Government

[Ulsan Technopark] Region-led AI Transformation Project

Ulsan Technopark built a shared AI platform on Cheetah to support AI development and validation for local manufacturers, creating an environment that efficiently allocates GPU resources to resident companies and supports them from AI development through to validation.

CheetahMLOps

Building Shared AI Infrastructure for AI Development and Validation by Local Manufacturers

To expand AI adoption among manufacturers in the Ulsan region and reduce the burden of building infrastructure for each company, Ulsan Technopark set out to build a shared AI platform that pools high-performance GPU resources and supports AI development and validation.

Enabling Shared GPU Use and AI Development and Validation for Resident Companies

Ulsan Technopark needed an environment where many resident companies could efficiently share limited GPU resources, and where even companies with little AI experience could develop and validate AI without building their own infrastructure.

  • Shared AI development and validation environment: A shared platform where resident companies can develop and validate AI without building their own infrastructure

  • Efficient GPU resource operations: A management framework to efficiently allocate and operate limited GPU resources across many manufacturers

  • Lower barriers to AI adoption: An environment where even companies lacking AI resources and experience can easily start AI development and validation

Building Unified GPU Management and a Shared AI Platform

Using Cheetah, we built a shared AI platform that centrally manages GPU resources, allocates them to each resident company as needed, and supports everything from AI model development to validation in a standardized environment.

  • Unified GPU resource management: Established an operating framework that manages GPUs centrally and efficiently allocates the resources each resident company needs

  • Standard AI development environment: Reduced the burden of building separate environments for each company and helped them start AI development quickly

  • AI development and validation environment: Provided an environment where resident companies use their allocated GPUs to develop AI models and validate services

Higher GPU Utilization and Wider AI Adoption Among Local Companies

Shared GPU infrastructure and a standardized AI development environment reduced resident companies' infrastructure burden and laid the groundwork for a wide range of local manufacturers to take part in AI development and validation.

  • Higher GPU utilization: Allocated and operated shared GPU resources based on each company’s demand, making better use of limited infrastructure

  • Less infrastructure burden per company: Companies can use the resources they need without building their own GPU and development environments

  • Wider AI adoption among local manufacturers: Accelerated AI adoption by resident companies and laid the groundwork for wider AI use in the regional manufacturing industry

  • Are you curious about an enterprise AI integration platform? → Cheetah

Have more questions?

Contact us anytime to learn more about AIFRICA solutions.

Contact Us