Comparing Energy Efficiency of MPI and MapReduce on ARM based Cluster
Jahanzeb Maqbool, Permata Nur Miftahur Rizki, Sangyoon Oh · 한국컴퓨터정보학회 학술발표논문집 · 2014
The performance of large scale software applications has been automatically increasing for last few decades under the influence of Moore’s law – the number of transistors on a microprocessor roughly doubled every eighteen months. However, on-chip transistors limitations and heating issues led to the emergence of multicore processors. The energy efficient ARM based System-on-Chip (SoC) processors are being considered for future high performance computing systems. In this paper, we present a case study of two widely used parallel programming models i.e. MPI and MapReduce on distributed memory cluster of ARM SoC development boards. The case study application, Black-Scholes option pricing equation, was parallelized and evaluated in terms of power consumption and throughput. The results show that the Hadoop implementation has low instantaneous power consumption that of MPI, but MPI outperforms Hadoop implementation by a factor of 1.46 in terms of total power consumption to execution time ratio.