# Applying the Roofline model for Deep Learning performance optimizations

arXiv: https://arxiv.org/abs/2009.11224 · HTML: https://mlsanity.com/paper/2009.11224/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Sep 2020.

## Built on by (most cited first, 2 of 2)

- [The Sparsity Roofline: Understanding the Hardware Limits of Sparse Neural Networks](https://mlsanity.com/paper/2310.00496/) (2023)
- [The Energy Consumption of Transformer Fine-Tuning: A Roofline-Inspired Scaling Model](https://mlsanity.com/paper/2606.23546/) (2026)

## Abstract (arXiv)

In this paper We present a methodology for creating Roofline models automatically for Non-Unified Memory Access (NUMA) using Intel Xeon as an example. Finally, we present an evaluation of highly efficient deep learning primitives as implemented in the Intel oneDNN Library.