Analysis of Key Research Trends in High-Performance Computing Using Topic Modeling Technique

Abstract

The intellectual structure of scientific discipline consists of a set of interacting topics. The evolution of these topics is the subject of special attention because it reflects the actual interest of researchers and stakeholders. This paper analyzes issues of High-Performance Computing (HPC) on the base of the formal topic modeling technique. Analyzing the abstracts of 7661 publications referenced in Web of Science in 2005–2019, we identified seven topics that concern different aspects of HPC science. The central theme is the Large Scale Applications focused on practical and scientific problems solved using HPC. It is closely linked with Parallel Algorithms that should effectively exploit the thousands of processing cores, Parallel Software for heterogeneous distributed systems, and Interconnected systems that study the integration of HPC facilities in systems of larger size. These topics are relatively stable both in terms of popularity (number of publications) and impact (number of citations). The single topic, which popularity and impact continuously grow in the last 15 years, is Energy efficiency since power consumption is a critical issue of exascale systems. We also found that the topic of Heterogeneous systems dedicated mainly to GPU usage declines after the peak of interest in 2010–2015. The results obtained shed light on the structure of HPC science and supplement the known publications that declare research direction towards exascale performance.