Investigating the Resilience of Dynamic Loop Scheduling in Heterogeneous Computing Systems

To improve the performance of complex scientific applications, dynamic loop scheduling(DLS) techniques are often employed for load balancing. However, it is a challenge to select the most resilient scheduling technique for guaranteeing optimized performance of scientific applications on large-scale computing systems. Such systems comprise widely distributed and highly heterogeneous resources, and often are prone to failures. Hence, in this work we perform a comprehensive study of resilience of DLS techniques. In our study, we employed Sim Grid-based simulations. The use of a simulation framework assists in overcoming the limits of quantifying the resilience and evaluating the performance of the DLS techniques on real test beds by allowing us to model, control, and reproduce large scale computing systems with irregular behaviour in order to analyze the resilience of DLS technique son computationally intensive scientific applications. The results are used to compare the resilience of scheduling techniques under different case scenarios comprising of variable problem sizes, system sizes, characteristics of the variations in the application task computation times, and those of the processor availabilities and failures.