[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 1985, the Institute of Electrical and Electronics Engineers (IEEE) established IEEE 754, a standard for floating point formats and arithmetic that would become the model for practically all FP ...

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 ...

Celoxica has available a toolkit for floating-point arithmetic implementation in high-density programmable logic. The IEEE 754 compliant libraries support single, double and custom precision ...

The uM-FPU64 floating point coprocessor chip provides support for IEEE 754-compatible, 64-bit floating point and integer calculations, expanded digital I/O, and analog input capabilities as well as ...

An unfortunate reality of trying to represent continuous real numbers in a fixed space (e.g. with a limited number of bits) is that this comes with an inevitable loss of both precision and accuracy.

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 ...

Although something that’s taken for granted these days, the ability to perform floating-point operations in hardware was, for the longest time, something reserved for people with big wallets. This ...

Hardware for integer or fixed-point arithmetic is relatively simple to design, at least at the register-transfer level. If the range of values and precision that can be represented with these formats ...