NVIDIA Tesla P40 · 24GB VRAM

Наука за податоци GPU VPS

Процесира масивни податоци 10-100x побрзо со GPU забрзани алатки за податоци. RAPIDS, Jupyter и целокупниот PyData куп на NVIDIA хардвер.

Вклучи го GPU- серверот Сите опции на GPU

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

Што е {име} на GPU VPS?

Науката на податоците со GPU ја користи NVIDIA RAPIDS за да се извршат панди, сцикит-ученици и други алатки за податоци директно на GPU. Процесорните сетови на податоци кои ќе траат со часови на процесорот за минути.

Зошто {име} на VPS.org ГПУ

RAPIDS- апартманName

CuDF (ГПУ панди), cuML (ГПУ сцикит-ученик), cuGraph (GPU NetworkX).

Јупитер подготвен

Пред-конфигуриран JupyterLab со ГПУ поддршка.

Големи податочни множества

24ГБ меморија на ГПУ за обработка на податоци во сеќавање.

Визуализација

Визуализацијата на GPU е забрзана со CuXfilter и Plotly.

Популарни {име} Случаи за користење

Голема анализа на настанот со податоци

Инженерирање на карактеристики

ETL- забрзување

Статистичко моделирање

Графика аналитика

Геопространствена анализа

Вклучи го GPU- серверот

GPU спецификации

ГПУNVIDIA Tesla P40

VRAM24 GB GDDR5X

Јадрото на КУДА3,840

ФП3212 TFLOPS

INT847 TOPS

BW меморија346 GB/s

АрхитектураPascal (GP102)

Поминување низПЦИЕ на боите- метали

Често поставувани прашања

What is Data Science on a GPU VPS?

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?

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?

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?

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?

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?

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?

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?

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?

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?

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?

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?

Yes — 30-day money-back guarantee on every plan including GPU. Try Data Science on a GPU VPS risk-free.