InTune: Reinforcement Learning-based Data Pipeline Optimization for Deep Recommendation Models

13 August 2023

Papers citing "InTune: Reinforcement Learning-based Data Pipeline Optimization for Deep Recommendation Models"

9 / 9 papers shown

Title
PreSto: An In-Storage Data Preprocessing System for Training Recommendation Models Yunjae Lee Hyeseong Kim Minsoo Rhu 24 3 0 11 Jun 2024
Towards a Systems Theory of Algorithms Florian Dorfler Zhiyu He Giuseppe Belgioioso S. Bolognani John Lygeros Michael Muehlebach AI4CE 25 10 0 25 Jan 2024
Saturn: An Optimized Data System for Large Model Deep Learning Workloads Kabir Nagrecha Arun Kumar 11 6 0 03 Sep 2023
RecShard: Statistical Feature-Based Memory Optimization for Industry-Scale Neural Recommendation Geet Sethi Bilge Acun Niket Agarwal Christos Kozyrakis Caroline Trippel Carole-Jean Wu 36 65 0 25 Jan 2022
Hydra: A System for Large Multi-Model Deep Learning Kabir Nagrecha Arun Kumar MoE AI4CE 22 5 0 16 Oct 2021
Model-Parallel Model Selection for Deep Learning Systems Kabir Nagrecha 29 16 0 14 Jul 2021
tf.data: A Machine Learning Data Processing Framework D. Murray Jiří Šimša Ana Klimovic Ihor Indyk PINN AI4CE LMTD 39 86 0 28 Jan 2021
ZeRO-Offload: Democratizing Billion-Scale Model Training Jie Ren Samyam Rajbhandari Reza Yazdani Aminabadi Olatunji Ruwase Shuangyang Yang Minjia Zhang Dong Li Yuxiong He MoE 160 399 0 18 Jan 2021
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism M. Shoeybi M. Patwary Raul Puri P. LeGresley Jared Casper Bryan Catanzaro MoE 243 1,791 0 17 Sep 2019