- Visão geral
Speaker: Drew Schmidt, University of Tennessee
So it would seem that R is here to stay, including on the cluster. Unsurprisingly, in the age of big(ger) data, statisticians, scientists, and all other analyzers of data are increasingly finding themselves in the need of high-performance computing (HPC) resources. When they need to move to small campus clusters, national resources for supercomputers, or the cloud, they want to bring R with them. However, R was built with the desktop, not the cluster, in mind. To address this, the open-source R community is steadily developing solutions to transform R from merely being a "high productivity" language, into a legitimate high-performance language. These external packages enhance R computations to use multithreaded and compiled kernels, access coprocessor cards like GPUs and the Intel® Xeon Phi™ coprocessors, and even elevate R to large distributed resources, living atop technologies like message-passing interface (MPI) and Apache Spark*.
This talk explores the package's landscape, and describes the history of R's usage on HPC resources, as well as the current state of the art.