Acceleration of the SPADE Method Using a Custom-Tailored FP-Growth Implementation.

ABSTRACT: The SPADE (spatio-temporal Spike PAttern Detection and Evaluation) method was developed to find reoccurring spatio-temporal patterns in neuronal spike activity (parallel spike trains). However, depending on the number of spike trains and the length of recording, this method can exhibit long runtimes. Based on a realistic benchmark data set, we identified that the combination of pattern mining (using the FP-Growth algorithm) and the result filtering account for 85-90% of the method's total runtime. Therefore, in this paper, we propose a customized FP-Growth implementation tailored to the requirements of SPADE, which significantly accelerates pattern mining and result filtering. Our version allows for parallel and distributed execution,

SUBMITTER: Porrmann F 

PROVIDER: S-EPMC8483730 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature