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 ...

Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more Parallel Domain, a startup developing a ...

As hardware designers turn toward multicore processors to improve computing power, software programmers must find new programming strategies that harness the power of parallel computing. One technique ...

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 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, ...