Performance evaluation of R with Intel Xeon Phi coprocessor
Performance evaluation of R with Intel Xeon Phi coprocessor
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使用英特尔至强融核协处理器的 R 性能评估
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Hui Zhang
中科院分区：
文献类型：
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作者：
Y. E. Khamra;N. Gaffney;David Walling;E. Wernert;Weijia Xu;Hui Zhang
多年来，R已被许多领域采用为主要的数据分析和挖掘工具。随着大数据对这些领域的扩展，现有R解决方案的计算需求和工作量显着增加。随着最近硬件和软件的发展，有可能在几乎不修改的情况下实现与现有R解决方案的大规模并行性。在本文中，我们评估了利用英特尔数学核心库和自动卸载到英特尔至强融核SE 10 P协处理器来加速R计算的方法。测试工作量包括一个流行的R基准测试和健康信息学中的实际应用。对于某些计算任务，使用具有16个内核的MKL而不修改现有代码，可以获得高达5倍的加速增益。卸载到Phi协处理器进一步提高了性能。通过并行化获得的性能随着数据大小的增加而增加，这是未来采用R解决大数据问题的一个有希望的结果。
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 automatic 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.