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, ...

Floating-point arithmetic can be expensive if you're using an integer-only processor. But floating-point values can be manipulated as integers, asa less expensive alternative. One advantage of using a ...

Floating-point arithmetic is a cornerstone of modern computational science, providing an efficient means to approximate real numbers within a finite precision framework. Its ubiquity across scientific ...

Floating-point arithmetic is a cornerstone of numerical computation, enabling the approximate representation of real numbers in a format that balances range and precision. Its widespread applicability ...

Most of the algorithms implemented in FPGAs used to be fixed-point. Floating-point operations are useful for computations involving large dynamic range, but they require significantly more resources ...

In this video from the HPC Advisory Council Australia Conference, John Gustafson from the National University of Singapore presents: Beating Floating Point at its own game – Posit Arithmetic. “Dr.

John Gustafson from A*STAR will host a BoF on Posit arithmetic at SC17. Entitled, “Improving Numerical Computation with Practical Tools and Novel Computer Arithmetic,” this BOF will be co-hosted by ...

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 ...

Today’s digital signal processing applications such as radar, echo cancellation, and image processing are demanding more dynamic range and computation accuracy. Floating-point arithmetic units offer ...

Freescale Semiconductor has added floating point capability to its QorIQ Qonverge B4 range of DSP-based system-on-chip devices. The B4420 and B4860 are the first devices in the family to include ...