E-ba le marang-rang a neural ka lisebelisoa tsa NVIDIA GPU tse etselitsoeng. CNNs, transformers, GANs, le li-architecture life kapa life tsa ho ithuta ka botebo le tšehetso e felletseng ea CUDA.
$ pip install torch torchvision && python -c "import torch; print(torch.cuda.is_available())" # Ho sebetsa ka NVIDIA Tesla P40 (24GB) E loketse. _
Ho ithuta ka botebo ho hloka ho potlakisa GPU ho koetlisa marang-rang a neural ka nako e loketseng. GPU VPS e fana ka lisebelisoa tsa NVIDIA tse etselitsoeng ho koetlisa ts'ebetso ea ho ithuta ka botebo ntle le ho hlekefetsa lireschorente.
PyTorch, TensorFlow, JAX, MXNet, kapa li-framework life kapa life tsa CUDA.
Li-GPU tse ngata li fana ka li-processor tse ikemetseng bakeng sa ho sebetsana le li-request.
2400 BC) e ne e le moqapi oa li-archetypes le li-archetypes tsa khale.
E phethela mesebetsi e telele ea ho ithuta ntle le ho hloloheloa.
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.
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.
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.
GPU VPS plans are billed monthly with no lock-in contracts and can be cancelled anytime. Contact us for current GPU pricing tiers.
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.
Yes. Full root SSH on every GPU VPS — install drivers, swap CUDA versions, customize the environment for Deep Learning however you need.
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.
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.
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.
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.
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.
Yes — 30-day money-back guarantee on every plan including GPU. Try Deep Learning on a GPU VPS risk-free.
Sebetsa NVIDIA GPU server ka metsotso. Ha ho na li-reservations, ha ho na li-call tsa thekiso.