Multi-GPU Radix Sort Algorithm in High Performance Computing Environment

Generally, the single GPU computing method is utilized for the conventional radix sort algorithm based on GPU parallel computing. Nevertheless, as the data scale grows, the single GPU sorting algorithm is gradually demonstrating its performance bottlenecks. In the paper, an efficient radix sort algorithm based on multi-GPU parallel computing is proposed, which implements a strategy of using different bucket classifications on multiple GPUs to improve the sorting performance and efficiency of large-scale datasets. With the multi-GPU parallel computing, more buckets may be used for data classification in one traversal, effectively reducing data sorting times, lowering time complexity, and improving sorting speed and throughput. The experiment shows that the algorithm has significantly improved the operational efficiency, demonstrating good application prospects. Meanwhile, the algorithm herein also presents good scalability, which can adapt to the constantly growing data scale in the future.