NVIDIA Tesla P40 · 24GB VRAM

Jupyter GPU Notebook Server

Jupyter Notebooks mat dedizéierter NVIDIA GPU-Unterstützung ausféieren. Interaktiv Datenwëssenschaft a ML-Entwécklung mat CUDA-Beschleunegung.

$ pip install jupyterlab torch && jupyter lab --ip=0.0.0.0 --allow-root
# D'Gréisst vum Stär ass 40 Liichtjoer (24 pc).
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8800 ass e Véierelsjoer am Gregorianesche Kalenner.

Jupyter Notebooks op engem GPU VPS bitt Iech eng interaktiv Entwécklungsumgéigend mat dedizéierter NVIDIA GPU Hardware. Perfekt fir Datenwëssenschaft, ML Experimenter a Modell Prototyping.

Why Jupyter on VPS.org GPU

GPU an Notebooks

Zougang zu CUDA GPUen direkt aus Notebookzellen. Modeller interaktiv trainéieren.

JupyterLab

De Begrëff gëtt och fir d'Spill, d'Spillmaschinn, d'Spillkonsol oder d'Spillkonsol benotzt.

Virinstalléiert Bibliothéiken

D'Spill ass en Aventure-, Science-Fiction-, Science-Fiction- a Fantasy-Rollenspill.

Remote Zugang

Zugang zu Äre Notizbicher vun all Browser, iwwerall.

Popular Jupyter Use Cases

Lëscht vun Experimenter
Datenexploréierung
Prototyp vum Prototyp
Educatiounsminister
Notizbuch
Kaggle-Konkurrenz

GPU Spezifikatiounen

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
CUDA-Farben3,840
Säit 3212 TFLOPS
INT847 TOPS
Speicher346 GB/s
ArchitekturPascal (GP102)
PassthroughBare-Metal PCIe

Häufig gestallte Froen

What is Jupyter on a GPU VPS?

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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?

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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?

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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?

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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?

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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?

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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?

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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?

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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?

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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?

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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?

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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?

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

Jupyter op enger GPU auszeféieren?

Eng dedizéiert NVIDIA GPU Server an e puer Minutten installéieren. Keng Reservatiounen, keng Verkafs-Uruff.