Efficient spatial co-location pattern mining on multiple GPUs
作者：
Highlights：
• A generic parallel algorithm for Co-location Pattern Mining.
• Support for multi GPU architectures.
• A specialized variant of the algorithm optimized for the NVIDIA GPUs.
• Memory-aware solution.
• A dedicated algorithm for compression of input data.
摘要
•A generic parallel algorithm for Co-location Pattern Mining.•Support for multi GPU architectures.•A specialized variant of the algorithm optimized for the NVIDIA GPUs.•Memory-aware solution.•A dedicated algorithm for compression of input data.
论文关键词：GPGPU,Spatial co-location,Parallel computing,Compression,Data mining,Co-location pattern mining
论文评审过程：Received 30 March 2017, Revised 10 October 2017, Accepted 10 October 2017, Available online 12 October 2017, Version of Record 5 November 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2017.10.025
