[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 ...

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 ...

[Alan Burlison] is working on an Arduino project with an accelerometer and a few LEDs. Having the LEDs light up as his board is tilted to one side or another is an easy enough project a computer ...

Radar, navigation and guidance systems process data that is acquired using arrays of sensors. The energy delta from sensor to sensor over time holds the key to information such as targets, position or ...

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 ...

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 ...