Infrastructure Assessment is the diagnostic phase of High-Performance Computing. Before buying new hardware or changing software, you must understand exactly how the current system is performing and where it is failing.

In HPC, an assessment isn't just "checking if servers are on." It involves deep forensic analysis to answer questions like: "Why is our 10,000-core cluster only running at 40% efficiency?" or "Will our current storage survive the upgrade to AI workloads?"

Here is the detailed breakdown of the fundamentals, the strategic approach, and the downloadable Word file.

1. The Fundamentals: The Three Pillars

An assessment analyzes three distinct layers to find bottlenecks.

1. Physical Infrastructure (Hardware):
• Utilization: Are nodes sitting idle? Are we buying more RAM when we actually need more Memory Bandwidth?
• Network Topology: Are there "hotspots" in the switches where data traffic jams occur?
• Storage Latency: Is the expensive supercomputer waiting for the cheap hard drives to write data?
2. Software Environment:
• OS & Kernel: Are outdated drivers slowing down the InfiniBand network?
• Libraries: Are users running generic binaries instead of code compiled for the specific CPU architecture (AVX-512)?
3. Workload efficiency:
• Job Scheduling: Is the "Tetris" logic of the scheduler leaving massive gaps of unused time?
• User Behavior: Are users requesting 100GB of RAM but only using 10GB, wasting resources that others could use?

2. The Strategy: "Discover, Measure, Recommend"

A professional assessment follows a strict strategic path.

Phase 1: Discovery (The "As-Is" State)

• Automated Inventory: Use tools to map every asset. You cannot optimize what you don't know you have.
• Configuration Audit: Compare the configuration of Node 1 vs. Node 100. "Drift" (slight differences) often causes obscure bugs.

Phase 2: Workload Characterization

• Profiling: We don't just look at averages. We look at peaks.
• Classification: We categorize jobs into "Compute Bound" (needs faster CPUs), "Memory Bound" (needs faster RAM), or "I/O Bound" (needs faster Disk).
• Example Finding: “70% of your jobs are serial (single-core), but you are running them on expensive interconnect nodes. Move them to cheap commodity servers.”

Phase 3: Gap Analysis & Roadmap

• Future Proofing: Compare the current system against future goals (e.g., "We want to do Deep Learning").
• Result: A Gap Analysis report stating: "Your storage is fast enough, but your network latency will crash your AI training."

3. Key Tools Used for Assessment

Category	Tool	Usage
Historical Usage	Splunk / ELK Stack	Analyzing years of scheduler logs to find usage trends and wasted resources.
Performance Metrics	Prometheus + Grafana	visualising long-term trends (e.g., "CPU usage drops every Tuesday").
Profiling	Intel VTune / Mosquitto	Deep-diving into specific applications to see why they run slowly on the current hardware.
Storage Analysis	IOzone / IOR	Benchmarking the file system to find the maximum read/write limits.
Network Analysis	OSU Micro-Benchmarks	Testing the latency and bandwidth of the interconnect.