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 ...

Artificial intelligence (AI) has become pervasive in our lives, improving our phones, cars, homes, medical centers, and more. As currently structured, these models primarily run in power-hungry, ...

[Editor's note: For an intro to fixed-point math, see Fixed-Point DSP and Algorithm Implementation. For a comparison of fixed- and floating-point hardware, see Fixed vs. floating point: a surprisingly ...

In this video from the HPC Advisory Council Australia Conference, John Gustafson from the National University of Singapore presents: Beating Floating Point at its own game – Posit Arithmetic. “Dr.

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 ...

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 ...

In this video, John Gustafson from the National University of Singapore presents: Beyond Floating Point: Next Generation Computer Arithmetic. “A new data type called a “posit” is designed for direct ...

A way to represent very large and very small numbers using the same quantity of numeric positions. Floating point also enables calculating a wide range of numbers very quickly. Although floating point ...

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 ...