Scalability & Flexibility Planning
Designing HPC systems that grow without breaking.
Beyond "Buying a Bigger Server"
In standard IT, scaling often means vertical growth. In Supercomputing, physics limits the size of a single server. Therefore, HPC relies on Horizontal Scaling. However, adding 1,000 nodes to a cluster designed for 100 will choke the network and freeze the storage. Scalability Planning prevents infrastructure collapse.
Scale-Out (Horizontal)
Adding more compute nodes.
Ideal for running more simulations simultaneously or one massive parallel simulation. The main bottleneck is the Interconnect—switch topology must be non-blocking to avoid slowdowns.
Scale-Up (Vertical)
Strengthening individual nodes.
Adding GPUs or massive RAM to existing servers for AI training. The main bottleneck is Power & Cooling—a single GPU-dense rack can require up to 60kW.
Strategic Planning Layers
Infrastructure Readiness
Installing "Dark Power" and piping for Day 5 capacity (e.g. 2MW) while only using 500kW on Day 1. Future-proofing floor weights for heavy liquid-cooled racks.
Network Topology
Sizing Spine switches with empty ports to allow seamless leaf switch expansion. No need to rip out the cabling backbone when adding nodes.
Storage Namespaces
Using Parallel File Systems (Lustre/GPFS) to add capacity via new Object Storage Targets (OST) without changing the user's mount point.
Flexibility: Cloud Bursting
Scalability often means handling a temporary spike too large for hardware purchases. We configure schedulers like Slurm to treat public clouds (AWS/Azure) as an overflow partition.
- Hybrid Architecture Integration
- Automated Spillovers
- Zero Permanent Footprint
Infinite Scalability
On-demand core expansion
Download Scalability Worksheet
Assess your current facility limits and plan your expansion with our engineering worksheet.
Download Planning Guide (.docx)