19 citations · 66 across the 10 of their papers we have counts for
3 papers · 1 filter
Bamboo: Making Preemptible Instances Resilient for Affordable Training of Large DNNs
John Thorpe, Pengzhan Zhao, Jonathan Eyolfson +5
DNN models across many domains continue to grow in size, resulting in high resource requirements for effective training, and unpalatable (and often unaffordable) costs for organiza…
Dorylus: Affordable, Scalable, and Accurate GNN Training with Distributed CPU Servers and Serverless Threads
John Thorpe, Yifan Qiao, Jonathan Eyolfson +8
A graph neural network (GNN) enables deep learning on structured graph data. There are two major GNN training obstacles: 1) it relies on high-end servers with many GPUs which are e…
Algorithm-Directed Crash Consistence in Non-Volatile Memory for HPC
Shuo Yang, Kai Wu, Yifan Qiao +2
Fault tolerance is one of the major design goals for HPC. The emergence of non-volatile memories (NVM) provides a solution to build fault tolerant HPC. Data in NVM-based main memor…