Dual Knowledge Distillation for neural machine translation

Summary: This paper addresses the issue of better utilizing GPUs for similarity search tasks, proposing a novel design for k-selection which outperforms existing approaches by large margins. The implementation achieves up to 55 percent of theoretical peak performance and enables significantly faster nearest neighbor implementations on GPU. It also allows for the construction of high accuracy k-NN graphs on large datasets in a fraction of the time compared to prior methods.