Archive for the ‘My Research’ Category

CU Janus Supercomputer

Thursday, September 29th, 2011

Last night I had the opportunity to tour the supercomputer recently built here at CU named “Janus” that I’ve been using. It is a 16,000-core Dell cluster using 6-core Intel processors running RedHat Linux. It was built in an interesting way. Instead of building a machine room in a building and then filling it with cooling ducts, pipes, and power connections, the machine room is made up of standard shipping containers that had all those connections in place, similar to a pre-fab house. These were shipped from the factory (in Canada, I think) on trucks, and then dropped next to each other in a parking lot behind a campus building. Unfortunately, because it was nighttime, I don’t have a good picture of the outside, but the link above has a good picture of it.

Below are some pictures I took of Janus.

The machine racks. The door encloses the 'hot' side of the machines, where the air is sucked to the heat exchangers.

The cooling system.

The blinky and hot end of the machines. Lots of wires!

A close up of the back of a compute node. Notice that they have serial ports, which are based on a 40+ year old standard. At least they have USB ports, too.

It was using 415 kW of power. I think it can go much higher than that when the machine is under heavy load on a hot day.

Blob Identification

Friday, April 22nd, 2011

I have access to some of the fastest computers in the world. I can summon thousands of processors, petabytes of disk storage, and terabytes of memory with a few keystrokes. You’d think with that kind of power, analysis could be automated and done in massive pipelines. But that’s not always true. Sometimes things are so subtle that the most efficient method is still to use the human eye.

Today I was pretty ill, with a sore throat and congestion. It was the kind of day for lying on the couch and watching movies. Luckily, I was able to accomplish some work that didn’t require too much concentration. First, some context.

One of my current projects is looking at the centers of simulated galaxy clusters, and it is actually surprisingly difficult to find the centers of the clusters. Clusters are complicated places, with clumps of matter falling in, sloshing stuff around, making the core not exactly clear. In order to semi-automate the process, I wrote a script that makes pictures of the clusters (which have been previously identified in a automated fashion), that have density contours superimposed. The density contours are analogous to the lines on a topographical map.

The picture above is an example of the output of the script. The colors indicate gas density, blue to red is low to high. If you look at the full-sized image, you can see that there are two dense clumps numbered 0 and 1. I can’t just pick the most dense cluster because that might be a tiny blob of matter falling into the larger cluster; more care is needed. So I need to make the decision with my adaptable brain. The script spits out the image, and then I have to input which clump I think is the most central clump, and a record is made which I’ll use for the next step in my chain of analysis. I spent most of today looking at these pictures and entering numbers. Yay for tax payers!

This is very similar to the Galaxy Zoo project that aimed to identify the morphology of actual galaxies, but my effort is on a much smaller and simpler scale.

So – which clump do you think is the most central above?

Volume Rendered Movies

Wednesday, October 27th, 2010

It’s show-and-tell time! Below are two movies I made using the volume rendering tools of yt. I’ve been using yt for a few years to analyze and visualize the cosmological simulations I make with Enzo, and only recently have I had time to begin to play with the new volume rendering stuff.

The first movie is a slow rotation around the entire volume of a simulation at a contemporary epoch, which means that this image is produced from the state of simulation at its end, 13 billion years after it started. The colors correspond to the density of matter in the volume, from dark blue to white as density increases. The simulation is a periodic cube with dimensions 20 Mpc/h on a side. In comparison, the diameter of our galaxy is somewhere around one thousand times smaller. This means that the whitest areas correspond to clusters of galaxies, and our galaxy would be just a small part of one of the white blobs. Be sure to watch the movie full screen!

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(Quicktime version)

Below shows the time evolution of the simulation from beginning to end. This is a thin slab of the center of the simulation (10% thickness) viewed from a corner of the cube. Notice that early on the matter is very clumpy everywhere, but rapidly forms dense knots connected by thin filaments. This is how the real universe looks! After about the half-way point of the movie you’ll notice that not much happens. Again, this is how the real universe looks! Much of the large-scale evolution of the universe was finished about 7 billion years ago. This movie uses comoving coordinates, that compensate for the expansion of the universe. If I were to use proper coordinates, which are the kind we use every day to measure normal things with rulers, the movie would show the simulation starting very small and then blowing up. Again, use the full screen option for the best image.

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(Quicktime version)

Back in San Diego (Temporarily)

Monday, September 20th, 2010

I’m back in San Diego for the next week and a half in order to graduate. I defend in one week on the 27th. The photo above is of a tarantula that lives in the office that I used to sit in, and that I am sitting in again while I’m here. That is its full significance to this post.

If the tarantula isn’t big enough above, you can make it bigger by clicking on the image!

SDSC Optiportal

Tuesday, October 14th, 2008

My adviser Professor Mike Norman, as part of his job at the San Diego Supercomputer Center, purchased an optiportal system for the new SDSC building which is opening today. An optiportal system is a wall of monitors powered by networked computers such that the screens behave as one monitor. Very high resolution images and movies can be tiled across the screens, as you can see below. Movies and animations can also be tiled across the screens.

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