• Title/Summary/Keyword: file system cache

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Optimizing LRU Lock Management in the Linux Kernel for Improving Parallel Write Throughout in Many-Core CPU Systems (매니코어 CPU 시스템의 병렬 쓰기 성능 향상을 위한 리눅스 커널의 LRU 관리 최적화 기법)

  • Eun-Kyu Byun;Gibeom Gu;Kwang-Jin Oh;Jiwoo Bang
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.7
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    • pp.209-216
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    • 2023
  • Modern HPC systems are equipped with many-core CPUs with dozens of cores. When performing parallel I/O in such a system, there is a limit to scalability due to the problem of the LRU lock management policy of the Linux system. The study proposes an improved FinerLRU to solve this problem. Our new FinerLRU improves the parallel write performance of file systems using the buffer cache through granular lock management by increasing the number of LRU locks upto the maximum number of cores. The proposed method was implemented in Linux 5.18.11, and the performance was measured on two types of CPUs, Intel Icelake Xeon and Intel Knights landing, with different characteristics, and it was found that a performance improvement of about two times can be obtained in both types of systems.

A Content-Aware toad Balancing Technique Based on Histogram Transformation in a Cluster Web Server (클러스터 웹 서버 상에서 히스토그램 변환을 이용한 내용 기반 부하 분산 기법)

  • Hong Gi Ho;Kwon Chun Ja;Choi Hwang Kyu
    • Journal of Internet Computing and Services
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    • v.6 no.2
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    • pp.69-84
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    • 2005
  • As the Internet users are increasing rapidly, a cluster web server system is attracted by many researchers and Internet service providers. The cluster web server has been developed to efficiently support a larger number of users as well as to provide high scalable and available system. In order to provide the high performance in the cluster web server, efficient load distribution is important, and recently many content-aware request distribution techniques have been proposed. In this paper, we propose a new content-aware load balancing technique that can evenly distribute the workload to each node in the cluster web server. The proposed technique is based on the hash histogram transformation, in which each URL entry of the web log file is hashed, and the access frequency and file size are accumulated as a histogram. Each user request is assigned into a node by mapping of (hashed value-server node) in the histogram transformation. In the proposed technique, the histogram is updated periodically and then the even distribution of user requests can be maintained continuously. In addition to the load balancing, our technique can exploit the cache effect to improve the performance. The simulation results show that the performance of our technique is quite better than that of the traditional round-robin method and we can improve the performance more than $10\%$ compared with the existing workload-aware load balancing(WARD) method.

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Improving Flash Translation Layer for Hybrid Flash-Disk Storage through Sequential Pattern Mining based 2-Level Prefetching Technique (하이브리드 플래시-디스크 저장장치용 Flash Translation Layer의 성능 개선을 위한 순차패턴 마이닝 기반 2단계 프리패칭 기법)

  • Chang, Jae-Young;Yoon, Un-Keum;Kim, Han-Joon
    • The Journal of Society for e-Business Studies
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    • v.15 no.4
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    • pp.101-121
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    • 2010
  • This paper presents an intelligent prefetching technique that significantly improves performance of hybrid fash-disk storage, a combination of flash memory and hard disk. Since flash memory embedded in a hybrid device is much faster than hard disk in terms of I/O operations, it can be utilized as a 'cache' space to improve system performance. The basic strategy for prefetching is to utilize sequential pattern mining, with which we can extract the access patterns of objects from historical access sequences. We use two techniques for enhancing the performance of hybrid storage with prefetching. One of them is to modify a FAST algorithm for mapping the flash memory. The other is to extend the unit of prefetching to a block level as well as a file level for effectively utilizing flash memory space. For evaluating the proposed technique, we perform the experiments using the synthetic data and real UCC data, and prove the usability of our technique.