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 ...

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 ...

Alex Krizhevsky, a member of the Google Brain Team, explained the differences between data parallelism and model parallelism in a paper about parallelizing network training. With data parallelism ...

And I really want to emphasise that when you look to do parallelism, one of the things we want to avoid is approaching the problem by going to the lowest programming model available for ...

In the task-parallel model represented by OpenMP, the user specifies the distribution of iterations among processors and then the data travels to the computations. In data-parallel programming, the ...

For instance, most theories of parallelism are typically about interactions ... Co-design is another research direction: since the IMP model keeps track of where data is, hardware can be simplified to ...