Quotation Theußl, Stefan. 2008. Getting the Most out of your CPUs - Parallel Computing Strategies in R. Rmetrics Workshop, Meielisalp, Schweiz, 28.06.-02.07.




Facing complex models in finance one has to consider to take advantage of parallel computing. With the availability of multicore architectures even in commodity computers there is an increased demand for practical strategies for utilizing these architectures. Generally there are two different types of architectures: shared memory systems and distributed memory systems. Each of which has its advantages and disadvantages which have to be considered when creating parallel applications. In this talk we present cluster@WU, a cluster of workstations employed at the Wirtschaftsuniversit at Wien, and how it is utilized to solve computational problems. Furthermore, we present strategies for parallelizing programs using different packages available in R. On the basis of an example in numerical algebra we illustrate how both hardware architectures can be used to achieve higher performance: For distributed memory systems such as clusters of workstations we show how MPI can be used to explicitly parallelize a program. For shared memory systems OpenMP can improve the performance of a sequential program by implicit (compiler-driven) parallelization. Finally, we present results of a benchmark experiment comparing the presented parallel routines with their sequential counterpart.


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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Paper presented at an academic conference or symposium
Language English
Title Getting the Most out of your CPUs - Parallel Computing Strategies in R
Event Rmetrics Workshop
Year 2008
Date 28.06.-02.07
Country Switzerland
Location Meielisalp
URL http://www.rmetrics.org/


Theußl, Stefan (Details)
Institute for Statistics and Mathematics IN (Details)
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