https://github.com/SotaroKaneda/MLCarbon

End-to-end carbon footprint mod- eling tool
https://github.com/SotaroKaneda/MLCarbon

Last synced: 6 days ago
JSON representation

End-to-end carbon footprint mod- eling tool

• Host: GitHub
• URL: https://github.com/SotaroKaneda/MLCarbon
• Owner: SotaroKaneda
• Created: 2023-07-26T18:13:56.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-05-14T15:52:54.000Z (6 months ago)
• Last Synced: 2024-08-02T06:11:56.978Z (3 months ago)
• Language: Python
• Size: 2.01 MB
• Stars: 27
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• awesome-green-ai - MLCarbon - End-to-end carbon footprint modeling tool. (🛠 Tools / Calculation Tools)
• Awesome-Resource-Efficient-LLM-Papers - LLMCarbon

README

        
# LLMCarbon

A prelimiary code repo for LLMCarbon: Modeling the End-to-End Carbon Footprint of Large Language Models. More details can be viewed at https://github.com/UnchartedRLab/LLMCarbon. LLMCarbon provides precise predictions of both operational and embodied carbon footprints of large language models (LLMs), enabling effective exploration of the design space by considering the trade-off between test loss and carbon footprint. These carbon footprint exploration can be considered before training an LLM to ensure responsible and sustainable development.

## Run Validations

To generate the data in the table 4 and table 5 in the paper

```

python3 llmcarbon_tutorial.py

```

## Estimation of CO2 equivalent emissions of tranformer based large language models

Estimated regression coefficients used for polynomial fit  $\mathbf{y = ax^2 + bx + c} $

- Tensor model throughput: $$a= -8.82079068\times 10^{-20},  b= 1.68591116\times 10^{-09},  c= 1.33954735\times 10^{+02}$$

- Pipeline model throughput: $$a= -5.60233749\times 10^{-23},  b= 8.45435587\times 10^{-11},  c= 1.34546129\times 10^{+02}$$

- Total number of GPUs: $$a= -2.12910565\times 10^{-21},  b= 4.39684339\times 10^{-09},  c=7.99173057\times 10^{+02}$$

- Batch Size: $$a = -4.29439186\times 10^{-01},  b= 5.21376002\times 10^{+01},  c= 1.43737095\times 10^{+03}$$

![alt text](https://github.com/SotaroKaneda/MLCarbon/blob/main/img/ml_para_set_1.jpg)

## Bibtex

```

@inproceedings{

faiz2024llmcarbon,

title={{LLMC}arbon: Modeling the End-to-End Carbon Footprint of Large Language Models},

author={Ahmad Faiz and Sotaro Kaneda and Ruhan Wang and Rita Chukwunyere Osi and Prateek Sharma and Fan Chen and Lei Jiang},

booktitle={The Twelfth International Conference on Learning Representations},

year={2024},

url={https://openreview.net/forum?id=aIok3ZD9to}

}

```