[floren]

The thing to keep in mind about supercomputers is that they are designed for particular applications. Nuclear weapons simulation, biological analysis (can we run simulations and get a vaccine?), cryptanalysis. These applications are usually written in MPI, which is what coordinates communication between nodes.

If you want to play with it at home, connect those laptops to an ethernet network and install MPI on them both--you should be able to find tutorials with a little web searching. Then you could probably run Linpack if you felt like it, but if you wanted to learn a little more about how HPC applications actually work, you could write your own MPI application. I wrote an MPI raytracer in college; it's a relatively quick project and, again, you can probably find a tutorial for it online.

Edit: Your cluster is going to suck terribly in comparison to "real" supercomputers, but scientists frequently do build their own small-scale clusters for application development. The actual big machines like Sequoia are all batch-processing and must be scheduled in advance, so it's a lot easier (and cheaper, supercomputer time costs money) to test your application locally in real-time.

[gnufx]

Summit and Sierra, for instance, actually run a fair range of applications fast, though Sierra is probably targetted mainly at weapons simulation-type tasks. A typical HPC system for research, e.g. university or regional, has to be pretty general purpose.

[timthorn]

Step by step instructions for building an Arm-based MPI cluster using Raspberry Pis: https://epcced.github.io/wee_archlet/