With Thunder Compute, run your current workload on cloud GPUs with one line of code. You can develop without paying for a GPU and then instantly connect your environment to as many GPUs as you need to move to production.
https://www.youtube.com/watch?v=qsOBFQZtsFM
Hi everyone, we’re Carl and Brian, aka the team behind Thunder Compute.
Before Thunder Compute, Carl was a Management Consultant at Bain & Company, and Brian was a Quantitative Developer at Citadel Securities. Carl and Brian met at Georgia Tech and have been close friends for over 6 years.
Developers spend hours configuring cloud platforms to meet the ever-changing needs of their projects. Today’s cloud platforms trade-off between:
Thunder Compute is a flexible cloud environment that adapts to the needs of any project with a single command, for example:
Using your local filesystem?
$ tnr start --sync
Scaling to 50 A100 GPUs?
$ tnr device A100 -n 50
Running a Jupyter Notebook?
$ notebook
Developing without a GPU?
$ tnr device cpu
All of this is available at industry-leading prices and can be set up in minutes - just pip install tnr.
Think VMware for GPUs: Thunder Compute tricks your computer into thinking it’s attached to a GPU, which actually sits across a network. This means that CPU-only machines can behave exactly as if they have dedicated GPUs, while the physical GPUs are actually shared among several machines.
To help us test our systems at scale, we are giving free open beta access to NVIDIA T4 instances. Try Thunder Compute today at thundercompute.com. all we ask in return is that you please report any bugs 🙂
If you have questions, need technical support, or want to rant about the current state of GPUs, join our discord at https://discord.gg/nwuETS9jJK or contact us at founders@thundercompute.com.
Carl Peterson and Brian Model met as freshmen at Georgia Tech and became close friends. The idea for Thunder Compute sparked from Brian's experience in his Systems for AI lab, where researchers made GPU reservations weeks in advance via Google Sheets, severely hindering research progress. This inefficiency inspired us to explore ways to improve GPU utilization and the developer experience of using GPUs. \Our thesis was (and still is) that virtualization over a network is the optimal way to manage GPUs within a cloud platform and founded Thunder Compute to bring our technology to market.