bsp is a bridging model between abstract execution and concrete parallel systems. Structure and abstraction brought by bsp allow to have portable parallel programs with scalable performance predictions, without dealing with low-level details of architectures. In the past, we designed bsml for programming bsp algorithms in ml. However, the simplicity of the bsp model does not fit the complexity of today's hierarchical architectures such as clusters of machines with multiple multi-core processors. The multi-bsp model is an extension of the bsp model which brings a tree-based view of nested components of hierarchical architectures. To program multi-bsp algorithms in ml, we propose the multi-ml language as an extension of bsml where a specific kind of recursion is used to go through a hierarchy of computing nodes. We define a formal semantics of the language and present preliminary experiments which show performance improvements with respect to bsml.

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We have designed a parallel language called MULTI-ML for programming MULTI-BSP algorithms in ML. The MULTI-BSP model provides a tree-based view of nested components of hierarchical architectures. The structure and abstraction brought by MULTI-BSP allows for portable parallel programs with scalable performance predictions, without dealing with low-level details of architecture. The MULTI-ML language is essentially based on the concept of multi-functions which are recursive functions used to execute perform recursions on the nested subcomponents through the MULTI-BSP (hierarchical) architecture. In this paper we design a generic compilation scheme of the MULTI-ML language dedicated to parallel machines performing data exchanges using synchronous requests, derived from any ML compilation. This ensures that the implementation follows the semantics, allowing greater confidence in the safety of execution.