The artifact contains the latest version of our codebase, called "Catamount", which is a compute graph analysis tool to load, construct, and modify deep learning (DL) models and to symbolically analyze their compute requirements. Catamount can read DL model checkpoints saved from DL frameworks (e.g., from Tensorflow). This artifact includes (A) Tensorflow checkpoints for each of the models (compute graphs) analyzed in the PPoPP 2019 paper, Beyond Human Level Accuracy: Computational Challenges in Deep Learning and (B) shell scripts to run graph analytics and generate results for Figures 7 to 10 of the paper. To validate the results, run the test script, which generates and collects the corresponding outputs:
~$ bash catamount/frameworks/example_graphs/tensorflow/full_models/generate_results.sh