Profiling Python code in terms of CPU Cycles (or similar) rather than time? ie universal profiling?












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I appreciate that Python has a range of profiling packages available (CProfile, LineProfiler etc) which give a useful breakdown of code execution times on a line-by-line basis.



However, all these tools seem to use execution time as the metric, which unfortunately varies depending on which computer the profiler is run on, and indeed, on other background tasks that may be running too.



Is there are way to achieve "universal profiling" in some sort of more global metric. Perhaps number of cycles per instruction?



I appreciate different computers have very different architectures and the slow-down may be in different components (memory access, CPU etc.), but is there any other approach for profiling and optimizing code other than relying on time?



Thanks!










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    0















    I appreciate that Python has a range of profiling packages available (CProfile, LineProfiler etc) which give a useful breakdown of code execution times on a line-by-line basis.



    However, all these tools seem to use execution time as the metric, which unfortunately varies depending on which computer the profiler is run on, and indeed, on other background tasks that may be running too.



    Is there are way to achieve "universal profiling" in some sort of more global metric. Perhaps number of cycles per instruction?



    I appreciate different computers have very different architectures and the slow-down may be in different components (memory access, CPU etc.), but is there any other approach for profiling and optimizing code other than relying on time?



    Thanks!










    share|improve this question

























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      0








      I appreciate that Python has a range of profiling packages available (CProfile, LineProfiler etc) which give a useful breakdown of code execution times on a line-by-line basis.



      However, all these tools seem to use execution time as the metric, which unfortunately varies depending on which computer the profiler is run on, and indeed, on other background tasks that may be running too.



      Is there are way to achieve "universal profiling" in some sort of more global metric. Perhaps number of cycles per instruction?



      I appreciate different computers have very different architectures and the slow-down may be in different components (memory access, CPU etc.), but is there any other approach for profiling and optimizing code other than relying on time?



      Thanks!










      share|improve this question














      I appreciate that Python has a range of profiling packages available (CProfile, LineProfiler etc) which give a useful breakdown of code execution times on a line-by-line basis.



      However, all these tools seem to use execution time as the metric, which unfortunately varies depending on which computer the profiler is run on, and indeed, on other background tasks that may be running too.



      Is there are way to achieve "universal profiling" in some sort of more global metric. Perhaps number of cycles per instruction?



      I appreciate different computers have very different architectures and the slow-down may be in different components (memory access, CPU etc.), but is there any other approach for profiling and optimizing code other than relying on time?



      Thanks!







      python python-3.x optimization profiling






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      asked Nov 24 '18 at 22:44









      SFlowtYSFlowtY

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