Future extreme-scale systems are expected to contain homogeneous and heterogeneous many-core processors, with O(10^3) cores per node and O(10^6) nodes overall. Effective combination of inter node and intra-node parallelism is recognized to be a major software challenge for such systems. Further, applications will have to deal with constrained energy budgets as well as frequent faults and failures. To aid programmers manage these complexities and enhance programmability, much of recent research has focused on designing state-of-art software runtime systems. Such runtime systems are expected to be a critical component of the software ecosystem for the management of parallelism, locality, load balancing, energy and resilience on extreme-scale systems.

In this dissertation, we address three key challenges faced by a runtime system using a dynamic task parallel framework for extreme-scale computing. First, we address the challenge of integrating an intra-node task parallel runtime with a communication system for scalable performance. We present a runtime communication system, called HC-COMM, designed to use dedicated communication cores on a system. We introduce the HCMPI programming model which integrates the Habanero-C asynchronous dynamic task parallel language with the MPI message passing communication model on the HC-COMM runtime. We also introduce the HAPGNS model that enables dataflow programming for extreme-scale systems in which the user does not require knowledge of MPI. Second, we address the challenge of separating locality optimizations from a programmer with domain specific knowledge. We present a tuning framework, through which performance experts can optimize existing applications by specifying runtime operations aimed at co-scheduling of affinitized tasks. Finally, we address the challenge of scalable synchronization for long running tasks on a dynamic task parallel runtime. We use the phaser construct to present a generalized tree-based synchronization algorithm and support unified collective operations at both inter-node and intra-node levels. Overcoming these runtime challenges are a first step towards effective programming on extreme-scale systems.