[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 ...

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 ...

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 ...

Under CMS, floating-point representation (unlike scientific notation) uses a base of 16 rather than base 10. IBM mainframe systems all use the same floating-point representation, which is made up of 4 ...

Multiplication on a common microcontroller is easy. But division is much more difficult. Even with hardware assistance, a 32-bit division on a modern 64-bit x86 CPU can run between 9 and 15 cycles.

Once the domain of esoteric scientific and business computing, floating point calculations are now practically everywhere. From video games to large language models and kin, it would seem that a ...

There is a natural preference to use floating-point implementations in custom embedded applications because they offer a much higher dynamic range and as a byproduct bypass the design hassle of ...