Performance Comparison of MPICH and MPI4py on Raspberry Pi-3B Beowulf Cluster

TL;DR

This study compares the performance of MPICH and MPI4py on a Raspberry Pi-3B Beowulf cluster, demonstrating that parallel computing on low-cost hardware can outperform high-end single-core processors for certain tasks.

Contribution

It provides a practical comparison of MPI implementations on commodity hardware, highlighting the effectiveness of parallelism on affordable clusters.

Findings

Parallel programs ran faster than sequential ones.

Cluster outperformed a high-end 6500-core processor.

MPI4py and MPICH enabled effective parallel computation.

Abstract

Moore's Law is running out. Instead of making powerful computer by increasing number of transistor now we are moving toward Parallelism. Beowulf cluster means cluster of any Commodity hardware. Our Cluster works exactly similar to current day's supercomputers. The motivation is to create a small sized, cheap device on which students and researchers can get hands on experience. There is a master node, which interacts with user and all other nodes are slave nodes. Load is equally divided among all nodes and they send their results to master. Master combines those results and show the final output to the user. For communication between nodes we have created a network over Ethernet. We are using MPI4py, which a Python based implantation of Message Passing Interface (MPI) and MPICH which also an open source implementation of MPI and allows us to code in C, C++ and Fortran. MPI is a standard for writing codes for such clusters. We have written parallel programs of Monte Carlo's Simulation for finding value of pi and prime number generator in Python and C++ making use of MPI4py and MPICH respectively. We have also written sequential programs applying same algorithms in Python. Then we compared the time it takes to run them on cluster in parallel and in sequential on a computer having 6500 core i7 Intel processor. It is found that making use of parallelism; we were able to outperform an expensive computer which costs much more than our cluster.