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 ...

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 ...

Based on recent technological developments, high-performance floating-point signal processing can, for the very first time, be easily achieved using FPGAs. To date, virtually all FPGA-based signal ...

[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 ...

The traditional view is that the floating-point number format is superior to the fixed-point number format when it comes to representing sound digitally. In fact, while it may be counter-intuitive, ...

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 ...