Last semester while working on deep learning side projects (most notably a TensorFlow CharRNN chatbot trained on ~500k of my own text messages) I'd always come across the same problem: I couldn't afford GPUs as a broke college student.
After being fed up spending more money on cloud resources than I did on food, I decided to build my own cloud GPU provider with prices ~3-5x less than AWS, GCP, and Azure. I did this by aggregated underutilized servers from different hosting providers across the world and developing a layer of abstraction over their heterogenous hardware which lets anyone access it for far cheaper than AWS.
Last semester while working on deep learning side projects (most notably a TensorFlow CharRNN chatbot trained on ~500k of my own text messages) I'd always come across the same problem: I couldn't afford GPUs as a broke college student.
After being fed up spending more money on cloud resources than I did on food, I decided to build my own cloud GPU provider with prices ~3-5x less than AWS, GCP, and Azure. I did this by aggregated underutilized servers from different hosting providers across the world and developing a layer of abstraction over their heterogenous hardware which lets anyone access it for far cheaper than AWS.
It's live at https://vectordash.com - you can create a Linux VM within seconds.
Any feedback or feature requests would be much appreciated and happy training!