Building an HPC Environment for Data-Driven Decision Making - Large Enterprise F
Company F implemented a general-purpose HPC cluster to enable enterprise-wide data integration and high-performance computing. This reduced operating costs and improved energy efficiency by 30%, while establishing a global collaboration environment.
Challenge
Large Enterprise F operates multiple business divisions and recently faced a surge in demand for AI, big data, and simulation-based analytics. The company found that its existing general-purpose infrastructure and distributed data environment were insufficient to meet these needs. Competition for computing resources among divisions caused severe bottlenecks in analytics operations, making it urgent for the company to establish group-wide data integration and high-performance computing capabilities.
Solution
The company designed and built an HPC cluster comprising high-performance computing nodes and high-bandwidth networks, and introduced a parallel file system to optimize large-scale data processing. Large Enterprise F implemented Kubernetes-based workload orchestration to automatically distribute and manage diverse computational workloads. The company also formulated resource allocation policies tailored to the characteristics of each business sector, creating a fair and efficient structure for resource utilization."
Results
- Strengthened capability for simultaneous multi-project processing: Improved analysis task processing speed by resolving resource bottlenecks
- 30% improvement in operating costs and energy efficiency: Maximized resource efficiency through cluster optimization
- Established a global collaboration environment: Streamlined joint projects with overseas research institutes and partners
- Accelerated data-driven decision making: Enhanced management insight by quickly processing complex analysis tasks