Today a company called Bounded Floating Point announced a “breakthrough patent in processor design, which allows representation of real numbers accurate to the last digit for the first time in ...

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 ...

People learn in different ways, but sometimes the establishment fixates on explaining a concept in one way. If that’s not your way you might be out of luck. If you have trouble internalizing floating ...

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 ...

This week's tip comes from Bobby Orndorff of GrapeCity software. He's the Chief Architect for Spread.NET, and implemented the Spread Calculation Engine and the Chart component. Floating point numbers ...

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 ...

Why floating point is important for developing machine-learning models. What floating-point formats are used with machine learning? Over the last two decades, compute-intensive artificial-intelligence ...

I don’t know about you, but I typically have a number of “back-burner” projects on the go. Currently I'm playing with creating my own simple binary floating-point format as part of an educational tool ...

In a recent survey conducted by AccelChip Inc. (recently acquired by Xilinx), 53% of the respondents identified floating- to fixed-point conversion as the most difficult aspect of implementing an ...