Physical Architecture

The physical architecture of Titan is just as interesting as the high level core and transistor counts. I mentioned earlier that Titan is built from 200 cabinets. Inside each cabinets are Cray XK7 boards, each of which has four AMD G34 sockets and four PCIe slots. These aren't standard desktop PCIe slots, but rather much smaller SXM slots. The K20s NVIDIA sells to Cray come on little SXM cards without frivolous features like display outputs. The SXM form factor is similar to the MXM form factor used in some notebooks.

There's no way around it. ORNL techs had to install 18,688 CPUs and GPUs over the past few weeks in order to get Titan up and running. Around 10 of the formerly-Jaguar cabinets had these new XK boards but were using Fermi GPUs. I got to witness one of the older boards get upgraded to K20. The process isn't all that different from what you'd see in a desktop: remove screws, remove old card, install new card, replace screws. The form factor and scale of installation are obviously very different, but the basic premise remains.

As with all computer components, there's no guarantee that every single chip and card is going to work. When you're dealing with over 18,000 computers as a part of a single entity, there are bound to be failures. All of the compute nodes go through testing, and faulty hardware swapped out, before the upgrade is technically complete.

OS & Software

Titan runs the Cray Linux Environment, which is based on SUSE 11. The OS has to be hardened and modified for operation on such a large scale. In order to prevent serialization caused by interrupts, Cray takes some of the cores and uses them to run all of the OS tasks so that applications running elsewhere aren't interrupted by the OS.

Jobs are batch scheduled on Titan using Moab and Torque.

AMD CPUs and NVIDIA GPUs

If you're curious about why Titan uses Opterons, the explanation is actually pretty simple. Titan is a large installation of Cray XK7 cabinets, so CPU support is actually defined by Cray. Back in 2005 when Jaguar made its debut, AMD's Opterons were superior to the Intel Xeon alternative. The evolution of Cray's XT/XK lines simply stemmed from that point, with Opteron being the supported CPU of choice.

The GPU decision was just as simple. NVIDIA has been focusing on non-gaming compute applications for its GPUs for years now. The decision to partner with NVIDIA on the Titan project was made around 3 years ago. At the time, AMD didn't have a competitive GPU compute roadmap. If you remember back to our first Fermi architecture article from back in 2009, I wrote the following:

"By adding support for ECC, enabling C++ and easier Visual Studio integration, NVIDIA believes that Fermi will open its Tesla business up to a group of clients that would previously not so much as speak to NVIDIA. ECC is the killer feature there."

At the time I didn't know it, but ORNL was one of those clients. With almost 19,000 GPUs, errors are bound to happen. Having ECC support was a must have for GPU enabled Jaguar and Titan compute nodes. The ORNL folks tell me that CUDA was also a big selling point for NVIDIA.

Finally, some of the new features specific to K20/GK110 (e.g. Hyper Q and GPU Direct) made Kepler the right point to go all-in with GPU compute.

Power Delivery & Cooling

Titan's cabinets require 480V input to reduce overall cable thickness compared to standard 208V cabling. Total power consumption for Titan should be around 9 megawatts under full load and around 7 megawatts during typical use. The building that Titan is housed in has over 25 megawatts of power delivered to it.

In the event of a power failure there's no cost effective way to keep the compute portion of Titan up and running (remember, 9 megawatts), but you still want IO and networking operational. Flywheel based UPSes kick in, in the event of a power interruption. They can power Titan's network and IO for long enough to give diesel generators time to come on line.

The cabinets themselves are air cooled, however the air itself is chilled using liquid cooling before entering the cabinet. ORNL has over 6600 tons of cooling capacity just to keep the recirculated air going into these cabinets cool.

Oak Ridge National Laboratory Applying for Time on Titan & Supercomputing Applications
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  • Krysto - Wednesday, October 31, 2012 - link

    It's 46 million GPU cores:

    http://www.brightsideofnews.com/news/2012/10/29/ti...

    This is embarrassing.
  • iMacmatician - Wednesday, October 31, 2012 - link

    No, it's not. BSN's numbers are incorrect.
  • MetalManTN - Wednesday, October 31, 2012 - link

    I've read articles on anandtech for years, but I register an account for the first time today to comment on how wonderful this article is. The scope of what is covered in the article is nothing short of fascinating, and the quality of the writing and attention to detail is superb. Thank you!
  • Creig - Wednesday, October 31, 2012 - link

    and we already know the answer is 42.
  • spaghetti_taco - Wednesday, October 31, 2012 - link

    Very interesting article, loved the 30,000 foot explanation of the supernova modeling, really helped me to understand in more concrete detail what types of things scientists are using these supercomputers for.

    One thing I'd love to see is more in depth discussion of the networking. As you pointed out, the networking connectivity is just as important as the data processing, but you really just glossed over it. At least something as simple as vendor, models, host bus adapters, etc.
  • WaitingForNehalem - Wednesday, October 31, 2012 - link

    Anand, you should have visited me at the University of Tennessee!
  • zero2dash - Wednesday, October 31, 2012 - link

    I want to work there. :D
    Holy Santa Claus shit. I think I'd need a motorized cart for the tour; I'd be too weak to walk.
    [drool]

    Great article and major kudos for all the photos...a few of these are gonna be desktop wallpapers. ;)
  • BSMonitor - Wednesday, October 31, 2012 - link

    If they used Sandy Bridge Xeon's, that'd be about 4 Mega Watts and no giant pipes with coolant!!
  • Braincruser - Wednesday, October 31, 2012 - link

    And new motherboards, memory systems, optimisations... practically they would have to exclude the GPU's to fit it in any realistic spending.
  • JMC2000 - Wednesday, October 31, 2012 - link

    Problem is, there more than likely was a queue of clients that couldn't wait for ORNL/Cray to completely replace every node, which would have taken much longer.

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