(likely to be evicted sooner). The RRIP backend is the part that does the actual eviction decisions. The sampled cache and OPT generator are only used to set the initial RRPV value of the inserted cache lines. Hawkeye won the CRC2 cache championship in 2017, beating all other cache replacement policies at the time. Harmony is an extension of Hawkeye that improves prefetching performance. Mockingjay Mockingjay tries to improve upon Hawkeye in multiple ways. First, it drops the binary prediction, allowing it to make more fine grained decisions about which cache lines to evict. Second, it leaves the decision about which cache line to evict later on, after more information is available. It achieves this by keeping a sampled cache of unique accesses, the PCs that produced them and their timestamps. When a line in the sampled cache gets accessed again, the difference in time will be sent to the Reuse Distance Predictor, which uses Temporal Difference Learning, where the new RDP vale will be incremented or decremented by a small number to compensate for outliers. The number is calculated as . Except when the value has not been initialized, in which case the observed reuse distance is inserted directly. If the sampled cache is full, and we need to throw away a line, we train the RDP 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. Every few accesses to the set, decrement all the ETR counters of the set (which can fall into the negative, if not accesses past their estimated time of reuse). On a cache miss, the line with the highest absolute ETR value is evicted (The line which is estimated to be reused farthest in the future, or has been estimated to be reused farthest in the past and hasn't been reused). Mockingjay achieves results that are very close to the optimal Bélády's algorithm, typically within only a few percent performance difference. Cache replacement policies using machine learning Multiple cache replacement policies have attempted to use perceptrons, markov chains or other types of machine learning to predict while line to evict. There are also learning augmented algorithms for the cache replacement problem. Other cache replacement policies Low inter-reference recency set (LIRS) LIRS is a page replacement algorithm with an improved performance over