HPC infrastructure
We design, build, and operate compute at scale — from bare-metal clusters to hybrid cloud.
Architecture
- Slurm — Job scheduling, resource management, partition design, fair-share policies, and accounting for multi-tenant environments.
- GPU computing — NVIDIA GPU partitioning, scheduling, and software-based GPU slicing for oversubscribed partitions.
- Storage — Parallel filesystems, tiered storage, and high-throughput I/O for compute workloads.
- Networking — InfiniBand, high-speed Ethernet, and network architecture for low-latency interconnects.
- Hybrid & cloud — Bare-metal to cloud burst. On-prem clusters with cloud overflow for peak demand.
What we deliver
- Cluster design and build — hardware selection, rack layout, network topology, and Slurm configuration.
- Job scheduling optimization — partition design, preemption policies, GPU scheduling, and QoS tuning.
- GPU management — driver stack, CUDA toolkit, container runtimes, and GPU slicing for shared partitions.
- Monitoring and operations — Prometheus, Grafana, alerting, and capacity planning.
- Migration — moving workloads from legacy clusters or cloud to new infrastructure.
Applications
Research computing, defence and government HPC, ML training at scale (our AI/ML platforms run on HPC infrastructure), scientific simulation, financial modelling, and any workload that needs serious compute managed reliably.
See Projects for examples, or consulting for custom cluster builds — get in touch to discuss your requirements.