Someone in the lab recently came to me asking for help in diagnosing a strange problem. The time output from their program was drifting inexplicably — that is, they were adding a certain increment every iteration, but the time was changing by some value slightly different from that increment. It turns out that this was because they were using single-precision floating-point (a.k.a “float”) variables. The problem did not show up right away. In fact, it would not have been an issue were they not adding an increment so very many times.
To diagnose this problem, (because I haven’t dealt with this issue in a long while), I wrote this little piece of code: Continue reading →
As the models used in our lab become larger both in resolution (more detail) and gross size (bigger pieces of tissue), the time and effort required to visualize and otherwise check results increase. With the largest model currently used in the lab (mine), one short simulation produces 2.0 GB of uncompressed data. Compression gets it down to about 500 MB or so. That still means that — just to make sure the simulation ran correctly — I have to download 500 MB of data, load my model into a viewer of some kind, and load and view the data. This is not acceptable, especially since even loading the data requires a machine with significant graphical power and a large hard drive.
There are other ways to visualize our data. A little while ago (two years?), our programmers Rob and Umar put together an off-screen renderer for the IBVRE project. It’s based on VTK and coded in Python. It simply loads the model with views from all 6 sides, maps the data on to the surface, and then writes an image file.
I spent 12 hours Saturday resurrecting this software and tweaking it for my own needs. Now it just loads one view of my model, efficiently steps through a specified number of time steps (it did this very very inefficiently before), writing them all to image files, and then exits. I run this on the cluster with a script that joins all of the images into a movie, and then emails them to me.
I currently have the cluster email me when a job is done. I also have mail filters that forward these messages to my phone. However, I can now do better. I have integrated the rendering program with my cluster run scripts, such that the following happens. When a simulation is finished, the visualization program is run and dumps images of all of the time steps. They are then joined to make a movie, emailed to me, and emailed directly to my phone. Thus, when the simulation is finished, I not only get an email notification, but I can review the video right on my phone.
If you’re not a geeky type, this may not impress you. To me, it is the very apex of cool. Enough so that it drove me to stay at work for nearly 13 hours on a Saturday. Here’s a sample video:
Now, instead of downloading 500 MB or more to a high-powered workstation (or let it limp on my laptop) to check the outcome of a simulation, I can have a 1 to 4 MB video automatically sent to my mobile phone and watch it wherever I am.
Bicycle commuting, and using a bicycle as one’s main mode of transportation in general, is an interesting thing. Before starting to do it on a regular basis, it seemed so mysterious. How does one handle rain? Snow? What about transporting large or oddly-shaped objects? What about really hot weather? Do you shower when you arrive?
