HPCClusters helps SME teams classify workloads, choose the right deployment model, and build on OpenHPC and Kubernetes together — spanning on-prem, colocation, cloud, and hybrid, down to the data center itself.
Four ways to work with us, from setting infrastructure strategy through running it in the facility.
Vendor-neutral guidance on what to build, buy, colocate, or consume from the cloud. We classify your AI and HPC workloads, balance CPU and GPU capacity, and turn it into an investment roadmap.
$ workload --classify --tcoNeed a cluster that spans traditional HPC and cloud-native workloads? We deploy OpenHPC and Kubernetes side by side, so batch scientific computing and containerized AI/ML pipelines share one infrastructure.
$ kubectl apply -f ohpc-hybrid.yamlWe function as an extension of your operations team — deployment strategy, capacity planning, utilization, and day-to-day troubleshooting across on-prem, hybrid, and cloud environments.
$ systemctl status clusterServer architecture is only half the system. We advise on power density, cooling strategy, rack layout, and facility lifecycle — so the physical plant keeps pace with AI and HPC workload growth.
$ facility --power --coolingSteve Jones is Director of the High Performance Computing Center at Stanford University and has designed and administered numerous Top 500 supercomputers. Our engineers and executives bring a combined well over a century of experience — from workload strategy down to the data center floor.
Beyond consulting, HPCClusters runs and supports HPC education year-round — from a Stanford summer course to community meetups.
Tell us about your project and we'll get back to you with ideas on training and implementation.