Memory allocation anomalies in high-performance computing applications: A study with numerical simulations

摘要

A memory allocation anomaly occurs when the allocation of a set of heap blocks imposes an unnecessary overhead on the execution of an application. This overhead is particularly disturbing for high-performance computing (HPC) applications running on shared resources-for example, numerical simulations running on clusters or clouds-because it may increase either the execution time of the application (contributing to a reduction on the overall efficiency of the shared resource) or its memory consumption (eventually inhibiting its capacity to handle larger problems). In this article, 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 both its execution time and the memory footprint of its processes, irrespective of the specific heap allocator being employed with it. We conclude that the developer of HPC applications can benefit from the method and tool during the software development cycle.