NVIDIA Tesla P40 · 24GB VRAM

Углубленное обучение GPU VPS

Тренировать нейронные сети на специализированном аппаратном обеспечении NVIDIA GPU. Си-эн, трансформаторы, GAN и любую архитектуру глубокого обучения при полной поддержке CUDA.

$ pip install torch torchvision && python -c "import torch; print(torch.cuda.is_available())"
# Работает на NVIDIA Tesla P40 (24GB)
Готов. _

Что такое GPU VPS?

Глубокое обучение требует ускорения GPU для обучения нейронных сетей в разумные сроки. GPU VPS предоставляет специальное оборудование NVIDIA для обучения любой архитектуре глубокого обучения без каких-либо проблем с ресурсами.

Почему {имя} на VPS.org GPU

Любые рамки

PyTorch, TensorFlow, JAX, MXNet или любые рамки CUDA.

Быстрая итерация

Специализированный GPU означает последовательные скорости подготовки для воспроизводимых исследований.

Крупные модели

24GB VRAM поддерживает подготовку крупных архитектур и партий.

24/7 Наличие

Занимайся долгой тренировкой без перерыва.

Популярные случаи использования {имя}

Учебная подготовка по CNN
Трансформированные модели
Профессиональная подготовка в области ГАН
Укрепление системы обучения
Эксперименты AutomL
Поиск нейронной архитектуры

Спецификации GPU

ГПУNVIDIA Tesla P40
VRAM24 GB GDDR5X
CUDA Kopes3,840
РП3212 TFLOPS
INT847 TOPS
Память346 GB/s
АрхитектураPascal (GP102)
ПроходБрюшная металлургическая PCIe

Часто задаваемые вопросы

What is Deep Learning on a GPU VPS?

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Deep Learning on a GPU VPS is a CUDA-accelerated deployment. Deep 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 Deep Learning.

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

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Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install torch torchvision && python -c "import torch; print(torch.cuda.is_available())". Your Deep Learning environment is ready in minutes with full GPU acceleration.

How much VRAM do I need for Deep Learning?

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

Is Deep 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 Deep 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 Deep Learning.

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

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

Which CUDA version is installed for Deep 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 Deep Learning workload.

Does my Deep Learning GPU VPS persist between sessions?

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Yes — your Deep 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 Deep Learning workload?

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

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

Готовы запустить GPU?

Развертывать специальный сервер NVIDIA GPU в минутах.

Запустить VPS
От 2,0 долл. США/мо