Hi,
Could soumeone explain me why the methods CPU Times are allways different when succesive profilings are made for the same application on the same conditions?
I'm running on Windows Xp, and I tried both sampling and tracing profiling methods.
Thank you.
Difference between the methods CPU Times
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Are the methods purely computational?
In order to answer:
All I want to measure is the execution time of an iterative optimization algorithm under different optimization scenarios.
There are small differences between these scenarios.
So I need a quite accurate execution times measurments.
I can tell you that after each iteration there is a routine the writes same data into a buffer and when the algorithm stops the buffer is written into an output file.
Do you think that this may cause differences between the profiled times?
If this represents the problem...could you suggest me how to use the profiler?
If I ignored these methods for being profiled could I obtain more accurate results?
Thank you!
In order to answer:
All I want to measure is the execution time of an iterative optimization algorithm under different optimization scenarios.
There are small differences between these scenarios.
So I need a quite accurate execution times measurments.
I can tell you that after each iteration there is a routine the writes same data into a buffer and when the algorithm stops the buffer is written into an output file.
Do you think that this may cause differences between the profiled times?
If this represents the problem...could you suggest me how to use the profiler?
If I ignored these methods for being profiled could I obtain more accurate results?
Thank you!
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- Posts: 6172
- Joined: Wed Aug 11, 2004 8:37 am
File output can be one of reasons of execution time fluctuations.
If need most accurate results, you can:
1. Artificially increase number of repetitions of your algorithm for purposes of profiling. E.g. wrap it with a 'for' cycle. The bigger execution time, the smaller share of stochastic fluctuations.
2. For a more precise measuring, use tracing. Although it may be requires to tune filter set to receive most adequate results.
If need most accurate results, you can:
1. Artificially increase number of repetitions of your algorithm for purposes of profiling. E.g. wrap it with a 'for' cycle. The bigger execution time, the smaller share of stochastic fluctuations.
2. For a more precise measuring, use tracing. Although it may be requires to tune filter set to receive most adequate results.