Identification and Characterization of Memory Allocation Anomalies in High-Performance Computing Applications

Abstract

A memory allocation anomaly occurs when the allocation of a set of heap blocks imposes an unnecessary overhead on the execution of an application. In this paper, we propose a method for identifying, locating, characterizing and fixing allocation anomalies, and a tool for developers to apply the method. We experiment our method and tool with a numerical simulator aimed at approximating the solutions to partial differential equations using a finite element method. We show that taming allocation anomalies in this simulator reduces the memory footprint of its processes by 37.27% and the execution time by 16.52%. We conclude that the developer of high-performance computing applications can benefit from the method and tool during the software development cycle.