Speed up gradient boosting, array math and model training with the GPU on an NVIDIA Tesla P40 (24 GB VRAM, Pascal architecture). GPU servers are not orderable yet; contact us to be notified when they are.
$ pip install cuml-cu12 xgboost cudf-cu12
# Example install command
GPU-accelerated machine learning uses CUDA to speed up training and prediction. Libraries such as XGBoost and CuPy can use the GPU; NVIDIA RAPIDS needs newer GPUs than the Pascal P40.
Train gradient boosting models on the GPU.
NumPy-compatible arrays that run on the GPU.
Train neural models alongside classical ones on the same server.
Install the library versions your pipeline needs.
Machine Learning can use an NVIDIA GPU to speed up its work. VPS.org GPU servers are not available to order yet; contact us to hear when they are. Machine Learning is a general GPU-accelerated workload. Make sure your software has CUDA support and that your driver / runtime versions match the workload requirements for Machine Learning.
GPU servers are not available to order yet. Today you can run Machine Learning on a regular CPU plan, where it works far more slowly than on a GPU: SSH in and run pip install cuml-cu12 xgboost cudf-cu12.
VRAM needs for Machine Learning depend on the model and batch size; check the project documentation for current figures.
GPU pricing will be published when GPU servers can be ordered. Contact us if you want to hear when that happens.
Yes. Every VPS.org server comes with full root access, so you can run other tools alongside Machine Learning within the server's RAM and storage.
Every VPS.org server comes with full root SSH access, so you can install drivers, libraries and Machine Learning however you need.
No. No server comes with a CUDA runtime or NVIDIA driver preinstalled, and GPU servers are not available to order yet. You install the versions Machine Learning needs yourself.
Yes. VPS.org servers are persistent virtual machines, not ephemeral instances: Machine Learning models, configs and data stay on the server's SSD storage until you delete them.
Keep working data on the server's SSD for fast access during Machine Learning runs, and copy finished artifacts (weights, generations, embeddings) to storage outside VPS.org; snapshots and backups stay on the same storage cluster.
You can upgrade any VPS.org server to a larger plan from the control panel; the resize restarts it and your Machine Learning install carries over. GPU servers are not available yet.
Yes. Backups are a paid add-on (daily +30% of the plan price, kept 7 days; weekly +20%, kept 28 days) and snapshots are free, which is useful before long Machine Learning runs. Both stay on the same storage cluster as the server.
Contact support within 30 days of your first purchase to request a refund. GPU servers are not sold yet, so no GPU order is involved.
GPU servers are not orderable yet. Tell us about your workload and we will let you know when they are.