IaaS with GPU
Computing infrastructure for AI projects
Polcom IaaS with GPUs is a service that provides virtual machines equipped with dedicated graphics processing units. The environment has been designed to handle workloads requiring massive parallel processing, such as model training, fine-tuning, inference, high-density graphics computing and working with large datasets.
Technical specifications:
- NVIDIA MIG (Multi-Instance GPU) – hardware-based partitioning of a physical GPU into isolated instances, with the option to utilise a portion of the GPU’s resources. This allows for cost optimisation during periods of lower workload.
- PCI Passthrough – direct mapping of the physical GPU chip to the virtual machine, bypassing the virtualisation layer. This solution reduces system latency and allows the full hardware performance to be utilised.
- Supporting infrastructure – DDR5 RAM and NVMe-based storage ensure efficient data flow throughout the environment.
- Scalability – the ability to add further GPU units to the existing environment as the project develops and the demand for computing power grows.
The infrastructure utilises the latest NVIDIA RTX PRO 6000 Blackwell Server Edition cards, ensuring cutting-edge performance and reliability. Each unit features 96 GB of ultra-fast GDDR7 memory, enabling the execution of demanding projects in the fields of multimodal AI, physical AI, generative AI and advanced data analysis.
Key benefits of the GPU-powered IaaS service
The GPU-powered IaaS service available through Polcom AI Cloud allows you to utilise high-performance infrastructure without having to invest in your own servers, graphics accelerators, cooling systems and data centre facilities. This solution is designed for organisations that wish to launch AI projects more quickly, maintain control over their environment and plan costs predictably.
Key benefits:
- Cost predictability – the ability to use GPU resources based on contracts tailored to the scale and duration of the project, without the need for significant capital expenditure on proprietary hardware.
- Low latency – the physical location of the infrastructure in Poland supports short response times for models and applications running in the region.
- Continuous innovation – access to the latest generations of GPUs without the need for costly upgrades to your own infrastructure every few years.
- Data sovereignty – data processing and storage within Polish infrastructure, with greater control over the location of the environment and the protection of intellectual property.
- Flexible scaling – the ability to expand the environment as the requirements of your AI project grow.
- Expert support – access to a team that helps you tailor infrastructure parameters to your specific business and technological requirements.
This solution is designed specifically for
- Companies developing their own AI models or fine-tuned models
- Data science, machine learning and MLOps teams
- Software houses building AI-based applications
- Organisations implementing chatbots, AI assistants and process automation
- Companies processing large volumes of data, documents or multimedia content
- Public sector bodies and regulated industries
- Entities that do not wish to send data to external public models
- Organisations seeking alternatives to global public clouds for their AI projects