Control, optimization and diagnostics of machines and systems based on AI approaches usually poses high demands on computational resources. Distributed computing topologies can be used to maintain reasonable complexity, costs and efficient use of the resources in such applications. This service allows experimentation on such distributed computational systems, combining embedded systems, edge-computing and local/cloud HPC resources. The main objective of experiments is assessment of suitability of the selected computing environment for the given AI industrial implementation. The provided service also allows access to available computing resources for AI models training.
Benefits for companies:
- Possibility to test applications in complex/hybrid computing environments without necessity of large initial investment to the equipment.
- Access to state-of-the-art computing resources connected directly to industrial production technologies. In comparison to super-computing centres services, real-time data processing is offered.
