Infrastructure Provisioning

Heterogeneous Architectures: Tailoring Compute, Storage, and Fabric for Modern Science.

Moving Beyond One-Size-Fits-All

Modern research is diverse: an AI researcher needs massive GPU power, a genomicist needs 2TB of RAM, and a climate modeler requires ultra-low latency. Provisioning a resilient HPC facility means moving away from identical generic nodes and embracing a Heterogeneous Architecture designed for high-impact outcomes.

1. The Specialized Partition Model

The Workhorse

Target: General MPI (CFD, Weather). Dual-socket x86 with standard RAM and mandatory high-speed InfiniBand HDR/NDR fabric.

The Accelerator

Target: AI/ML & Deep Learning. Dense GPU nodes (4x/8x H100) with NVLink for direct peer-to-peer communication.

The Big Brain

Target: Genome Assembly & Graph DBs. Quad-socket nodes with 1.5TB to 4TB of RAM for massive in-memory analytics.

2. The Tiered Data Lifecycle

Tier Technology Purpose Policy
Tier 1: Scratch NVMe / Lustre / GPFS Active I/O Performance Volatile (Auto-purge 30 days)
Tier 2: Project SAS HDD / NFS Active Datasets & Code Persistent (Daily Backups)
Tier 3: Archive LTO Tape / S3 Glacier Long-term Retention Cold Storage (Compliance)

3. Connectivity & Elastic Bursting

"Invisible" Fabric Optimization

We implement non-blocking topologies (Fat Tree/Dragonfly) to ensure consistent latency across the entire cluster. For external collaboration, we provision 100Gbps+ Data Transfer Nodes (DTNs) within a Science DMZ.

Cloud "Burst" Capability

Building for peak capacity is wasteful. We configure Slurm to recognize "Cloud Partitions," allowing critical grant deadlines to burst into AWS/Azure when local resources are at 100%.

4. Governance & Fair Share

Distributing resources fairly is a policy challenge. We implement a three-tiered allocation model:

  • Startup Allocation: Instant approval for small jobs to generate preliminary grant data.
  • Research Allocation: Peer-reviewed requests for massive, multi-node projects.
  • Fair Share Decay: An algorithm that automatically adjusts priority based on historical usage to prevent monopoly.

Provisioning Checklist

Power & Cooling: Evaluation of Direct Liquid Cooling (DLC) for high-TDP chips.
Container Cache: Local Harbor registry to prevent Docker Hub throttling.
Licensing: Centralized license servers for VASP, MATLAB, and ANSYS.
Interconnect Balance: Ensuring H100 nodes aren't starved by 10GbE bottlenecks.

Build for the Future of Science

Download our "Heterogeneous HPC Design Blueprint" and learn how to balance GPU, Memory, and Fabric requirements.

Download Provisioning Guide (.pdf)