High performing caching package for node/javascript
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Updated
May 13, 2024 - TypeScript
High performing caching package for node/javascript
"Implementation of Virtual Memory available in operating systems"
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.
Trace-driven cache memory simulator with LRU, MRU, RR and Belady replacement policies.
In-memory LRU Cache implementation using multiple Design Patterns
Template implementation of a dynamically memory allocated linked list cache using the least recently used (LRU) algorithm.
This is an implementation of the Least Recently Used (LRU) page replacement algorithm.
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.
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.
Implementation and comparison of various caching policies, on different type of workloads
Cashed is an LRU based caching service written in plain c.
Page replacement algorithms for memory management in operating systems
Dump for all Operating System Lab Codes
This repository contains the Python Programs for various algorithms of Operating Systems
Java based cache implementations
"Least Recently Used" (LRU) cache compatible to ES6 Map
LRU Stands for Least Recently Used and LRU Cache help identify the least recently used items in a System.
A thread-safe, hash-mapped LRU cache instance
Memory management simulator, using Hashed Page Table. Page Replacement Algorithms: Least Recently Used (LRU) and Second Chance.
Thread-safe LRU cache implementation
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