I am about to embark in very detailed benchmarking of a set of complex functions in C. This is "science level" detail. I'm wondering, what would be the best way to do serious benchmarking? I was thinking about running them, say, 10 times each, averaging the timing results and give the standard dev, for instance, just using <time.h>. What would you guys do to obtain good benchmarks?
Reporting an average and standard deviation gives a good description of a distribution when the distribution in question is approximately normal. However, this is rarely true of computational performance measurements. Instead, performance measurements tend to more closely resemble a poisson distribution. This makes sense, because not many random events on a computer will cause a program to go faster; essentially all of the measurement noise is in how many random events occur that cause it to slow down. (A normal distribution, by contrast, makes no intuitive sense at all; it would require the belief that a program has a non-zero probability of finishing in negative time).
In light of this, I find it most useful to report the minimum time over many runs of a program, rather than the average; the noise in the distribution is typically noise of the measuring system, rather than meaningful information about the algorithm. For complex algorithms that have early out conditions, and other shortcuts, you need to be a little more careful, but the minimum of many runs where each run handles a representative balance of inputs usually works well.
"10 times each" sounds like very few iterations to me. I generally do something on the order of thousands (or more, depending on the function/system) of runs unless that's completely infeasible. At a bare minimum, you need to make sure that you run the timing for sufficiently long as to shake out any dependence on system state, some of which may change at fairly large time granularity.
The other thing you should be aware of is that essentially every system has a platform-specific timer available that is much more accurate than what is available <time.h>. Find out what it is on your target platform[s] and use it instead.
I am assuming you are looking at benchmarking pure Algorithmic computation in your program and there is no user input or output which can take unpredictable time. Now for purely number crunching programs, your results could vary based on the time your program actually runs which will be impacted by other ongoing activities in the system. There could be other factor which you may choose to ignore depending upon level of accuracy desired i.e. impact due to cache miss, different access time through the memory hierarchy" One of the methods is as you suggested calculation average over a number of runs. Or you could try to look at the assembly code and see the instructions generated. And then based on the processor get the cycle count for these instructions. This method may not be practical depending on the amount of code you are looking to benchmark. If you are particular about memory hierarchy impact then you may want to control execution environment very carefully i.e. where program is loaded, where its data is loaded etc. But as I mentioned depending on the accuracy desired, you may absorb the variation caused due to memory hierarchy in you statistical variation" . You may need to carefully design the test input for you functions to ensure the path coverage and may choose to publish statistics of performance as a function of test input. This will show how function behaves across range of inputs
来源：https://stackoverflow.com/questions/4532536/how-to-do-good-benchmarking-of-complex-functions