  The ability to express a program as a hierarchical composition of parts is an
essential tool in managing the complexity of software and a key abstraction
this provides is to separate the representation of data from the computation.
Many current parallel programming models use a shared memory model to provide
data abstraction but this doesn't scale well with large numbers of cores due to
non-determinism and access latency. This paper proposes a simple programming
model that allows scalable parallel programs to be expressed with distributed
representations of data and it provides the programmer with the flexibility to
employ shared or distributed styles of data-parallelism where applicable. It is
capable of an efficient implementation, and with the provision of a small set
of primitive capabilities in the hardware, it can be compiled to operate
directly on the hardware, in the same way stack-based allocation operates for
subroutines in sequential machines.
