How to Run Llama 3 405B on Home Devices? Build AI Cluster

A prediction: distributed LAN AI will soon be a normal network device, as simple as a media server to install and run. Querying your home AI instead of Alexa or Siri. Desktop integration. Hints of Tony Stsrk's Jarvis.

An interesting idea, but there's no discussion about benchmarks in the article, cpu or other hardware requirements beyond 230 GB RAM for the cluster.

It seems impractical that a home would have 4 machines with 64 gb ram that would be dedicated to a distributed system. Max, core count, 16 cores from Consumer AMD CPUs? From a cost perspective build a system with 256gb ram and AMD Epic CPU?

The only thing I can think of that pushes a need for a distributed system is multi-GPU across multiple systems.

Surely not with GPUs? Could you direct me to them please?

Unless you buy some obsolete Epyc CPU with a small number of cores, which would be slower than even one up-to-date Ryzen 9 9950X (which can beat even 32-core older Epycs in compute-limited tasks that use vector instructions), 4 Ryzen boxes with 16 cores & 64 GB ECC memory each should be significantly cheaper (probably not exceeding $6000) and also faster than one box with an Epyc CPU and 256 GB, where the CPU alone could be more expensive than the complete Ryzen systems, if bought at retail prices.

I actually happen to have in my home a cluster of five eATX cases, which stay on two adjacent IKEA metallic tables and which are connected in a ring of direct 10 Gb/s Ethernet links (i.e. they all have dual-port NICs). Therefore it is not really impractical, even if such a configuration may be infrequent.

In the distant past, I was using dual-socket Xeon or Opteron motherboards in those cases, because such MBs and CPUs were much cheaper than today. Then, by the time of Zen 1, when the Epyc CPUs were still very cheap, the upgrades have been to single-socket Epyc MBs. More recently, Epyc became much more expensive and Ryzen CPUs have much better performance per dollar, so the latest upgrades have been to Ryzen MBs. I look forward to the launch of Ryzen 9 9950X, which should double the throughput of the vector operations, 5 years after Ryzen 9 3950X (Zen 2) has done the same in 2019.

As my PC, I use an Intel NUC. Whenever I need to execute something for which that would be too weak, I launch it on one or more of the servers, by using Wake-on-LAN and shutting them down after the task is completed. In this way, my average electrical power consumption is much less than if I used a beefy desktop, while the peak performance is much higher.

There's a bit of info on the project page. It's CPU only, which is why GPU and VRAM is never mentioned: https://github.com/b4rtaz/distributed-llama

I'm using an old x99 board for my desktop currently. If I swap out the i7 with a Xeon it can take up to 512GB of ram. That would be pricey, but I could do 256 and the Xeon for under $300 total. Still a lot for a toy, and I'm sure it would be super slow...