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Journal articles on the topic 'Memory management'

Author: Grafiati

Published: 4 June 2021

Last updated: 8 June 2024

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1

Raghuvanshi, Durgesh. "Memory Management in Operating System." International Journal of Trend in Scientific Research and Development Volume-2, Issue-5 (August 31, 2018): 2346–47. http://dx.doi.org/10.31142/ijtsrd18342.

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2

Bharti, Bhavna, and Prof Avinash Sharma. "Memory Management in BigData: A Perpective View." International Journal of Trend in Scientific Research and Development Volume-2, Issue-4 (June 30, 2018): 1993–98. http://dx.doi.org/10.31142/ijtsrd14436.

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3

Karunarathna, Harshinie, Jennifer Brown, Riccardo Briganti, Dabravka Pockrajac, Ivan Haigh, Christian Beck, Pushpa Dissanayake, Diego Pedrozo-Acuna, Kathryn Sparrow, and Mathew Wadey. "MODELLING MEMORY OF COASTAL FLOOD SYSTEMS." Coastal Engineering Proceedings 1, no. 34 (October 28, 2014): 19. http://dx.doi.org/10.9753/icce.v34.management.19.

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4

Nilakanta, Sree, L. L. Miller, and Dan Zhu. "Organizational Memory Management." Journal of Database Management 17, no. 1 (January 2006): 85–94. http://dx.doi.org/10.4018/jdm.2006010106.

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5

Milligan, Peter. "Distributed memory management." Microprocessing and Microprogramming 38, no. 1-5 (September 1993): 97–98. http://dx.doi.org/10.1016/0165-6074(93)90131-4.

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6

Hung, Ting-Wei, Yen-Hao Chen, and Yi-Yu Liu. "Memory management for dual-addressing memory architecture." IEICE Electronics Express 10, no. 15 (2013): 20130467. http://dx.doi.org/10.1587/elex.10.20130467.

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7

JOHNSON, THEODORE, and TIMOTHY A. DAVIS. "PARALLEL BUDDY MEMORY MANAGEMENT." Parallel Processing Letters 02, no. 04 (December 1992): 391–98. http://dx.doi.org/10.1142/s0129626492000544.

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Shared memory multiprocessor systems need efficient dynamic storage allocators, both for system purposes and to support parallel programs. Memory managers are often based on the buddy system, which provides fast allocation and release. Previous parallel buddy memory managers made no attempt to coordinate the allocation, splitting and release of blocks, and as a result needlessly fragment memory. We present a fast and simple parallel buddy memory manager that is also as space efficient as a serial buddy memory manager. We test our algorithms using memory allocation/deallocation traces collected from a parallel sparse matrix algorithm.

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8

Perez, Gilberto, and Isabel Ramos. "Understanding Organizational Memory from the Integrated Management Systems (ERP)." Journal of Information Systems and Technology Management 10, no. 3 (December 30, 2013): 541–60. http://dx.doi.org/10.4301/s1807-17752013000300005.

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9

Milenkovic, M. "Microprocessor memory management units." IEEE Micro 10, no. 2 (April 1990): 70–85. http://dx.doi.org/10.1109/40.52948.

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10

Aiken, Alexander, Manuel Fähndrich, and Raph Levien. "Better static memory management." ACM SIGPLAN Notices 30, no. 6 (June 1995): 174–85. http://dx.doi.org/10.1145/223428.207137.

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11

Kacsuk, P. "Memory management in LOGFLOW." Microprocessing and Microprogramming 39, no. 2-5 (December 1993): 79–82. http://dx.doi.org/10.1016/0165-6074(93)90061-o.

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12

Tofte, Mads, and Jean-Pierre Talpin. "Region-Based Memory Management." Information and Computation 132, no. 2 (February 1997): 109–76. http://dx.doi.org/10.1006/inco.1996.2613.

