  Exascale systems, expected to emerge by the end of the next decade, will
require the exploitation of billion-way parallelism at multiple hierarchical
levels in order to achieve the desired sustained performance. The task of
assessing future machine performance is approached by identifying the factors
which currently challenge the scalability of parallel applications. It is
suggested that the root cause of these challenges is the incoherent coupling
between the current enabling technologies, such as Non-Uniform Memory Access of
present multicore nodes equipped with optional hardware accelerators and the
decades older execution model, i.e., the Communicating Sequential Processes
(CSP) model best exemplified by the message passing interface (MPI) application
programming interface. A new execution model, ParalleX, is introduced as an
alternative to the CSP model. In this paper, an overview of the ParalleX
execution model is presented along with details about a ParalleX-compliant
runtime system implementation called High Performance ParalleX (HPX). Scaling
and performance results for an adaptive mesh refinement numerical relativity
application developed using HPX are discussed. The performance results of this
HPX-based application are compared with a counterpart MPI-based mesh refinement
code. The overheads associated with HPX are explored and hardware solutions are
introduced for accelerating the runtime system.
