- Resource-efficient Machine Learning in 2 KB RAM for the Internet of Things.
Describes Bonsai, a part of Microsoft Research Indias open-source EdgeML.
Bonsay is tree-based algorithm. Relatively powerful nodes to enable short trees (reduce RAM usage).
Uses sparse trees, and the final prediction is a sum of all the nodes (path-based).
Optimization:
tanh(x) ≈ x if x < 1 and signum(x) otherwise. Can run on Atmel AVR8 - ProtoNN: Compressed and Accurate kNN for Resource-scarce Devices. k-Nearest Neighbor implementation. Can run on Atmel AVR8
- SeeDot. DSL and compiler for fixed-point ML inference on microcontrollers. PDLI paper. Tested on models. Bonsai, ProtoNN, and LeNet CNN. Hardware. Arduino Uno (AVR8) and Arduino MK1000 (Cortex-M0+), FPGA. Comparison with floating-point, TensorFlow Lite quantization, and MATLAB Coder/Embedded Coder/Fixed-point Designed . 2-20x improvements in inference time. Also implements a fast-exponensiation trick. Schraudolph, 1999.