NVIDIA Tesla P40 · 24GB VRAM

데이터 과학 GPU VPS

GPU 가속 데이터 과학 도구로 대규모 데이터 세트를 10~100배 더 빠르게 처리합니다. NVIDIA 하드웨어에서 RAPIDS, Jupyter 및 완전한 PyData 스택을 사용합니다.

$ pip install cudf-cu12 cuml-cu12 jupyterlab && jupyter lab --ip=0.0.0.0
# NVIDIA Tesla P40 (24GB)에서 실행 중
준비됐어요 _

GPU VPS에서 Data Science는 무엇입니까?

GPU 가속 데이터 과학은 NVIDIA RAPIDS를 사용하여 pandas, scikit-learn 및 기타 데이터 툴을 GPU에서 직접 실행합니다. CPU에서 몇 시간이 걸리는 데이터 세트를 몇 분 안에 처리할 수 있습니다.

VPS.org GPU에서 Data Science을 사용하는 이유

RAPIDS 제품군

cuDF (GPU pandas), cuML (GPU scikit-learn), cuGraph (GPU NetworkX)를 지원한다.

주파이터 준비됨

GPU 지원을 갖춘 미리 구성된 JupyterLab.

대형 데이터 집합

메모리 내 데이터 처리를 위한 24GB GPU 메모리.

시각화

cuXfilter 및 Plotly를 사용한 GPU 가속 시각화.

인기 있는 Data Science 사용 사례

대규모 데이터셋 분석
기능 엔지니어링
ETL 가속화
통계 모델링
그래프 분석
지리 공간 분석

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 Data Science on a GPU VPS?

+

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

How do I set up Data Science on a GPU VPS?

+

Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install cudf-cu12 cuml-cu12 jupyterlab && jupyter lab --ip=0.0.0.0. Your Data Science environment is ready in minutes with full GPU acceleration.

How much VRAM do I need for Data Science?

+

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

Is Data Science GPU VPS billed hourly or monthly?

+

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 Data Science?

+

Yes — you have full root on the GPU VPS. Run whatever fits inside the 24 GB VRAM and the available RAM / storage budget alongside Data Science.

Do I get full root on the Data Science GPU VPS?

+

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

Which CUDA version is installed for Data Science?

+

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 Data Science workload.

Does my Data Science GPU VPS persist between sessions?

+

Yes — your Data Science 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 Data Science workload?

+

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

Can I scale my Data Science GPU VPS later?

+

Yes — plan upgrades are instant from your control panel; the GPU itself can be swapped to a larger tier on request. Your Data Science install carries over.

Are backups available for my GPU VPS?

+

Yes. Automated daily backups are an add-on; manual snapshots are free. Useful for long Data Science training runs where you want a checkpointable server state.

Is there a money-back guarantee on the GPU VPS?

+

Yes — 30-day money-back guarantee on every plan including GPU. Try Data Science on a GPU VPS risk-free.

GPU에서 Data Science를 실행할 준비가 되셨습니까?

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

VPS를 시작하세요
최저 $2.0/월