OnSort: An O(n) Comparison-Free Sorter for Large-Scale Dataset With Parallel Prefetching and Sparse-Aware Mechanism

This brief proposes OnSort, a parallel comparison-free sorting architecture with $\mathcal {O}(n)$ time complexity, utilizing the SRAM structure to support large-scale datasets efficiently. The performance of existing comparison-free sorters is limited by uneven value distribution and variable element numbers. To address these issues, we introduce a parallel prefetching strategy to accelerate the indexing process and a sparse-aware mechanism to narrow the indexing search range. Furthermore, OnSort implements streaming execution through a pipelined design, thereby optimizing the previously overlooked latency of the counting phase. Experimental results show that, under the configuration of sorting 65,536 16-bit data elements, OnSort achieves a $1.97\times $ speedup and a $22.6\times $ throughput-to-area ratio compared to the existing design. The source code is available at https://github.com/gmx-hub/OnSort.