NVIDIA Tesla P40 · 24GB VRAM

Мэдээллийн шинжлэх ухаан

ГП-ийн хурдасгасан мэдээллийн шинжлэх ухааны хэрэгслээр том хэмжээний өгөгдлийг 10-100 дахин хурдан боловсруулна. RAPIDS, Jupyter, NVIDIA-ийн тоног төхөөрөмж дээрх PyData-ийн бүрэн багц.

График сервер Бүх график процессорын сонголтууд

$ pip install cudf-cu12 cuml-cu12 jupyterlab && jupyter lab --ip=0.0.0.0
# NVIDIA Tesla P40 (24ГБ) дээр ажилладаг
Хэрэггүй _

GPU VPS дээрх Data Science гэж юу вэ?

ГПҮ-ийн хурдасгасан мэдээллийн шинжлэх ухаан нь NVIDIA RAPIDS-ийг ашиглан pandas, scikit-learn, болон бусад мэдээллийн хэрэгслийг ГПҮ дээр шууд ажиллуулдаг. Цөмийн процессор дээр цаг хугацаа шаардах мэдээллийн багцыг минутанд боловсруулдаг.

VPS.org график процессор дээр Data Science яагаад

RAPIDS багц

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

Юпитер бэлэн

График процессор дэмждэг урьдчилан тохируулсан JupyterLab.

Их хэмжээний мэдээллийн багц

24GB GPU санах ой нь санах ойд байгаа мэдээллийг боловсруулдаг.

Зураглал

cuXfilter болон Plotly-ийн тусламжтайгаар график процессороор хурдасгасан дүрслэл.

Data Science түгээмэл хэрэглээний тохиолдол

Их хэмжээний мэдээллийн дүн шинжилгээ

Үйлдэл

ETL хурдсуулга

Статистик загварчлал

Графикийн анализ

Геогеометрийн анализ

График сервер

График процессорын тодорхойлолт

График процессорNVIDIA Tesla P40

ВРАМ24 GB GDDR5X

Цагаан3,840

FP3212 TFLOPS

INT847 TOPS

Цэнхэр дурсамж346 GB/s

АрхитектурPascal (GP102)

ДараахБар-метал PCIe

Заримдаа асуудаг асуултууд

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.