Using NVIDIA GPUs for Scientific Research

Posted on April 3, 2025

Hi everyone,

I’ve been exploring the potential of NVIDIA GPUs for accelerating scientific computations, especially in biological research. I recently came across MDA-MB-231 cells, which are widely used in cancer studies, and I was curious—has anyone here used GPU acceleration for processing large datasets related to cell imaging or molecular simulations?

Would Digital Ocean’s cloud-based GPU instances be a viable option for running deep learning models on biological data? Looking forward to insights from anyone who has experience with this!

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alexdo

April 3, 2025

Heya, @cecafe1ceb9f4e5dbb6d5da92f1e7e

With the GPU Droplets, you can:

Reliably run training and inference on AI/ML models
Process large data sets and complex neural networks for deep learning use cases
Tackle high-performance computing (HPC) tasks with ease

You can check our full article here:

https://www.digitalocean.com/resources/articles/cloud-gpu-provider#build-with-ai-on-digitalocean

https://www.digitalocean.com/resources/articles/cloud-gpu-provider

Hope that this helps!

Bobby Iliev

April 3, 2025

Hey there! 👋

Yes, DigitalOcean’s GPU droplets can definitely be a solid option for running deep learning models, especially if you’re working with large biological datasets like MDA-MB-231 imaging or molecular simulations. I’ve seen folks use them for similar workloads in research and education.