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 ...

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 ...

Native Floating-Point HDL code generation allows you to generate VHDL or Verilog for floating-point implementation in hardware without the effort of fixed-point conversion. Native Floating-Point HDL ...

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 ...

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 ...

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 ...

Embedded C and C++ programmers are familiar with signed and unsigned integers and floating-point values of various sizes, but a number of numerical formats can be used in embedded applications. Here ...

The shift to larger data words and higher sampling rates in audio applications is creating challenges for the audio developer. Here’s some advice on how to deal with the transition. The demand for ...