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 ...

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 units (fpu) can increase the range and precision of mathematical calculations or enable greater throughput in less time, making it easier to meet real time requirements. Or, by enabling ...

Why floating point is important for developing machine-learning models. What floating-point formats are used with machine learning? Over the last two decades, compute-intensive artificial-intelligence ...

Texas Instruments recently introduced what it calls “the first floating-point digital signal controller (DSC).” (The term DSC is relatively new in the industry; it refers to a low-cost embedded ...

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 ...

This article was originally published by computer historian Ken Shirriff on his blog. Thanks to his kind permission, the article is reproduced here. Eine Übertragung ins Deutsche ist ebenfalls ...