- https://boinc.berkeley.edu/wiki/Computation_credit#Recent_Average_Credit

You basically need to run your rigs for weeks to be comparable as you've rightly concluded that you can get batches of "lucky" (uncalibrated) work every once in a while.

For a more fair comparison, I've outlined above a protocol that could work better. TL;DR:
- Grab the WU command line from `ps -e f` (I think it is also included in a file)
- Stop BOINC
- Copy away the slot directory of a running WU
- Run the given command line for each core (preferably from separate directories)
- Check how many decoys it produces after 8 hours (sleep && kill) and/or plot the decoy production progress on a graph as per the state/log (may need pipe through a timestamping tool or polling)
- The executables are not compatible between a Pi and a PC, but the data files and parameters should be (TODO).

This could already give a hint, but to be even more fair, you would need to repeat this for each representative kind of WU (I think there are less than a dozen of them).

I'm not at all surprised that you find a legacy desktop computer much less efficient, this can be seen from the earlier numbers, but the right kind of legacy laptop is much more competitive with an rPi4, as they usually containing high efficiency ultra low power CPUs.

- Running on a 4GB Raspberry Pi 4 - How to?
- Running Rosetta on Raspberry Pi 3B+ (how to guide)
- How to Recycle Android Phones for BOINC or Folding Rig Without Using Batteries, also runs on Amlogic Smart TV Boxes

You can actually compute an approximate performance/watt quite easily from the CPU list shared earlier in this thread and some Wikipedia or datasheet lookups for power consumption.

BOINC can run on many Android phones in the background regardless of whether you are using it or not. An aging phone from many years ago can still crank out as much RAC as a Raspberry Pi 4. It is usually set up so it only computes when it is on charger and having finished the charging cycle during the night. At the same time, phones with iOS can only compute with DreamLab while the screen is on.

As you've rightly noted that a PC is more universal and supports more projects. Although an SBC can be more power efficient credit/watt or credit/$ and could take up less space, but you will need to maintain more nodes. With the right tools and experience, this shouldn't be an issue, but you should keep this in mind.

So although we may not be able to declare a clear winner, it's good to be aware of all the options.

- Update to latest beta firmware
- Use WiFi instead of ethernet
- Don't use an enclosure or use a metallic one
- Disable unused peripherals
- Undervolt
- Underclock unused domains (TODO: underclock other things and measure the difference)
- Use an efficient SD card
- Operate the device perpendicular to the ground https://www.raspberrypi.org/blog/free-raspberry-pi-4-cooling-stand-with-the-magpi-90/

- https://www.reddit.com/r/ASRock/comments/ff2e2s/is_there_b350b450_asrock_mobo_for_am4_with/
- https://www.reddit.com/r/Amd/comments/7ur5ni/dear_am4_users_can_you_boot_without_a_gpu_and_if/
- https://forums.overclockers.co.uk/threads/asus-prime-b450m-a-or-prime-b450-plus-headless.18832054/#post-32163396
- https://www.reddit.com/r/homelab/comments/a45nk4/headless_ryzen/ebbsy16/

I guess we'll just have to try and if it won't boot, I'll grab some cheap/second hand option preferably from the non-power hungry passive kind, like a GT710 for $40, a GT210 for $15 or an Nvidia P283 for $5, though this would cost dearly in electricity, so I hope they underclock and undervolt well.

21428.9 TFlops;97.8928 GFlops/host mean;218902 host
20.34 GFlops/host median
  64915 < 5 GFlops
  10834 < 10 GFlops
  19593 < 15 GFlops
  12726 < 20 GFlops
  11298 < 25 GFlops
  10666 < 30 GFlops
   8273 < 35 GFlops
   5766 < 40 GFlops
   1993 < 45 GFlops
   2626 < 50 GFlops
   1451 < 55 GFlops
   3696 < 60 GFlops
   2406 < 65 GFlops
   1783 < 70 GFlops
   1363 < 75 GFlops
   1437 < 80 GFlops
   2547 < 85 GFlops
   1959 < 90 GFlops
   4437 < 95 GFlops
    198 < 100 GFlops
    332 < 105 GFlops
    133 < 110 GFlops
     22 < 115 GFlops
    298 < 120 GFlops
  28904 < 125 GFlops
    102 < 135 GFlops
    452 < 140 GFlops
    404 < 145 GFlops
    228 < 150 GFlops
     22 < 160 GFlops
    355 < 165 GFlops
     14 < 175 GFlops
     15 < 180 GFlops
     23 < 195 GFlops
     21 < 200 GFlops
     20 < 205 GFlops
     20 < 210 GFlops
     11 < 215 GFlops
     19 < 220 GFlops
     16 < 225 GFlops
    174 < 245 GFlops
    126 < 250 GFlops
     12 < 275 GFlops
     19 < 290 GFlops
     30 < 315 GFlops
     55 < 335 GFlops
    135 < 380 GFlops
     14 < 405 GFlops
     11 < 630 GFlops
     47 < 645 GFlops
  16686 < 830 GFlops

