Performance evaluation of R with Intel Xeon Phi coprocessor

Yaakoub El-Khamra, Niall Gaffney, David Walling, Eric Wernert, Weijia Xu, Hui Zhang
2013 2013 IEEE International Conference on Big Data  
Over the years, R has been adopted as a major data analysis and mining tool in many domain fields. As Big Data overwhelms those fields, the computational needs and workload of existing R solutions increases significantly. With recent hardware and software developments, it is possible to enable massive parallelism with existing R solutions with little to no modification. In this paper, we evaluated approaches to speed up R computations with the utilization of the Intel Math Kernel Library and
more » ... omatic offloading to Intel Xeon Phi SE10P Co-processor. The testing workload includes a popular R benchmark and a practical application in health informatics. There are up to five times speedup gains from using MKL with a 16 cores without modification to the existing code for certain computing tasks. Offloading to Phi co-processor further improves the performance. The performance gains through parallelization increases as the data size increases, a promising result for adopting R for big data problem in the future. 
doi:10.1109/bigdata.2013.6691695 dblp:conf/bigdataconf/KhamraGWWXZ13 fatcat:vansjz4x5bddfnkae46xh4n7py