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<div align="center">
# 🚀 🔥 Fractional GPU! ⚡ 📣
## Run multiple containers on the same GPU with driver level memory limitation ✨ and compute time-slicing 🎊
`🌟 Leave a star to support the project! 🌟`
</div>
## 🔰 Introduction
Sharing high-end GPUs or even prosumer & consumer GPUs between multiple users is the most cost-effective
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```
### 🐳 Containers
| Memory Limit | CUDA Ver | Ubuntu Ver | Docker Image |
|:-------------:|:--------:|:----------:|:----------------------------------------:|
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Build your own containers and inherit form the original containers
You can find a few examples [here](https://github.com/allegroai/clearml-fractional-gpu/tree/main/examples).
You can find a few examples [here](https://github.com/allegroai/clearml-fractional-gpu/docker-examples).
## 🌸 Implications
## ☸ Kubernetes
Our fractional GPU containers can be used on bare-metal executions as well as Kubernetes PODs.
Yes! By using one our Fractional GPU containers you can limit the memory consumption your Job/Pod and
Fractional GPU containers can be used on bare-metal executions as well as Kubernetes PODs.
Yes! By using one the Fractional GPU containers you can limit the memory consumption your Job/Pod and
allow you to easily share GPUs without fearing they will memory crash one another!
Here's a simple Kubernetes POD template:
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The containers support Nvidia drivers <= `545.x.x`
We will keep updating & supporting new drivers as they continue to be released
**Supported GPUs**: GTX series 10, 20, 30, 40, RTX A series, and Data-Center P100, A100, A10/A40, L40/s, H100
**Supported GPUs**: RTX series 10, 20, 30, 40, A series, and Data-Center P100, A100, A10/A40, L40/s, H100
**Limitations**: Windows Host machines are currently not supported, if this is important for you, leave a request in the [Issues](/issues) section
## ❓ FAQ