Title :
Tight Coupling of R and Distributed Linear Algebra for High-Level Programming with Big Data
Author :
Schmidt, Dan ; Ostrouchov, George ; Wei-Chen Chen ; Patel, Pragati
Author_Institution :
Remote Anal. & Visualization Center, Univ. of Tennessee, Knoxville, TN, USA
Abstract :
We present a new distributed programming extension of the R programming language. By tightly coupling R to the well-known ScaLAPACK and MPI libraries, we are able to achieve highly scalable implementations of common statistical methods, allowing the user to analyze bigger datasets with R than ever before. Early benchmarks show great optimism for the project and its future.
Keywords :
distributed programming; linear algebra; message passing; programming languages; statistical analysis; MPI library; R programming language; ScaLAPACK library; big data; distributed linear algebra; distributed programming; high-level programming; message passing interface; statistical method; Big data; Distributed computing; Large scale analytics; MPI; R; ScaLAPACK;
Conference_Titel :
High Performance Computing, Networking, Storage and Analysis (SCC), 2012 SC Companion:
Conference_Location :
Salt Lake City, UT
Print_ISBN :
978-1-4673-6218-4
DOI :
10.1109/SC.Companion.2012.113
