Editing Cache replacement policies (section)

==== Mockingjay ====
Mockingjay<ref>{{Cite journal |last1=Shah |first1=Ishan |last2=Jain |first2=Akanksha |last3=Lin |first3=Calvin |date=April 2022 |title=Effective Mimicry of Belady's MIN Policy |journal=HPCA}}</ref> tries to improve on Hawkeye in several ways. It drops the binary prediction, allowing it to make more fine-grained decisions about which cache lines to evict, and leaves the decision about which cache line to evict for when more information is available.

Mockingjay keeps a sampled cache of unique accesses, the PCs that produced them, and their timestamps. When a line in the sampled cache is accessed again, the time difference will be sent to the reuse distance predictor. The RDP uses temporal difference learning,<ref>{{Cite journal |last=Sutton |first=Richard S. |date=1988-08-01 |title=Learning to predict by the methods of temporal differences |journal=Machine Learning |language=en |volume=3 |issue=1 |pages=9–44 |doi=10.1007/BF00115009 |s2cid=207771194 |issn=1573-0565|doi-access=free }}</ref> where the new RDP value will be increased or decreased by a small number to compensate for outliers; the number is calculated as <math>w = \min\left(1, \frac{\text{timestamp difference}}{16}\right)</math>. If the value has not been initialized, the observed reuse distance is inserted directly. If the sampled cache is full and a line needs to be discarded, the RDP is instructed that the PC that last accessed it produces streaming accesses.

On an access or insertion, the estimated time of reuse (ETR) for this line is updated to reflect the predicted reuse distance. On a cache miss, the line with the highest ETR value is evicted. Mockingjay has results which are close to the optimal Bélády's algorithm.