Parallel SAX/GA for financial pattern matching using NVIDIA’s GPU

作者：

Highlights：

• A new financial computation approach is presented.

• The SAX/GA algorithm is adapted to efficiently execute in GPU architectures.

• The implemented solution accelerates SAX/GA execution to a maximum of 180 times.

摘要

•A new financial computation approach is presented.•The SAX/GA algorithm is adapted to efficiently execute in GPU architectures.•The implemented solution accelerates SAX/GA execution to a maximum of 180 times.

论文关键词：Genetic Algorithms,Finance computation,Pattern matching,Symbolic Aggregate ApproXimation,GPU,CUDA

论文评审过程：Received 3 December 2017, Revised 21 February 2018, Accepted 14 March 2018, Available online 20 March 2018, Version of Record 4 April 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.03.026