Comment by cwal37 | Hacker News Reader

Comment by cwal37 | Hacker News Reader

I spent some time at Livermore, and I work at Oak Ridge now. It's been interesting to see the difference in how the HPC assets are referred to, or not, and I think it reflects the culture and layouts of the labs.

At LLNL it was constant, and everyone I interacted with had something to say about being at or near the #1 spot in the top 500 list (with Sequoia at the time), and advice on projects to try and get time. I went on a tour of the facility too, and it was really neat to get some perspective on the physical aspects of it all.

I've been at ORNL since February, and haven't heard Titan mentioned once. Partially I think this is due to the more cohesive overall mission of LLNL vs. ORNL, but I think geography plays a role as well.

The labs have fairly similar numbers of employees, but with one major difference; ORNL is spread out over a pretty large area and LLNL is a single square mile. Perhaps as a result of that, groups at ORNL feel a bit more insular. Heck, I've been to the "main" cafeteria once here, because I work on an edge of the campus, but at LLNL I went every day because it was easy to get to.

I wonder if a more compressed area results in a more useful utilization of huge assets like HPC because there are a lot more connections to be made between different departments. Then again, I also got the feeling that at LLNL it was a carrot they could try and dangle to draw people out of the valley. ORNL doesn't really have that same local competition for talent.

EDIT: And the article even specifically mentions the difference in lab missions by noting the new computers' uses: security vs. open science.

There was some discussion in Dewars book "To the End of the Solar System"[1] about the different cultures at the national labs related to the development of nuclear thermal rockets. Something about the Los Alamos guys being all about experimentation, and blowing radioactive material out of the tail of the rocket, until an Oak Ridge director was brought in and mandating more modelling of internal behavoir. I may have those labs mixed up, it's been a long time since I've read the book.

[1]http://books.google.com/books/about/To_the_End_of_the_Solar_...

The nuclear rocket stuff was in the 50s and 60s. With the shift to stock-pile stewardship at the end of the cold war all of the labs became fairly focused on modeling. It also depends on what group you work for. I worked for one of the modeling groups so we were obviously talking about it all the time. Many other groups did to. Some were more experiment focused. Most the physicists treated it as a third branch to the classic experimental, theoretical split in physics.

Why do nuclear stockpiles require HPC?

Since actually testing nuclear weapons is banned, the only way to verify (ha! verify with simulation) that the current nuclear stockpile is reliable is with simulation. In brief, the idea is to model degradation of current warheads and how that effects their performance/reliability.

For example, the National Ignition Facility (the warp core in Into Darkness) was created partly too provide a source of fusion that could be used to verify the computer models used to simulate nuclear weapon stability. Ie, write a general enough model to see what happens in the fusion bit of a nuke, then apply the model to something like what the NIF does, and then actually test it in the NIF. If the NIF experimental outcomes are in agreement with the model predictions, then we now have higher confidence that the model predictions with regards to the actual nukes are useful.

http://en.wikipedia.org/wiki/Stockpile_stewardship

Really? The times I have visited ORNL, they've pretty much talked non-stop about all the fun things being done on Titan.

I am/was affiliated with CASL and used it for some of my research work. It's a nice system and we got amazing performance, it would have taken literally years to run the same calculations back on the cluster at my university. We didn't really take full advantage, though, as we weren't using the coprocessors. But I guess our mission is computational science, so maybe that's why we heard so much about it.

I just saw the most interesting presentation the other day. Tom Evans' group is apparently working on these nice new methods to solve linear systems via Monte Carlo sampling. It's one of the projects in pursuit of exa-scale systems. The Monte Carlo algorithms are interesting because while they're a lot slower in terms of CPU hours, they do much better in terms of scaling and resiliency at those sorts of extremes.

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