Efficient Implementation of Allreduce on BlueGene/L Collective Network

BlueGene/L is currently in the pole position on the Top500 list[4]. In its full configuration the system will leverage 65,536 compute nodes. Application scalability is a crucial issue for a system of such size. On BlueGene/L scalability is made possible through the efficient exploitation of special communication. The BlueGene/L system software provides its own optimized version for collective communication routines in addition to the general purpose MPICH2 implementation. The collective network is a natural platform for reduction operations due to its built-in arithmetic units. Unfortunately ALUs of the collective network can handle only fixed point operands. Therefore efficient exploitation of that network for the purpose of floating point reductions is a challenging task. In this paper we present our experiences with implementing an efficient collective network algorithm for Allreduce sums of floating point numbers.