Cray Introduces Adaptive Supercomputing

David Greene writes "HPCWire has a story about Cray's newly-introduced vision of Adaptive Supercomputing. The new system will combine multiple processor architectures to broaden applicability of HPC systems and reduce the complexity of HPC application development. Cray CTO Steve Scott says, 'The Cray motto is: adapt the system to the application - not the application to the system.'"

Comments

Coolest Looking Supercomputers

[Eightyford]

Cray always made the coolest looking supercomputers. Here's an interesting bit of trivia:

The Cray T3D MC cabinet had an Apple Macintosh PowerBook laptop built into its front. Its only purpose was to display animated Cray Research and T3D logos on its color LCD screen.

Complexity, current machines

[gordyf]

It seems like the idea of combining multiple architectures into a single machine is already being done -- we have fast general purpose CPUs (single and dual core x86 offerings from AMD and Intel), paired with very fast streaming vector chips on video cards, which can be used for other non-graphical operations like a coprocessor.

The only difference I see is that they're relying on an intelligent compiler to decide which bits to send to which processing unit, but I'm not sure how much faith can be placed there. Cray certainly has a lot of supercomputing experience, but relying on compiler improvements to make or break an architecture doesn't have a good track record. I'm curious to see how they fare.

Re:Complexity, current machines

[flaming-opus]

They really aren't rellying on compiler improvements, so much as passing the code through their vectorizing compiler, and a tool for generating their fpga codes. If the code optimization for these 2 steps fails to optimize very much, you bail out and send it to the general purpose (opteron) processors.

Your being fairly pedantic about the computer architecture anyway. Yes, pairing multipe processor types together is not new, but most mpp supercomputers use identical node types.

The jist of this story is simpler than it sounds. Cray has 4 product lines with 4 cpu types, 4 interconnect routers, 4 cabinet types, and 4 operating systems. They would like to condense this down. The first step is to reuse components from one machine to the next. There are distinct advantages for keeping the 4 cpu types for various problem sets, but most everything else could be multi-purpose. From the sounds of things, it's using the next generation of the seastar router in all of the machines. Thus you use the same router chips, cabling, backplane, and frame for all the products. This reduces the number of unique components cray has to worry about. If they go to DDR2 memory on the X1 and mta, that further simplifies things, though I suspect they won't.

Well, once you share parts, why not make a frame with a bunch of general purpose CPUs for unoptimized codes, and a few fpga or vector cpus for the highly optimized codes? It allows customers more flexibility, and introduces cray's mid-range customers to the possibility of using the really high-end vector processors currently reserved for the high-end X1 systems. It's also a win for the current high-end customers. On the current X1 systems, you have these very elaborate processors running the user's optimized application, but the vector cpu's also end up running scalar codes like utilities and the operating system. These are tasks the vector cpu's aren't terribly good at, and you're using a $40,000 processor to run tasks a $1000 opteron will do better. Even if the customer isn't interested in mix-n-match codes on the system, (which I'm skeptical any cray customer really is), you probably want to throw a few dozen opteron nodes into the X1's successor, just to handle the OS, filesystems, networking, and the batch scheduler.

building machines around problems

[deadline]

Cray finally figured it out. I have been saying for years:

HPC/Beowulf clusters are about building machines around problems

That is why Clusters are such a powerful paradigm. If your problem needs more processors/memory/bandwidth/data access, you can design a cluster to fit your problem and only buy what your need. In the past you had to buy a large supercomputer with lots of engineering you did not need. Designing clusters is an art, but the payoff is very good price-to-performance. I even wrote an article on Cluster Urban Legends the explains many of these issues.

Re:Good Motto

[dildo]

It is possible to build comptuers that are optimized for certain kinds of calculations.

For example, Gerald Sussman of MIT (a computer scientist) and a Jack Wisdom (a physicist) decided they wanted to do long-term modelling of the solar system's evolution over time. Long time modelling of a multi-body system requires a fantastic amount of calculation. What is the best way to do it?

Sussman and Wisdom came up with a crafty idea: build a computer that is specially configured at the hardware level to do the modelling. Sussman and his colleagues decided that with off-the-shelf parts they could build a computer that would be just as or more capable of modeling this system than a supercomputer would be. The result was the Digital Orrery, a relativlely cheap computer that gave great results. (It is now featured in the Smithsonian museum.)

Think of it: if your computer is going to be doing the Fast Fourier Transform 6.02x10^23 times per day, why not build a superfast chip that does nothing but the FFT rather than express it as software? It's a pretty cool idea. I think this is the sort of thing that Cray computers claims to want to do with its motto.

Re:Co-processors anyone?

[sketerpot]

There are actually processors out there with compilers which can compile a few bottleneck C/C++ functions into hardware on an integrated FPGA. This expands the CPU instruction set in application-specific ways and can, in some cases, give absolutely enormous speedups.

In other words, they're working on processors which are programmed in general-purpose languages, but which adapt their hardware to the specific program.