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Even though in recent years the scale of statistical analysis problems hasincreased tremendously, many statistical software tools are still limited tosingle-node computations. However, statistical analyses are largely based ondense linear algebra operations, which have been deeply studied, optimized andparallelized in the high-performance-computing community. To makehigh-performance distributed computations available for statistical analysis,and thus enable large scale statistical computations, we introduce RElem, anopen source package that integrates the distributed dense linear algebralibrary Elemental into R. While on the one hand, RElem provides direct wrappersof Elemental's routines, on the other hand, it overloads various operators andfunctions to provide an entirely native R experience for distributedcomputations. We showcase how simple it is to port existing R programs to Relemand demonstrate that Relem indeed allows to scale beyond the single-nodelimitation of R with the full performance of Elemental without any overhead.

Large Scale Parallel Computations in R through Elemental