An analytical tool for studying architectural performance rooflines of arbitrary workloads on different chips.
The original Roofline paper visualized the achieved TFLOPS versus operational intensity of a workload for a given chip.
This tool instead plots achieved workload throughput versus operational intensity for a given chip.
It lets you explore how different hardware compare for the same workload, and also how different implementations of the same workload compare on the same hardware.
Take a look at notebooks/tpu.ipynb for an example study that plots the performance of ResNet-50 and BERT (in samples/sec) on TPUv1 and TPUv4i.
rooflining-util/
├─ notebooks/ # Contains independent Jupyter notebooks; each should represent a unique rooflining study.
├─ src/ # Common classes, functions, and their corresponding unit tests that are shared across notebooks.
└─ README.adoc # This document.You need Python 3 and Jupyter installed on your system.
If you’re using Visual Studio Code (VSCode) as your development environment, this can be accomplished by installing the appropriate extensions from Microsoft.
kbd:[cmd+P] (open the VSCode command box)
ext install ms-python.python
kbd:[cmd+P] (open the VSCode command box)
ext install ms-toolsai.jupyter
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