A key challenge in cross-platform telemetry is that every vendor (NVIDIA, AMD, Intel, Apple) uses different names and units for the same metric. The TelemetryX Normalization Pipeline solves this.
Most common metrics (e.g., NV_GPU_TEMP, AMD_HOTSPOT_TEMP) are mapped in an O(1) hash table. If a match is found, normalization rules are applied immediately.
When a new driver or hardware is released with unknown metric names, TelemetryX uses a lightweight ML model:
- Embedder: Converts the metric name (e.g. "Core_Voltage_Aux") into a semantic vector.
- Similarity Search: Compares the vector against the canonical schema.
- Auto-Mapping: The system "learns" the mapping and caches it in the runtime override table.
All data is converted to standardized international units:
- Temperature: Celsius (°C)
- Power: Watts (W) or Milliwatts (mW)
- Clock: Megahertz (MHz)
- Memory: Megabytes (MB)
- Latency: Milliseconds (ms)
- Gauges: (Temperature, Load) Stored as raw values.
- Counters: (Bytes Sent, Frame Count) The pipeline calculates the Delta between polls to provide meaningful "per second" or "per frame" rates.
Before a metric reaches the UI, it passes through a validation check:
- Range Check: Clamping values to realistic bounds (e.g. 0-100% load).
- Quality Flags: Marking data as "Stale" or "Invalid" if a collector fails, preventing erratic UI behavior.