NVIDIA Tesla P40 · 24GB VRAM

Машины сургалт

ГП-ийн хүчээр машин суралцах болон дүгнэлт хийхийг хурдасга. RAPIDS, XGBoost GPU, scikit-learn нь зориулалтын NVIDIA тоног төхөөрөмж дээр ажилладаг.

График сервер Бүх график процессорын сонголтууд

$ pip install cuml-cu12 xgboost cudf-cu12
# NVIDIA Tesla P40 (24ГБ) дээр ажилладаг
Хэрэггүй _

GPU VPS дээрх Machine Learning гэж юу вэ?

ГПҮ-ийн хурдасгасан машин суралцах нь NVIDIA CUDA-г ашиглан ML алгоритмын сургалт, таамаглалыг хурдасгадаг. RAPIDS болон XGBoost ГПҮ нь зөвхөн ЦПУ-ийн гүйцэтгэлээс 10-100 дахин хурдасгадаг.

VPS.org график процессор дээр Machine Learning яагаад

RAPIDS cuML

ГПҮ-ээр хурдасгасан scikit-learn-тэй нийцтэй алгоритмууд.

XGBoost график процессор

Градиент нэмэгдүүлэх загварыг график процессор дээр 10 дахин хурдан бэлтгэх.

cuDF & cuPy

ГПҮ-ээр хурдасгасан pandas болон numpy нь мэдээллийг урьдчилан боловсруулдаг.

График процессор

Максимум хурдны тулд бүх ML хоолойг график процессор дээр байлга.

Machine Learning түгээмэл хэрэглээний тохиолдол

Бүлэг ба регресс

Хөгжмийн зохиолч

Тодорхойлолтууд

Их хэмжээний мэдээллийн багц боловсруулах

АвтоML хоолой

Модель

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 Machine Learning on a GPU VPS?

Machine Learning on a GPU VPS is a CUDA-accelerated deployment. Machine Learning is a general GPU-accelerated workload. Make sure your software has CUDA support and that your driver / runtime versions match the workload requirements for Machine Learning.

How do I set up Machine Learning on a GPU VPS?

Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install cuml-cu12 xgboost cudf-cu12. Your Machine Learning environment is ready in minutes with full GPU acceleration.

How much VRAM do I need for Machine Learning?

Our GPU VPS ships with 24 GB GDDR5X VRAM on the NVIDIA Tesla P40, which is sufficient for most Machine Learning workloads. Multi-GPU configurations are available on request.

Is Machine Learning 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 Machine Learning?

Yes — you have full root on the GPU VPS. Run whatever fits inside the 24 GB VRAM and the available RAM / storage budget alongside Machine Learning.

Do I get full root on the Machine Learning GPU VPS?

Yes. Full root SSH on every GPU VPS — install drivers, swap CUDA versions, customize the environment for Machine Learning however you need.

Which CUDA version is installed for Machine Learning?

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 Machine Learning workload.

Does my Machine Learning GPU VPS persist between sessions?

Yes — your Machine Learning 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 Machine Learning workload?

Keep working data on the VPS SSD for fast access during Machine Learning runs; back up finished artifacts (weights, generations, embeddings) off-server via snapshots or object storage for safety.

Can I scale my Machine Learning 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 Machine Learning 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 Machine Learning 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 Machine Learning on a GPU VPS risk-free.