Performance and profiling of OpenMP C++ code in VS107











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I have a performance critical piece of C++ code running in Visual Studio 2017 that I've been profiling to look for potential bottlenecks. The profiler at a high level shows about 80% CPU usage across my eight cores executing this code. Having loaded in all the kernel symbols, the profiler shows that the busiest function is NTYieldExecution at 52% usage.
NTYieldExecution My guess is that this 52% is not correct, possibly 52% of one thread, but even then I'd be keen to know what's going on under the hood. I also have my own thread pool code which lead to 100% CPU usage on other code, so I'm wondering whether to move this code to an alternative multi-threading model. OpenMP is very convenient, but is it inefficient in Visual Studio 2017? More importantly, is it possible to isolate and remove any such inefficiencies?






c++ visual-studio-2017 openmp







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  • This call stack looks very strange. It does not seem to contain your code at all. Time spent in openmp runtime or in system libraries.
    – VTT
    Nov 7 at 10:41












  • @VTT, it doesn't, which is what leads me to suspect that OpenMP on Visual Studio 2017 may be taking a separate thread of its own, or at least significant CPU usage. That said, the section of call tree which includes my own code is listed as 14.5% usage, which I also suspect is totally incorrect. I know this because if I run the same code without OMP enabled it is about 5-6 times slower.
    – SmacL
    Nov 7 at 10:58















up vote
0
down vote

favorite












I have a performance critical piece of C++ code running in Visual Studio 2017 that I've been profiling to look for potential bottlenecks. The profiler at a high level shows about 80% CPU usage across my eight cores executing this code. Having loaded in all the kernel symbols, the profiler shows that the busiest function is NTYieldExecution at 52% usage.
NTYieldExecution My guess is that this 52% is not correct, possibly 52% of one thread, but even then I'd be keen to know what's going on under the hood. I also have my own thread pool code which lead to 100% CPU usage on other code, so I'm wondering whether to move this code to an alternative multi-threading model. OpenMP is very convenient, but is it inefficient in Visual Studio 2017? More importantly, is it possible to isolate and remove any such inefficiencies?






c++ visual-studio-2017 openmp







share|improve this question






















  • This call stack looks very strange. It does not seem to contain your code at all. Time spent in openmp runtime or in system libraries.
    – VTT
    Nov 7 at 10:41












  • @VTT, it doesn't, which is what leads me to suspect that OpenMP on Visual Studio 2017 may be taking a separate thread of its own, or at least significant CPU usage. That said, the section of call tree which includes my own code is listed as 14.5% usage, which I also suspect is totally incorrect. I know this because if I run the same code without OMP enabled it is about 5-6 times slower.
    – SmacL
    Nov 7 at 10:58













up vote
0
down vote

favorite









up vote
0
down vote

favorite











I have a performance critical piece of C++ code running in Visual Studio 2017 that I've been profiling to look for potential bottlenecks. The profiler at a high level shows about 80% CPU usage across my eight cores executing this code. Having loaded in all the kernel symbols, the profiler shows that the busiest function is NTYieldExecution at 52% usage.
NTYieldExecution My guess is that this 52% is not correct, possibly 52% of one thread, but even then I'd be keen to know what's going on under the hood. I also have my own thread pool code which lead to 100% CPU usage on other code, so I'm wondering whether to move this code to an alternative multi-threading model. OpenMP is very convenient, but is it inefficient in Visual Studio 2017? More importantly, is it possible to isolate and remove any such inefficiencies?






c++ visual-studio-2017 openmp







share|improve this question













I have a performance critical piece of C++ code running in Visual Studio 2017 that I've been profiling to look for potential bottlenecks. The profiler at a high level shows about 80% CPU usage across my eight cores executing this code. Having loaded in all the kernel symbols, the profiler shows that the busiest function is NTYieldExecution at 52% usage.
NTYieldExecution My guess is that this 52% is not correct, possibly 52% of one thread, but even then I'd be keen to know what's going on under the hood. I also have my own thread pool code which lead to 100% CPU usage on other code, so I'm wondering whether to move this code to an alternative multi-threading model. OpenMP is very convenient, but is it inefficient in Visual Studio 2017? More importantly, is it possible to isolate and remove any such inefficiencies?






c++ visual-studio-2017 openmp




c++ visual-studio-2017 openmp






share|improve this question













share|improve this question











share|improve this question




share|improve this question










asked Nov 7 at 10:24









SmacL

16.4k1075137




16.4k1075137












  • This call stack looks very strange. It does not seem to contain your code at all. Time spent in openmp runtime or in system libraries.
    – VTT
    Nov 7 at 10:41












  • @VTT, it doesn't, which is what leads me to suspect that OpenMP on Visual Studio 2017 may be taking a separate thread of its own, or at least significant CPU usage. That said, the section of call tree which includes my own code is listed as 14.5% usage, which I also suspect is totally incorrect. I know this because if I run the same code without OMP enabled it is about 5-6 times slower.
    – SmacL
    Nov 7 at 10:58


















  • This call stack looks very strange. It does not seem to contain your code at all. Time spent in openmp runtime or in system libraries.
    – VTT
    Nov 7 at 10:41












  • @VTT, it doesn't, which is what leads me to suspect that OpenMP on Visual Studio 2017 may be taking a separate thread of its own, or at least significant CPU usage. That said, the section of call tree which includes my own code is listed as 14.5% usage, which I also suspect is totally incorrect. I know this because if I run the same code without OMP enabled it is about 5-6 times slower.
    – SmacL
    Nov 7 at 10:58
















This call stack looks very strange. It does not seem to contain your code at all. Time spent in openmp runtime or in system libraries.
– VTT
Nov 7 at 10:41






This call stack looks very strange. It does not seem to contain your code at all. Time spent in openmp runtime or in system libraries.
– VTT
Nov 7 at 10:41














@VTT, it doesn't, which is what leads me to suspect that OpenMP on Visual Studio 2017 may be taking a separate thread of its own, or at least significant CPU usage. That said, the section of call tree which includes my own code is listed as 14.5% usage, which I also suspect is totally incorrect. I know this because if I run the same code without OMP enabled it is about 5-6 times slower.
– SmacL
Nov 7 at 10:58




@VTT, it doesn't, which is what leads me to suspect that OpenMP on Visual Studio 2017 may be taking a separate thread of its own, or at least significant CPU usage. That said, the section of call tree which includes my own code is listed as 14.5% usage, which I also suspect is totally incorrect. I know this because if I run the same code without OMP enabled it is about 5-6 times slower.
– SmacL
Nov 7 at 10:58

















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