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23 Second Kernel Compiles
b-side.org writes "As a fine testament to how quickly linux is absorbing technology formerly available only to the computing elite, an LKML member posted a
23 second kernel compile time to the list this morning as a result of building a 16-way NUMA cluster. The NUMA technology comes gifted from IBM and SGI. Just one year ago, a
Sequent NUMA-Q would have cost you about USD $100,000. These days, you can probably build a 16-way Xeon (4X 4-way SMP) system off of ebay for two grand, and the NUMA comes free of charge!"
No way. Just a no-CPU, no-memory case and
motherboard costs $500. More like $2000
to $3000 for an old quad.
23 seconds is impressive. I, personally, have seen a 42 second compile time of a 2.2 series kernel on a Intel 8-way system (8GB ram, 8 550Mhz PIII Xeons w/ 1mb L2). It was in the 1 minute range with a 2.4 kernel.
Definately the most impressive x86 system I have ever seen.
is there some hidden application of this that I'm not seeing?
How about doing other stuff really fast?
3D modeling. 3D simulations. Even extensive photoshop editing with complex filters can benefit from this kind of raw speed.
It wouldn't be a catchy headline, though, if it said "render a scene of a house in 40 seconds--oh, and here are the details of the scene so you can be impressed if you understand 3D rendering..."
There are hundreds of applications for this, many of which we don't do every day on our desktop simply because they take too much juice to be useful. With ever-faster computers, we will continue to envision and benefit from these new possibilities.
Donate background CPU time to fight cancer.
NUMA is rather different than Beowulf.
NUMA is just a strategy used for making computers that are too large for normal SMP techniques. I read a few good papers on sgi.com a couple of years ago that explained it in detail, and the NUMA link in the article had a quick definition. NUMA systems run one incarnation of one OS throughout the whole cluster, and usually imply some kind of crazy-ass bandwidth running between different machines. I don't think you could actually create a NUMA cluster of seperate quad Xeons boxes, and it would probably be ungodly slow if you tried.
There probably isn't any difference for kernel compiles between the two, but NUMA clusters don't require any reworking of normal multithreaded programs to utilize the cluster and can be commanded as one coherent entity (make -j 32, wheee).
I went and looked at the email and noticed that the very first patch he mentions was from the woman who came and gave a talk to EUGLUG last spring. For one of our Demo Days we emailed IBM and asked them if they would send down someone to talk about IBM's Linux effort. We were kind of worried that they would send a marketing type in a suit who would tell us all about how much money they were going to spend, etc., etc. But we were very pleasantly surprised when they sent down a hardcore engineer who had been with Sequent until they were swallowed by IBM.
She did a pretty broadranging overview of the linux projects currently in place at IBM, and then dived into the NUMA/Q stuff that she had been working on. The main gist of which is that Sequent had these 16-way fault-tolerant redundant servers that needed linux because the number of applications that ran on the native OS was small and getting smaller. Turned out that even the SMP code that was in the current tree at the time did not quite do it. She had some fairly hairy debugging stories, apparently sprinkling print statements through the code doesn't work too well when you're dealing with boot time on a multiprocessor system because it causes the kernel to serialize when in normal circumstances it wouldn't...
I think the end result of all this progress with multiprocessor systems is that we'll be able to go down to the hardware store and buy more nodes plug 'em into the bus; and compute away.
That's not the point - kernel compilation (or the compilation of any large project like KDE or XFree[1]) is a fairly common benchmark for general performance. It chews up disk access and memory and works the CPU quite nicely.
[1] Large is, of course, a relative thing. Also, some compilers (notably Borland) are incredibly efficent at compiling (sometimes through manipulating the language specs so the programmer lines things up so the compiler can just go through the source once and compiles as it goes).
Still, benchmarks are suspect to begin with, and kernel compile time is a decent loose benchmark. What was that quote from Linus about the latest release being so good he benchmarked an infinate loop at just under 6 seconds? :)
--
Evan
"$30 for the One True Ring. $10 each additional ring!" -- JRR "Bob" Tolkien
But the reserve for this machine is $3850. The article says 16 way, which would be four of these four-way SMP systems. That also doesn't take into account the need for a high-bandwidth, low latency interconnect (like SGI's NumaLink.) If you aren't expecting more than 16-way SMP, then you can probably get away with switched Gigabit Ethernet, as long as it is kept distinct from the nornal network connectivity. If the Gigabit upgrade is still dual portm then you are set. If not, you'll neet another NIC - though you will only really need one for the whole cluster.
Maybe instead of two grand, the poster meant twenty-grand. Either way, $20 grand is better than $100K!
Reason? Not enough information as to the options.
Never the less:
I WANT ONE
www.eFax.com are spammers
http://samba.org/~anton/e10000/maketime_24
Wheeeeeee!
And seriously, I saw some comments about needed a really fast interconnect... check out Sun's Wildcat.
--NBVB
Probably because compilercache is a way to AVOID compiling. . .
NUMA is somewhere in between clustering (e.g. Beowulf) and SMP.
:-)
On a normal desktop machine, you typically have one CPU and one set of main memory. The CPU is basically the only user of the memory (other than DMA from peripherals, etc.) so there's no problem.
SMP machines have multiple CPUs, but each process running on each CPU can still see every byte of the same main memory. This can be a bottleneck as you scale up, since larger and larger numbers of processors that can theoretically run in parallel are being serviced by the same, serial memory.
NUMA means that there are multiple sets of main memory -- typically one chunk of main memory for every processor. Despite the fact that memory is physically distributed, it still looks the same as one big set of centralized main memory -- that is, every processor sees the same (large) address space. Every processor can access every byte of memory. Of course, there is a performance penalty for accessing nonlocal memory, but NUMA machines typically have extremely fast interconnects to minimize this cost.
Multi-computers, or clustering, etc. such as Beowulf completely disconnects memory spaces from each other. That is, each processor has its own independent view of its own independent memory. The only way to share data across processors is by explicit message-passing.
I think the advantage of NUMA over beowulf from the point of view of compiling a kernel is just that you can launch 32 parallel copies of gcc, and the the cost of migrating those processes to processors is nearly 0. With beowulf, you'd have to write a special version of 'make' that understood MPI or some other way of manually distributing processes to processors. Even with something like MOSIX, an OS that automatically migrates processes to remote nodes in a multicomputer for you, the cost of process migration is very high compared to the typically short lifetime of a typical instantiation of 'gcc', so it's not a big win. (MOSIX is basically control software on top of a beowulf style cluster, and the kernel mods needed to do transparent process migration)
I hope this clarified the situation rather than further confusing you.
Seriously, I wonder how long it takes to boot.
They do take a good bit of time to boot. In fact, it makes me much more careful when booting new kernels on them because if I screw up, I've got to wait 5 minutes, or so, for it to boot again! But, they do boot a lot faster when you run them as a single quad and turn off the detection of other quads.