Cost Optimization & TCO Analysis finds the "hidden leaks" in a supercomputing budget.

In HPC, buying the servers (CapEx) is often only 25-30% of the total cost over 5 years. The other 70%—electricity, cooling, commercial software licenses, and administration (OpEx)—is where the real money is spent.

Consulting in this area involves identifying where you are overpaying for performance you aren't using. For example, running a 5-year-old server might seem "free" because it's paid off, but if it consumes $5,000/year in electricity and $20,000/year in software licenses to do the same work as a modern $10,000 server, it is actually burning cash.

Here is the detailed breakdown of the "Iceberg" concept, the strategies for optimization, and the downloadable Word file.

1. The Iceberg Model: Where the Money Goes

TCO Analysis looks below the waterline.

• Visible Cost (Hardware): The invoice from Dell/HPE.
• Hidden Cost 1 (Power & Cooling): An HPC rack can consume $30,000+ per year in electricity. Efficiency (PUE) matters more than hardware price.
• Hidden Cost 2 (Software Licenses): This is often the biggest cost.
• Scenario: Commercial Engineering software (like Ansys or LS-DYNA) charges per CPU core.
• The Trap: If you run this software on old, slow cores, you need more licenses to finish the job.
• The Fix: Buy the fastest, most expensive CPUs possible. You buy fewer hardware cores, which drastically lowers your massive software bill.

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2. Optimization Strategies

A. License-Aware Hardware Selection

• Problem: You have a budget of $1M for hardware and $2M for software licenses.
• Strategy: Don't buy "standard" servers. Buy "High Frequency" servers.
• Instead of 64 slow cores (2.0 GHz), buy 32 fast cores (4.0 GHz).
• The hardware cost is the same. The simulation speed is the same. But you pay 50% less in software license fees.

B. Energy-Aware Scheduling

• Green Computing: Modern schedulers (Slurm) can read the electricity price market.
• Strategy: Configure the cluster to run non-urgent, massive jobs at night when electricity is cheaper, or throttle down CPU frequency by 10% (saving 30% power) with only a 2% performance loss.

C. Storage Tiering (Lifecycle Management)

• Problem: Storing 5-year-old simulation data on expensive NVMe Flash storage ($300/TB).
• Strategy: Implement automated policies. Data untouched for 90 days moves to HDD ($20/TB). Data untouched for 1 year moves to Tape ($5/TB).

3. Key Tools & Applications

Category	Tool	Usage
License Management	FlexLM / OpenLM	Tracks exactly who is using expensive licenses and identifies "Hoarding" (users checking out licenses and going to lunch).
Power Monitoring	IPMI / Redfish	Pulls real-time power draw data from the server power supplies to calculate PUE.
Financial Modeling	Cloud TCO Calculators	Compare the "All-In" cost of running a job On-Premises vs. AWS/Azure.
Scheduling	Slurm Energy Plugin	Automatically lowers CPU frequency during idle times or specific jobs.