Well from what I can see the faster one also has 3D V-cache, so not apples to apples.

That said, at such low core count the primary Epyc advantage is PCIe lanes no?

This is certainly interesting, and is something I often wonder about. In our case we mostly run Kubernetes clusters on EX130 servers (Xeon, 24c, 256GB). In this situation there are a lot of processes running, for which increased cores-count and memory availability seems worth it. Particularly when we have the cost of 10-25g private networking for each server, lower node counts seems to come out being more economical.

But, but with fewer processes I can totally believe this works out to be the better option. Thank you for the write-up!

> Once network IO became the main bottleneck, the faster CPU mattered less.

It is surprisingly hard to keep a modern CPU core properly saturated unless you are baking global illumination, searching primes or mining crypto currency. I/O and latency will almost always dominate at scale. Moving information is way more expensive than processing it.

AMD’s fastest consumer CPUs are a great value for small servers. If you’re doing just one task (like in this article) the clock speed is a huge benefit.

The larger server grade parts start to shine when the server is doing a lot of different things. The extra memory bandwidth helps keep the CPU fed and the higher core count reduces the need for context switching because your workloads aren’t competing as much.

The best part about the AMD consumer CPUs is that you can even use ECC RAM if you get the right motherboard.

Consumer grade CPUs aren't meant to be pushed with heavy load 24/7, meaning, durability becomes another variable which, in my experience, will quickly outweigh the brief burst of speed.

As a consumer who nursed an overclocked 1080ti along for 2.5 gens longer than I would've liked thanks to crypto and then AI, I was reading this fearing a positive conclusion - thinking "Oh great, just when it's time to upgrade my 5600x CPU data centers will start driving up already over-priced consumer CPUs too."

Although said somewhat tongue in cheek, it has been a rough several years for tech hobbyist consumers. At least the end of Moore's law scaling and the bite of Dennard scaling combined to nerf generational improvements enough that getting by on existing hardware wasn't as nearly as bad as it would've been 20 yrs ago.

Now that maybe the AI bubble is just starting to burst, we've got tariffs to ensure tech consumers still won't see undistorted prices. The silver lining in all this is that it got me into retro gaming and computing which, frankly, is really great.

If you are running engineering jobs (HPC) like electrical simulation for chip design the only two thingd you care about are the CPU clock speed and memory RW speed.

It's unfortunate that we can only have 16 core CPUs running at 5+ GHz. I would have loved to have a 32 or 64 core Ryzen 9. The software we use charge per core used, so 30% less performance is that much extra cost, which is easily an order of magnitude higher than a flagship server CPU. These licenses cost millions per year for couple 16 core seats.

So, at the end, CPU speed is determining how fast abd economically chips are developed.

Unfortunately, the page's numbers are represented in a sloppy way. A benchmark number with a dollar sign. Different job counts. Lacking documentation. I wouldn't trust this data too much.

*Do

How can I make sure that each github runner uses exactly one cpu core?