An $O(N)$ Sorting Algorithm: Machine Learning Sort
This work addresses the challenge of sorting big data efficiently for applications in high-performance computing, though it appears incremental as it builds on existing machine learning and parallel sorting concepts.
The authors tackled the problem of sorting large datasets by proposing an O(N·M) sorting algorithm using machine learning, which is suitable for parallel processing and GPU/TPU acceleration, and discussed its application to sparse hash tables.
We propose an $O(N\cdot M)$ sorting algorithm by Machine Learning method, which shows a huge potential sorting big data. This sorting algorithm can be applied to parallel sorting and is suitable for GPU or TPU acceleration. Furthermore, we discuss the application of this algorithm to sparse hash table.