A Cache-Efficient Sorting Algorithm for Database and Data Mining Computations using Graphics Processors

TL;DR: A fast sorting algorithm using graphics processors (GPUs) that adapts well to database and data mining applications and has a memoryefficient data access pattern and an efficient instruction dispatch mechanism to improve the overall sorting performance.

Abstract: We present a fast sorting algorithm using graphics processors (GPUs) that adapts well to database and data mining applications. Our algorithm uses texture mapping and blending functionalities of GPUs to implement an efficient bitonic sorting network. We take into account the communication bandwidth overhead to the video memory on the GPUs and reduce the memory bandwidth requirements. We also present strategies to exploit the tile-based computational model of GPUs. Our new algorithm has a memoryefficient data access pattern and we describe an efficient instruction dispatch mechanism to improve the overall sorting performance. We have used our sorting algorithm to accelerate join-based queries and stream mining algorithms. Our results indicate up to an order of magnitude improvement over prior CPU-based and GPU-based sorting algorithms