The GRFPU is an IEEE-754 compliant floating-point unit, supporting both single and double precision operands. The pipelined design combines high throu ...

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 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 ...

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.

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 ...

As defined by the IEEE 754 standard, floating-point values are represented in three fields: a significand or mantissa, a sign bit for the significand and an exponent field. The exponent is a biased ...

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 ...

Hardware floating point can be attractive in many embedded applications where integer or fixed point algorithms produce either overflow/underflow or unacceptably long word lengths. In such cases ...