NVIDIA Tesla P40 · 24GB VRAM

Ciencia de datos GPU VPS

Procese conxuntos de datos masivos 10-100 veces máis rápido con ferramentas de ciencia de datos aceleradas por GPU. RAPIDS, Jupyter e a pila completa de PyData en hardware NVIDIA.

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

Que é Data Science nun VPS con GPU?

A ciencia de datos acelerada pola GPU usa NVIDIA RAPIDS para executar pandas, scikit-learn e outras ferramentas de datos directamente na GPU. Procese conxuntos de datos que levarían horas na CPU en minutos.

Por que Data Science en VPS.org GPU

Suite RAPIDS

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

Preparado para Jupyter

JupyterLab preconfigurado con soporte para GPU.

Conxuntos de datos grandes

24 GB de memoria GPU para o procesamento de datos en memoria.

Visualización

Visualización acelerada por GPU con cuXfilter e Plotly.

Casos de uso populares de Data Science

Análise de conxuntos de datos grandes
Enxeñaría de características
Aceleración de ETL
Modelado estatístico
Análise gráfica
Análise xeoespacial

Especificacións da GPU

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
Cores CUDA3,840
FP3212 TFLOPS
INT847 TOPS
Memoria BW346 GB/s
ArquitecturaPascal (GP102)
TransmisiónPCIe de metal desnudo

Preguntas frecuentes

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.

Listo para executar Data Science na GPU?

Despliegue un servidor dedicado de GPU NVIDIA en minutos. Sen reservas, sen chamadas de vendas.

Inicie o seu VPS
Desde $2.0/mes