Does this method your demonstrating using the MPI library allow these RPi's to combine system resources ? I know you said that it sees 4 Pi's = 16 Cores , does it also pool the RAM ? Assuming the answer to both those questions are yes , can you still enable ZRAM within the cluster ? When compiling programs on the Pi it tends to hit swap after a point , ZRAM allows the Pi to swap to the RAM instead of the MicroSD (im sure you familiar). I would want to use a setup like this for compiling , does this cluster configuration help me in that regard ? Thanks Gary .

I suggest another rack with fan kit: www.amazon.com/dp/B07MW24S61 and for the UK: www.amazon.co.uk/dp/B07J9VMNBL

Hello Gary, I would like to thank you for making this video and maintaining such an informative channel. you are very easy to listen to and your explanations are to the point. Keep up the good work. Today was the first day i saw your channel link and decided to give it a go. the raspberry pi is a great pltform. However the raspberry PI Zero is a very compact development board as well. The Pi Zero does not have the compute power of the big pi. however the integration of the wifi on the board makes it one of my favorites. I built a super computer using the PI Zero as the main board. I loaded each PI with aversion of Windows 2008 data Center Server. I used RUFUS to flash 64 GB microSD cards with the OS. Once i had the OS working I cloned it using tis program... clonezilla.org/clonezilla-SE/ I have a multi-slot microSD card reader. It holds 24 microSD cards and connects via usb 3.1. I installed teh Windows 2008 Data Center Server on the microSD cards in about 15 minutes. Windows Server 2008 Data Center can cluster up to 32 machines processors at once. The Windows platform is very stable yet it is a little large. About 3 GB on each microSD. I used the data center server services to aggregate all the Raspberry PI processors and resources. i used the Wifi on each chip to bridge them all together. I only spaced them about 1/2 inch apart. The network and teh data processing is so fast that it returns almost instantly. I mainly use the cluster just to browse the web and play games. It is absolutely over kill on any kind of gaming or graphics program. I set the paging file on all the drives to 512 initial max 4096. I also connected an external 3.0 6 TB hard disk to the USB mini on one of the PI. Number 32 in the cluster. Then all teh data i download goes thru the other 31 and passes down stream directly to the external like a funnel. I can download a 4K movie in about 55 seconds with my AT&T fiber. I thought you might be interested in looking at this flavor of PI super computer. Of course i have Python, PHP 7.2 and AMPPS installed on the cluster. Automatic load balancing and wifi VLAN tagging. The windows 2008 server data center can open up a whole venue of new and powerful applications you may be interested in

@@kevindeng1889 hi

@@eg3730 hi

But if every desktop computer is a supercomputer…

@@SS-ARYAN then we can only dream bigger, my guy 😎

considering the physical limitations of transistors, the only way to turn a single device into a supercomputer is through the cloud.

Guessing you have that 4 year bachelor's degree and you're referring to it aren't you?

No. Just no.

I know you're trying to compliment the video (maybe inflate the audience's ego?) but I think your university ripped you off...

the university teaches you in more detail and less effort. this video is less in detail (in a nutshell)

@@infinity5288 Less in detail with more effort put into explaining the detail. I would say that teaches more, because the less effort put in, the less that you get your point understood, therefore you teach LESS because it is not taught, just stated.

So this video is misleading? 🤔

@@hammercanttouchthis it was a nice simple example.

It depends on the problem you're trying to solve. If the problem you're trying to solve requires minimal network bandwidth(small inputs and outputs) but requires a large amount of CPU processing time... Then the older pi's will work just fine.

@@hammercanttouchthis It was obviously a demo of a theory of clustering put to practise, not a video about optimisating data bandwidth and latency.

I agree... He is very good at the explanation and easy to listen to.

Watch tech quickie on yt

@@falcondarkshadow8711 agreed linus and the gang really do good job there

@@philh98 definitely

WOW!

Yeah, even the chips you find in those musical birthday cards have more computing power than all the Allied Forces put together did in WW2. It's crazy.

@@AbhinavSubramanian but we went to the moon on that power?

@@dashboy007 even your current computer/laptop/phone no matter the model is still many times more powerful than the greatest computers of the ones used for the first few moon landings

@@bnbnism I was trying to be sarcastic. There is no way my phone today could power anything else but itself, let alone a rocket ship.

