  We present DASH, a C++ template library that offers distributed data
structures and parallel algorithms and implements a compiler-free PGAS
(partitioned global address space) approach. DASH offers many productivity and
performance features such as global-view data structures, efficient support for
the owner-computes model, flexible multidimensional data distribution schemes
and inter-operability with STL (standard template library) algorithms. DASH
also features a flexible representation of the parallel target machine and
allows the exploitation of several hierarchically organized levels of locality
through a concept of Teams. We evaluate DASH on a number of benchmark
applications and we port a scientific proxy application using the MPI two-sided
model to DASH. We find that DASH offers excellent productivity and performance
and demonstrate scalability up to 9800 cores.
