Record Linkage for Auto-tuning of High Performance Computing Systems

To become auto-adaptive, computer systems should be able to have some knowledge of incoming applications even before launching the application on the system, so that the runtime environment can be customized to the particular needs of this application. In this paper, we propose the architecture of an auto-tuner which relies on record linkage methods to match an incoming application with a database of already known applications. We then present a concrete implementation of this auto-tuner on High Performance Computing (HPC) systems, to submit unknown incoming applications with the best possible parametrization of a smart prefetch strategy by analyzing their metadata. We test this auto-tuner in conditions close to a production environment, and show an improvement of 28% compared to using the default parametrization. The conducted evaluation reveals a negligible overhead of our auto-tuner when running in production and a significant resilience for parallel use on a high-traffic HPC cluster.