It's not cheap, but it's efficient. At least, that's my hope.
Over the past few months, I worked with a number of vendors to assemble what I hope will make an efficient but high-performance arm64 NAS. In the video embedded below, I've put together the following (some of these links are affiliate links):
This is the fastest Arm desktop in the world, yes, even faster than the M2 Ultra Mac Pro. And today, I made it even faster.
I upgraded everything: Faster RAM, 128 core CPU, 40 series GPU, I did it all, and we'll see how much we can obliterate the M2 Mac Pro.
128 cores—that's five times more cores, I'm also going to upgrade this thing from 96 all the way to 384 gigabytes of RAM. The Mac Pro? Sorry, it only goes up to 192.
And we're just in time for the new Cinebench 2024 benchmark, which—yes—this machine dominates.
I'm testing Adlink's Ampere Altra Developer Platform. This machine has a 96-core Arm CPU, but now they sell a 128-core version. Apple also recently released the M2 Ultra Mac Pro, so the model I'm testing isn't the "fastest in the world" like I could boast a couple months ago... but it's close, and I actually doubled my performance from last time—I'll show how later.
If you're tired of waiting for Apple to migrate its Mac Pro workstation-class desktop to Apple Silicon, the Ampere Altra Developer Platform might be the next best thing:
I somehow convinced Ampere/ADLINK to send me a workstation after my now years-long frustrated attempts at getting graphics cards working on the Raspberry Pi. And they sent me a beast of a machine:
Sometimes life has a funny way of lining up opportunities, and one presented itself when Patrick from ServeTheHome reached out and said, "Jeff, I have an Ampere Altra Max server. You wanna come see it?"
Of course I did.
But seeing as Patrick is more than 800 miles away, I had to come up with a reason to go see it, so I pulled out my 6-node Raspberry Pi cluster—with it's 24 ARM Cortex A72 CPU cores—and decided to have a little competition.
And of course that competition is documented in a YouTube video: