The Idle Edge Compiler

The Idle Edge Compiler converts standard ML models (ONNX, TensorFlow Lite, PyTorch exported to ONNX) into lightweight C code or pre-compiled binaries that can run directly on MCUs (Microcontrollers) or IoT devices.

Why OEM Needs This:

• Most IoT/MCU devices run on 256 KB – 1 MB SRAM. Traditional ML runtimes (TensorFlow Lite Micro, PyTorch Mobile) are too heavy, adding ~100 KB+ runtime overhead.

• Idle’s compiler reduces overhead to <10 KB, allowing inference at near bare-metal speed.

• Supports quantization (INT8, INT4, even binary neural nets), making models fit into ultra-constrained devices.

Example Flow:

• OEM engineer trains a model in PyTorch (e.g., anomaly detection for motor vibration).

• Export model → ONNX format.

• Run Idle Compiler → outputs optimized C library + lightweight Idle Node hooks.

• OEM integrates compiled code into their device firmware image.