[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 ...

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 ...

"Dr. Gustafson has recently finished writing a book, The End of Error: Unum Computing, that presents a new approach to computer arithmetic: the unum. The universal number, or unum format, encompasses ...

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

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, ...

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 ...

[Editor's note: For an intro to floating-point math, see Tutorial: Floating-point arithmetic on FPGAs. For a comparison of fixed- and floating-point hardware, see Fixed vs. floating point: a ...

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 ...

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

Recently, a new 8-bit floating-point format (FP8) has been suggested for efficient deep-learning network training. As some layers in neural networks can be trained in FP8 as opposed to the incumbent ...