On Wed, 20 Jan 2016, Daniel Lezcano wrote: [...] One more comment:
> + /* > + * If the mean value is null, just ignore this wakeup > + * source. > + */ > + mean = stats_mean(&w->stats); > + if (!mean) > + continue; > + > + variance = stats_variance(&w->stats, mean); > + /* > + * We want to check the last interval is: > + * > + * mean - stddev < interval < mean + stddev > + * > + * That simplifies to: > + * > + * -stddev < interval - mean < stddev > + * > + * abs(interval - mean) < stddev > + * > + * The standard deviation is the sqrt of the variance: > + * > + * abs(interval - mean) < sqrt(variance) > + * > + * and we want to prevent to do an sqrt, so we square > + * the equation: > + * > + * (interval - mean)^2 < variance > + * > + * So if the latest value of the stats complies with > + * this condition, then the wakeup source is > + * considered predictable and can be used to predict > + * the next event. > + */ > + interval = w->stats.values[w->stats.w_ptr]; > + if ((u64)((interval - mean) * (interval - mean)) > variance) > + continue; > + > + /* > + * Let's compute the next event: the wakeup source is > + * considered predictable, we add the average interval > + * time added to the latest interruption event time. > + */ > + next = ktime_add_us(w->timestamp, stats_mean(&w->stats)); You don't need to call stats_mean() again as you have it in the 'mean' variable already. Nicolas
