NVIDIA Tesla P40 · 24GB VRAM

Ulwazi lwedatha GPU VPS

Inqubo yedatha enkulu 10-100x ngokushesha nge-GPU-ekhawulelwe amathuluzi esayensi yedatha. RAPIDS, Jupyter, kanye ne-PyData stack ephelele kwi-NVIDIA hardware.

$ pip install cudf-cu12 cuml-cu12 jupyterlab && jupyter lab --ip=0.0.0.0
# Isebenza ku-NVIDIA Tesla P40 (24GB)
Kulungile. _

Yini i-{igama} ku-GPU VPS?

Ulwazi lwedatha olukhawulelwe yi-GPU lusebenzisa i-NVIDIA RAPIDS ukuqhuba ama-pandas, i-scikit-learn, nezinye izinto zolwazi ngokuqondile ku-GPU. Uhlelo lwedatha oluzothatha amahora ku-CPU emaminithini.

Kungani {igama} ku-VPS.org GPU

I-RAPID Suite

cuDF (GPU pandas), cuML (GPU scikit-learn), cuGraph (GPU NetworkX).

I-Jupyter ilungile

I-JupyterLab elungiselelwe ngaphambi kokuqala exhaswe yi-GPU.

Amasethingi amakhulu wedatha

24GB GPU memory for in-memory data processing.

Ukubukeka

Ukubonisa okukhawulelwe yi-GPU nge-cuXfilter ne-Plotly.

Isibonelo sokusetshenziswa esithandwayo {igama}

Ucwaningo lwedatha enkulu
Unjiniyela wezici
Ukukhawulela kwe-ETL
Ukumodelwa kwe-statistics
Ucwaningo lwezibalo
Ucwaningo lwendawo

Izici ze-GPU

I-GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
Imibala ye-CUDA3,840
FP3212 TFLOPS
INT847 TOPS
Inkumbulo346 GB/s
UkwakhiwaPascal (GP102)
UkudluliswaI-PCIe yensimbi engenasici

Imibuzo ebuzwa kaningi

What is Data Science on a GPU VPS?

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

How do I set up Data Science on a GPU VPS?

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Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install cudf-cu12 cuml-cu12 jupyterlab && jupyter lab --ip=0.0.0.0. Your Data Science environment is ready in minutes with full GPU acceleration.

How much VRAM do I need for Data Science?

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

Is Data Science 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 Data Science?

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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 Data Science.

Do I get full root on the Data Science GPU VPS?

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

Which CUDA version is installed for Data Science?

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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 Data Science workload.

Does my Data Science GPU VPS persist between sessions?

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Yes — your Data Science 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 Data Science workload?

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

Can I scale my Data Science 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 Data Science 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 Data Science 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 Data Science on a GPU VPS risk-free.

Ukulungele ukuqhuba i-{igama} ku-GPU?

Sebenzisa i-NVIDIA GPU server ekhethekile emizuzwini. Akukho ukubhukha, akukho ukudlulisa.

Qala i-VPS yakho
Kusuka ku-$2.0/ngonyaka