VirtualFlow: Decoupling Deep Learning Models from the Underlying Hardware

20 September 2020

Papers citing "VirtualFlow: Decoupling Deep Learning Models from the Underlying Hardware"

4 / 4 papers shown

Title
HAP: SPMD DNN Training on Heterogeneous GPU Clusters with Automated Program Synthesis Shiwei Zhang Lansong Diao Chuan Wu Zongyan Cao Siyu Wang Wei Lin 43 12 0 11 Jan 2024
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism M. Shoeybi M. Patwary Raul Puri P. LeGresley Jared Casper Bryan Catanzaro MoE 245 1,826 0 17 Sep 2019
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 297 6,959 0 20 Apr 2018
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 308 2,890 0 15 Sep 2016