NVIDIA Tesla P40 · 24GB VRAM

Lëscht vun de lëtzebuergesche Vëlossportler

Acceleréiert TensorFlow Workloads mat dedizéierter NVIDIA GPU Hardware. Trainéiert Modeller, maacht Viraussiichtsfunktioun a baut ML Pipelines mat voller CUDA Ënnerstëtzung.

$ pip install tensorflow[and-cuda]
# D'Gréisst vum Stär ass 40 Liichtjoer (24 pc).
Bereet. _

8800 ass e Véierelsjoer am Gregorianesche Kalenner.

TensorFlow ass de Google Open-Source-Framework fir d'Entwécklung a Verdeelung vun ML-Modeller. Mat GPU VPS kritt Dir dedizéiert Hardware fir Training a Inferenz ze beschleunegen ouni Ressourcen ze deelen.

Why TensorFlow on VPS.org GPU

GPU-Beschleunigt

Native CUDA-Unterstützung für TensorFlow-Operationen. Bis zu 50x schneller als CPU.

Kompatibel Festplack

De Stär ass eng grouss Kugelstärekëscht mat engem héije Grad un Dicht.

TensorBoard

De Veräin spillt seng Heemspiller am Stade de la Mosson.

Lëscht vun de Gemengen

D'Produktioun vun der Uebst- a Geméiszuel ass op der Héicht.

Popular TensorFlow Use Cases

Klassifikatioun
Objekterkennung
Naturwëssenschaft
Recommandatiounssystemer
Lëscht vun de Stäre
Lëscht vu lëtzebuergesche Filmer

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 TensorFlow on a GPU VPS?

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TensorFlow on a GPU VPS is a CUDA-accelerated deployment. TensorFlow is a training / fine-tuning workload. Plan for long-running jobs — snapshot your VPS regularly, and consider an external cold-storage backup for trained weights.

How do I set up TensorFlow on a GPU VPS?

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Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install tensorflow[and-cuda]. Your TensorFlow environment is ready in minutes with full GPU acceleration.

How much VRAM do I need for TensorFlow?

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Training VRAM is dominated by the optimizer state plus activations. Full fine-tuning of a 7B LLM needs ~24-48 GB; LoRA / QLoRA fits in 8-16 GB. Our Tesla P40 supports LoRA-class fine-tuning out of the box; full training of larger models requires multi-GPU.

Is TensorFlow 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 TensorFlow?

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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 TensorFlow.

Do I get full root on the TensorFlow GPU VPS?

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

Which CUDA version is installed for TensorFlow?

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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 TensorFlow workload.

Does my TensorFlow GPU VPS persist between sessions?

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Yes — your TensorFlow 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 TensorFlow workload?

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

Can I scale my TensorFlow 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 TensorFlow 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 TensorFlow 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 TensorFlow on a GPU VPS risk-free.

TensorFlow op enger GPU auszeféieren?

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