Title :
Comparing the Performance and Power Usage of GPU and ARM Clusters for Map-Reduce
Author :
Delplace, Vivian ; Manneback, Pierre ; Pinel, Frederic ; Varrette, Sebastien ; Bouvry, Pascal
Author_Institution :
Fac. of Eng., Univ. of Mons, Mons, Belgium
fDate :
Sept. 30 2013-Oct. 2 2013
Abstract :
This paper compares two parallel architectures, the GPU and the integrated ARM cluster, for the execution of map-reduce applications. The comparison targets performance and power usage. The increasing importance of energy efficiency, especially for large distributed systems - such as frequently used for map-reduce - motivates the comparison of alternative parallel architectures. Because the different hardware platforms require specific map-reduce implementations, we selected two different implementations and showed that GPU provides a better performance per watt than ARM cluster, but by less than an order of magnitude. These results indicate the great potential of ARM clusters, given the differences in hardware and software between the alternatives.
Keywords :
distributed processing; graphics processing units; parallel architectures; performance evaluation; power aware computing; ARM clusters; GPU; Map-Reduce; distributed systems; energy efficiency; integrated ARM cluster; parallel architectures; performance; power usage; Benchmark testing; Computer architecture; Graphics processing units; Hardware; Measurement; ARM Cortex A9; Energy-effiency; GPU; HPC; MapReduce; Performance evaluation;
Conference_Titel :
Cloud and Green Computing (CGC), 2013 Third International Conference on
Conference_Location :
Karlsruhe
DOI :
10.1109/CGC.2013.38