22 citations · 40 across the 5 of their papers we have counts for
5 papers
Torch.fx: Practical Program Capture and Transformation for Deep Learning in Python
James K. Reed, Zachary DeVito, Horace He +2
Modern deep learning frameworks provide imperative, eager execution programming interfaces embedded in Python to provide a productive development experience. However, deep learning…
CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research
Chris Cummins, Bram Wasti, Jiadong Guo +9
Interest in applying Artificial Intelligence (AI) techniques to compiler optimizations is increasing rapidly, but compiler research has a high entry barrier. Unlike in other domain…
Using Python for Model Inference in Deep Learning
Zachary DeVito, Jason Ansel, Will Constable +3
Python has become the de-facto language for training deep neural networks, coupling a large suite of scientific computing libraries with efficient libraries for tensor computation…
Tight Prediction Intervals Using Expanded Interval Minimization
Dongqi Su, Ying Yin Ting, Jason Ansel
Prediction intervals are a valuable way of quantifying uncertainty in regression problems. Good prediction intervals should be both correct, containing the actual value between the…
DMTCP: Transparent Checkpointing for Cluster Computations and the Desktop
Jason Ansel, Kapil Arya, Gene Cooperman
DMTCP (Distributed MultiThreaded CheckPointing) is a transparent user-level checkpointing package for distributed applications. Checkpointing and restart is demonstrated for a wide…