NVIDIA Tesla P40 · 24GB VRAM

텐서플로우 GPU VPS

전용 NVIDIA GPU 하드웨어로 TensorFlow 워크로드를 가속화하세요. 완벽한 CUDA 지원으로 모델을 훈련하고 예측을 제공하며 ML 파이프라인을 구축하세요.

$ pip install tensorflow[and-cuda]
# NVIDIA Tesla P40 (24GB)에서 실행 중
준비됐어요 _

GPU VPS에서 TensorFlow는 무엇입니까?

TensorFlow는 ML 모델을 구축하고 배포하는 Google의 오픈 소스 머신 러닝 프레임워크입니다. GPU VPS를 사용하면 리소스를 공유하지 않고도 훈련 및 추론을 가속화할 수 있는 전용 하드웨어를 얻을 수 있습니다.

VPS.org GPU에서 TensorFlow을 사용하는 이유

GPU 가속

TensorFlow 작업을 위한 기본 CUDA 지원. CPU보다 최대 50배 빠르다.

호환 하드웨어

GPU 백엔드와의 고급 모델 구축을 위한 완벽한 Keras 통합.

텐서보드

자신의 서버에서 TensorBoard로 훈련을 모니터링합니다.

TF 서빙 준비

GPU에서 TensorFlow Serving을 사용하여 모델을 프리미엄에 배포합니다.

인기 있는 TensorFlow 사용 사례

이미지 분류
개체 감지
자연어 처리
추천 시스템
시계열 예측
생산 ML 파이프라인

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 TensorFlow on a GPU VPS?

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TensorFlow on a GPU VPS is a CUDA-accelerated deployment. TensorFlow is a training / fine-tuning workload. Plan for long-running jobs — snapshot your VPS regularly, and consider an external cold-storage backup for trained weights.

How do I set up TensorFlow on a GPU VPS?

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Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install tensorflow[and-cuda]. Your TensorFlow environment is ready in minutes with full GPU acceleration.

How much VRAM do I need for TensorFlow?

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Training VRAM is dominated by the optimizer state plus activations. Full fine-tuning of a 7B LLM needs ~24-48 GB; LoRA / QLoRA fits in 8-16 GB. Our Tesla P40 supports LoRA-class fine-tuning out of the box; full training of larger models requires multi-GPU.

Is TensorFlow 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 TensorFlow?

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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 TensorFlow.

Do I get full root on the TensorFlow GPU VPS?

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

Which CUDA version is installed for TensorFlow?

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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 TensorFlow workload.

Does my TensorFlow GPU VPS persist between sessions?

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Yes — your TensorFlow 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 TensorFlow workload?

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

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

GPU에서 TensorFlow를 실행할 준비가 되셨습니까?

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

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