International Rectifier continues its recent theme of offering packaged solutions based on its power devices with the release of the iMotion integrated design package for motor control (Picture). At ...

DSP systems are best described by using a combination of both graphical-and language-based methods. The MathWorks, an industry leader in DSP modeling software, caters to this dichotomy by providing a ...

Despite some of the inherent complexities of using FPGAs for implementing deep neural networks, there is a strong efficiency case for using reprogrammable devices for both training and inference.

In this special guest feature from Scientific Computing World, Robert Roe writes that FPGAs provide an early insight into possibile architectural specialization options for HPC and machine learning.

In the last couple of years, we have written and heard about the usefulness of GPUs for deep learning training as well as, to a lesser extent, custom ASICs and FPGAs. All of these options have shown ...

Today Intel announced record results on a new benchmark in deep learning and convolutional neural networks (CNN). Developed with ZTE, a leading technology telecommunications equipment and systems ...