Designing multi-leader-based Allgather algorithms for multi-core clusters

The increasing demand for computational cycles is being met by the use of multi-core processors. Having large number of cores per node necessitates multi-core aware designs to extract the best performance. The Message Passing Interface (MPI) is the dominant parallel programming model on modern high performance computing clusters. The MPI collective operations take a significant portion of the communication time for an application. The existing optimizations for collectives exploit shared memory for intra-node communication to improve performance. However, it still would not scale well as the number of cores per node increase. In this work, we propose a novel and scalable multi-leader-based hierarchical Allgather design. This design allows better cache sharing for Non-Uniform Memory Access (NUMA) machines and makes better use of the network speed available with high performance interconnects such as InfiniBand. The new multi-leader-based scheme achieves a performance improvement of up to 58% for small messages and 70% for medium sized messages.