- more recent than 5 years
- more recent than 10 years underclocked
- more recent than 10 years portable

You could actually produce a histogram/median/average of our current fleet from this data: https://boinc.bakerlab.org/rosetta/cpu_list.php

Although I think the machine distribution is quite skewed towards the higher end compared to the general population, so it shouldn't be considered representative. Also note that computers are usually recycled after about 15-20 years of age in general, so you shouldn't see a large number of them in operation anyway.

By "only a few top notch computers" I meant that I expect them to be much less than 1% of the population according to my gut feeling.

Also, I expect that most deployed high performance computers already serve a purpose and usually couldn't offer their unused capacity for volunteer computing, as a given company made a big investment to purchase and operate them. On the other hand, there exist a vast amount of computers just sitting there all day long in businesses, schools and homes. If we assume that we are only talking about the more efficient crunchers, the benefit of their computation should far outweigh their cost in electricity.

And if you are not running 24/7 but are running BOINC in the background with low priority, it still has higher energy efficiency due to the components that are shared between a given project and the user. For example, if a user's machine idles at 30W, then the +60W CPU power cost would be less than operating a dedicated cruscher at 90W either in their own home, or in a separate lab. Thus reducing global warming, and also producing less electric waste (less servers to manufacture - less of them to dispose of).

- Gigabyte B450M DS3H Ultra Durable
- G.SKILL 16GB (2x8GB) Aegis DDR4 3000MHz CL16 KIT F4-3000C16D-16GISB
- AMD Ryzen 7 3700X AM4 BOX
- Kingmax 120GB SATA3
- FSP400-60APN 85+

- https://foldingathome.org/faqs/smp/determine-points-platform/bigadv-work-units/
- https://foldingathome.org/support/faq/points/

Over time, this resulted in people running 24/7, upgrading their boxes, and generally better equipped computers to join.

On the flip side, this caused people with less than top-notch hardware to leave or not join in the first place because they didn't feel their contribution to be competitive or valuable.

On the contrary, volunteer computing works the best if as many join as possible (up to a certain level of energy efficiency, like up to 10 years old hardware) - every little counts. We only have a few top notch 32+ cores machines with beefy GPUs around the world, but if we contributed every phone, tablet and low-mid end office machine, typically with 2-4 cores, our computing capacity could increase by orders of magnitude. (I.e., we have way less than a million hosts and there exist billions of personal computing devices in the world)

- https://boinc.bakerlab.org/rosetta/results.php?hostid=3710842&offset=0&show_names=0&state=4&appid=

We can only tell how the power efficiency of a Pi3 vs. Pi3 vs Ryzen compare if somebody posts power consumption estimates after having done every available power optimization step.

For best results, you should have an AP in each room you are placing a node in. You may consider connecting them either via cabling or by configuring them to be WDS repeaters or mesh routers, ideally on a separate backhaul band if it is dual band. OpenWrt can do all this on many cheap routers. You can get a cheap OpenWrt-capable wifi router with external antenna for $5-10, it is usually much more reliable in most use cases to spread out three of these in your house on separate channels than to try to purchase the most powerful one available.

Just for kicks, you may even experiment with building a Bluetooth piconet, Wifi P2P Direct or mesh networking between the Pi nodes as well, not sure how well its hardware is suitable for this.

- https://github.com/simondlevy/RPiAdHocWiFi
- https://medium.com/swlh/setting-up-an-ad-hoc-mesh-network-with-raspberry-pi-3b-using-batman-adv-1c08ee565165