15 citations · 33 across the 8 of their papers we have counts for
3 papers · 1 filter
VirtualFlow: Decoupling Deep Learning Models from the Underlying Hardware
Andrew Or, Haoyu Zhang, Michael J. Freedman
State-of-the-art deep learning systems such as TensorFlow and PyTorch tightly couple the model with the underlying hardware. This coupling requires the user to modify application l…
Live Recovery of Bit Corruptions in Datacenter Storage Systems
Amy Tai, Andrew Kryczka, Shobhit Kanaujia +6
Due to its high performance and decreasing cost per bit, flash is becoming the main storage medium in datacenters for hot data. However, flash endurance is a perpetual problem, and…
SLAQ: Quality-Driven Scheduling for Distributed Machine Learning
Haoyu Zhang, Logan Stafman, Andrew Or +1
Training machine learning (ML) models with large datasets can incur significant resource contention on shared clusters. This training typically involves many iterations that contin…