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SGI to Scale Linux Across 1024 CPUs
im333mfg writes "ComputerWorld has an article up about an upcoming SGI Machine, being built for the National Center for Supercomputing Applications, "that will run a single Linux operating system image across 1,024 Intel Corp. Itanium 2 processors and 3TB of shared memory.""
Sweet, now we'll be able to run Doom3 at highest detail in *SOFTWARE*-rendering mode!
But does it run--crap. I mean what about a Beowulf--doh!
Damn you SGI!
Why not fork?
Yeah, but can it run Longhorn?
Intel's sales figures for Itanic^Hum CPUs more than doubled as a result.
--
"Open source is good." - Steve Jobs
"Open source is evil." - Microsoft
It seems that if they pull this off one of the dtrongholds of solaris (namely massivly parralell computing) will have been conqurered by linux. I wonder how sun are feeling at the moment?
The link to the press release as of July 14.
CC.
TaijiQuan (Huang, 5 loosenings)
so does this mean KDE and Openoffice will finally run at decent speed?
No, you're going to need quantum computing for that.
...how easy it is to install printer and sound drivers?
Microsoft made a statement today reminding everyone that Windows Server 2003 can handle as many as 32 processors, at the same time even.
When shown the report about Linux running on 1024 processors, Gates purportedly responded, "32 processors ought to be enough for anybody."
Unknown host pong.
They decided it was too RISCy maybe?
Why not fork?
yes, according to the project leader "on this supercomputer, OpenOffice will finally *run* at decent speed, but waiting for the JVM to start up will still be a bitch" As for KDE, he stated "we're still waiting for the qt toolkit to initialize, but we're confident we can be fully logged in before August"
AMD and Intel happened. What do you think is running your computer right now (assuming it's an x86)? It a RISC chip that has x86 translater attached, the core of the chip is RISC.
Scientific computing means data crunching (floating point). Complex, powerful processors are needed. The "stupider, but more" tradeoff doesn't work anymore. Sun processors have fallen behind in this respect.
The Raven
RISC stands for "reduced instruction set computer". It made sense in the 1980's when the "CISC", complex instruction set computers, took tens or hundreds of clock cycles to execute some instructions. With RISC one had less instructions, but each instruction executed in less clock cycles, resulting in a faster computer. Today, CPU's with full-size instruction sets execute most of them as fast as a RISC CPU does, so there is no need to limit the instruction set anymore. Even such complex instructions as multyplying double-precision floating point numbers are executed in a single clock cycle in a Pentium 4.
Sun hardware has additional, wonderful resiliency features like - allowing cpu's to "fail-over" to other cpus in case of failure. The same holds true for memory, network interfaces, etc. Solaris is aware of these hardware features and can "map out" the bad memory and cpus on the fly (or allow swap-in replacements). The engineers can then replace the broken cpus/memory/interfaces WITHOUT BRINGING THE MACHINE DOWN. This lends itself to an environment than can enjoy nearly 100% uptime. Finally, since Sun has been doing the "lots of cpus" thing for many years, their process management and scalability tends to be much better.
I don't work for Sun, I'm just an SA that deals with both Solaris and Linux boxes. You don't pick sun for just "lots of cpus", you pick it for a very scalable OS and amazing hardware that allows for a very, very solid datacenter. If downtime costs a lot (ie. you lose a lot of money for being down), you should have Sun and/or IBM zseries hardware. Unfortunately those features cost a lot and most times you can use Linux clustering instead for a fraction of the cost and a high percentage of the availability.
I wish I had that much disk space...
RISC and CISC offer no final advantage over the other, so the one that dominated is the one that was here first.
Quick examples: RISC use less power because it has less logic? No, it needs to run at a higher frequency to maintain the same speed as a slower CISC.
RISC is easier to program? Depends on the person. A compiler can take advantage of large instructions very well which are hardware optimized.
RISC easier to develop/manage? I'll say yes for RISC on this one. There's simply less logic on the chip so less logical errors possible. There's plenty more cache which can break but broken parts can be fused off.
RISC is physically smaller? No. RISC needs a higher clock frequency because many more instructions need to be executed. The result of this is that a much larger instruction cache is needed on chip.
I don't remember every comparison but it pretty much comes out that neither is better than the other. That being said RISC is better than x86. Everything is better than x86. However CISC vs RISC is much harder to judge. Having done x86, 68k, and MIPS I must say that RISC is a pleasure.
The Sun hardware is more difficult to deal with, since there isn't a virtual machine abstraction. You can't do everything below the OS. Still, Linux 2.6 has hot-plug CPU support that will do the job without help from a virtual machine. Hot-plug memory patches were posted a day or two ago. Again, this is NOT required for hot-plug on the zSeries. IBM whips Sun.
I'd trust the zSeries hardware far more than Sun's junk. A zSeries CPU has two pipelines running the exact same operations. Results get compared at the end, before committing them to memory. If the results differ, the CPU is taken down without corrupting memory as it dies. This lets the OS continue that app on another CPU without having the app crash.
