Study of Raspberry Pi 2 quad-core Cortex-A7 CPU cluster as a mini supercomputer

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. Today's 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.

Towards Testbed as-a-Service: design and implementation of an unattended SoC cluster

“…There are different approaches in literature for building a Raspberry Pi cluster, indeed the low realization and operational costs make it usable for learning parallel computing [1], [2], run distributed algorithms [3], [4] or just for studying the energy and the computation power system [5], [6], [7].…”

“…Concluding, [5] studies a Raspberry Pi cluster as a highperformance computing (HPC) cluster, considering the computing and the electric power the work provides performance results regarding the number of cores and the number of computing nodes in a cluster.…”

“…Table II shows the Bill of Materials (BOM) of the board, it can be used for ordering the components from the supplier 5 . The components are: the 24pin female connector, two fan ports, two 4pin peripheral power connectors and eleven generic bipole clamps.…”

Leveraging teaching on demand: Approaching HPC to undergrads

“…Of course, production HPC clusters are not based on Raspberry Pi, but more powerful components, although there exist actual low-cost energy-aware clusters based on these devices [6,7,8]. However, in rough outlines, there exists straightforward parallelism between what students can observe when building the cluster employing these simpler devices and what forms actual HPC supercomputers that allows learning the HPC basics [9,10]. The similarities and differences between production HPC clusters and Raspberry Pi based clusters are explained to students along the course.…”

HPC as a Service: A naïve model

“…The architecture presented built an HPC platform by providing a group of nodes that were booted with a desired HPC environment bypassing the virtualization layer by employing technologies like Wake-on-LAN and network booting with the specific functionality of starting, scaling and terminating the computer cluster. In 2016 Abrrachman Mappuji et al [4] presented a utilization of multiple Raspberry pi 2 SBCs as a cluster to compensate its computing power. The findings were that the increase in every SBC member in a cluster is not necessarily a measure for a significant increase in computational capabilities, and also recommending that 4 nodes are a maximum for an SBC cluster; based for optimum power consumption.…”