Study of Raspberry Pi 2 Quad-core Cortex A7 CPU Cluster as a Mini Supercomputer

TL;DR

This study evaluates Raspberry Pi 2 clusters as mini supercomputers, analyzing their performance and energy efficiency, and finds that four nodes are optimal for balancing power and computing capacity.

Contribution

It demonstrates the feasibility of using Raspberry Pi 2 clusters as cost-effective mini supercomputers and provides insights into optimal cluster size based on performance and power consumption.

Findings

Adding more than four nodes does not significantly improve performance.

Power consumption increases with more nodes, limiting scalability.

Four nodes is the optimal cluster size for performance and energy efficiency.

Abstract

High performance computing (HPC) devices is no longer exclusive for academic, R&D, or military purposes. The use of HPC device such as supercomputer now growing rapidly as some new area arise such as big data, and computer simulation. It makes the use of supercomputer more inclusive. Todays supercomputer has a huge computing power, but requires an enormous amount of energy to operate. In contrast a single board computer (SBC) such as Raspberry Pi has minimum computing power, but require a small amount of energy to operate, and as a bonus it is small and cheap. This paper covers the result of utilizing many Raspberry Pi 2 SBCs, a quad-core Cortex A7 900 MHz, as a cluster to compensate its computing power. The high performance linpack (HPL) is used to benchmark the computing power, and a power meter with resolution 10mV / 10mA is used to measure the power consumption. The experiment shows that the increase of number of cores in every SBC member in a cluster is not giving significant increase in computing power. This experiment give a recommendation that 4 nodes is a maximum number of nodes for SBC cluster based on the characteristic of computing performance and power consumption.