"will run a single Linux operating system image across 1,024 Intel Corp. Itanium 2 processors..."
"The National Center for Supercomputing Applications will use it for research"
1. Make a system that generates more heat than a supernova.
2.Research a solution to global warming.
3. Profit!
SCO gained $715,776
I have replaced Sun Hardware/Software combo's in the core datacenter for many of our customers, and I can tell you that yes - Sun brings some amazing features to the table - most of which are there to serve old technology. Linux on simple CPU's delivers such an amazing price performance (depending on the job, we see an average of 3x to 4x performance increase for 25% of the cost. That means that if I were to spend the same, lifecycle-wise, on a Linux cluster as I would on a big Sun box like the 10k or 15k, I'd end up with 12x to 16x the performance of the Sun solution.
The same functionality in terms of cpu and ram (and other hardware) failure is available on the Linux cluster, albeit in less graceful form - the magic spell to invoke goes like this: if I have 300 machines crunching my data, I can afford to lose a couple, and can afford to have a few hot-standby's.
Of course, the massively parrallel architecture does not work for all applications, and in those cases you would look to use either OpenMOSIX or of course the (relatively expensive) SGI box mentioned in this article.
People who think they know everything are a great annoyance to those of us who do.
well, sgi uses/hacks NUMA, spinlocks, etc to make this happen in a more efficient manner. We recently had a SGI rep come and explain their 512CPU architechture at our LUG meeting... and he basically said that SGI has their own implementation of all of the clustering/cpu stacking techs... which they will eventually feed back into the community.. all good stuff.. understandably they will wait for a year or so so they can get their money's worth before they release their changes.
The purpose of that computer is to solve complex scientific problems such as weather simulations, high-energy particle simulations, protine folding, etc. Many of these simulations involve iterated systems of equations that can take decades to solve on the fastest CPU's we have today.
The only way to get meaningful results in a meaningful amount of time is to break the problem apart into smaller problems and solve them in parallel.
Some projects, such as Folding@Home and Find-A-Drug go the distributed computing route -- use many disconnected systems to solve the problem.
The downside to that approach is that not all problems can be easily broken apart -- and some classes of problems can exist without tight coupling but they loose efficiency. The impressive thing about this particular super computer is that it has a single, unified memory image.
This is very useful for some classes of simulation problems when the entire simulation must be present for each iteration.
It's ok for embedded and other areas (slower CPUs) but with desktop/server CPUs being much faster than memory speeds and remaining so for the forseeable future, having common and popular instructions being shorter than other instructions is actually an advantage despite the complexity that involves.
It's like having on-the-fly instruction decompression. e.g. CISC programs tend to be smaller in main memory+cache, and they travel in CISC/"compressed" form taking up less memory bandwidth over the memory/cache buses to the CPU instruction decoder where they are "decompressed" to RISC micro-ops to be executed.
Look at the mainstream desktop/workstation/server CPUs. Only the SPARC is RISC. IBM POWER/PowerPC is barely RISC[1], some people think it's more CISC than RISC. Itanium isn't RISC. x86 isn't. The rest (Alpha, MIPS, PA-RISC) are either out of the market or on their way out.
As long as CPUs are fast and much faster than RAM (and cache remaining expensive), it's often worth doing the compression/decompression thing.
[1] I believe IBM's POWER chips actually decode their "RISC" instructions to simpler instructions, some of their "RISC" instructions are pretty complex- kinda oxymoronic... But as I mentioned, that may not be such a bad thing.
Fire up apache and then post a link to it here on slashdot. We love a challenge.
The UNIX made by SGI (the company making the machine referenced in the article) is more scalable than Solaris. Remember, IRIX was the first OS to scale a single Unix OS image across 512 CPUs. And now they've eclipsed that, with Linux.
None of that is unique to Sun.
Better than what? And says who? They've never decisively convinced the market that they're beter at this than HP, SGI, IBM or Compaq.
In addition to ignoring the other good Unix architectures out there in a dumb way with this comparison, you're also totally missing the point of the article. Linux supercomputing isn't just about cheap clusters anymore. Expensive UNIX machines on one side and cheap Linux clusters on the other is a false dichotomy.
Now before I get modded down, I be to remind whoever might read this that what I am saying is FACT. - bogaboga
That's almost enough to run Emacs!
SGI has had 512 and 1024-cpu MIPS-based systems in operation for more than 5 years. Much work was done on the Irix systems to initialize large parallel computations and provide libraries and compiler support for these configurations. One technique is to provide message-passing libraries that use shared memory. A better technique is to morph (slightly) parallel mesh apps so that each computational mesh node exposes the array elements to be shared with neighbors. No message-passing needed - you push data after a big iteration and then use the (really fast) sync primitives to launch into the next iteration. With shared-nothing clusters (i.e. Beowulf) a computation (and its memory) must be partitioned among the compute nodes. The improvement over a "classical" cluster can be startling especially with computations that are more communications-bound than compute-bound. This means there is no value for replacing a render farm with a big system. But there are big compute problems, e.g. finite element, for which the shared-nothing cluster is often inadequate.
