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Cache replacement algorithms are used to optimize the time taken by processor to process the information by storing the information needed by processor at that time and possibly in future so that if processor needs that information, it can be provided immediately. There are a number of techniques (LIFO, FIFO, LRU, MRU, Hybrid) used to organize information in such a way that processor remains busy almost all the time. But there are some limitations of every technique. We tried to overcome those limitations. We used Probabilistic Graphical Model(PGM), which gives conditional dependency between random variables using directed or undirected graph. In our research, we exploited the Bayesian network technique to predict the future request by processor. The main goal of the research was to increase the cache hit rate but not by increasing the size of cache and also reducing or maintaining the overhead. We achieved 7% more cache hits in best case scenario than those classical algorithms by using PGM technique. This proves the success of our technique as far as cache hits are concerned. Also, pre-eviction proves to be a better technique to get more cache hits. Combining both pre-eviction and pre-fetching using PGM gives us the results which were intended to achieve as the sole purpose of this research.
Given an undirected, weighted graph, the minimum spanning tree (MST) is a tree that connects all of the vertices of the graph with minimum sum of edge weights. In real world applications, network designers often seek to quickly find a replacement edg
Program execution speed critically depends on increasing cache hits, as cache hits are orders of magnitude faster than misses. To increase cache hits, we focus on the problem of cache replacement: choosing which cache line to evict upon inserting a n
A mesh is a graph that divides physical space into regularly-shaped regions. Meshes computations form the basis of many applications, e.g. finite-element methods, image rendering, and collision detection. In one important mesh primitive, called a mes
This report describes an implementation of a non-blocking concurrent shared-memory hash trie based on single-word compare-and-swap instructions. Insert, lookup and remove operations modifying different parts of the hash trie can be run independent of
Graph search is one of the most successful algorithmic trends in near neighbor search. Several of the most popular and empirically successful algorithms are, at their core, a simple walk along a pruned near neighbor graph. Such algorithms consistentl