This is a schematic showing data parallelism vs. model parallelism, as they relate to neural network training. Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases ...

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 ...

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 ...

Data plus algorithms equals machine learning, but how does that all unfold? Let’s lift the lid on the way those pieces fit together, beginning to end It’s tempting to think of machine learning as a ...

Victor Eijkhout: I see several problems with the state of parallel programming. For starters, we have too many different programming models, such as threading, message passing, and SIMD or SIMT ...

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 ...