# Comparative Analysis of CPU and GPU Profiling for Deep Learning Models

arXiv: https://arxiv.org/abs/2309.02521 · HTML: https://mlsanity.com/paper/2309.02521/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 11 references that are in the map.
- First posted on arXiv 5 Sep 2023.

## Builds on (most cited first, 3 of 3)

- [PyTorch: An Imperative Style, High-Performance Deep Learning Library](https://mlsanity.com/paper/1912.01703/) (2019)
- [Densely Connected Convolutional Networks](https://mlsanity.com/paper/1608.06993/) (2016)
- [Comparative Analysis of Multiple Deep CNN Models for Waste Classification](https://mlsanity.com/paper/2004.02168/) (2020)

## Built on by (most cited first, 4 of 4)

- [Efficient Whole Slide Pathology VQA via Token Compression](https://mlsanity.com/paper/2507.14497/) (2025)
- [ProfilingAgent: Profiling-Guided Agentic Reasoning for Adaptive Model Optimization](https://mlsanity.com/paper/2509.05584/) (2025)
- [FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Review](https://mlsanity.com/paper/2505.13461/) (2025)
- [Backdoor Learning in Language Models and Vision-Language Models](https://mlsanity.com/paper/2608.18095/) (2026)

## Abstract (arXiv)

Deep Learning(DL) and Machine Learning(ML) applications are rapidly increasing in recent days. Massive amounts of data are being generated over the internet which can derive meaningful results by the use of ML and DL algorithms. Hardware resources and open-source libraries have made it easy to implement these algorithms. Tensorflow and Pytorch are one of the leading frameworks for implementing ML projects. By using those frameworks, we can trace the operations executed on both GPU and CPU to analyze the resource allocations and consumption. This paper presents the time and memory allocation of CPU and GPU while training deep neural networks using Pytorch. This paper analysis shows that GPU has a lower running time as compared to CPU for deep neural networks. For a simpler network, there are not many significant improvements in GPU over the CPU.