MARK!!

Wow, thank you!

What version of DOS did it run on? And did you mean it ran on the IBM PC or XT? :)

@@hammercanttouchthis By that time, 1991? I was running it mostly at work on IBM XTs running MSDOS 3.3 or later, as i recall because we had 3.5 inch floppies. The entire programming environment and game fit on a single diskette. It was only 10,000 lines of QuickBASIC code. I never released it to the public, but I had one other friend who was interested in programming who liked writing R-code for the warbots.

Reminds me of Robot Wars. My friend and I had a blast programming our robots to pummel each other in the ring.

Yeah, I agree that would be interesting. In fact building different clusters from various bits of historical and new hardware and then benchmarking them would be quite interesting, but alas very time consuming!

@@GaryExplains my master thesis where done in the early 90:es, and it was about creating dynamic computing clusters using heterogeneous computers (various hardware architectures at the time). Given the overall limitations we identified types of problems which could scale using the available technique. Great fun and on the cutting edge for it's time. The main benefit was that the computer clients connected where largely unaware that they committed computing cycles, the jobs was running int the background. The base was done in pvm, in many aspects the successor to mpi.

Glad you think so!

PCIe doesn't act super friendly all the time. It's probably better using InfiniBand cards

@@NoorquackerInd Well if you're going to use a comm card, it would be a lot easier to put a ten Gb network card in the pcie slot. I was just thinking to keep costs down, you could try to run the messages over just the pcie lanes.

Processing wise yes because you would end up with around 3.6 ghz of processing power for 130 dollars wich is a good deal Idk whether it would be effective though because of the low power gpu the pi has

And would disabling the Desktop interface from raspi-config increase the performance?

@@0lAlex0 heck yes. You'd have gained about a 20% performance increase. The GUI is a beast.

But the demo video would suck

Because he doesn't actually want to calculate prime numbers as efficiently as possible, he just wants to make a video about cluster nodes lol.

@@YouArentValid Yeah, this struck me as one of those "I need content for my channel" videos. I'll bet he took it from a howto found on the Interwebs too? Plus, it's been done to death already.

That was done with the PS3.

Yup, that was a project that the US Military did because the PS3s had a lot of cores in a relatively compact form. It made being able to source machines from around the world really eaay.

No, unfortunately I am not going to SciPy.

You can use different models but beware that if you sent the same load to each node then the slower nodes will take longer to complete.

Loren Sims does each node have to match the rest, or can any machine get added to the array?

I have a friend who uses a Pi with a laser cutter and with a 3D printer, so I guess the answer is yes, with caveats about models, interfaces, drivers, etc.

raspi's aren't really powerful enough to make this useful or scalable, but there's probably a researcher or two somewhere out there using an SBC cluster made from more expensive boards, especially ones that support PCIe.

@@AmeshaSpentaArmaiti ok I see, thank you! So with pis it really is just a theoretical exercise. Shame, since I have a few, but they're good for lots of things!

I used the standard Raspberry Pi 3 Model B+

@@GaryExplains thanks! I am purchasing a kit and wondered if you have any recommendations. Great video!

The Pi is great because of the price. You can get started relatively cheaply. If are you a looking for a way to learning MPI and other technologies like Docker and Kubernetes on a cluster then this kind of setup is great. HOWEVER, performance is an issue. If you want actual results, to run actual projects etc, then you will need to look at better hardware. But that costs more money!

Boyd McKay the Raspberry Pi is made by the Raspberry Pi Foundation, www.raspberrypi.org. The Raspberry Pi 4 was released right when this video was posted and is the current model as I write this. It is what you would want. Most people looking to use it for computing tasks like this (vs maker/electronics projects) are going for the model with 4GB of memory, vs the 2GB model. In addition to the distributed processing demonstrated in this video, for home use, they're great Docker containers and similar applications. They're available from many online retailers.

That would be pointless, because unless your doing instense audio processing, there would be no point in having a dedicated audio pi, and just one pi is not enough to do much video editing on, and at that point what would your third be used for if not everything else?

It is python code written for clusters. You can find it on my GitHub page. Link in the description.

@@GaryExplains I didn't find it, but I'll look closer. Thanks again ;)

WTF in front of my eyes XD

They do return the values.

Glad you liked it!