Scalable near-repeat and event chain calculations over heterogeneous computer architecture and systems

Abstract

As a case of space–time interaction, near-repeat calculation indicates that when an event takes place at a certain location, its immediate geographical surroundings would face an increased risk of experiencing subsequent events within a fairly short period of time. This paper presents an exploratory study that extends the investigation of the near-repeat phenomena to a series of space–time interaction, namely event chain calculation. Existing near-repeat tools can only deal with a limited amount of data due to computation constraints, let alone the event chain analysis. By deploying the modern accelerator technology and hybrid computer systems, this study demonstrates that large-scale near-repeat calculation or event chain analysis can be partially resolved through high-performance computing solutions to advance such a challenging statistical problem in both spatial analysis and crime geography.