NVIDIA Tesla P40 · 24GB VRAM

TensorFlow GPU VPS

Ускоряване на работната натовареност TensorFlow с специализиран NVIDIA GPU хардуер. Влакови модели, обслужват прогнози, и изграждане на ML тръби с пълна подкрепа на CUDA.

$ pip install tensorflow[and-cuda]
# Тичане на NVIDIA Tesla P40 (24GB)
Готови. _

Какво е {име} на GPU VPS?

ТенсорФлоу е системата за отворено машинно обучение на Google за изграждане и разгръщане на модели на ML. С GPU VPS получавате специален хардуер за ускоряване на обучението и изчисляването без споделяне на ресурсите.

Защо {име} на VPS.org ГПУ

Ускорен GPU

Поддръжка на CUDA за операции TensorFlow. До 50x по-бързо от процесора.

Keras съвместим

Пълна интеграция на Keras за високо ниво моделна сграда с GPU борд.

Тенсор Борд

Монитор обучение с TensorBoard на вашия сървър.

TF Сервирането е готово

Разработете модели за производство с TensorFlow сервиз на GPU.

Популярни {име} Случаи на употреба

Класификация на изображения
Откриване на обекта
Обработка на естествен език
Системи за препоръки
Предупреждение на времеви редове
Производствени ML тръбопроводи

Спецификации на GPU

ГПУNVIDIA Tesla P40
ВРАМ24 GB GDDR5X
Ядра на КУДА3,840
ФП3212 TFLOPS
INT847 TOPS
Памет BW346 GB/s
АрхитектураPascal (GP102)
ПреминаванеБареметалов PCIe

Често задавани въпроси

What is TensorFlow on a GPU VPS?

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TensorFlow on a GPU VPS is a CUDA-accelerated deployment. TensorFlow is a training / fine-tuning workload. Plan for long-running jobs — snapshot your VPS regularly, and consider an external cold-storage backup for trained weights.

How do I set up TensorFlow on a GPU VPS?

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Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install tensorflow[and-cuda]. Your TensorFlow environment is ready in minutes with full GPU acceleration.

How much VRAM do I need for TensorFlow?

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Training VRAM is dominated by the optimizer state plus activations. Full fine-tuning of a 7B LLM needs ~24-48 GB; LoRA / QLoRA fits in 8-16 GB. Our Tesla P40 supports LoRA-class fine-tuning out of the box; full training of larger models requires multi-GPU.

Is TensorFlow 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 TensorFlow?

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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 TensorFlow.

Do I get full root on the TensorFlow GPU VPS?

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

Which CUDA version is installed for TensorFlow?

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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 TensorFlow workload.

Does my TensorFlow GPU VPS persist between sessions?

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Yes — your TensorFlow 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 TensorFlow workload?

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

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

Готов ли си да изпълниш {име} на GPU?

Пригответе специален сървър на NVIDIA GPU в минути. Без резервации, без обаждания за продажба.

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