShard: Flexible Sharding for Industry-Scale Sequence Recommendation Models
Geet Sethi
Pallab Bhattacharya
Dhruv Choudhary
Carole-Jean Wu
Christos Kozyrakis
24
5
0
08 Jan 2023
A Comprehensive Survey on Trustworthy Recommender Systems
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
43
46
0
21 Sep 2022
Heterogeneous Acceleration Pipeline for Recommendation System Training
Heterogeneous Acceleration Pipeline for Recommendation System Training
Muhammad Adnan
Yassaman Ebrahimzadeh Maboud
Divyat Mahajan
Prashant J. Nair
34
18
0
11 Apr 2022
GROW: A Row-Stationary Sparse-Dense GEMM Accelerator for
  Memory-Efficient Graph Convolutional Neural Networks
GROW: A Row-Stationary Sparse-Dense GEMM Accelerator for Memory-Efficient Graph Convolutional Neural Networks
Ranggi Hwang
M. Kang
Jiwon Lee
D. Kam
Youngjoo Lee
Minsoo Rhu
GNN
16
20
0
01 Mar 2022
BagPipe: Accelerating Deep Recommendation Model Training
BagPipe: Accelerating Deep Recommendation Model Training
Saurabh Agarwal
Chengpo Yan
Ziyi Zhang
Shivaram Venkataraman
37
17
0
24 Feb 2022
Distributed Hierarchical GPU Parameter Server for Massive Scale Deep
  Learning Ads Systems
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
59
150
0
12 Mar 2020
RecNMP: Accelerating Personalized Recommendation with Near-Memory
  Processing
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
49
214
0
30 Dec 2019
1