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13

JANG, Hakbeom, Jonghyun BAE, Tae Jun HAM, and Jae W. LEE. "Eager Memory Management for In-Memory Data Analytics." IEICE Transactions on Information and Systems E102.D, no. 3 (March 1, 2019): 632–36. http://dx.doi.org/10.1587/transinf.2018edl8199.

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14

Oluwatosin Abayomi, Ademodi, Ajayi Abayomi Olukayode, and Green Oluwole Olakunle. "An Overview of Cache Memory in Memory Management." Automation, Control and Intelligent Systems 8, no. 3 (2020): 24. http://dx.doi.org/10.11648/j.acis.20200803.11.

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15

Wu, Zhangling, Peiquan Jin, Chengcheng Yang, and Lihua Yue. "Efficient Memory Management for NVM-Based Hybrid Memory Systems." International Journal of Control and Automation 9, no. 1 (January 31, 2016): 445–58. http://dx.doi.org/10.14257/ijca.2016.9.1.38.

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16

Li, Han-Lin, Chia-Lin Yang, and Hung-Wei Tseng. "Energy-Aware Flash Memory Management in Virtual Memory System." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 16, no. 8 (August 2008): 952–64. http://dx.doi.org/10.1109/tvlsi.2008.2000517.

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17

Wen, Fei, Mian Qin, Paul V. Gratz, and A. L. Narasimha Reddy. "Hardware Memory Management for Future Mobile Hybrid Memory Systems." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 39, no. 11 (November 2020): 3627–37. http://dx.doi.org/10.1109/tcad.2020.3012213.

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18

Kamble, Abhijeet, Sahil Kakurle, Manish Shetkar, and Malhar Kapshe. "Memory Management in Mobile OS." International Journal for Research in Applied Science and Engineering Technology 10, no. 12 (December 31, 2022): 1676–81. http://dx.doi.org/10.22214/ijraset.2022.48292.

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Abstract: The mobile phones are increasing day by day and the usage is also increasing. Some of the phones have limited space or do not have much memory due to this user's face issue related to running mobile. For using memory effectively many of the techniques related to memory management are proposed. In this paper, we have reviewed memory management and its optimization techniques in various available mobile OSs, some of the basic techniques are discussed and comparison of various operating systems have been shown in the paper. Some of the details like which operating system is better and various information related to it is mentioned in the paper. Some of the basic solutions to optimize the memory in mobile OS are also mentioned in this paper

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19

Aboubacar, Adamou Souleymane. "Kilobyte Virtual Machine Memory Management." International Review on Computers and Software (IRECOS) 15, no. 1 (June 30, 2020): 14. http://dx.doi.org/10.15866/irecos.v15i1.19314.

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20

Riehle, Richard. "Institutional memory and risk management." ACM SIGSOFT Software Engineering Notes 32, no. 6 (November 2007): 5. http://dx.doi.org/10.1145/1317471.1317477.

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21

McKinley, Kathryn S. "Next Generation Virtual Memory Management." ACM SIGPLAN Notices 51, no. 7 (October 11, 2016): 107. http://dx.doi.org/10.1145/3007611.2892244.

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22

Roberts, Carole. "The Management of Memory Disorders." British Journal of Occupational Therapy 48, no. 3 (March 1985): 76–78. http://dx.doi.org/10.1177/030802268504800306.

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This article discusses the range of methods that are available to help patients with memory problems, including both external and internal strategies. Learning these strategies is difficult, so care must be taken in choosing a suitable method for each patient. Memory games can then be used to teach patients how to use the most effective strategy to improve memory function.

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23

Gay, David, and Alex Aiken. "Memory management with explicit regions." ACM SIGPLAN Notices 33, no. 5 (May 1998): 313–23. http://dx.doi.org/10.1145/277652.277748.

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24

Liu, Lei, Yong Li, Zehan Cui, Yungang Bao, Mingyu Chen, and Chengyong Wu. "Going vertical in memory management." ACM SIGARCH Computer Architecture News 42, no. 3 (October 16, 2014): 169–80. http://dx.doi.org/10.1145/2678373.2665698.

