Floating-point arithmetic is necessary to meet precision and performance requirements for an increasing number of applications. Today, most 32-bit embedded processors that offer this functionality are ...

This article explains the basics of floating-point arithmetic, how floating-point units (FPUs) work, and how to use FPGAs for easy, low-cost floating-point processing. Inside microprocessors, numbers ...

Most of the algorithms implemented in FPGAs used to be fixed-point. Floating-point operations are useful for computations involving large dynamic range, ...

Floating-point arithmetic is a cornerstone of modern computational science, providing an efficient means to approximate real numbers within a finite precision framework.

Unfortunately, AVRs don’t have floating point arithmetic so [Alan] used fixed point arithmetic – a system similar to balancing your checkbook in cents rather than dollars.

Other than proving that floating point arithmetic is cursed, this also raises the question of why this works. Simplified numerator and denominator with floating point delta.

A similar conclusionwas reached recently by Microsoft and Meta: Floating-point arithmetic is just much less efficient than integer arithmetic.

I am working on a viewshed* algorithm that does some floating point arithmetic. The algorithm sacrifices accuracy for speed and so only builds an approximate viewshed. The algorithm iteratively ...