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 ...