Towards the Reproducibility of Using DLS Techniques in Scientific Applications

Abstract

Reproducibility of the execution of scientific applications on parallel and distributed systems is a growing interest, underlying the trustworthiness of the experiments and the conclusions derived from experiments. Dynamic loop scheduling (DLS) techniques are an effective approach towards performance improvement of scientific applications via load balancing. These techniques address algorithmic and systemic sources of load imbalance by dynamically assigning tasks to processing elements. The DLS techniques have demonstrated their effectiveness when applied in real applications. Complementing native experiments, simulation is a powerful tool for studying the behavior of parallel and distributed applications. This work is a comprehensive reproducibility study of experiments using DLS techniques published in earlier literature to verify their implementations into SimGrid-MSG. In earlier work, it was shown that having a detailed degree of information regarding the experiments to be reproduced is essential for a successful reproduction. This work concentrates on the reproduction of experiments with variable application behaviour and high degree of parallelism of applications and systems. It is shown that reproducing measurements of applications with high variance in task execution times is challenging, albeit feasible and useful. The success of the present reproducibility study signifies the fact that the implementation of the DLS techniques in SimGrid-MSG is verified for the considered applications and systems. Thus, it enables well-founded future research using the DLS techniques in simulation.