Dynamic Self-Aware Runtime Software for Exascale Systems

At exascale, the power consumption, resilience, and load balancing constraints, especially their dynamic nature and interdependence, and the scale of the system require a radical change in future high-performance computing (HPC) operating systems and runtimes (OS/Rs). In contrast to the existing static OS/R solutions, an exas-cale OS/R is needed that is aware of the dynamically changing re-sources, constraints, and application needs, and that is able to autonomously coordinate (sometimes conflicting) responses to dif-ferent changes in the system, simultaneously and at scale. To pro-vide awareness and autonomic management, a novel, scalable and self-aware OS/R is needed that becomes the “brains ” of the entire X-stack (Figure 1). It dynamically analyzes past, current, and future system status and application needs. It optimizes system usage by scheduling, migrating, and restarting tasks within and across nodes as needed to deal with multi-dimensional constraints