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Home/ Questions/Q 3390538
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Editorial Team
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Editorial Team
Asked: May 18, 20262026-05-18T03:42:12+00:00 2026-05-18T03:42:12+00:00

I have some heavily templated c++ code that I am working with. I can

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I have some heavily templated c++ code that I am working with. I can compile and profile with AMD tools and sleepy in debug mode. However without optimisation most of time spent concentrated in the templated code and STL. With optimised compilation, all the profile tools that I know produce garbage information. Does anybody know a good way to profile optimised native code

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The code that I am writing is also heavily templated. Most of the time spent in the unoptimised code will be optimized away. I am talking about 96-97% of the run time are spent in templated code without optimisation. This is going to corrupt the accuracy of the profiling. And yes I can change many templated code or at least what part of the templated code is introducing the most trouble and I can do better in those places.

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  1. Editorial Team
    Editorial Team
    2026-05-18T03:42:13+00:00Added an answer on May 18, 2026 at 3:42 am

    You should focus on the code you wrote because that is what you can change, time spent in STL is irrelevant, just ignore it and focus on the callers of that code. If too much time is spent in STL you probably can call some other STL primitive instead of the current one.

    Profiling unoptimized code is less interesting, but you can still get some informations. If used algorithms from some parts of code are totally flawed it will show up even there. But you should be able to get useful informations from any good profiling tool in optimized code. What tools do you use exactly and why do you call their output garbage ?

    Also it’s usually easy enough to instrument your code by hand and find out exactly which parts are efficient and which are not. It’s just a matter of calling timer functions (or reading cycle count of processor if possible) at well chosen points. I usually do that from unit tests to have reproducible results, but all depends of the specifics of your program.

    Tools or instrumenting code are the easy part of optimization. The hard part is finding ways to get faster code where it’s needed.

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