Floating-point data in embedded software

Colin Walls, Mentor Graphics
embedded.com (September 16, 2015)

Although many embedded applications can be implemented using integer arithmetic, there are times when the ability to deal with floating point (real) numbers is required. This article looks at the details of floating point operations, when floating point should and should not be used, some of the pitfalls of its use and how its use may sometimes be avoided.

Floating Point and Integers

Nowadays, most embedded systems are built using 32-bit CPUs. These devices give plenty of scope for performing the arithmetical processing required for various applications. Calculations can be performed on signed or unsigned integers and 32 bits gives a good range of values: +/- 2 billion or up to 4 billion respectively. Extending to 64 bits is reasonably straightforward.

If you need to stray outside of these ranges of values or perform more sophisticated operations, then you need to think in terms of floating point and this presents a selection of new challenges.

The concept of a floating point number is simple enough - the value is stored as two integers: the mantissa and the exponent. The number represented is the mantissa multiplied by 2 to the power of the exponent. Typically, these two integers are stored in bit fields in a 32-bit word, but higher precision variants are also available. The most common format is IEEE 754-1985.

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