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IBM's Blue Gene Runs Continuously At 1 Petaflop
An anonymous reader writes "ZDNet is reporting on IBM's claim that the Blue Gene/P will continuously operate at more than 1 petaflop. It is actually capable of 3 quadrillion operations a second, or 3 petaflops. IBM claims that at 1 petaflop, Blue Gene/P is performing more operations than a 1.5-mile-high stack of laptops! 'Like the vast majority of other modern supercomputers, Blue Gene/P is composed of several racks of servers lashed together in clusters for large computing tasks, such as running programs that can graphically simulate worldwide weather patterns. Technologies designed for these computers trickle down into the mainstream while conventional technologies and components are used to cut the costs of building these systems. The chip inside Blue Gene/P consists of four PowerPC 450 cores running at 850MHz each. A 2x2 foot circuit board containing 32 of the Blue Gene/P chips can churn out 435 billion operations a second. Thirty two of these boards can be stuffed into a 6-foot-high rack.'"
If you have a large dataset or input domain to perform work upon, split it into X chunks, each chunk processed on a CPU. Hence supercomputers usually being useful for problems that have large datasets/input domains
"I am not bound to please thee with my answers" [William Shakespeare]
...the next step (10**18) is the "exaflop."
--I'm so big, my sig has its own sig.
-- See?
I wonder if I will ever be able to read slashdot articles without using the google calculator...
1.5 mile = 2.414016 kilometers
2 "foot" = 0.6096 meters
6 feet = 1.8288 meters
Well the the stack of laptops might be tall, but even the 216 racks would stack up to 1/5 of a mile high.
How many of these are "real world"? Well, medical and CFD applications are significant, but hardly what you'd call mainstream, and the raytracing may have been used in Titanic on a smaller scale, but IMAX is under no threat at this time.
It's a small world and it smells funny; I'd buy another if it wasn't for the money; Take back what I paid (SoM)
Sure you can sort in O(1/(n^(1/2))) time. By Using a Shear Sort Algroithm.
If something is so important that you feel the need to post it on the internet... It probably isn't that important.
While the new IBM Blue Gene/P system is impressive, I'm more curious to see what sort of new supercomputer Andreas Bechtolsheim of Sun Microsystems has put together.
Here's an interesting quote about Bechtolsheim from the article: 'He's a perfectionist,' said Eric Schmidt, Google's chief executive, who worked with Mr. Bechtolsheim beginning in 1983 at Sun. 'He works 18 hours a day and he's very disciplined. Every computer he has built has been the fastest of its generation.'
Even with the computing power weather would be impossible to calculate. It isn't because of a lack of understanding either. In order to calculate weather you don't just need to know how weather works, you need to have precise data on every variable across the globe and these measurments would need to be taken to a resolution that is simply insane. If you had a fast enough machine, it could even catch up with current weather from that point, but your snapshot would have to be exact and all measurements would have to be taken simultaneously.
THAT is what we can't do. Even if we could mount instrumentation in every square meter of the earth AND its atmosphere to get our current status map and we configured the machine to predict the interactions of those currents we would still be lost. Aside from tracking the output of the sun, the weather system would need to account for ocean currents, tides, bonfires and heating systems, volcanoes, body heat, pig sex, etc.
That is right my friend, every time you pull out and shoot a load on her stomach the weather system would have to take it into account, because the air disturbed might be the first of a chain of complex interactions that leads to a hurricane that devestates louisana... again (because there are actually people so ignorant that they are going to rebuild a city in the same bad location).
When the previous generation (BG/L) was released, a rack (1024 nodes, 2048 cores) would cost about US$1.5m. Apparently IBM sells them considerably cheaper now, with BG/P around the corner...
Contrary to most people that think a singular way of representing floating point speed is FLOP, it is FLOPS because FLOPS is not plural. FLOPS is Floating Point Operations Per Second. So, I chuckle everytime I read 1 PETAFLOP. Guys, just turn off your singular/plural alarm and say with me 1 and only 1 PETAFLOPS.
BG/P will support 2 GB standard for each compute node. A compute node has 4 core processors. An option for 4 GB of memory is also available. On BG/L the initial memory configuration at Livermore was 512 MB per compute node which consisted of 2 core processors. Since 2007 BG/L has offered 1 GB memory as the standard configuration.
A tricky question, but not all that interesting. A fast server processor is within a factor of 4 of the fastest supercomputer processor in the world. That does not mean that you can do equivalent work with the server processor. Among other things, processing performance (gigaflops) of a CPU, is no longer the interesting part of a supercomputer. (It never really was) memory bandwidth, interconnect bandwidth and latency, and I/O performance are the more interesting features of supers. 12 year old Cray processors still have five times the memory bandwidth of modern PC processors, and twenty times the I/O bandwidth.
You'll notice, that 98% of the supercomputers, sold in the last 10 years, all use server processors. (Blue Gene actually uses an embedded systems processor, but it's the same idea) However, in the late 80's putting 256 processors in a super was cutting edge. In the 90's, a few thousand. Soon you'll see a quarter million cores. So supers are actually getting faster at a higher rate than are desktops, at least by most measures.
There is also OpenMP (more of an extension to C/C++ than just a header, you need pragmas and stuff to use it); I find it easy to fall into race conditions in that library because you really need to think about what you are doing.
Technically, pthreads ought to be able to provide enough functionality to get up and running if your environment acts as a single machine, or even the System.Threading namespace if you have the ability to run managed code. However, you don't have control then over if your thread gets its own cpu or not (unless it is guaranteed by the OS). In most cases that isn't actually necessary, your algorithm can be written in such a way that it doesn't matter if it is running on a 8 cpu system or a 2^32 cpu system (with exception to the fact that time to completion will vary); the troubles come in with optimizations.
Recently I have been experimenting with simple web services on a server to farm out pieces of the solution in a distributed fashion for attempting a brute force on a salted sha1 hash in a database situation where you know the salt:
on server: on clients: