Digital signal processors (DSPs) represent one of the fastest growing segments of the embedded world. Yet despite their ubiquity, DSPs present difficult challenges for programmers. In particular, ...

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 ...

RENO, NEVADA (April 13, 2005) - Sundance Digital Processing Inc,, a worldwide supplier and manufacturer of advanced digital signal processing (DSP) and reconfigurable computing platforms, today ...

There is a natural preference to use floating-point implementations in custom embedded applications because they offer a much higher dynamic range and as a byproduct bypass the design hassle of ...

If you are used to writing software for modern machines, you probably don’t think much about computing something like one divided by three. Modern computers handle floating point quite well. However, ...

If you are used to writing software for modern machines, you probably don’t think much about computing something like one divided by three. Modern computers handle floating point quite well. However, ...

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 ...

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 ...

Recently Colin Walls had an article on this site about floating point math. Once it was common for embedded engineers to scoff at floats; many have told me they have no place in this space. That’s ...