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QCoreApplication mini benchmark

Published on Tuesday August 14, 2012 by Harald Fernengel in Performance Qt | Comments

For robustness and security reasons, it often makes sense to split functionality into various smaller binaries (daemons) rather than having a few big and monolithic applications.

Qt 4 introduced modularized Qt libraries in order to enable Qt based daemons that don't require any GUI. Thanks to the strong embedded focus and several sane architecture decisions, Qt 5 brings this to a new level.

Let's look at some simple main function:

QCoreApplication app(argc, argv);
QTimer::singleShot(3000, &app, SLOT(quit()));
return app.exec();

This non-gui Qt app idles for about 3 seconds, then quits.

On my vanilla i386 Kubuntu 12.04 with Qt 4.8.1, valgrind's massif tool reports a peak heap memory usage of around 102 kb, while callgrind reports an instruction cost of about 1.9 million (*).

Let's have a look at the numbers from today's build of Qt 5: Massif reports a peak heap of 4.9 kb and callgrind reports an instruction cost of about 114k.

This means that Qt 5 uses about 20 times less memory and about 16 times less instructions to construct a QCoreApplication and spin an event loop.

There are several reasons for that. Most notably, Qt 5 assumes that all strings are unicode, so the initialization of text conversion codecs only happens when the first non-unicode string comes along. Even though Qt 5 has vastly improved plugin loading performance, not loading them is even faster :)

Various other improvements also add up, e.g. the C++11 support in Qt 5 means that we require no allocation to create unicode QString objects and moving objects around also got cheaper.

In summary, have fun writing Qt 5 based daemons, and if you have any idea how to make the code even more performant, we'll see you at Qt's codereview :)

(*) Disclaimer: The instruction cost does not show how fast the code is, but how many instructions were processed by the CPU. Note that in all cases I only measured the performance of main(), ignoring the overhead of the OS's symbol and library resolving, as that can be optimized with prelinking or forking from a master process.

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