The arithmetic unit is one of the important components of CPU design. For computation of complex arithmetic functions on hardware, the CORDIC algorithm is an attractive fixed-point algorithm that uses ...

Engineers targeting DSP to FPGAs have traditionally used fixed-point arithmetic, mainly because of the high cost associated with implementing floating-point arithmetic. That cost comes in the form of ...

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

Most AI chips and hardware accelerators that power machine learning (ML) and deep learning (DL) applications include floating-point units (FPUs). Algorithms used in neural networks today are often ...

An unfortunate reality of trying to represent continuous real numbers in a fixed space (e.g. with a limited number of bits) is that this comes with an inevitable loss of both precision and accuracy.

Floating-point arithmetic is a cornerstone of numerical computation, enabling the approximate representation of real numbers in a format that balances range and precision. Its widespread applicability ...

Although something that’s taken for granted these days, the ability to perform floating-point operations in hardware was, for the longest time, something reserved for people with big wallets. This ...

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 ...

The new Half type is composed of 16 bits and will be geared towards speeding up machine learning workflows by enabling faster computation and smaller storage requirements at the expense of precision.