Those 8 pis have all their hardware, though. The Ryzen needs all the rest of the hardware to finish off the computer.

Well, he also needed to add a cooler and a bunch of tubes & eight mounts to get coolant running on each Pi, eight ethernet cables, eight power cables, a power supply with enough outputs, a 16-port ethernet switch, and (correct me if I'm wrong) eight SD cards, if only to store a bootloader that can do pxe.

So eight Pies alone do not make a complete cluster, just as one Ryzen alone does not make a complete computer. A few times eight times cheap can turn out to be quite expensive, depending on how much cheap actually is.

I haven't paid much attention to component prices recently but my rule of thumb for budget builds is to start with $80 for each component that isn't a GPU or CPU. Go with stock cooler, grab 80 for PSU, 80 for mobo, 80 for RAM, 80 for storage, see where you end up. In the same ballpark, but the real computer will pack a whole lot more punch (even if you had less RAM total).

Jeff Geerling did a blog post[0] and video (series) on this very thing a while ago that goes into some of the hardware and costs. Whilst the costs can be negligible, it looks like a hella lot of fun!

[0] https://www.jeffgeerling.com/blog/2020/raspberry-pi-cluster-...

Don’t forget this quote from that page:

> It's slightly more cost-effective and usually more power-efficient to build or buy a small NUC ("Next Unit of Computing") machine that has more raw CPU performance, more RAM, a fast SSD, and more expansion capabilities.

But is building some VMs to simulate a cluster on an NUC fun?

I would say, "No." Well, not as much as building a cluster of Raspberry Pis!

---

You don’t build a RPi cluster for speed or cost or efficiency. You do it because it’s fun. And that’s okay.

2GB pi starts at $35 at actual Raspberry Pi distributors, 4GB at $55, although there will probably be added shipping cost.

Yeah, nice. I just assumed Amazon is representative of what most people would end up paying for them.

For my region, the actual distributors start at 44 EUR for 2GB and 64 EUR for 4GB.

Would it though? The cluster has more cores (each PI4 has a quad core), so for certain workloads it seems like it could realistically beat a single 8-core with higher clocks.

As always, a benchmark is the only thing that will prove it.

It absolutely would. These cores are in a completely different class.

If you care about benchmarks, a Pi4 will score around 200 points (1 core) or 550 points (4 core) at 1.5GHz on GB5. At 2GHz you can reach around 700 points multi-core.

Ryzen 2700 will easily go above 6000 points in multi-core bench without overclocking.

So even in a theoretical, embarrasingly parallel workload with minimal sharing between cluster nodes, the Zen will be faster than eight pies. It's not even a contest if you also need some I/O, shared memory, or heavy SIMD.

Where are you getting these "points" from? Without a real world benchmark I don't see why you're so confident about this.

The video in the OP showed 8 pis, and assuming 4 cores each that's 32 cores total.

A raytracing benchmark would be interesting because you could divide the work up-front and not have to worry about communication between nodes in the cluster, and each node doesn't need that much memory.

Maybe the ryzen 2700 beats the 8 PI cluster, but clearly there's an X number of PIs that will beat the ryzen. Maybe it's X = 10 PIs, or 20, or 200? Idk, but it could also just be 8. There's no way to know for sure without a benchmark.

GB5 = Geekbench 5. It is a real world benchmark.

In terms of computer per dollar yes. In terms of compute per joule, no.

I don't think that's true either. You can get 8-core desktop Ryzen parts that have a TDP of 65 watts. I have a passively cooled 8-core Ryzen system that uses a 240 watt power supply.

Also: by the time you've wired up 8 raspis you end up using quite a bit of power just to connect them all together with a switch.

Raspberry Pi 4s need a maximum of 15 watts each. So 120 watts just for the computers. Even if you discount the power consumption of the switch, my 240 watt Ryzen computer is still going to beat that joule-for-joule.

Edit: one more thing, that 240 watt system also powers a 75 watt GPU, so it's definitely more wattage than really required for the CPU alone.

You're calculating the raspi 4 power consumption based off of recommended USB power supply current rating. The actual expected load power consumption without peripherals is 1/5 to 1/3 of that (3-5 W rather than 15 W).

https://www.raspberrypi.org/documentation/hardware/raspberry...

https://www.pidramble.com/wiki/benchmarks/power-consumption

https://raspi.tv/2019/how-much-power-does-the-pi4b-use-power...

You can just undervolt the Ryzen and it will still run cycles around the Raspberry Pi while consuming less power if you are into that sort of thing.

That is not true. The energy efficiency will go down if you downclock because the static to dynamic power ratio will increase.

static to dynamic power ratio isn't efficiency though (and static power in modern desktop chips is tiny compared to the dynamic power). The dynamic power is not linearly related to processing speed (in fact it's much worse). If you downclock and undervolt a ryzen processor it will use much less power than the decrease in speed (e.g. from stock, if you drop performance by ~20% you might get a ~40% power decrease). Obviously at a certain point you will start to get worse again but most chips are not at peak performance/watt at their stock settings because raw performance and performance/cost also matters.

That scaling has a limited range before static power becomes dominant. Compute efficiency is compute / energy (total power * time). Total power includes static power. An SBC pulls far less from the wall than an x86 desktop could ever hope to when calculating the first million digits of pi.

As an example: even if I halted my desktop at 0 MHz and it still magically took the same time to calculate the first million digits of pi as a raspberry pi, it still would be using far more power.

Static power ratio is increasing in modern processing nodes, to the point where a "rush to idle state" strategy starts to make sense because you can power down subsystems in idle states but you can't do that if you lower processing speed. The tradeoff would of course be different in a chip that was architecturally designed from the ground up for low-performance use, but that would be from things other than just a lower frequency for the same chip.