Turn Your Raspberry Pis Into a Mini-Supercomputer

A computing cluster may be used to train AI algorithms, model complex physical phenomena, render 3D animations, and perform many other computationally intensive tasks. The systems used in these cases are very powerful and very expensive, which makes them inaccessible to most people. Unfortunately, this makes it impossible for a hobbyist to tinker around with them and educate themselves about the technology at home.

But if you think smaller, you actually can experiment with computing clusters right in your own workshop. A common way to build a multi-node cluster at home is with Raspberry Pi boards or other single-board computers. You won’t have a massive amount of computing power at your disposal, but spinning up four or more machines is relatively inexpensive. Most importantly, the same basic principles and tools are used on more powerful clusters, giving you important insights into how they operate.

If you’re looking for some guidance to get started, Jeff Geerling has just detailed the construction of a Raspberry Pi cluster. It’s not necessarily going to amaze you with its raw computing power, but it is perfect for learning and experimentation.

Geerling’s cluster is built around the DeskPi Super4C, an ITX-sized carrier board designed specifically to host multiple Raspberry Pi Compute Modules. In this case, the cluster uses four Raspberry Pi Compute Module 5 units, each equipped with 16GB of RAM. Combined, that gives the system a respectable 64GB of memory — plenty for experimenting with distributed workloads and parallel processing techniques.

Each compute node is equipped with dual networking options: a 2.5 Gigabit Ethernet connection routed through USB 3.0, and a separate 1 Gigabit Ethernet port tied directly to the module’s native controller. This dual-network setup enables flexible experimentation with network configurations.

Each node supports NVMe SSDs via M.2 slots, along with more traditional MicroSD cards and USB boot options. Adding to its server-like capabilities, the board includes an ESP32 microcontroller that allows remote power management of each node over Wi-Fi — similar to enterprise-grade systems with built-in management controllers.

The cluster is housed in an aluminum rack enclosure with a distinctive ventilated design, giving it both a professional appearance and practical airflow. During testing, passive cooling proved insufficient under heavy loads, prompting the addition of a 120mm fan to maintain performance and prevent thermal throttling.

To enhance portability, Geerling incorporated a small uninterruptible power supply (UPS) into the build. This allows the cluster to remain operational even when unplugged briefly, making it easy to transport without shutting down running processes.

On the software side, each node runs Raspberry Pi OS, with cluster-wide management handled by automation tools like Ansible. This enables synchronized updates, command execution, and system control across all nodes from a single interface.

Performance-wise, the system achieves around 140 gigaflops on the High-Performance LINPACK benchmark while consuming roughly 70 watts of power. While that pales in comparison to modern desktop systems, the real value lies in accessibility. For enthusiasts and learners, this tiny “supercomputer” offers a hands-on introduction to the same distributed computing concepts used in the world’s most powerful machines.