An Adaptive Buffer Cache Management Scheme

2016 ◽  
Author(s):  
Hsung-Pin Chang ◽  
Cheng-Pang Chiang ◽  
Yu-Cheng Yu
Keyword(s):  
Cache Management ◽  
Management Scheme ◽  
Buffer Cache

Practical buffer cache management scheme based on simple prefetching

2006 ◽  
Vol 52 (3) ◽  
pp. 926-934 ◽  
Author(s):  
Heung Seok Jeon
Keyword(s):  
Cache Management ◽  
Management Scheme ◽  
Buffer Cache

A buffer cache management scheme exploiting both temporal and spatial localities

2007 ◽  
Vol 3 (2) ◽  
pp. 5 ◽  
Author(s):  
Xiaoning Ding ◽  
Song Jiang ◽  
Feng Chen
Keyword(s):  
Cache Management ◽  
Management Scheme ◽  
Buffer Cache ◽  
Temporal And Spatial

A Unified Write Buffer Cache Management Scheme for Flash Memory

2014 ◽  
Vol 22 (12) ◽  
pp. 2779-2792 ◽  
Author(s):  
Liang Shi ◽  
Jianhua Li ◽  
Qingan Li ◽  
Chun Jason Xue ◽  
Chengmo Yang ◽  
...  
Keyword(s):  
Flash Memory ◽  
Cache Management ◽  
Management Scheme ◽  
Buffer Cache ◽  
Write Buffer

A hybrid buffer cache management scheme for VOD server

2003 ◽  
Author(s):  
Kyongwoon Cho ◽  
Yeonseung Ryu ◽  
Youjip Won ◽  
Kern Koh
Keyword(s):  
Cache Management ◽  
Management Scheme ◽  
Buffer Cache ◽  
Vod Server

scholarly journals File Type and Access Pattern Aware Buffer Cache Management for Rendering Systems

Electronics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 164 ◽  
Author(s):  
Donghee Shin ◽  
Kyungwoon Cho ◽  
Hyokyung Bahn
Keyword(s):  
General Purpose ◽  
Cache Management ◽  
Computing Systems ◽  
File Access ◽  
Management Scheme ◽  
Buffer Cache ◽  
Significant Performance ◽  
High Resolution Images ◽  
Access Patterns ◽  
Cache System

Rendering is the process of generating high-resolution images by software, which is widely used in animation, video games and visual effects in movies. Although rendering is a computation-intensive job, we observe that storage accesses may become another performance bottleneck in desktop-rendering systems. In this article, we present a new buffer cache management scheme specialized for rendering systems. Unlike general-purpose computing systems, rendering systems exhibit specific file access patterns, and we show that this results in significant performance degradation in the buffer cache system. To cope with this situation, we collect various file input/output (I/O) traces of rendering workloads and analyze their access patterns. The results of this analysis show that file I/Os in rendering processes consist of long loops for configuration, short loops for texture input, random reads for input, and single-writes for output. Based on this observation, we propose a new buffer cache management scheme for improving the storage performance of rendering systems. Experimental results show that the proposed scheme improves the storage I/O performance by an average of 19% and a maximum of 55% compared to the conventional buffer cache system.

Penalty- and Locality-aware Memory Allocation in Redis Using Enhanced AET

2021 ◽  
Vol 17 (2) ◽  
pp. 1-45
Author(s):  
Cheng Pan ◽  
Xiaolin Wang ◽  
Yingwei Luo ◽  
Zhenlin Wang
Keyword(s):  
Large Data ◽  
Data Locality ◽  
Memory Allocation ◽  
Cache Management ◽  
Cache Replacement ◽  
Time Model ◽  
Memory Cache ◽  
Management Scheme ◽  
Data Volume ◽  
Replacement Algorithms

Due to large data volume and low latency requirements of modern web services, the use of an in-memory key-value (KV) cache often becomes an inevitable choice (e.g., Redis and Memcached). The in-memory cache holds hot data, reduces request latency, and alleviates the load on background databases. Inheriting from the traditional hardware cache design, many existing KV cache systems still use recency-based cache replacement algorithms, e.g., least recently used or its approximations. However, the diversity of miss penalty distinguishes a KV cache from a hardware cache. Inadequate consideration of penalty can substantially compromise space utilization and request service time. KV accesses also demonstrate locality, which needs to be coordinated with miss penalty to guide cache management. In this article, we first discuss how to enhance the existing cache model, the Average Eviction Time model, so that it can adapt to modeling a KV cache. After that, we apply the model to Redis and propose pRedis, Penalty- and Locality-aware Memory Allocation in Redis, which synthesizes data locality and miss penalty, in a quantitative manner, to guide memory allocation and replacement in Redis. At the same time, we also explore the diurnal behavior of a KV store and exploit long-term reuse. We replace the original passive eviction mechanism with an automatic dump/load mechanism, to smooth the transition between access peaks and valleys. Our evaluation shows that pRedis effectively reduces the average and tail access latency with minimal time and space overhead. For both real-world and synthetic workloads, our approach delivers an average of 14.0%∼52.3% latency reduction over a state-of-the-art penalty-aware cache management scheme, Hyperbolic Caching (HC), and shows more quantitative predictability of performance. Moreover, we can obtain even lower average latency (1.1%∼5.5%) when dynamically switching policies between pRedis and HC.

scholarly journals AOIO: Application Oriented I/O Optimization for Buffer Management

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 573
Author(s):  
Xiaochang Li ◽  
Zhengjun Zhai ◽  
Xin Ye
Keyword(s):  
System Performance ◽  
Simulation Experiment ◽  
Buffer Management ◽  
Input Output ◽  
Output Data ◽  
Program Counter ◽  
Efficient Management ◽  
Management Scheme ◽  
Buffer Cache ◽  
Management Schemes

Emerging scale-out I/O intensive applications are broadly used now, which process a large amount of data in buffer/cache for reorganization or analysis and their performances are greatly affected by the speed of the I/O system. Efficient management scheme of the limited kernel buffer plays a key role in improving I/O system performance, such as caching hinted data for reuse in future, prefetching hinted data, and expelling data not to be accessed again from a buffer, which are called proactive mechanisms in buffer management. However, most of the existing buffer management schemes cannot identify data reference regularities (i.e., sequential or looping patterns) that can benefit proactive mechanisms, and they also cannot perform in the application level for managing specified applications. In this paper, we present an A pplication Oriented I/O Optimization (AOIO) technique automatically benefiting the kernel buffer/cache by exploring the I/O regularities of applications based on program counter technique. In our design, the input/output data and the looping pattern are in strict symmetry. According to AOIO, each application can provide more appropriate predictions to operating system which achieve significantly better accuracy than other buffer management schemes. The trace-driven simulation experiment results show that the hit ratios are improved by an average of 25.9% and the execution times are reduced by as much as 20.2% compared to other schemes for the workloads we used.

RFFE: A Buffer Cache Management Algorithm for Flash-Memory-Based SSD to Improve Write Performance

2015 ◽  
Vol 38 (3) ◽  
pp. 219-231 ◽  
Author(s):  
Arul Selvan Ramasamy ◽  
Porkumaran Karantharaj
Keyword(s):  
Flash Memory ◽  
Cache Management ◽  
Management Algorithm ◽  
Buffer Cache
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