NVIDIA Tesla P40 · 24GB VRAM

Маълумоти илмӣ GPU VPS

Обработка массивов данных 10-100x быстрее с GPU-ускоряемыми инструментами науки данных. RAPIDS, Jupyter, и полный PyData stack на аппаратуре NVIDIA.

Сервери GPU- ро насб кунед Ҳамаи интихобҳои GPU

$ pip install cudf-cu12 cuml-cu12 jupyterlab && jupyter lab --ip=0.0.0.0
# Коркарди NVIDIA Tesla P40 (24 ГБ)
& Иловаи забон _

{ном} дар GPU VPS чист?

Маълумоти илмӣ бо суръати GPU NVIDIA RAPIDS-ро барои иҷрои pandas, scikit-learn ва дигар абзорҳои маълумотӣ бевосита дар GPU истифода мебарад. Маълумоти ҷамъшударо, ки дар CPU соатҳо вақт мегирифтанд, дар дақиқаҳо коркард мекунад.

Чаро {ном} дар VPS.org GPU

Ҷойгоҳи RAPIDS

1990), футболбози қирғиз, нимҳимоятгари «Истиқлол» (Душанбе), «Истиқлол» (Душанбе), «Истиқлол» (Душанбе).

Юпитер омода аст

JupyterLab-и пешакӣ танзимшуда бо пуштибонии GPU.

Наборы данных

24 феврали соли 1999 дар шаҳри Душанбе ба дунё омадааст.

Намоиш

Намоиши GPU- тезонидашуда бо cuXfilter ва Plotly.

Data Science истифодаи маъмул

Таҳлили маҷмӯи маълумотҳои калон

Инженерии хусусиятҳо

Шӯркунии ETL

Модели статистӣ

Таҳлили график

Таҳлили геопространственный

Сервери GPU- ро насб кунед

Муайянкунии GPU

ГПЧNVIDIA Tesla P40

ВРАМ24 GB GDDR5X

Рангҳои CUDA3,840

FP3212 TFLOPS

INT847 TOPS

Хотираи сиёҳ- сафед346 GB/s

МеъморӣPascal (GP102)

ДаромаданБар- метал PCIe

Саволҳои пурсидашуда

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.