  The bulk-synchronous parallel (BSP) model provides a framework for writing
parallel programs with predictable performance. In this paper we extend the BSP
model to support what we will call pseudo-streaming algorithms for
accelerators. We also generalize the BSP cost function to these algorithms, so
that it is possible to predict the running time for programs targeting
many-core accelerators and to identify possible bottlenecks. Several examples
of algorithms within this new framework will be explored. We extend the BSPlib
standard by proposing a small number of new BSP primitives to create and use
streams in a portable way. We will introduce a software library called Epiphany
BSP that implements these ideas for the Parallella development board. Finally
we will give experimental results for pseudo-streaming algorithms on the
Parallella platform.
