[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 ...

The new Half type is composed of 16 bits and will be geared towards speeding up machine learning workflows by enabling faster computation and smaller storage requirements at the expense of precision.

Routines for the PIC16/17 families are provided in a modified IEEE 754 32-bit format together with versions in 24-bit reduced format. Although fixed point arithmetic can usually be employed in many ...

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 ...

The original article is published on Nervana site: Accelerating Neural Networks with Binary Arithmetic. Please go to Nervana Homepage to learn more on Intel Nervana's deep learning technologies. At ...

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 ...

I am working on a viewshed* algorithm that does some floating point arithmetic. The algorithm sacrifices accuracy for speed and so only builds an approximate viewshed. The algorithm iteratively ...