NVIDIA Tesla P40 · 24GB VRAM

Server notebook della GPU Jupyter

Eseguire notebook Jupyter con supporto dedicato NVIDIA GPU. Analisi dati interattiva e sviluppo ML con accelerazione CUDA.

$ pip install jupyterlab torch && jupyter lab --ip=0.0.0.0 --allow-root
# Esecuzione su NVIDIA Tesla P40 (24GB)
Pronti. _

Che cos'è {nome} su un VPS GPU?

I taccuini Jupyter su un VPS GPU offrono un ambiente di sviluppo interattivo con hardware dedicato NVIDIA GPU. Perfetto per la data science, la sperimentazione ML e la prototipazione di modelli.

Perché {nome} su VPS.org GPU

GPU in Notebook

Accedi alle GPU CUDA direttamente dalle celle dei taccuini. Train models interattivamente.

JupyterLabCity name (optional, probably does not need a translation)

IDE completo di JupyterLab con terminale, file browser ed estensioni.

Librerie preinstallate

PyTorch, TensorFlow, scikit-learn, panda, e più pronto all'uso.

Accesso remoto

Accedere ai taccuini da qualsiasi browser, ovunque.

Casi di utilizzo popolari {nome}

Sperimentazione ML
Esplorazione dei dati
Prototipazione modello
Workshop educativi
Quaderni di ricerca
Concorsi Kaggle

Specifiche GPU

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
Core CUDA3,840
32° PQ12 TFLOPS
INT847 TOPS
Memoria BW346 GB/s
ArchitetturaPascal (GP102)
PassaggioPCI Bare-metal

Domande frequenti

What is Jupyter on a GPU VPS?

+

Jupyter on a GPU VPS is a CUDA-accelerated deployment. Jupyter is a general GPU-accelerated workload. Make sure your software has CUDA support and that your driver / runtime versions match the workload requirements for Jupyter.

How do I set up Jupyter on a GPU VPS?

+

Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install jupyterlab torch && jupyter lab --ip=0.0.0.0 --allow-root. Your Jupyter environment is ready in minutes with full GPU acceleration.

How much VRAM do I need for Jupyter?

+

Our GPU VPS ships with 24 GB GDDR5X VRAM on the NVIDIA Tesla P40, which is sufficient for most Jupyter workloads. Multi-GPU configurations are available on request.

Is Jupyter GPU VPS billed hourly or monthly?

+

GPU VPS plans are billed monthly with no lock-in contracts and can be cancelled anytime. Contact us for current GPU pricing tiers.

Can I run other tools alongside Jupyter?

+

Yes — you have full root on the GPU VPS. Run whatever fits inside the 24 GB VRAM and the available RAM / storage budget alongside Jupyter.

Do I get full root on the Jupyter GPU VPS?

+

Yes. Full root SSH on every GPU VPS — install drivers, swap CUDA versions, customize the environment for Jupyter however you need.

Which CUDA version is installed for Jupyter?

+

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 Jupyter workload.

Does my Jupyter GPU VPS persist between sessions?

+

Yes — your Jupyter GPU VPS is a long-running persistent server, not an ephemeral instance. Models, configs, and data stay on the SSD between sessions.

Where should I store data for my Jupyter workload?

+

Keep working data on the VPS SSD for fast access during Jupyter runs; back up finished artifacts (weights, generations, embeddings) off-server via snapshots or object storage for safety.

Can I scale my Jupyter GPU VPS later?

+

Yes — plan upgrades are instant from your control panel; the GPU itself can be swapped to a larger tier on request. Your Jupyter install carries over.

Are backups available for my GPU VPS?

+

Yes. Automated daily backups are an add-on; manual snapshots are free. Useful for long Jupyter training runs where you want a checkpointable server state.

Is there a money-back guarantee on the GPU VPS?

+

Yes — 30-day money-back guarantee on every plan including GPU. Try Jupyter on a GPU VPS risk-free.

Pronto per eseguire {nome} sulla GPU?

Distribuisci un server dedicato NVIDIA GPU in pochi minuti. Nessuna prenotazione, nessuna chiamata di vendita.

Lancia il tuo VPS
Da $ 2,0/mo