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Qtopia Core Performance Tuning

When building embedded applications on low-powered devices, a number of options are available that are not relevant for desktop applications. These options reduce the memory and/or CPU requirements by making various trade-offs.

The most direct way of saving resources is to avoid compiling in features that are not required. See The Feature Definition File for details.

General Programming Style

The following guidelines will improve CPU performance:

Static vs. Dynamic Linking

A lot of CPU and memory is used by the ELF linking process. You can make significant savings by using a static build of your application suite. This means that rather than having dynamic Qt libraries and a collection of executables which link dynamically to these libraries, you build all the applications into a single executable and statically link that with static Qt libraries. This improves start-up time, and reduces memory usage, at the expense of flexibility (to add a new application, you must recompile the single executable) and robustness (if one application has a bug, it might harm other applications). If you need to install end-user applications, this may not be an option, but if you are building a single application suite for a device with limited CPU power and memory, this option could be very beneficial.

To compile Qt as a static library, use the -static option when you run configure.

To build your application suite as an all-in-one application, design each application as a stand-alone widget or set of widgets, with only minimal code in the main() function. Then, write an application that provides a means of switching between the applications (e.g. a QIconView). The Qtopia is an example of this. It can be built either as a set of dynamically linked executables, or as a single static application.

Note that you should generally still link dynamically against the standard C library and any other libraries which might be used by other applications on your device.

Alternative Memory Allocation

We have found that the libraries shipped with some C++ compilers on some platforms have poor performance in the built-in "new" and "delete" operators. You might gain performance by re-implementing these functions. For example, you can switch to the plain C allocators by adding the following to your code:

    void *operator new[](size_t size)
    {
        return malloc(size);
    }

    void *operator new(size_t size)
    {
        return malloc(size);
    }

    void operator delete[](void *ptr)
    {
        free(ptr);
    }

    void operator delete[](void *ptr, size_t)
    {
        free(ptr);
    }

    void operator delete(void *ptr)
    {
        free(ptr);
    }

    void operator delete(void *ptr, size_t)
    {
        free(ptr);
    }


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