NVIDIA Tesla P40 · 24GB VRAM

Scientific Computing GPU VPS

Accelerate scientific simulations and HPC workloads with dedicated NVIDIA GPU hardware. CUDA and OpenCL ready.

$ apt install nvidia-cuda-toolkit && nvcc --version
# Running on NVIDIA Tesla P40 (24GB)
Ready. _

What is Scientific Computing on a GPU VPS?

Scientific computing on GPU VPS leverages NVIDIA CUDA cores for massive parallelism. Run molecular dynamics, climate models, CFD simulations, and other HPC workloads faster than on CPU clusters.

Why Scientific Computing on VPS.org GPU

CUDA & OpenCL

Full support for CUDA and OpenCL scientific computing frameworks.

3,840 CUDA Cores

Massive parallel processing for simulation workloads.

12 TFLOPS FP32

High single-precision performance for numerical computing.

Persistent Environment

Keep your research environment running 24/7.

Popular Scientific Computing Use Cases

Molecular dynamics (GROMACS)
Climate modeling
Fluid dynamics (CFD)
Genomics analysis
Physics simulations
Financial modeling

GPU Specifications

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5X
CUDA Cores3,840
FP3212 TFLOPS
INT847 TOPS
Memory BW346 GB/s
ArchitecturePascal (GP102)
PassthroughBare-metal PCIe

Frequently Asked Questions

What is Scientific Computing on a GPU VPS?

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

How do I set up Scientific Computing on a GPU VPS?

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Deploy a GPU VPS with the NVIDIA Tesla P40, SSH in, and run apt install nvidia-cuda-toolkit && nvcc --version. Your Scientific Computing environment is ready in minutes with full GPU acceleration.

How much VRAM do I need for Scientific Computing?

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

Is Scientific Computing 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 Scientific Computing?

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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 Scientific Computing.

Do I get full root on the Scientific Computing GPU VPS?

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

Which CUDA version is installed for Scientific Computing?

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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 Scientific Computing workload.

Does my Scientific Computing GPU VPS persist between sessions?

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Yes — your Scientific Computing 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 Scientific Computing workload?

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

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

Ready to Run Scientific Computing on GPU?

Deploy a dedicated NVIDIA GPU server in minutes. No reservations, no sales calls.

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