Depending on the deep learning architecture, data size, and task at hand, we sometimes require 1 GPU, and sometimes, several of them, a decision data scientist needs to make based on known ...

A new technical paper titled “Hardware-software co-exploration with racetrack memory based in-memory computing for CNN ...

“Deep compression is useful in real-world neural networks and can save a great deal in terms of the number of computations and the bandwidth demands.” Below is the Aristotle architecture, which is ...

Neural architecture search promises to speed up the process of finding neural network architectures that will yield good models for a given dataset. Topics Spotlight: AI-ready data centers ...

Synthetic cannabinoids, a class of new psychoactive substances, have emerged as a significant public health and social stability threat due to their structural diversity, rapid iteration, and stronger ...

There has been much written about the potential for FPGAs to take a leadership role in accelerating deep learning but in practice, the hurdles of getting from concept to high performance hardware ...