First, consider a 4-bit counter with two adjustable thresholds (Figure 12). When Count is greater than High Threshold, Algorithm A is deemed appropriate; the same is true concerning Algorithm B and Count less than Low Threshold.
For the range between High Threshold and Low Threshold, either algorithm may be in effect. This is because a switch from Algorithm B to Algorithm A will occur only with Count greater than High Threshold and increasing and a switch from Algorithm A to Algorithm B will occur only with Count less than Low Threshold and decreasing.
The overlap range is also the Target Range as the system will naturally attempt to maintain Counter between these two points. This is true since Algorithm A tends to lower Count while Algorithm B tends to raise Count. This system acts to reduce or eliminate rapid thrashing between algorithms.
Figure 12. Another way of looking at this: if the MSB of Count is a 1, then the page close policy is too loose
Next, define a truth table (Figure 13) defining how Count will vary. By doing so we can encode a feedback mechanism into our system. Successful predictions by the Adaptive Page Close Logic - a prevented page-miss access (good) in response to a decision to close a page or a facilitated page-hit access (good) in response to a decision to leave a page open - suggest no change to policy is required and so never modify Count.
For a facilitated page-miss access (bad) due to a poor decision to leave a page open, increment Count. If Count were to trend upward we could conceivably conclude that the current policy was most often wrong and not only that, tended to leave pages open far too long while "fishing" for page-hit operations. The current algorithm must not be closing pages aggressively enough.
For a prevented page-hit access (bad) due to a poor decision to close a page early, decrement Count. If Count were to trend downward we would suspect the opposite: the algorithm is too aggressively closing pages and leaving potential page-hits on the cutting room floor.
Figure 13. The policy is controlling just right whenever we reduce the number of page-miss operations and increase the number of page-hit operations
As best we can tell, this construct represent reality for APM Technology. Although we would like to believe the system has more than two gears (algorithms), our model perfectly explains the existing control register both in type and number.
Looking ahead you will see Max Page Close Limit and Min Page Close Limit are the specified High and Low Threshold values, respectively. Setting a larger difference increases the size of the feedback dead band, slowing the rate at which system responds to its own evaluative efforts. Mistake Counter is represented by the starting Count and should be set somewhere near the middle of the dead band.
Adaptive Timeout Counter sets the assertion time of any decision to keep a page open (i.e. how long before the decision to keep a page open stands before we give up hope of a page-hit access). Repeated access to the same page will reset this counter each time as long as the remaining lifetime is non-zero. Lower values result in a more aggressive page close policy and vice versa for higher values.
Request Rate, we believe, controls how often Count (Mistake Counter) is updated, and therefore how smoothly the system adapts to quickly changing workloads. There must be a good reason not to flippantly set this interrupt rate as low as possible. Perhaps this depletes hardware resources needed for other operations or maybe higher duty cycles disproportionally raises power consumption. Whatever the reason, there's more than a fair chance you can hurt performance if you're just spit-balling with this setting.
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