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Student and Professor Build Budget Supercomputer
Luke writes "This past winter Calvin College professor Joel Adams and then Calvin senior Tim Brom built Microwulf, a portable supercomputer with 26.25 gigaflops peak performance, that cost less than $2,500 to construct, becoming the most cost-efficient supercomputer anywhere that Adams knows of. "It's small enough to check on an airplane or fit next to a desk," said Brom. Instead of a bunch of researchers having to share a single Beowulf cluster supercomputer, now each researcher can have their own."
It's just four motherboards sitting in a single frame. connected by an ethernet switch.
True supercomputing machines (sun, ibm) have a little bit better interconnectivity between the components than a mere 1Gb/s line. This can serve its purpose though, VASP will run wonderfully on it. GAMESS probably as well.
B.
Every experiment which ends in a big bang is a good experiment.
It's small enough to check on an airplane
With security concerns nowadays, it's the amount of cables coming out of it that worries an airline, not the size or weight of this machine.
Virtual Betting on Facebook for non-geeks.
I am impressed with how amazingly lame this story is. It should have been entitled, "College Senior and Professor discover Ethernet, MicroATX, and PXE boot. Funding dried up before paying for cases. News at 3 am because we can't find anything else to report."
Honestly, our whole research lab is filled with PXE booting MicroATX computers connected via ethernet. And I guarantee that four "nodes", aka Linux PCs, are cheaper than $2500. Whoop-de-freaking-do.
...this is *hardly* a supercomputer. This is 152.57 times slower than entry number 500 on the Top 500 List. There isn't a nice neat definition of what a supercomputer is anymore, but "capable of running Beowulf" isn't it. Leaving aside the more custom machines that the company I work for (and a few others) build, there are plenty of Linux clusters that *do* qualify. The fastest one seems to be number 8 on the current Top 500 list (a Dell Infiniband cluster at NCSA).
Go Badgers! -- #include "std/disclaimer.h"
One of the problems with supercomputers is that there aren't really very many of them, because of the size and cost. It means that the tools you use to run your supercomputing applications are similarly unusual. The skills to use and develop on parallel systems are then equally scarce. Access to a supercomputer isn't exactly common.
Microwulf could make all of the above common. For the price of a high spec PC. The commodity nature of it could bring super computing and super computing applications to the masses.
Then you can scale your application from microwulf to miniwulf to superwulf with little more effort than installing it on the bigger machine.
Course, they'd have to produce a commodity pre-built system.
Deleted
This is kind of like the old joke about a dog chasing a car...what's it gonna do with the thing if it catches it.
I've thought several times about building a small cluster, just for the experience and the nerd factor. But I never do because I also get in to the issue of just what am I going to do with it once its finished, other than heat my workshop.
I want a new quote. One that won't spill. One that don't cost too much. Or come in a pill.
"a portable supercomputer with 26.25 gigaflops peak performance, that cost less than $2,500 to construct, becoming the most cost-efficient supercomputer anywhere that Adams knows of."
Dear "Dr." Adams,
One PS3, converted to Linux, has been demonstrated to have a performance of around 100 GFlops. That is significantly cheaper, more cost efficient, and higher performance than your $2,500 pile of crap. Plus, it comes with a shiny case. For $2,500, you could even buy 4 of them and wire them together into a small cluster. That's around 16x the cost-efficiency of your rats nest. Your claim has been directly refuted. Maybe you should read more modern research conference proceedings.
Sincerely,
The Research Community
gigaflops, schmigaglops.
/.
this is
i thought performance was measured in fps?
In this case, I think it's a somewhat serious idea. This design has only four nodes, so connecting several in a modular fashion might make sense, and retain some of the advantages in portability and cost. You could move the individual Microwulfs around, but bring them together for really big problems. Think of it as a LAN party for scientists.
The University of Kentucky (where he is coincidently going to grad school) beat his price point years ago on a "real" supercomputer. This super computer was built for about $84 per GFLOP in 2003 and it made the Top500 list when it was built. The Aggregate team at UK is one of the tops in the field when it comes to supercomputers on the cheap.
Seems like 2GB per (dual core) node is a little on the low side for practical usage. Not surprisingly though, RAM is the biggest cost of the system (992$ total) and switching to 2GB or 4GB modules will raise the system price considerably. Would still be cheap though.
RTFA They bound the onboard NIC to one core of each CPU and bound the add-on NIC to the other core. That way, each core had its own dedicated communications channel.
In http://clustercompute.com/ you could find better design in term of compactness. Another thing is that the cluster does not need KVM (in process only at test mode) and as noted in several research papers dual 100M can beat gigabit (source http://en.wikipedia.org/wiki/Kentucky_Linux_Athlon _Testbed )
Forget about the bus there :-)
:-)
;-)
A serious floating-point job often iterates over a dataset, modifying it, so data traffic happens mostly between the registers and the caches. Fresh data from memory (or over network) can be brought in while this computation is going on.
Actually, for about a decade, programmer focus has indeed been shifting toward data traffic efficiency, and away from how to bum the algorithm into the fastest possible shape. Number-crunching monsters like Sony's PS3 and Nvidia's Tesla add-ons cards (graphics accelerators without graphics...) in fact require a completely data-oriented program design -- you begin by architecting your data and it's movements first and only then continue to algorithms and what you are actually trying to do with said data...
Hope this helped! And... "Everyone's a newbie once in everything, and always in something."
And actually, your instinct that "1 Hz = 1 FlOPS" is pretty much true for many architectures. Of course it simplifies the matter vastly, but you knew that