Enabling Compute-Communication Overlap in Distributed Deep Learning Training Platforms-Reference-Cited by-同舟云学术

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Enabling Compute-Communication Overlap in Distributed Deep Learning Training Platforms

Published:2021-06 Issue: Volume: Page:
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Container-title:2021 ACM/IEEE 48th Annual International Symposium on Computer Architecture (ISCA)
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Author:

Rashidi Saeed,Denton Matthew,Sridharan Srinivas,Srinivasan Sudarshan,Suresh Amoghavarsha,Nie Jade,Krishna Tushar

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9499716/9499722/09499904.pdf?arnumber=9499904

Cited by 25 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Towards a Standardized Representation for Deep Learning Collective Algorithms;2024 IEEE Symposium on High-Performance Interconnects (HOTI);2024-08-21

2. Improving Automatic Parallel Training via Balanced Memory Workload Optimization;IEEE Transactions on Knowledge and Data Engineering;2024-08

3. PID-Comm: A Fast and Flexible Collective Communication Framework for Commodity Processing-in-DIMM Devices;2024 ACM/IEEE 51st Annual International Symposium on Computer Architecture (ISCA);2024-06-29

4. Galaxy: A Resource-Efficient Collaborative Edge AI System for In-situ Transformer Inference;IEEE INFOCOM 2024 - IEEE Conference on Computer Communications;2024-05-20

5. LIBRA: Enabling Workload-Aware Multi-Dimensional Network Topology Optimization for Distributed Training of Large AI Models;2024 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS);2024-05-05

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