Distributed-R was developed as an [open source project][1] by HP Labs and Vertica. By distributing data and computations across multi-core and multi-node infrastructure, it eliminates the performance and scale constraints of R. The platform includes parallel algorithms for classification, regression, clustering, ensemble modeling, and graph processing, and can be used to accelerate large-scale machine learning, statistical analysis, and graph processing.
