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Data pre-processing is a fundamental component in any data-drivenapplication. With the increasing complexity of data processing operations andvolume of data, Cylon, a distributed dataframe system, is developed tofacilitate data processing both as a standalone application and as a library,especially for Python applications. While Cylon shows promising performanceresults, we experienced difficulties trying to integrate with frameworksincompatible with the traditional Message Passing Interface (MPI). While MPIimplementations encompass scalable and efficient communication routines, theirprocess launching mechanisms work well with mainstream HPC systems but areincompatible with some environments that adopt their own resource managementsystems. In this work, we alleviated this issue by directly integrating theUnified Communication X (UCX) framework, which supports a variety of classicHPC and non-HPC process-bootstrapping mechanisms as our communicationframework. While we experimented with our methodology on Cylon, the sametechnique can be used to bring MPI communication to other applications that donot employ MPI's built-in process management approach.

Hybrid Cloud and HPC Approach to High-Performance Dataframes