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. 2301.08984
  4. Cited By
SuperScaler: Supporting Flexible DNN Parallelization via a Unified
  Abstraction

SuperScaler: Supporting Flexible DNN Parallelization via a Unified Abstraction

21 January 2023
Zhiqi Lin
Youshan Miao
Guodong Liu
Xiaoxiang Shi
Quanlu Zhang
Fan Yang
Saeed Maleki
Yi Zhu
Xu Cao
Cheng-Wu Li
Mao Yang
Lintao Zhang
Lidong Zhou
ArXivPDFHTML

Papers citing "SuperScaler: Supporting Flexible DNN Parallelization via a Unified Abstraction"

4 / 4 papers shown
Title
Moirai: Towards Optimal Placement for Distributed Inference on
  Heterogeneous Devices
Moirai: Towards Optimal Placement for Distributed Inference on Heterogeneous Devices
Beibei Zhang
Hongwei Zhu
Feng Gao
Zhihui Yang
Xiaoyang Sean Wang
14
1
0
07 Dec 2023
Chimera: Efficiently Training Large-Scale Neural Networks with
  Bidirectional Pipelines
Chimera: Efficiently Training Large-Scale Neural Networks with Bidirectional Pipelines
Shigang Li
Torsten Hoefler
GNN
AI4CE
LRM
77
130
0
14 Jul 2021
ZeRO-Offload: Democratizing Billion-Scale Model Training
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
413
0
18 Jan 2021
Megatron-LM: Training Multi-Billion Parameter Language Models Using
  Model Parallelism
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
1,815
0
17 Sep 2019
1