Image Interpretation: System Problems Due to Sensor Delay
This diagram explains system performance issues caused by the Time Constant (delay) of temperature sensors.
Top Section: Two Workload Scenarios
LLM Workload (AI Tasks)
- Runs at 100% workload
- Almost no delay (No Delay almost)
- Result: Performance Down and Workload Cost waste
GPU Workload
- Operating at 80°C
- Thermal Throttling occurs
- Transport Delay exists
- Performance degradation starts at 60°C → Step down
Bottom Section: Core of the Sensor Delay Problem
Timeline:
- Sensor UP start (Temperature Sensor activation)
- Big Delay due to Time Constant
- TC63 (After 10-20 seconds)
- Sensor detects 63% temperature rise
- Actual temperature is already higher
- After 30-40 seconds
- Sensor detects 86% rise
- Temperature Divergence, Late Cooling problem occurs
Key Issues
Due to the sensor’s Time Constant delay:
- Takes too long to detect actual temperature rise
- Cooling system activates too late
- GPU already overheated, causing thermal throttling
- Results in workload cost waste and performance degradation
Summary
Sensor delays create a critical gap between actual temperature and detected temperature, causing cooling systems to react too late. This results in GPU thermal throttling, performance degradation, and wasted computational resources. Real-time monitoring with fast-response sensors is essential for optimal system performance.
#ThermalManagement #SensorDelay #TimeConstant #GPUThrottling #DataCenter #PerformanceOptimization #CoolingSystem #AIWorkload #SystemMonitoring #HardwareEngineering #ThermalThrottling #LatencyChallenges #ComputeEfficiency #ITInfrastructure #TemperatureSensing
With Claude
Lechuck Park 