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25

Zhang, Hao, Bogdan Marius Tudor, Gang Chen, and Beng Chin Ooi. "Efficient in-memory data management." Proceedings of the VLDB Endowment 7, no. 10 (June 2014): 833–36. http://dx.doi.org/10.14778/2732951.2732956.

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26

Arge, Lars, and Jeffrey Scott Vitter. "Optimal External Memory Interval Management." SIAM Journal on Computing 32, no. 6 (January 2003): 1488–508. http://dx.doi.org/10.1137/s009753970240481x.

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27

Wilson, Barbara A., and Nick Moffat. "Clinical Management of Memory Problems." Physiotherapy 78, no. 11 (November 1992): 876. http://dx.doi.org/10.1016/s0031-9406(10)60483-x.

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28

Chang, J. Morris, Witawas Srisa-an, Chia-Tien Dan Lo, and Edward F. Gehringer. "DMMX: Dynamic memory management extensions." Journal of Systems and Software 63, no. 3 (September 2002): 187–99. http://dx.doi.org/10.1016/s0164-1212(02)00014-6.

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29

Spirn, Jeffrey R., and Shalom Tsur. "Memory management for B-trees." Performance Evaluation 5, no. 3 (August 1985): 159–74. http://dx.doi.org/10.1016/0166-5316(85)90010-0.

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30

Smith, Mary Ellen. "Clinical Management of Memory Problems." Topics in Geriatric Rehabilitation 2, no. 2 (January 1987): 84. http://dx.doi.org/10.1097/00013614-198701000-00014.

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31

V. Umoh, Glory. "Memory Management in Computer System." International Journal of Engineering Trends and Technology 18, no. 4 (December 25, 2014): 158–61. http://dx.doi.org/10.14445/22315381/ijett-v18p231.

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32

Caplan, Bruce. "Clinical Management of Memory Problems." Journal of Head Trauma Rehabilitation 1, no. 1 (March 1986): 85–86. http://dx.doi.org/10.1097/00001199-198603000-00016.

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33

Bolla-Wilson, Karen, and Robert G. Robinson. "Clinical Management of Memory Problems." Journal of Nervous and Mental Disease 174, no. 5 (May 1986): 315. http://dx.doi.org/10.1097/00005053-198605000-00012.

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34

van Wezenbeek, Anton M., and Willem Jan Withagen. "A survey of memory management." Microprocessing and Microprogramming 36, no. 3 (May 1993): 141–62. http://dx.doi.org/10.1016/0165-6074(93)90254-i.

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35

Kopelman, M. "Clinical management of memory problems." Behaviour Research and Therapy 23, no. 2 (1985): 237. http://dx.doi.org/10.1016/0005-7967(85)90056-7.

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36

Snyder, Charles A., Denise Johnson McManus, and Larry Todd Wilson. "Corporate memory management: a knowledge management process model." International Journal of Technology Management 20, no. 5/6/7/8 (2000): 752. http://dx.doi.org/10.1504/ijtm.2000.002894.

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37

Ananthanarayanan, R., Sathis Menon, Ajay Mohindra, and Umakishore Ramachandran. "Experiences in integrating distributed shared memory with virtual memory management." ACM SIGOPS Operating Systems Review 26, no. 3 (July 1992): 4–26. http://dx.doi.org/10.1145/130888.130889.

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38

Gopal, Bal, Rizwan Beg, and Pankaj Kumar. "Memory Management Technique for Paging on Distributed Shared Memory Framework." International journal of computer science & information Technology 2, no. 2 (April 25, 2010): 143–53. http://dx.doi.org/10.5121/ijcsit.2010.2212.

