How to Make a Raspberry Pi Cluster Function as a Unified Computer

Creating a Raspberry Pi cluster that acts as a single computer leveraging the power of all nodes involves setting up a distributed computing environment. Here are the key steps to achieve this goal:

Hardware Setup

Raspberry Pis: Gather multiple Raspberry Pi units, such as Raspberry Pi 4. These will serve as the computational nodes in your cluster. Networking: Connect all Pis to the same local network, preferably via Ethernet to ensure better performance. Power Supply: Ensure each Pi has a stable power source to avoid any potential issues during the operation.

Operating System

Install a compatible OS on each Raspberry Pi. Raspbian Raspberry Pi OS is commonly used. Ensure all Pis are updated:

sudo apt update  sudo apt upgrade

Cluster Software

To make the cluster function as a single unit, you can use clustering software. Here are a few options:

MPI (Message Passing Interface): Install MPI: Use OpenMPI or MPICH for parallel programming. Write MPI Programs: Develop programs that utilize MPI to distribute tasks across the cluster. Kubernetes: While you mentioned avoiding containers, Kubernetes can orchestrate containerized applications effectively, allowing resource sharing and management. If you prefer not to use containers, you can skip this option. Beowulf Cluster: Set up a Beowulf cluster using software like MPICH or OpenMPI. This setup allows multiple Pis to work on the same task simultaneously. Configure the hosts file to recognize all nodes in the cluster.

Networking Configuration

Static IPs: Assign static IP addresses to each Pi for easier communication. SSH Access: Set up SSH keys for passwordless access between nodes. This simplifies managing multiple Pis and enhances efficiency.

ssh-keygen
ssh-copy-id 

Job Scheduling

Use job schedulers like SLURM or Torque to manage workloads across the cluster. Install the scheduler and configure it to recognize all nodes:

Testing the Cluster

Run a simple MPI program to test communication between nodes. For example, you can use the following code:

/* hello_mpi.c */
#include mpi.h
int main(int argc, char *argv) {
MPI_Init(argc, argv);
int world_rank;
MPI_Comm_rank(MPI_COMM_WORLD, world_rank);
MPI_Finalize();
printf(Hello from node %d
, world_rank);
}

Compile and run on all nodes:

mpicc hello_mpi.c -o hello_mpi
mpirun -np 4 -host pi1-ip pi2-ip pi3-ip pi4-ip ./hello_mpi

Resource Management

Monitor resource usage across the cluster using tools like htop or Glances to ensure efficient operation. This helps in identifying bottlenecks and optimizing performance.

Conclusion

By following these steps, you can effectively set up a Raspberry Pi cluster that operates as a single unit, allowing you to harness the combined power of all nodes for parallel processing tasks. The key is to use the right software tools and ensure proper configuration and networking.