NVIDIA Tesla P40 · 24GB VRAM

TensorFlow GPU VPS

Ubrzati TensorFlow radno vrijeme s posebnim NVIDIA GPU hardverom. Vlak modeli, služe predviđanja, i izgraditi ML gasovoda s punom podrškom CUDA.

$ pip install tensorflow[and-cuda]
# Trčanje na NVIDIA Tesla P40 (24GB)
Spreman. _

Što je {ime} na GPU VPS?

TensorFlow je Googleov otvoreni sustav strojnog učenja za izgradnju i raspoređivanje modela ML. S GPU VPS-om dobivate posebnu opremu za ubrzavanje treninga i zaključak bez dijeljenja resursa.

Zašto {ime} na VPS.org GPU

GPU ubrzano

Podrška CUDA za TensorFlow operacije. Do 50x brže od CPU-a.

Keras kompatibilan

Puna Keras integracija za zgradu modela visoke razine s GPU podrškom.

TensorBoard

Trening monitora s TensorBoardom na vlastitom poslužitelju.

TF servisiranje spremno

Pokrenite modele na proizvodnju s TensorFlow servisom na GPU.

Popularne {ime} Slučaji korištenja

Klasifikacija slike
Otkrivanje objekta
Prerada prirodnog jezika
Preporučni sustavi
Prognoza vremenskih nizova
Proizvodnja ML cjevovoda

GPU specifikacije

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
CUDA jezgre3,840
FP3212 TFLOPS
INT847 TOPS
Memorija BW346 GB/s
ArhitekturaPascal (GP102)
ProlazPCIe od borovog metala

Česta pitanja

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.

Spreman za pokretanje {ime} na GPU?

Pokrenite posvećeni NVIDIA GPU poslužitelj u minutama. Bez rezervacije, bez prodajnih poziva.

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