NVIDIA Tesla P40 · 24GB VRAM

Màquina d' aprenentatge del director de la GPU

Adoreu les màquines amb formació de la GPU i inferència.

$ pip install cuml-cu12 xgboost cudf-cu12
# Corrent a NVIDIA Tesla P40 (24GB)
Llest. _

Què és el Machine Learning en un vicepresident de la GPU?

L'aprenentatge de la màquina de la GPU utilitza RIA NVIDIA CUDA per accelerar l'entrenament i prediccions per als algorismes ML clàssics ML. ARPIDS i XGost GPU poden proporcionar 10 100 velocitats de velocitat sobre implementacions de CPU.

Why Machine Learning on VPS.org GPU

RAPIDS cuMLConstellation name (optional)

Algorismes compatibles amb la GPU.

La GPU XGBoost

Els models de degradats impulsen 10x més ràpid a la GPU.

cuDF & cuPy

pandades amb la GPU i els números per a la preprocessació de dades.

Final- a- final GPU

Mantingueu tota la vostra canonada ML a la GPU per a màxima velocitat.

Casos d' ús famosos Machine Learning

Classificació i regressió
Funcionalitat d' enginyeria a escala
prediccions en temps real
Processament de conjunts de dades grans
Preduccions AutoML
Anomenció del model

Especificacions de la GPU

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
CUDA Cores3,840
FP3212 TFLOPS
INT847 TOPS
Memòria BW346 GB/s
ArquitecturaPascal (GP102)
PassatBare- metàl· lic PCIe

Preguntes més freqüents

What is Machine Learning on a GPU VPS?

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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?

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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?

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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?

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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 Machine Learning?

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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 Machine Learning.

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

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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?

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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 Machine Learning workload.

Does my Machine Learning GPU VPS persist between sessions?

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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?

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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?

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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 Machine Learning 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 Machine Learning 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 Machine Learning on a GPU VPS risk-free.

A punt per executar Machine Learning a la GPU?

Deploy un servidor de la GPU de la NVIDIA dedicat en minuts. No hi ha reserves, ni trucades de vendes.

Inicieu els vostres directors.
Des de $2. 0/mo