NVIDIA Tesla P40 · 24GB VRAM

파이토치 GPU VPS

전용 NVIDIA GPU에서 PyTorch를 사용하여 딥 러닝 모델을 훈련하고 배포합니다.

$ pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124
# NVIDIA Tesla P40 (24GB)에서 실행 중
준비됐어요 _

GPU VPS에서 PyTorch는 무엇입니까?

PyTorch는 전 세계 연구자와 엔지니어들이 사용하는 선도적인 딥 러닝 프레임워크입니다. GPU VPS는 전용 NVIDIA 하드웨어를 제공하여 모델을 더 빠르게 훈련하고 규모에 맞게 추론을 실행할 수 있습니다.

VPS.org GPU에서 PyTorch을 사용하는 이유

CUDA 준비됨

미리 구성된 NVIDIA 드라이버와 CUDA 툴킷을 사용하여 즉시 훈련을 시작하십시오.

전체 GPU 메모리

대형 모델과 더 큰 배치 크기를 훈련하기 위한 24GB VRAM.

주파이터 통합

대화형 개발을 위해 GPU 지원을 갖춘 Jupyter 노트북을 실행합니다.

분산 훈련

대용량 데이터 세트에서 더 빠른 훈련을 위해 다중 GPU 설정으로 확장.

인기 있는 PyTorch 사용 사례

신경망 훈련
컴퓨터 비전 모델
NLP & 변환기 모델
생성적 AI 연구
모델 미세 조정
생산 추론

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 PyTorch on a GPU VPS?

+

PyTorch on a GPU VPS is a CUDA-accelerated deployment. PyTorch 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 PyTorch on a GPU VPS?

+

Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124. Your PyTorch environment is ready in minutes with full GPU acceleration.

How much VRAM do I need for PyTorch?

+

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 PyTorch 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 PyTorch?

+

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

Do I get full root on the PyTorch GPU VPS?

+

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

Which CUDA version is installed for PyTorch?

+

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 PyTorch workload.

Does my PyTorch GPU VPS persist between sessions?

+

Yes — your PyTorch 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 PyTorch workload?

+

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

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

GPU에서 PyTorch를 실행할 준비가 되셨습니까?

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

VPS를 시작하세요
최저 $2.0/월