NVIDIA Tesla P40 · 24GB VRAM

Głębokie uczenie się GPU VPS

Sieci neuronowe pociągu na dedykowanym sprzętu NVIDIA GPU. CNN, transformatory, GAN i każda głęboka architektura uczenia się z pełnym wsparciem CUDA.

$ pip install torch torchvision && python -c "import torch; print(torch.cuda.is_available())"
# Bieganie na NVIDIA Tesla P40 (24GB)
Gotowy. _

Jaka jest {nazwisko} na GPU VPS?

Głębokie uczenie wymaga przyspieszenia GPU do szkolenia sieci neurologicznych w rozsądnym czasie. GPU VPS zapewnia dedykowany sprzęt NVIDIA do szkolenia jakiejkolwiek głębokiej architektury uczenia się bez kwestionowania zasobów.

Dlaczego {nazwisko} na VPS.org GPU

Dowolne ramy

PyTorch, TensorFlow, JAX, MXNet lub jakiekolwiek ramy CCDA.

Szybka iteracja

Dedykowany GPU oznacza spójną prędkość szkolenia do ponownych badań.

Wielkie modele

24GB VRAM wspiera szkolenie dużych architektur i rozmiarów partii.

Dostępność 24/7

Bierz długie prace treningowe bez przerwy.

Popularne {nazwa} Przypadki użytkowania

Szkolenie CNN
Modele transformatorów
Szkolenie GAN
Uczenie się wzmocnienia
Eksperymenty AutoML
Wyszukiwanie architektury neurowej

Specyfikacje GPU

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
Rdzeń CUDA3,840
FP3212 TFLOPS
INT847 TOPS
Pamięć BW346 GB/s
ArchitekturaPascal (GP102)
PrzejścieBare-metal PCIe

Często zadawane pytania

What is Deep Learning on a GPU VPS?

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

How do I set up Deep Learning on a GPU VPS?

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Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install torch torchvision && python -c "import torch; print(torch.cuda.is_available())". Your Deep Learning environment is ready in minutes with full GPU acceleration.

How much VRAM do I need for Deep Learning?

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

Is Deep Learning 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 Deep Learning?

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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 Deep Learning.

Do I get full root on the Deep Learning GPU VPS?

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

Which CUDA version is installed for Deep Learning?

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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 Deep Learning workload.

Does my Deep Learning GPU VPS persist between sessions?

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Yes — your Deep Learning 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 Deep Learning workload?

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

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

Gotowy do uruchomienia {nazwa} na GPU?

Wysłać dedykowany serwer NVIDIA GPU w minutach. Żadnych rezerwacji, żadnych połączeń sprzedaży.

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