GPU Performance
More useful compute from every unit of energy.
Infrastructure performance is not defined by installed GPU capacity alone. It is defined by how effectively the complete system converts power, hardware and data into useful computing output.
What influences performance?
Performance is a system-level outcome.
- 01
GPU utilisation
- 02
CPU and memory bottlenecks
- 03
Network throughput
- 04
Storage performance
- 05
Cooling and power constraints
- 06
Workload scheduling
AI inference performance
Measure the output, not just the hardware.
| Metric | What it measures |
|---|---|
| Tokens per second | Generated output throughput |
| Time to first token | Initial response delay |
| Latency | Response time |
| Concurrent requests | Simultaneous workload capacity |
| Energy per token | Energy required for output |
| GPU utilisation | Accelerator activity |
Engineering performance framework
Connect infrastructure efficiency to computing outcomes.
We assess how electrical capacity, cooling performance, GPU configuration, network architecture and software workload characteristics influence the useful output of an AI computing environment.
Next steps