Patakbuhin Jupyter notebooks na may dedikadong NVIDIA GPU suporta. Interactive data science at ML pag-unlad na may CUDA acceleration.
$ pip install jupyterlab torch && jupyter lab --ip=0.0.0.0 --allow-root # Patakbo sa NVIDIA Tesla P40 (24GB) Nakahanda na. _
Ang Jupyter notebooks sa isang GPU VPS ay nagbibigay sa iyo ng isang interactive na kapaligiran sa pag-unlad na may dedikadong NVIDIA GPU hardware. Perpekto para sa agham ng data, ML experimentation, at modelo ng prototyping.
Mag-access CUDA GPUs direkta mula sa mga cell notebook. Train modelo interactively.
Ang mga terminal ay may mga terminal na pang-kompyuter, terminal na pang-komunikasyon, at terminal na pang-komunikasyon.
Ang mga halimbawa nito ay ang Python, Python-like, at Python-like.
Mag-access ng iyong mga notebook mula sa anumang browser, kahit saan.
Jupyter on a GPU VPS is a CUDA-accelerated deployment. Jupyter is a general GPU-accelerated workload. Make sure your software has CUDA support and that your driver / runtime versions match the workload requirements for Jupyter.
Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install jupyterlab torch && jupyter lab --ip=0.0.0.0 --allow-root. Your Jupyter 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 Jupyter 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 Jupyter.
Yes. Full root SSH on every GPU VPS — install drivers, swap CUDA versions, customize the environment for Jupyter 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 Jupyter workload.
Yes — your Jupyter 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 Jupyter 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 Jupyter install carries over.
Yes. Automated daily backups are an add-on; manual snapshots are free. Useful for long Jupyter training runs where you want a checkpointable server state.
Yes — 30-day money-back guarantee on every plan including GPU. Try Jupyter on a GPU VPS risk-free.
I-deploy ang isang dedikadong NVIDIA GPU server sa loob ng ilang minuto. Walang mga reserbasyon, walang mga tawag sa benta.