Because so many microcontrollers now include a floating-point unit (FPU) that performs math operations, engineers can tackle a wider range of applications that rely on precise values for control ...

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 ...

I recently received an email announcement from Texas Instruments that linked to an archived discussion of floating-point and fixed-point math with John Thorn of Texas Instruments, David Anderson of ...

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 ...

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.

The first three numbers are the load average over the last 1, 5, and 15 minutes. Load average being a measure of how busy the system is, the higher the load average the busier the system is.

Most low-end microprocessors (typical of embedded processors) do not provide hardware-assisted floating-point math. Microprocessor manufacturers unfortunately seem to feel that floating-point math is ...