Reply To: Can branch predictors perfectly predict counting loops?

I am not sure that my specific question has been answered. I am wondering if it is conceivable that there could be a mechanism whereby data from the running program that indicates how many iterations the loop plans on doing could be shipped over to the predictor. I know it often runs on historical data, but my question is whether “live” data could be used to override the history-based prediction. E.g. let’s say I have a loop that is supposed to run 5 times, this time. Maybe it ran 10 times last time. For simplicity let’s say I can only run one iteration of the loop at a time, and each iteration takes 4 cycles. So we know the loop will run for 20 cycles, then exit. We know we are going to run the loop 5 times because there is a counter on the belt with 5 in it. Because the loop is running for longer than the pipeline length of 5 cycles, we can send some live data over to the predictor and tell it, “when I sent the value, we had 5 iterations left to go”. Now because X cycles must have passed since that value was sent, maybe we have 4 iterations left to go, but still, the predictor now knows with certainty when an exit should occur, right? This could potentially be a side effect to some of the Mill’s loop-specific instructions. My apologies if this is completely untenable to implement, I do not know the pains of designing hardware.