NVIDIA Tesla P40 · 24GB VRAM

Jupyter GPU 노트북 서버

전용 NVIDIA GPU 지원으로 Jupyter 노트북을 실행하세요. CUDA 가속을 사용한 대화형 데이터 과학 및 ML 개발.

$ pip install jupyterlab torch && jupyter lab --ip=0.0.0.0 --allow-root
# NVIDIA Tesla P40 (24GB)에서 실행 중
준비됐어요 _

GPU VPS에서 Jupyter는 무엇입니까?

GPU VPS에서 Jupyter 노트북은 전용 NVIDIA GPU 하드웨어를 사용하여 대화형 개발 환경을 제공합니다. 데이터 과학, ML 실험 및 모델 프로토타이핑에 완벽합니다.

VPS.org GPU에서 Jupyter을 사용하는 이유

노트북의 GPU

노트북 셀에서 직접 CUDA GPU에 액세스합니다.

주파이터랩

터미널, 파일 브라우저 및 확장 기능이 있는 완전한 JupyterLab IDE.

사전 설치된 라이브러리

PyTorch, TensorFlow, scikit-learn, pandas 등을 사용할 준비가 되었습니다.

원격 액세스

어디서나 모든 브라우저에서 노트북에 액세스할 수 있습니다.

인기 있는 Jupyter 사용 사례

ML 실험
데이터 탐색
모델 프로토타이핑
교육 워크숍
연구용 노트북
Kaggle 대회

GPU 사양

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
CUDA 색상3,840
FP32 플랫폼12 TFLOPS
INT847 TOPS
메모리 흑백346 GB/s
아키텍처Pascal (GP102)
통과베어 메탈 PCIe

자주 묻는 질문

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.

GPU에서 Jupyter를 실행할 준비가 되셨습니까?

전용 NVIDIA GPU 서버를 몇 분 안에 배포하세요. 예약도, 영업 전화도 필요 없습니다.

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