Related papers: An O(1) algorithm for implementing the LFU cache e…
This paper presents a comprehensive comparison of distributed caching algorithms employed in modern distributed systems. We evaluate various caching strategies including Least Recently Used (LRU), Least Frequently Used (LFU), Adaptive…
Modern processors use cache memory: a memory access that "hits" the cache returns early, while a "miss" takes more time. Given a memory access in a program, cache analysis consists in deciding whether this access is always a hit, always a…
This paper presents a summary analysis of the Least Frequently Used (LFU) and Perfect Least Frequently Used (PLFU) cache eviction algorithms on real data, transferred on Content Delivery Nettworks (CDNs), as well as on Zipf distributed…
We study matrix-matrix multiplication of two matrices, $A$ and $B$, each of size $n \times n$. This operation results in a matrix $C$ of size $n\times n$. Our goal is to produce $C$ as efficiently as possible given a cache: a 1-D limited…
To cope with the ongoing changing demands of the internet, 'in-network caching' has been presented as an application solution for two decades. With the advent of information-centric network (ICN) architecture, 'in-network caching' becomes a…
Memory hierarchy is used to compete the processors speed. Cache memory is the fast memory which is used to conduit the speed difference of memory and processor. The access patterns of Level 1 cache (L1) and Level 2 cache (L2) are different,…
Efficient edge caching reduces latency and alleviates backhaul congestion in modern networks. Traditional caching policies, such as Least Recently Used (LRU) and Least Frequently Used (LFU), perform well under specific request patterns. LRU…
In modern GPU inference, cache efficiency remains a major bottleneck, and heuristic policies such as \textsc{LRU} can perform far worse than the offline optimum. Existing learning-based caching systems improve hit rates mainly through…
This paper proposes to use a frequency based cache admission policy in order to boost the effectiveness of caches subject to skewed access distributions. Given a newly accessed item and an eviction candidate from the cache, our scheme…
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…
For applications in worst-case execution time analysis and in security, it is desirable to statically classify memory accesses into those that result in cache hits, and those that result in cache misses. Among cache replacement policies,…
Caching plays a crucial role in networking systems to reduce the load on the network and is commonly employed by content delivery networks (CDNs) in order to improve performance. One of the commonly used mechanisms, Least Recently Used…
KV caching is a fundamental technique for accelerating Large Language Model (LLM) inference by reusing key-value (KV) pairs from previous queries, but its effectiveness under limited memory is highly sensitive to the eviction policy. The…
In a 2002 paper, Che and co-authors proposed a simple approach for estimating the hit rates of a cache operating the least recently used (LRU) replacement policy. The approximation proves remarkably accurate and is applicable to quite…
Modern applications can generate a large amount of data from different sources with high velocity, a combination that is difficult to store and process via traditional tools. Hadoop is one framework that is used for the parallel processing…
Commonly used caching policies, such as LRU (Least Recently Used) or LFU (Least Frequently Used), exhibit optimal performance only under specific traffic patterns. Even advanced machine learning-based methods, which detect patterns in…
The effective management of large amounts of data processed or required by today's cloud or edge computing systems remains a fundamental challenge. This paper focuses on cache management for applications where data objects can be stored in…
Prompt caching is critical for reducing latency and cost in LLM inference: OpenAI and Anthropic report up to 50-90% cost savings through prompt reuse. Despite its widespread success, little is known about what constitutes an optimal prompt…
We consider a generalization of the standard cache problem called file-bundle caching, where different queries (tasks), each containing $l\ge 1$ files, sequentially arrive. An online algorithm that does not know the sequence of queries…
In any caching system, the admission and eviction policies determine which contents are added and removed from a cache when a miss occurs. Usually, these policies are devised so as to mitigate staleness and increase the hit probability.…