The microprocessor chip technology revolution has moved rapidly to large-scale on-chip (hybrid) multiprocessing and parallel computing at an unprecedented scale and incorporation of different architecture types in the same system. Growing core-count and heterogeneity will produce increasingly fragmented resource pools in large-scale systems. Achieving efficiency, reliability and high performance will increasingly require flexible, dynamic, intelligent runtime resource management and corresponding activity scheduling for applications not present in existing software stacks. The needs far exceed what has existed in traditional runtimes support from current system vendors