1. Models NPU, GPU, and DSP performance to estimate FPS, latency, power consumption, and memory usage under different resolutions, batch sizes, and quantization levels.
2. Simulates the full AI pipeline—from pre-processing to inference and post-processing—to assess end-to-end latency, multi-model scheduling, task contention, I/O blocking, and NPU utilization.
3. Generates model conversion, quantization, and runtime settings, integrating TensorRT, TFLite, ONNX Runtime, and vendor SDKs for one-click Edge AI deployment.

-

eAI-SIM creates virtual environments based on the target Edge AI chipset, operating system, resources, and application requirements. Developers can evaluate model performance, system load, and bottlenecks without physical boards or complete firmware. After model tuning and configuration, validated models and system settings can be deployed to the target chipset with one click, accelerating on-device implementation.