Explanation
- This dataset captures both tabular metadata and graph representations from deep learning training workflows, extracted via TensorFlow's XLA compiler.
- This dataset captures both tabular metadata and graph representations from deep learning training workflows, extracted via TensorFlow's XLA compiler.
TapisUI provides a research oriented frontend to interact with Tapis and tenant components. In this case, the ICICLE extension extends TapisUI with custom branding
A dataset designed to support AI-driven resource estimation like runtime prediction to support HPC scheduling optimization by leveraging compiler-level High-Level Optimizer (HLO) graph features and deep learning workload metadata.
How to Predict Training Time Using Metadata
View the main TapisUI wiki to learn how to deploy and test TapisUI extensions locally.
This tapis ui extension enables additional icicle specific branding and tabs on tapisui.
Getting Started with the HLO Feature Dataset