NVIDIA Tesla P40 · 24GB VRAM

I-GPU ye-VPS yeSayensi yeData

Inkqubo yedatha enkulu ye-10-100x ekhawulezayo ngezixhobo zesayensi yedatha ekhawulezayo ye-GPU. RAPIDS, Jupyter, kunye ne-PyData epheleleyo kwihardware ye-NVIDIA.

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

Yintoni i-{igama} kwi-GPU VPS?

I-GPU-ekhawulezayo isebenzisa i-NVIDIA RAPIDS ukuqhubela phambili i-pandas, i-scikit-learn, nezinye izixhobo ze-data ngqo kwi-GPU. Inkqubo ye-dataset ethatha iiyure kwi-CPU kwimizuzu.

Kutheni i-Data Science kwi-VPS.org GPU

RAPIDS Suite

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

I-Jupyter ilungile

I-JupyterLab emiselweyo ngaphambili ene-GPU inkxaso. Name

Iinkqubo zedata ezikhulu

24GB GPU inkumbulo yokuqhubekeka kwedatha kwimemori.

Ukubonisa

Umboniso okhawulezayo we-GPU nge cuXfilter ne Plotly.

Iimeko zokuSebenza ezithandwayo {igama}

Uvavanyo lwedatha enkulu
Ubungcali bezinto ezibonakalayo
Unikezelo lwe-ETL
Uyilo lwezibalo
Uvavanyo lwegraph
Uvavanyo lwe-geospatial

Iinkcukacha ze-GPU

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
Imibala ye CUDA3,840
FP3212 TFLOPS
INT847 TOPS
Inkumbulo346 GB/s
Uyilo lwezindluPascal (GP102)
I-PassthroughI-Bare-metal PCIe

Imibuzo ebuzwa rhoqo

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.

Ilungile ukuphumeza i-Data Science kwi-GPU?

Sebenzisa i-NVIDIA GPU server ekhethekileyo kwimizuzu. Akukho kuhlala, akukho kuthengiswa koqhagamshelwano.

Qala i-VPS yakho
ukusuka kwi- $2.0/inyanga