Fixed-point arithmetic as a replacement for soft floats

The blog post discusses the advantages of using fixed-point arithmetic as a substitute for floating-point arithmetic in embedded systems, particularly on platforms like the Cortex M0+, which lack hardware support for floating-point operations. Fixed-point types, defined in ISO TR 18037, allow for efficient representation of fractional values using scaled integers, enabling arithmetic operations to be performed using standard integer instructions. This approach has demonstrated a significant performance improvement—approximately double the speed in classification algorithms—while also reducing binary size without compromising accuracy. The author highlights the limitations of floating-point arithmetic, especially in embedded contexts where software emulation can be costly. The blog also details the implementation of fixed-point types in a Google project, including the adaptation of mathematical functions like expf and sqrtf to work with fixed-point types. The author notes that careful normalization techniques can prevent overflow and maintain precision, ultimately enhancing performance. The transition to fixed-point arithmetic not only streamlines operations but also aligns with the constraints of embedded systems, making it a viable alternative to traditional floating-point methods.

- Fixed-point arithmetic can replace floating-point arithmetic in embedded systems for better performance.

- Using fixed-point types can lead to significant speed improvements and reduced binary size.

- The implementation of mathematical functions for fixed-point types is crucial for successful integration.

- Normalization techniques help prevent overflow and maintain precision in calculations.

- Fixed-point types are particularly beneficial for platforms lacking hardware support for floating-point operations.