NVIDIA Tesla P40 · 24GB VRAM

Àwọn Ìṣàfilọ́lẹ̀ GPU VPS

Ṣí àwọn nẹ́tiwọọki neural lórí àwọn ìṣàfilọ́lẹ̀ NVIDIA GPU. CNNs, àwọn ìṣàfilọ́lẹ̀, GANs, àti àwọn ìṣàfilọ́lẹ̀ ìmọ̀ nípa ìmọ̀ CUDA.

Fí Sáàbù GPU Hàn Àwọn Àtòjọ-ẹ̀yàn GPU

$ pip install torch torchvision && python -c "import torch; print(torch.cuda.is_available())"
# Ń bọ́ nípa NVIDIA Tesla P40 (24GB)
Tí a tì ṣè _

Àwọn àwọn ààyè-iṣẹ́ tí a fi pamọ́

Àkọ́kọ́ ìmọ̀ jú.

Kini idi ti Deep Learning lo lori VPS.org GPU

Àwọn àwọn àgbékalẹ̀

PyTorch, TensorFlow, JAX, MXNet, tàbí àwọn ààyè-iṣẹ́ CUDA.

Ìṣàfarawé àwọn àwọn ààyè-iṣẹ́

GPU ti a fi pamọ́ nínú.

Àwọn

24GB VRAM ń gbọ́dọ̀ kọ́ awọn áríǹrẹ̀sì nlà àtí àwọn ìwọ̀n àwọn ẹ̀yàn.

Àwọn Ìṣàfilọ́lẹ̀

Rọ́ọ̀nù àwọn iṣẹ́ ìṣàfilọ́lẹ̀ láti fi pamọ́.

Àwọn Ààyè Lòjútó Deep Learning

Àwọn ìṣàfilọ́lẹ̀ CNN

Àwọn ìṣàmúlò-ètò ìṣàfarawé

Àwọn ìwé-ìwé GAN

Àwọn ìṣàfilọ́lẹ̀

Àwọn ìṣàfarawégbèsì AutoML

Àwọn ààyè-iṣẹ́ ìṣàfihàn

Fí Sáàbù GPU Hàn

Àwọn À

GPUNVIDIA Tesla P40

VRAM24 GB GDDR5X

Àwọn àwọ̀ CUDA3,840

FP3212 TFLOPS

INT847 TOPS

Àwọn àwọn àmì-ìwé346 GB/s

Àwọn Ìṣàmúlò-ètòPascal (GP102)

Àwọn Ìjánu-ìṣàmúlò-ètòPCIe àìdárá

Àwọn Àtòjọ-ẹ̀yàn

What is Deep Learning on a GPU VPS?

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?

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?

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?

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?

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?

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?

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?

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?

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?

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?

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?

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