Development effort and performance trade-off in high-level parallel programming

Research on high-level parallel programming approaches systematically evaluate the performance of applications written using these approaches and informally argue that high-level parallel programming languages or libraries increase the productivity of programmers. In this paper we present a methodology that allows to evaluate the trade-off between programming effort and performance of applications developed using different programming models. We apply this methodology on some implementations of a function solving the all nearest smaller values problem. The high-level implementation is based on a new version of the BSP homomorphism algorithmic skeleton.