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
INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT8 INT847 TOPS
内存 BW346 GB/s
建筑结构结构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 。

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