Faʻavasegaina o faʻamatalaga tele 10-100x vave ma mea faigaluega o le GPU-faʻaititia o le faʻamatalaga o le faʻamatalaga. RAPIDS, Jupyter, ma le atoa PyData stack i luga o le NVIDIA hardware.
$ pip install cudf-cu12 cuml-cu12 jupyterlab && jupyter lab --ip=0.0.0.0 # Taʻalo i luga o NVIDIA Tesla P40 (24GB) Faʻatonu _
GPU-faʻaititia le saienisi o faʻamatalaga e faʻaaogaina ai NVIDIA RAPIDS e faʻagaioia ai pandas, scikit-learn, ma isi meafaigaluega faʻamatalaga faʻasolosolo i le GPU. Faʻavasegaina o faʻamatalaga e mafai ona faʻaalu itula i le CPU i minute.
cuDF (GPU pandas), cuML (GPU scikit-learn), cuGraph (GPU NetworkX).
Faʻatonu muamua JupyterLab ma le lagolago GPU.
24GB GPU memory mo le faʻaaogaina o faʻamatalaga i le faʻaputuga.
Faʻaaliga GPU-faʻaosoina ma cuXfilter ma Plotly.
Data Science on a GPU VPS is a CUDA-accelerated deployment. Data Science is a general GPU-accelerated workload. Make sure your software has CUDA support and that your driver / runtime versions match the workload requirements for Data Science.
Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install cudf-cu12 cuml-cu12 jupyterlab && jupyter lab --ip=0.0.0.0. Your Data Science environment is ready in minutes with full GPU acceleration.
Our GPU VPS ships with 24 GB GDDR5X VRAM on the NVIDIA Tesla P40, which is sufficient for most Data Science workloads. Multi-GPU configurations are available on request.
GPU VPS plans are billed monthly with no lock-in contracts and can be cancelled anytime. Contact us for current GPU pricing tiers.
Yes — you have full root on the GPU VPS. Run whatever fits inside the 24 GB VRAM and the available RAM / storage budget alongside Data Science.
Yes. Full root SSH on every GPU VPS — install drivers, swap CUDA versions, customize the environment for Data Science however you need.
GPU VPSs ship with a recent CUDA runtime and the matching NVIDIA driver pre-installed. You can pin or upgrade CUDA versions as required by your Data Science workload.
Yes — your Data Science GPU VPS is a long-running persistent server, not an ephemeral instance. Models, configs, and data stay on the SSD between sessions.
Keep working data on the VPS SSD for fast access during Data Science runs; back up finished artifacts (weights, generations, embeddings) off-server via snapshots or object storage for safety.
Yes — plan upgrades are instant from your control panel; the GPU itself can be swapped to a larger tier on request. Your Data Science install carries over.
Yes. Automated daily backups are an add-on; manual snapshots are free. Useful for long Data Science training runs where you want a checkpointable server state.
Yes — 30-day money-back guarantee on every plan including GPU. Try Data Science on a GPU VPS risk-free.
Faʻaaogaina se NVIDIA GPU server faʻapitoa i minute. E leai se faʻatapulaʻaina, leai se telefoni faʻatau.