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39

Oukid, Ismail, Daniel Booss, Adrien Lespinasse, Wolfgang Lehner, Thomas Willhalm, and Grégoire Gomes. "Memory management techniques for large-scale persistent-main-memory systems." Proceedings of the VLDB Endowment 10, no. 11 (August 2017): 1166–77. http://dx.doi.org/10.14778/3137628.3137629.

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40

Liu, Lei, Shengjie Yang, Lu Peng, and Xinyu Li. "Hierarchical Hybrid Memory Management in OS for Tiered Memory Systems." IEEE Transactions on Parallel and Distributed Systems 30, no. 10 (October 1, 2019): 2223–36. http://dx.doi.org/10.1109/tpds.2019.2908175.

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41

Atienza, David, Jose M. Mendias, Stylianos Mamagkakis, Dimitrios Soudris, and Francky Catthoor. "Systematic dynamic memory management design methodology for reduced memory footprint." ACM Transactions on Design Automation of Electronic Systems 11, no. 2 (April 2006): 465–89. http://dx.doi.org/10.1145/1142155.1142165.

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42

Bowen, N. S., and D. K. Pradhan. "A fault tolerant hybrid memory structure and memory management algorithms." IEEE Transactions on Computers 44, no. 3 (March 1995): 408–18. http://dx.doi.org/10.1109/12.372033.

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43

Sha, Mo, Yifan Cai, Sheng Wang, Linh Thi Xuan Phan, Feifei Li, and Kian-Lee Tan. "Object-oriented Unified Encrypted Memory Management for Heterogeneous Memory Architectures." Proceedings of the ACM on Management of Data 2, no. 3 (May 29, 2024): 1–29. http://dx.doi.org/10.1145/3654958.

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In contemporary database applications, the demand for memory resources is intensively high. To enhance adaptability to varying resource needs and improve cost efficiency, the integration of diverse storage technologies within heterogeneous memory architectures emerges as a promising solution. Despite the potential advantages, there exists a significant gap in research related to the security of data within these complex systems. This paper endeavors to fill this void by exploring the intricacies and challenges of ensuring data security in object-oriented heterogeneous memory systems. We introduce the concept of Unified Encrypted Memory (UEM) management, a novel approach that provides unified object references essential for data management platforms, while simultaneously concealing the complexities of physical scheduling from developers. At the heart of UEM lies the seamless and efficient integration of data encryption techniques, which are designed to ensure data integrity and guarantee the freshness of data upon access. Our research meticulously examines the security deficiencies present in existing heterogeneous memory system designs. By advancing centralized security enforcement strategies, we aim to achieve efficient object-centric data protection. Through extensive evaluations conducted across a variety of memory configurations and tasks, our findings highlight the effectiveness of UEM. The security features of UEM introduce low and acceptable overheads, and UEM outperforms conventional security measures in terms of speed and space efficiency.

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44

Meng, Zhao Fei, and Shu Dong Zhang. "Buddy Algorithm Optimization in Linux Memory Management." Applied Mechanics and Materials 423-426 (September 2013): 2746–50. http://dx.doi.org/10.4028/www.scientific.net/amm.423-426.2746.

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Buddy algorithm is one of the classical algorithms for Linux Memory Management. In buddy algorithm, free memory blocks, even if they have the same size and consecutive address, they cant be combined into a larger memory space because they dont have a partnership. For these shortcomings of the algorithm, this paper proposes an improved buddy algorithm which mainly include in the main data structure adding an array and a variable respectively to record the starting address and the number of two adjacent free memory blocks which are in the linked list of last order and do not meet the partnership, at the same time, improving memory allocation management and memory recovery management.By experiment, when the memory space is insufficient and memory allocation request is frequent, the improved algorithm can effectively reduce the number of failed memory requests and improve the memory utilization.

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45

Hao, Xiangpeng, Xinjing Zhou, Xiangyao Yu, and Michael Stonebraker. "Towards Buffer Management with Tiered Main Memory." Proceedings of the ACM on Management of Data 2, no. 1 (March 12, 2024): 1–26. http://dx.doi.org/10.1145/3639286.

