Why would GetMessageW take up massive CPU usage in my WPF application?

Question

I\'ve got a serious head-scratcher on my hands here. I\'m investigating performance issues with a WPF component in our application.

Our .net application is very large,

Answer 1

When profiling an application, you need to differentiate between time spent in a method and CPU cycles consumed. Many profiling tools show you the overall time spent in a method - which in the case of somthing like GetMessageW is going to be quite high. All of the activity of the main thread of a GUI application will appear to happen within that method. That's not necessarily a problem, however ... this may simply be the main message pump waiting on a synchronization objects and not actually consuming cycles.

I would suggest you start by using the sampling feature in the ANTS profiler to identify the methods that are called most often and correlate those to the methods that are consuming the most CPU cycles. Once you've done that, you decide where to instrument your application to dive in further and get an idea of what the call graphs look like for the places that are most CPU intensive.

You should start by suspecting your own code first. It's rare that something like the WPF or Win32 infrastructure is responsible for poor performance or high CPU utilization. Likely, the problem lies somewhere in your implementation - it helps you get an overall sense of where CPU cycles are spent in your program.

I suggest that you also spend some time learning the capabilities of the profiler to be most effective. Profilers can be sophisticated and confusing tools until you understand what it is that they are trying to show you. The linked tutoral from RedGate should be a good place to start, if you haven't done so already. For example, the Timeline view may actually be a good place to start to see where high-CPU activity is occurring, and confining your analysis to those segments of executed code.

The Call Graph is another useful tool in ANTS, as it helps you drill into areas of the code that are most expensive. The key is to make sure you are looking at the overall cost and not just the overall time.