NVIDIA Tesla P40 · 24GB VRAM

Jupyter GPU GPU 笔记本服务器

使用专门的 NVIDIA GPU 支持运行 Jupyter 笔记本。 交互式数据科学和 ML 开发与 CUDA 加速 。

$ pip install jupyterlab torch && jupyter lab --ip=0.0.0.0 --allow-root
# 运行于 NVIDIA Tesla P40 (24GB)
准备就绪 。 _

GPU VPS上是什么?

GPU VPS上的Jupyter笔记本为您提供了一个互动开发环境, 配有专门的 NVIDIA GPU 硬件。 适合数据科学、 ML 实验和模型原型。

为什么在 VPS.org GPU 上Jupyter

笔记本中的 GPU

直接从笔记本细胞获取 CUDA GPUs 。 交互式培训模型 。

吉比特拉拉布

全JupyterLab IDE, 带有终端、 文件浏览器和扩展名 。

预安装图书馆

PyToirch, Tensor Flow, Scikit-learn, 熊猫, 并且更愿意使用。

远程访问

从任何浏览器或任何地方访问您的笔记本。

流行 Jupyter 使用案例

ML实验
数据勘探
模型原型模型
教育讲习班
研究笔记本
Kaggle 比赛

GPU 指定

GPU 通用 GPUNVIDIA Tesla P40
卷内24 GB GDDR5X
CUDA核心3,840
FP3212 TFLOPS
INT847 TOPS
内存 BW346 GB/s
建筑结构Pascal (GP102)
被动通过巴巴金属多氯二苯基

常问问题

What is Jupyter on a GPU VPS?

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

How do I set up Jupyter on a GPU VPS?

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Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install jupyterlab torch && jupyter lab --ip=0.0.0.0 --allow-root. Your Jupyter environment is ready in minutes with full GPU acceleration.

How much VRAM do I need for Jupyter?

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

Is Jupyter 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 Jupyter?

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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 Jupyter.

Do I get full root on the Jupyter GPU VPS?

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

Which CUDA version is installed for Jupyter?

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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 Jupyter workload.

Does my Jupyter GPU VPS persist between sessions?

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Yes — your Jupyter 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 Jupyter workload?

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

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

准备在 GPU 上运行 Jupyter 吗?

在几分钟内部署专用的 NVIDIA GPU 服务器。 没有预约, 没有销售电话 。