Raspberry Pi Cluster

A Raspberry Pi cluster is a collection of Raspberry Pi single-board computers networked together to create a low-cost, energy-efficient computing cluster. These clusters are excellent for learning distributed computing, parallel processing, and cluster management.

Overview

Our Raspberry Pi cluster provides a platform for:

  • Distributed computing experiments
  • Container orchestration (Docker, Kubernetes)
  • Parallel processing tasks
  • Educational projects in cluster computing
  • Testing scalable applications

Cluster Specifications

Hardware Configuration

Nodes

  • Number of Nodes: 40
  • Model: Raspberry Pi 4 Model B
  • CPU: ARM Cortex-A72 (4 cores) @ 1.5GHz per node
  • Total CPU Cores: 160 cores (40 nodes × 4 cores)
  • RAM: 8GB per node
  • Total RAM: 320GB (40 nodes × 8GB)
  • Storage: 32GB microSD card per node
  • Total Storage: 1.28TB (40 nodes × 32GB)

Networking

  • Network Switch: TBD
  • Connection: Gigabit Ethernet
  • Topology: Star topology with central switch

Power Supply

  • Type: 12V 20A × 2 units
  • Total Power: 480W (2 × 12V × 20A)
  • Power per Node: 5V/3A USB-C (converted from 12V)
  • Max Power Consumption: ~15W per node
  • Total Max Consumption: ~600W (40 nodes × 15W)

Software Stack

Operating System

  • OS: Raspberry Pi OS (64-bit) or Ubuntu Server
  • Kernel: Linux ARM64

Container Platform

  • Docker: For containerized applications
  • Kubernetes: For container orchestration (k3s or MicroK8s)

Cluster Management

  • Cluster Manager: TBD (Kubernetes, Docker Swarm, or custom)
  • Monitoring: Prometheus + Grafana (optional)

Use Cases

1. Distributed Computing

  • MapReduce implementations
  • Parallel processing tasks
  • Scientific computations

2. Container Orchestration

  • Kubernetes cluster for microservices
  • Docker Swarm for container management
  • CI/CD pipeline testing

3. Educational Projects

  • Learning cluster architecture
  • Distributed systems coursework
  • Network programming experiments

4. Web Services

  • Load-balanced web applications
  • Database clusters (MySQL, PostgreSQL)
  • Message queue systems (RabbitMQ, Kafka)

Getting Started

Accessing the Cluster

Access instructions to be added

Basic Commands 

# SSH into the master node
ssh pi@cluster-master.local

# Check cluster status
kubectl get nodes

# View running pods
kubectl get pods --all-namespaces

# Deploy an application
kubectl apply -f deployment.yaml

Resources

Documentation

Tutorials

  • Building a Raspberry Pi cluster from scratch
  • Setting up Kubernetes on ARM
  • Distributed computing with MPI

Maintenance

Regular Tasks

  • Update system packages
  • Monitor node health
  • Check network connectivity
  • Backup configurations

Troubleshooting

  • Node offline: Check power and network connections
  • Performance issues: Monitor CPU and memory usage
  • Network problems: Verify switch configuration

Future Enhancements

  • Add more nodes to increase capacity
  • Implement distributed storage (Ceph, GlusterFS)
  • Set up monitoring dashboard
  • Install GPU accelerators for ML workloads
  • Configure automated backups

Contact

For questions or issues with the Raspberry Pi cluster, please contact the lab administrator.