This week in Dune performance testing

I started my project of bringing performance measuring to DUNE almost a month ago. Unfortunately I was attending a physics summer school in Cambridge for two weeks, so I didn’t have any results to write about yet. Now I managed to put together the first week of actual work.

So far, it is possible to measure the running time of any external command, as well as some other data like memory consumption and CPU utilization. These measurements, together with information about the host computer, are then stored in a temporary log file. Plain text log file are not very useful for comparisons and finding trends, so I started on a kind of a toolchain. A measurement is first stored in a log file, then a second program reads the contents of the file and stores them into a SQL database, and finally a third script read the values from the database and outputs an HTML file with tables and charts.

The separation into three separate Python programs/modules is done so that only the first part has to be run locally. A user could thus measure the performance of DUNE and his own programs without installing a bunch of dependencies, which are needed for database operations and visualization.

So far, the first part (measurement) pretty much works. I only say “pretty much” because we will probably decide to add more measured data later. The second part (database) is a little behind, because I want to first decide on the data entry format and at least most of the measured fields. These are details such as whether to store maximum or average RAM usage, or maybe both. Otherwise, interfacing with a SQLite3 database is pretty straightforward and I don’t anticipate any troubles here. I have only just started on the third, visualization part. This one is the most flexible (and the most fun), so it’s hard to tell how long it will take. I created a couple of HTML template files, and am now adding the programmatic part of reading from the DB and displaying the data.

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