[ThePythonicCow]

It's a single system image - off the shelf SUSE SLES 10, with just a few patches. Without any patches, we can boot that kernel, right off the SUSE DVD, on a 1024 CPU system.

It's what's called a cache coherent NUMA architecture.

One benchmark I saw go by just now was scaling at over 90 per-cent efficiency.

Every Unix command and system call sees just one kernel; there is just one kernel.

We've been doing some -serious- scaling of the main stream Linux kernel the last few years. Look for the configuration parameter CONFIG_NR_CPUS in the stock kernel that comes from Linux, in the various arch/*/configs/*_defconfig files. You will see values ranging from 2 to 1024, for various hardware architectures.

That means, for that hardware, you can run the kernel on a system with that many CPUs, if you can scrape together that much hardware and that much money for the kick ass interconnects that it takes to run stuff like this at speed.

Yes - I know what a cluster is, including some clusters that support shared memory and such transparently across the nodes.

This is not a cluster. Though we'd be happy to sell you a cluster as well. The main difference between a cluster and a big box like this is the interconnects. Running a cache coherent single system memory image across this much memory requires some seriously fat and fast wires, and some nasty routers. The memory controller chip, what would be the north bridge in an ordinary PC, is rather different too - not a commodity part.

For jobs that are sufficiently parallelizable, clusters are more economical. For jobs that are only coded to run in a single big memory, you need serious NUMA iron like this.

[Golden Eagle]

Interesting, how are you getting up to 2048 CPU, is it virtual? The largest SSI I've heard about are 1024, and that wasn't long ago. This probably isn't just straight "Linux" either is it, don't you need some proprietary SSI software from IBM or SGI, etc to provide the boot layer? I've heard about OpenSSI but it's nowhere close to this is it? You're right about the programming advantages though, I've heard programming for the clusters can be difficult, and why so many stick with their old Cray or IBM Mainframe.

[grey_whiskers]

One benchmark I saw go by just now was scaling at over 90 per-cent efficiency.

What was the benchmark? A numerical kernel or an application code?

What language was it written in?

Hint: drool drool. :-)