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The scaling of per-GB DRAM cost has slowed down in recent years. Recent research has suggested that adding remote memory to a system can further reduce the overall memory cost while maintaining good performance. Remote memory (i.e., tiered memory), connected to host servers via high-speed interconnect protocols such as RDMA and CXL, is expected to deliver 100x (less than 1µs) lower latency than SSD and be more cost-effective than local DRAM through pooling or adopting cheaper memory technologies. Tiered memory opens up a large number of potential use cases within database systems. But previous work has only explored limited ways of using tiered memory. Our study provides a systematic study for DBMS to build tiered memory buffer management with respect to a wide range of hardware performance characteristics. Specifically, we study five different indexing designs that leverage remote memory in different ways and evaluate them through a wide range of metrics including performance, tiered-memory latency sensitivity, and cost-effectiveness. In addition, we propose a new memory provisioning strategy that allocates an optimal amount of local and remote memory for a given workload. Our evaluations show that while some designs achieve higher performance than others, no design can win in all measured dimensions.

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46

Arvidsson, Ellen, Elias Castegren, Sylvan Clebsch, Sophia Drossopoulou, James Noble, Matthew J. Parkinson, and Tobias Wrigstad. "Reference Capabilities for Flexible Memory Management." Proceedings of the ACM on Programming Languages 7, OOPSLA2 (October 16, 2023): 1363–93. http://dx.doi.org/10.1145/3622846.

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Verona is a concurrent object-oriented programming language that organises all the objects in a program into a forest of isolated regions. Memory is managed locally for each region, so programmers can control a program's memory use by adjusting objects' partition into regions, and by setting each region's memory management strategy. A thread can only mutate (allocate, deallocate) objects within one active region---its "window of mutability". Memory management costs are localised to the active region, ensuring overheads can be predicted and controlled. Moving the mutability window between regions is explicit, so code can be executed wherever it is required, yet programs remain in control of memory use. An ownership type system based on reference capabilities enforces region isolation, controlling aliasing within and between regions, yet supporting objects moving between regions and threads. Data accesses never need expensive atomic operations, and are always thread-safe.

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47

Younan, Yves, Wouter Joosen, Frank Piessens, and Hans Van den Eynden. "Improving Memory Management Security for C and C++." International Journal of Secure Software Engineering 1, no. 2 (April 2010): 57–82. http://dx.doi.org/10.4018/jsse.2010040104.

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Memory managers are an important part of modern language and are used to dynamically allocate memory. Many managers exist; however, two major types can be identified: manual memory allocators and garbage collectors. In the case of manual memory allocators, the programmer must manually release memory back to the system when it is no longer needed. Problems can occur when a programmer forgets to release it, releases it twice or uses freed memory. These problems are solved in garbage collectors. However, both manual memory allocators and garbage collectors store management information. This paper describes several vulnerabilities for C and C++ and how these could be remedied by modifying the management information of a representative manual memory allocator and garbage collector. Additionally, the authors present an approach that, when applied to memory managers, will protect against these attack vectors.

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48

Shukla, Y. "Memory assessment clinics: process and management." Morecambe Bay Medical Journal 4, no. 6 (September 1, 2003): 184–89. http://dx.doi.org/10.48037/mbmj.v4i6.804.

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49

Raghunathan, Ram, Stefan K. Muller, Umut A. Acar, and Guy Blelloch. "Hierarchical memory management for parallel programs." ACM SIGPLAN Notices 51, no. 9 (December 5, 2016): 392–406. http://dx.doi.org/10.1145/3022670.2951935.

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50

Guatto, Adrien, Sam Westrick, Ram Raghunathan, Umut Acar, and Matthew Fluet. "Hierarchical memory management for mutable state." ACM SIGPLAN Notices 53, no. 1 (March 23, 2018): 81–93. http://dx.doi.org/10.1145/3200691.3178494.

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