These are the Python implementations of FIFO, LRU and OPT page replacement algorithms
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Updated
Jan 25, 2018 - Python
These are the Python implementations of FIFO, LRU and OPT page replacement algorithms
Memory management simulator, using Hashed Page Table. Page Replacement Algorithms: Least Recently Used (LRU) and Second Chance.
A low-latency LRU approximation cache in C++ using CLOCK second-chance algorithm. Multi level cache too. Up to 2.5 billion lookups per second.
Simulation of Virtual Memory Paging Algorithms
A C program that simulates an L1 cache. Uses the Least Recently Used replacement policy. Set associative.
A threadsafe map-like container implementing a least-recently-used cache
Implementation of some advanced caching policies
"Implementation of Virtual Memory available in operating systems"
golang-lru,simple switching between LRU,Cache,TwoQueueCache and ARCCache.
Simple implementation of LRU in Python.
Implementation and comparison of various caching policies, on different type of workloads
A configurable two-level cache (for caching Objects). Level 1 is memory, level 2 is filesystem. One can specify cache strategies and max sizes of both levels 1 and 2. Three cache replacement policies have been set: Least Frequently Used, Least Recently Used, Most Recently Used.
Asynchronous cache that implements Least Recently Used (LRU) - Clock - Second Chance algorithm with O(1) hit O(1) miss complexity. This Async cache hides latency of cache-misses behind each other and behind cache-hits.
LRU Stands for Least Recently Used and LRU Cache help identify the least recently used items in a System.
High performing caching package for node/javascript
A thread-safe, hash-mapped LRU cache instance
A direct-mapped cache for variable-length arrays with least recently used replacement and static allocation.
Cashed is an LRU based caching service written in plain c.
Page replacement algorithms for memory management in operating systems
A straightforward implementation of a least recently used (LRU) cache using JavaScript's Map 🗺️
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