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 arithmetic is used extensively in many applications across multiple market segments. These applications often require a large number of calculations and are prevalent in financial ...

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 ...

Here we provide rational for using Centar’s floating-point IP core for the new Altera Arria 10 and Stratix 10 FPGA platforms. After a short contextual discussion section, a comparison of various FFT ...

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 ...

Replacing computationally complex floating-point tensor multiplication with the much simpler integer addition is 20 times more efficient. Together with incoming hardware improvements this promises ...

[Ken Shirriff] has been sharing a really low-level look at Intel’s Pentium (1993) processor. The Pentium’s architecture was highly innovative in many ways, and one of [Ken]’s most recent discoveries ...

New Linear-complexity Multiplication (L-Mul) algorithm claims it can reduce energy costs by 95% for element-wise tensor multiplications and 80% for dot products in large language models. It maintains ...

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 ...