Case Study: Arquimea Research Center Doubles GPU Utilization with Valohai

Arquimea Research Center doubles GPU utilization to 85% with Valohai

Arquimea Research Center (ARC), the innovation hub of a global technology company, faced significant challenges with its on-premise GPU infrastructure. Their researchers were constantly fighting for access to a single "convenient" machine, leaving other GPUs approximately 50% idle. Furthermore, sharing and reproducing experiments was a major bottleneck, requiring 2-10 hours of manual knowledge transfer per session and creating weekly coordination overhead.

By implementing the Valohai machine learning platform on-premise, ARC unified all of its disparate GPU servers into a single control plane. Valohai eliminated infrastructure friction by automating data handling and job submission, which allowed the existing hardware to be utilized far more efficiently. As a result, GPU utilization rose to 75-85%, effectively doubling output and avoiding an estimated €180,000-270,000 in new hardware costs. Valohai also collapsed the knowledge transfer process to a simple "copy and run" operation using shared links, saving the organization an estimated €40,000-150,000 annually and enabling new researchers to contribute from their first day.

Arquimea Research Center (arc)