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2211.05239
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RecD: Deduplication for End-to-End Deep Learning Recommendation Model Training Infrastructure
9 November 2022
Mark Zhao
Dhruv Choudhary
Devashish Tyagi
A. Somani
Max Kaplan
Sung-Han Lin
S. Pumma
Jongsoo Park
Aarti Basant
Niket Agarwal
Carole-Jean Wu
Christos Kozyrakis
VLM
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Papers citing
"RecD: Deduplication for End-to-End Deep Learning Recommendation Model Training Infrastructure"
6 / 6 papers shown
Title
Characterizing and Efficiently Accelerating Multimodal Generation Model Inference
Yejin Lee
Anna Y. Sun
Basil Hosmer
Bilge Acun
Can Balioglu
...
Ram Pasunuru
Scott Yih
Sravya Popuri
Xing Liu
Carole-Jean Wu
50
2
0
30 Sep 2024
Efficient Tabular Data Preprocessing of ML Pipelines
Yu Zhu
Wenqi Jiang
Gustavo Alonso
LMTD
13
1
0
23 Sep 2024
PreSto: An In-Storage Data Preprocessing System for Training Recommendation Models
Yunjae Lee
Hyeseong Kim
Minsoo Rhu
29
3
0
11 Jun 2024
RecShard: Statistical Feature-Based Memory Optimization for Industry-Scale Neural Recommendation
Geet Sethi
Bilge Acun
Niket Agarwal
Christos Kozyrakis
Caroline Trippel
Carole-Jean Wu
39
66
0
25 Jan 2022
Deduplicating Training Data Makes Language Models Better
Katherine Lee
Daphne Ippolito
A. Nystrom
Chiyuan Zhang
Douglas Eck
Chris Callison-Burch
Nicholas Carlini
SyDa
237
588
0
14 Jul 2021
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
36
83
0
20 Mar 2020
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