A lightweight C++ implementation of the Brain Floating Point (bfloat16) format.

bfloat16 is a 16-bit floating point format developed by Google Brain for use in machine learning applications. It preserves the dynamic range of 32-bit floating point (using the same 8-bit exponent) while reducing precision by storing only 7 bits of mantissa (compared to 23 bits in float32).

• Header-only C++ implementation
• Conversions between bfloat16 and float32
• Basic arithmetic operations
• Standard mathematical functions
• IEEE 754 compatibility

This implementation represents bfloat16 as:

• 1 sign bit
• 8 exponent bits (same as float32)
• 7 mantissa bits

The format provides a balance between range and precision that is particularly suitable for neural network training and inference.

This is a header-only library. Simply include the header files in your project.

This project is licensed under the MIT License - see the LICENSE file for details.

• Google Brain bfloat16 specification
• TensorFlow bfloat16 implementation
• NVIDIA's bfloat16 implementation

Contributions are welcome! Please feel free to submit a Pull Request.