Effect of Parallelization, Execution Time and Inter-process Communication on Sorting Techniques using Message Passing Interface

Gaurav, Dev; Arora, Sahil; Gupta, Prashant

doi:10.5120/17681-8524

Cited by 1 publication

(1 citation statement)

References 9 publications

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“…There are numerous libraries in MPI, some of them are GridMPI, OpenMPI, MPICH-Madeleine, MPICH-G2, MPICH-VMI, MPICH2, LAM/MPI [2] [3]. all library of MPI have different process management but the purpose is integreted more than one computers or processors to be a single system with parallel process and establishing a portable, efficient, and flexible standard for message passing that used for writing message passing programs from node to node [4] [5].…”

Section: Introductionmentioning

confidence: 99%

Performance comparison analysis library communication cluster system using merge sort

Wulandari

Ramadhan

2018

J. Phys.: Conf. Ser.

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Abstract.Begins by using a single processor, to increase the speed of computing time, the use of multi-processor was introduced. The second paradigm is known as parallel computing, example cluster. The cluster must have the communication potocol for processing, one of it is message passing Interface (MPI). MPI have many library, both of them OPENMPI and MPICH2. Performance of the cluster machine depend on suitable between performance characters of library communication and characters of the problem so this study aims to analyze the comparative performances libraries in handling parallel computing process. The case study in this research are MPICH2 and OpenMPI. This case research execute sorting's problem to know the performance of cluster system. The sorting problem use mergesort method. The research method is by implementing OpenMPI and MPICH2 on a Linux-based cluster by using five computer virtual then analyze the performance of the system by different scenario tests and three parameters for to know the performance of MPICH2 and OpenMPI. These performances are execution time, speedup and efficiency. The results of this study showed that the addition of each data size makes OpenMPI and MPICH2 have an average speed-up and efficiency tend to increase but at a large data size decreases. increased data size doesn't necessarily increased speed up and efficiency but only execution time example in 100000 data size. OpenMPI has a execution time greater than MPICH2 example in 1000 data size average execution time with MPICH2 is 0,009721 and OpenMPI is 0,003895 OpenMPI can customize communication needs.

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Section: Introductionmentioning

confidence: 99%