Node Selection
Plan CPU, memory, local storage, GPU if needed, chassis choice, and spare capacity around the workload.
- Compute and memory sizing
- Chassis and serviceability planning
- Growth and replacement path
HPC Cluster Builds and Tuning
Cluster infrastructure for compute-heavy work.
Web Tech helps plan HPC-style clusters around node sizing, storage throughput, network layout, burn-in, tuning, and practical operation after deployment.
Cluster Scope
HPC work is not just a pile of nodes.
Cluster performance and supportability depend on CPU, memory, storage, network, power, software stack, burn-in, and handoff discipline.
This page avoids unsupported performance promises. Actual sizing depends on the workload, software, data movement, and operational constraints.
Storage and Network Layout
Balance shared storage, local scratch, network throughput, NIC selection, switching, optics, and cabling.
- Storage throughput and capacity
- Switching, NICs, optics, and cables
- Rack, power, and airflow constraints
Burn-In and Tuning
Plan basic burn-in, firmware checks, operating notes, performance sanity checks, and handoff documentation.
- Basic burn-in planning
- Firmware and configuration notes
- Performance tuning and handoff
What Web Tech Can Produce
Cluster planning that ties hardware to workload behavior.
Workload Profile
Software stack, data movement, CPU and memory needs, storage pattern, network path, and runtime goals.
Architecture Direction
Node mix, storage layout, network layout, sizing assumptions, rack and power limits, and growth considerations.
Validation Plan
Burn-in approach, sanity checks, firmware and configuration notes, and performance tuning considerations.
Operational Handoff
Documentation, support boundaries, follow-up tuning notes, replacement considerations, and refresh planning.
Workload First
The right cluster depends on where the bottleneck lives.
Some workloads need cores. Others need memory, fast scratch, shared storage, network bandwidth, or better operational discipline. Web Tech helps identify the constraints before hardware is specified.
Process
A cluster plan that can be supported.
Profile
Understand workload shape, data movement, software requirements, and performance pain points.
Design
Plan node mix, storage, network, rack, power, and management approach.
Validate
Use burn-in and sanity checks to catch hardware or configuration issues early.
Tune
Adjust configuration, capture notes, and hand off operational guidance.
Related Solutions
Cluster work touches the rest of the infrastructure.
Start Here
Send the workload profile.
Include software stack, data size, CPU and memory expectations, storage throughput, network needs, rack and power limits, and timeline.