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 ...

One of the things to avoid when it comes to parallelism is working with raw threads. Abstraction offers a way around the issue, by avoiding the need to deal with low-level details of parallel systems, ...

Last week’s discussion emphasized that to achieve truly good writing in English, we should aim for parallelism every time we make statements that present several grammar elements in a series. Elements ...

Parallel computing is an idea whose time has finally come, but not for the obvious reasons. Parallelism is a computer science concept that is older Moore’s Law. In fact, it first appeared in print in ...

Parallelism used to be the domain of supercomputers working on weather simulations or plutonium decay. It is now part of the architecture of most SoCs. But just how efficient, effective and widespread ...

The addition of multiple cores to microprocessors has created a significant opportunity for parallel programming, but a killer application is needed to push the concept into the mainstream, ...

Data parallelism is an approach towards parallel processing that depends on being able to break up data between multiple compute units (which could be cores in a processor, processors in a computer, ...

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 ...