sharkdp
Support for running a number of times that is not determined in advance
Hi!
Suppose that I am trying to optimize a tool and I want to have a precise view of the performance impact of a given change. I can use hyperfine to compare a run of the tool with a run of a modified version of the tool, and it detects the number of iterations to perform automatically according to the duration of the first run. However, I may or may not be happy with this number of iterations, depending on how the comparison turns out to be. If it's very clear after 3 runs of each that the change improves/degrades performance a lot, I can just stop. If it's not clear but I am still interested in a precise measure, I will want to run more, say 50, so that the statistical variations average out to give a more precise value of the mean. Before discovering hyperfine, I was using a hand-made tool that runs the processes alternatively (relates to #21), and prints the standard error of the mean live (N.B. not standard deviation, cf. https://en.wikipedia.org/wiki/Standard_error; I think the "σ" value hyperfine prints is the standard deviation?), allowing me to stop when I am happy with the significance of the comparison.
This feature request is a superset of #21: in addition to alternating the runs, it would mean printing an error estimate while benchmarking too (not only the mean estimate like hyperfine currently does), and supporting a mode where benchmarking never stops until interrupted by Ctrl-C (I guess this would only differ from -r 1000000 by not printing something similar to "run x out of 1000000).
Thanks for this tool, and thanks for your interest.
Thank you for your request. This sounds like a very useful feature. Any help in designing the details of this (CLI, implementation idea, …) would be very much appreciated
