Intel director James Reinders explains the difference between task and data parallelism, and how there is a way around the limits imposed by Amdahl's Law... I'm James Reinders, and I'm going to cover ...

Image sensors with programmable, highly parallel signal processing, so called Vision-Systems-on-Chip, perform computationally intensive tasks directly on the sensor itself. Therefore it is possible to ...

Distributed deep learning has emerged as an essential approach for training large-scale deep neural networks by utilising multiple computational nodes. This methodology partitions the workload either ...

TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...

A paper recently published in the journal Science Advances introduced a hypermultiplexed integrated photonics–based tensor optical processor (HITOP) for scalable optical computing with ...

I’m James Reinders, and I’m going to cover to key concepts involved with parallelism today. They are terms that you’ll hear when you start working with parallel programming, when you start looking at ...