The GPU server is a dedicated server with powerful NVIDIA graphics processors designed for high-performance parallel computing. Unlike conventional CPUs, GPUs contain thousands of computing cores, which makes them ideal for tasks requiring massive data processing.
The main scenarios for using GPU servers:
Parallel computing and simulation
Video and graphics processing
Scientific and engineering calculations
3D rendering and visualization
Machine learning and neural networks
CUDA applications and HPC
Cloud servers for different business tasks
Dedicated NVIDIA GPUs
Full access to the physical GPU without virtualization. No vGPUs — just real hardware for maximum performance.
Доступные модели:
RTX 4090
RTX A4000
RTX A5000
RTX 6000 Ada
NVIDIA A100
Full root access
Full control over the server: install any software, configure NVIDIA drivers, manage the CUDA Toolkit, and configure the system for your tasks.
Dedicated NVIDIA GPUs
Hardware isolation guarantees stable performance. GPU, CPU, and memory resources are fully allocated only for your tasks.
Professional GPUs
We use only professional NVIDIA GPUs with ECC memory support, certified drivers, and optimization for enterprise workloads.
Optimized CUDA environment
All GPU servers come with pre-installed software for working with CUDA applications. Start working immediately after activating the server.
Ready to work immediately after activation
Pre-installed software
The CUDA Toolkit
Latest versions for development
cuDNN
Libraries for deep learning
NVIDIA Drivers
Certified drivers
Docker + NVIDIA Container Toolkit
Containerization of GPU applications
Optional rendering software
On request: Blender, OctaneRender, etc.
AI Server Usage Scenarios
NVMe до 1M IOPS
Ultra-fast NVMe drives ensure minimal latency when working with large datasets
Network up to 10 Gbit/s
High-speed connection for fast transfer of renderers and large files
Low latency to European IX
Direct connection to AMS-IX, DE-CIX and other traffic exchange points
High SLA
We guarantee 99.9% reliability thanks to redundant power supply and Tier III network infrastructure
Hardware isolation
Complete separation at the hardware level eliminates the impact of neighboring servers on your performance
Cloud servers for different business tasks
Rendering and visualization
3D rendering in Blender, Maya, Cinema 4D. GPU-accelerated engines: Cycles, OctaneRender, Redshift, V-Ray
Animation and special effects
Architectural visualization
Render farms
Video and graphics processing
GPU-H.264/H.265 encoding, 4K/8K video processing, streaming and transcoding
Video editing and post-production
Streaming platforms
Real-time image processing
Machine learning and neural networks
Deep neural network training, computer vision, NLP, big data analysis
Training of PyTorch, TensorFlow models
Generative models (GAN, Stable Diffusion)
LLM fine-tuning and inference
Scientific calculations
Modeling of physical processes, molecular dynamics, computational fluid dynamics (CFD)
Engineering simulations
Bioinformatics and genomics
Financial modeling
A line of GPU servers
Choose a configuration for your tasks. Customization and multi-GPU configurations are possible.
