HPC Benchmark Reports
Strategic Observability: Translating Telemetry into Scientific Velocity.
The Observability Cockpit
In 2026, HPC benchmark reports have evolved from simple performance charts to strategic "Observability Cockpits." These systems prioritize throughput-per-watt, sustained time-to-solution, and the AI-for-Science lifecycle. We help you move beyond the High-Performance Linpack ($R_{max}$) to reflect the true heterogeneous nature of your workloads.
1. Key Performance Indicators (KPIs) 2026
| Metric Category | Key Metric | Significance in 2026 |
|---|---|---|
| Sustained Performance | ns/day or years/day | Measures real-world productivity for climate or molecular modeling. |
| Scaling Efficiency | Parallel Efficiency % | Identifies the exact point where adding nodes yields diminishing returns. |
| Data Movement | I/O Throughput (GB/s) | Tracks the "Memory Wall" and parallel filesystem (Lustre/GPFS) health. |
| Energy Efficiency | GFLOPS/Watt | Energy is now a primary first-order constraint for exascale deployments. |
| AI Integration | Training/Inference Ratio | Measures how well the fabric handles mixed AI and simulation workloads. |
2. Specialized Dashboard Architecture
Cluster Health & Heat Maps
Real-time visualization of node-level utilization. Heat maps identify "hot nodes" or "zombie jobs" that consume power without producing scientific output.
Self-Benchmarking Cockpits
Using Altair InsightPro™ and Darshan, researchers track their own job history to optimize resource requests and improve their throughput over time.
3. Industry Standard Monitoring Stacks
Infrastructure
Grafana + Prometheus: The gold standard for customizable, open-source cluster visualization.
Profiling
HPE CrayPat & NVIDIA Nsight: Deep-dives into routine-based hardware counters and GPU kernels.
Automated Reporting
LinearB: Automated quarterly templates focusing on AI velocity and scientific code quality.
4. Turning Data into Strategy
A good report guides future procurement and policy, rather than just recording the past. We focus on:
- Baseline Comparison: Using single-node performance to reveal parallel software overhead.
- Harmonic Mean Analysis: Correctly averaging rate metrics (ns/day) for scientifically accurate conclusions.
- Actionable Insights: Ending every report with clear steps, e.g., "Upgrade memory bandwidth on Partition B."
Optimize Your Reporting Today
Download our "Quarterly HPC Impact Report Template" to demonstrate your facility's value to PIs and University Administration.
Download Report Template (.xlsx)