An important question in evolutionary genetics concerns the extent to which adaptive convergence in protein function is caused by convergent or parallel changes at the amino acid level. Even when ...

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, ...