criterion performance measurements

overview

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programs/factor/fully optimized

lower bound estimate upper bound
OLS regression xxx xxx xxx
R² goodness-of-fit xxx xxx xxx
Mean execution time 1.6933639628485406e-2 1.711936550696215e-2 1.7489211941600434e-2
Standard deviation 3.135524105229344e-4 6.322347584149133e-4 1.0624820498027136e-3

Outlying measurements have moderate (0.12196060387964654%) effect on estimated standard deviation.

programs/factor/not optimized

lower bound estimate upper bound
OLS regression xxx xxx xxx
R² goodness-of-fit xxx xxx xxx
Mean execution time 5.804821413189681e-2 5.926256812723066e-2 6.305990096324315e-2
Standard deviation 1.0242274026527002e-3 3.4008881405907963e-3 5.7598324895296316e-3

Outlying measurements have moderate (0.15568388072838413%) effect on estimated standard deviation.

programs/allfeatures/fully optimized

lower bound estimate upper bound
OLS regression xxx xxx xxx
R² goodness-of-fit xxx xxx xxx
Mean execution time 1.0271521463795171e-5 1.0414946090376135e-5 1.0814166114448921e-5
Standard deviation 2.4224785236493634e-7 7.45958036773968e-7 1.4958553133201985e-6

Outlying measurements have severe (0.7618404965187816%) effect on estimated standard deviation.

programs/allfeatures/not optimized

lower bound estimate upper bound
OLS regression xxx xxx xxx
R² goodness-of-fit xxx xxx xxx
Mean execution time 3.852995372032881e-5 3.911661804328012e-5 4.084722689129049e-5
Standard deviation 1.288325312751046e-6 3.0679844671798198e-6 5.994192366888955e-6

Outlying measurements have severe (0.7609261830317536%) effect on estimated standard deviation.

understanding this report

In this report, each function benchmarked by criterion is assigned a section of its own. The charts in each section are active; if you hover your mouse over data points and annotations, you will see more details.

Under the charts is a small table. The first two rows are the results of a linear regression run on the measurements displayed in the right-hand chart.

We use a statistical technique called the bootstrap to provide confidence intervals on our estimates. The bootstrap-derived upper and lower bounds on estimates let you see how accurate we believe those estimates to be. (Hover the mouse over the table headers to see the confidence levels.)

A noisy benchmarking environment can cause some or many measurements to fall far from the mean. These outlying measurements can have a significant inflationary effect on the estimate of the standard deviation. We calculate and display an estimate of the extent to which the standard deviation has been inflated by outliers.