The performance of collective communication operations determines the overall
performance of MPI applications. Different algorithms have been developed and …

In recent years, the training requirements of many state-of-the-art Deep Learning (DL)
models have scaled beyond the compute and memory capabilities of a single processor …

Exascale supercomputers have renewed the exigence of improving distributed
communication, specifically MPI collectives. Previous works accelerated collectives for …

Most distributed-memory bulk-synchronous parallel programs in HPC assume that compute
resources are available continuously and homogeneously across the allocated set of …

MPI collective communication is an omnipresent communication model for high-
performance computing (HPC) systems. The performance of a collective operation depends …

Julia has quickly become one of the main programming languages for computational
sciences, mainly due to its speed and flexibility. The speed and efficiency of Julia are the …

The performance of collective operations has been a critical issue since the advent of
Message Passing Interface (MPI). Many algorithms have been proposed for each MPI …

According to recent performance analyses, MPI collective operations make up a quarter of
the execution time on production systems. Machine learning (ML) autotuners use supervised …

Collective communication operations, such as Broadcast or Reduce, are fundamental
cornerstones in many high-performance applications. Most collective operations can be …

MPI collective communications play an important role in coordinating and exchanging data
among parallel processes in high performance computing. Various algorithms exist for …