The ”Programming with Big Data in R” project (pbdR) is a set of R packages for large scale, distributed computing and profiling. Our packages include high performance, high-level interfaces to MPI, ScaLAPACK, NetCDF4, and more. While these libraries shine brightest on large distributed platforms, they also work rather well on small clusters and often, surprisingly, even on a laptop with only two cores
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References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- Gerber, Florian; Nychka, Douglas W.: Parallel cross-validation: a scalable fitting method for Gaussian process models (2021)
- Sameh Abdulah, Yuxiao Li, Jian Cao, Hatem Ltaief, David E. Keyes, Marc G. Genton, Ying Sun: ExaGeoStatR: A Package for Large-Scale Geostatistics in R (2019) arXiv
- Christopher Paciorek; Benjamin Lipshitz; Wei Zhuo; Prabhat; Cari G. Kaufman; Rollin Thomas: Parallelizing Gaussian Process Calculations in R (2015) not zbMATH
- Lawrence, Michael; Morgan, Martin: Scalable genomics with \textttRand bioconductor (2014)