Knowledge graph analytics kernels in high performance computing

Abstract

Data mining large-scale corpora of scholarly publications, such as the full biomedical literature, which may consist of tens of millions of papers spanning decades of research. The present disclosure provides a Distributed Accelerated Semiring All-Pairs Shortest Path (DSNAPSHOT) algorithm for computing shortest paths of a knowledge graph using distributed-memory parallel computers accelerated by GPUs. DSNAPSHOT implementations can analyze connected input graphs with millions of vertices using a large number graphics processing units (e.g., the 24,576 GPUs of the Oak Ridge National Laboratory's Summit supercomputer system). DSNAPSHOT provides sustained performance of about 136*10floating-point operations per second (136 petaflop/s) at a parallel efficiency of about 90% under weak scaling and, in absolute speed, 70% of the performance given our computation (in the single-precision tropical semiring or 'min-plus' algebra). DSNAPSHOT may enable mining of scholarly knowledge corpora when embedded and integrated into artificial intelligence-driven natural language processing workflows at scale.