With a single memory image system the computation can easily repartition dynamically as the computation proceeds. Its very costly (never say impossible!) to do this on a cluster because you have to physically move memory segments from one machine to another. On the NUMA system you just change a pointer. The hardware is good enough that you don't really have to worry about memory latency.
And let's not forget io. Folks seem to forget that you can dump any interesting section of the computation to/from the file system with a single io command. On these systems the io bandwidth is limited only by the number of parallel disk channels - a system like the one mentioned in the article can probably sustain a large number of GBytes/sec to the file system.
Let's not forget page size. The only way you can traverse a few TB of memory without TLB-faulting to death is to have multi-MByte-size pages (because TLB size is limited). SGI allowed a process to map regions of main memory with different page sizes (upto 64 MB I think) at least 10 years ago in order to support large image data base and compute apps.
When I used to work at SGI (5 years ago) the memory bandwidth at one cpu node was about 800 MBytes/s. My understanding is that the Altix compute nodes now deliver 12 GBytes/s at each memory controller. Although I haven't had a chance to test drive one of these new systems, it sounds like they have gradually been porting well-seasoned Irix algorithms to Linux. It is unlikely that a commodity computer really needs all of this stuff, but I'm looking at a 4-cpu Opteron that could really use many of the memory management improvements.
g
I will avoid the tech terms (partly because they would confuse you, partly because I don't know them all but mostly because they ain't needed.
A single CPU computer can execute ONE instruction at the time. Meaning one program thread running at the time. But wait you say, my OS can run multiple programs at the same time. WRONG. It can't. It is a trick. It is running one program at the time but it is switching the program it is running really fast. There is however a problem with this. When it has switched to a program all the other programs are effectevily at the the mercy of the program now running INCLUDING the OS. Wich is why DOS and Windows and Linux and Mac OS and all the others had "hangups". With an extremely well written OS these hangups (when a program doesn't switch back to the OS) can be avoided but it still remains a case that all the programs and the OS are fighting for time on 1 single cpu.
So what happens when you add a cpu? Well a lot less switching PLUS if a program for whatever reason does not switch properly the OS can still be run on the other processor. Just making a windows box a dual CPU instantly makes it far more robuust. I encountered this myself with an old dell P3 that had a dual board but no dual CPU installed. Before I added a second CPU it was the usual windows crap of hangs and reboots and BSoD. Afterwards it ran as stable as a unix machine. Simple things like openeing a complex folder in exploder no longer "froze" the desktop as it could simple run exploder on one CPU and say word or my mp3 player on the other.
Don't forget too that there think like ATA harddrives and CD-ROM need the cpu to drive them. This takes a lot of long cycles and a lot of waiting, not so much CPU power as just time on the CPU. With a second one to do all the other tasks this makes everything run far smoother.
So what is better? Running 1 2ghz cpu or 2 1ghz cpu's? Depends. If you are running 1 program thread go with the 1 cpu. It will take all the cpu time but will not need to share it. If however you are running countless small threads go with the 2 or more solution. Threads will have access faster and you will loose less cpu time on the time needed to execute switches.
Oh yeah that is another problem. Switching between programs takes cpu time as well. It is not unknown for single CPU systems to spend so much time on switching they don't have time to run anything anymore. The old to many running programs problem known from windows but wich affects every OS.
Lastly there is a simple problem. Say you want real power do you go for a quad 2ghz or a single 8ghz. Answer? It is a trick, no such thing as a 8ghz cpu.
If you get the chance buy a second hand dual P3 and install windows 2000+ or Linux on it and be amazed. That old system will respond a lot faster underload then your 3ghz monster.
MMO Quests are like orgasms:
You may solo them, I prefer them in a group.
I've been working all weekend to cluster 4 Honda Civics. When I'm done, I expect it to go 280MPH, get 12MPG and 0-60 in under 3 seconds.
The UNIX made by SGI (the company making the machine referenced in the article) is more scalable than Solaris. Remember, IRIX was the first OS to scale a single Unix OS image across 512 CPUs. And now they've eclipsed that, with Linux.
Scalability is a complex issue. SGI has put a whole lot of processors together and put a single Linux image on it (so that a single program can use all memory), but this says nothing about how that setup will actually perform for general purpose use. Just because the hardware allows threads on hundreds of processors to make calls into a single Linux kernel, does not mean that there will not be major performance issues if this actually happens.
There are performance issues with memory even on single processor systems with nominally a single large address space, and a developer may need to put a lot of work into ensuring that data is arranged to make best use of the various levels of cache.
Many of the multi-processor architectures require even greater care to ensure that the processors are actually used effectively.
The fact that a single Linux image has been attached to hundreds of processors is no indication of scalability. A certain program may scale well, or not.