Toward Performance Prediction for Multi-BSP Programs in ML.

bsml and multi-ml are functional parallel programming languages “a la ml ” based of the respectively the bsp and multi-bsp bridging models. multi-bsp extends bsp to take into account hierarchical architectures. For both models, it is possible to predict the performances of algorithms thanks to embedded cost models. To do so, we propose formal operational semantics with cost annotations for the two aforementioned languages. This work has been done in a incremental manner. First we recall the cost semantics of core-ml language. Then, we adapt it to bsml and then to multi-ml. It is then possible to evaluate the cost of a program following the annotated semantics. Finally, we compare the theoretical approach with the current implementation on a code example.