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HPC Research Clusters
Research teams need repeatable performance, queue reliability, and storage throughput. Exeton combines compute nodes, accelerators, schedulers, and storage into an architecture tuned to the application mix.
Workloads
CAE, CFD, EDA, ML
Compute
CPU and GPU nodes
Storage
Shared high I/O
Capabilities
- CPU and memory sizing by solver profile
- GPU acceleration planning for mixed workloads
- Scheduler-ready compute and login topology
- Storage tiering for scratch, project, and archive data
Architecture
- Login and management nodes
- CPU compute partitions
- GPU acceleration partitions
- Shared storage and backup tier
Outcomes
- Clear partitioning for multiple research teams
- Simpler expansion by node class
- Validated infrastructure before delivery
Build This Architecture
Talk with Exeton about sizing, procurement, integration, and support for your cluster or data center plan.