https://github.com/alisiahkoohi/conv-scaling

Small experiments w/ PyTorch
https://github.com/alisiahkoohi/conv-scaling

Last synced: 3 months ago
JSON representation

Small experiments w/ PyTorch

• Host: GitHub
• URL: https://github.com/alisiahkoohi/conv-scaling
• Owner: alisiahkoohi
• License: mit
• Created: 2020-10-16T19:11:47.000Z (over 4 years ago)
• Default Branch: main
• Last Pushed: 2020-10-17T16:17:36.000Z (over 4 years ago)
• Last Synced: 2025-02-10T00:43:13.082Z (5 months ago)
• Language: Python
• Size: 3.62 MB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# conv-scaling

[![DOI](https://zenodo.org/badge/304717537.svg)](https://zenodo.org/badge/latestdoi/304717537)

Small experiments comparing the wall-clock time and peak memory consumption of 2D convolution implemented with PyTorch (CPU) and Devito.

Throughout the examples below the image size is `n x n x nch` where `n` is the spacial dimension and `nch` is number of channels. We will run 50 2D convolutions where we vary number of input/output channels, the image size, and convolution kernel size. The wall-clock time and peak memory consumption are computed w/ `/usr/bin/time`.

## Installation

```bash

git clone https://github.com/alisiahkoohi/conv-scaling.git

cd conv-scaling

pip install -e .

```

## Wall-clock time

* number of channels: 2

![](figs/runtime_nch0)

* number of channels: 4

![](figs/runtime_nch1)

* number of channels: 8

![](figs/runtime_nch2)

* number of channels: 16

![](figs/runtime_nch3)

## Peak memory

* number of channels: 2

![](figs/memory_nch0)

* number of channels: 4

![](figs/memory_nch1)

* number of channels: 8

![](figs/memory_nch2)

* number of channels: 16

![](figs/memory_nch3)