• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.157-159
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• 2007

The conventional hard disk has been the dominant database storage system for over 25 years. Recently, hybrid systems which incorporate the advantages of flash memory into the conventional hard disks are considered to be the next dominant storage systems to support databases for desktops and server computers. Their features are satisfying the requirements like enhanced data I/O, energy consumption and reduced boot time, and they are sufficient to hybrid storage systems as major database storages. However, we need to improve traditional index node management schemes based on B-Tree due to the relatively slow characteristics of hard disk operations, as compared to flash memory. In order to achieve this goal, we propose a new index node management scheme called FNC-Tree. FNC-Tree-based index node management enhanced search and update performance by caching data objects in unused free area of flash leaf nodes to reduce slow hard disk I/Os in index access processes.

• Journal of the Semiconductor & Display Technology
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• v.19 no.3
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• pp.61-67
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• 2020

This paper is to propose a hybrid memory adaptor using next-generation nonvolatile memory devices such as phase-change memory to improve the performance limitations of OpenStack-based object storage systems. The proposed system aims to improve the performance of the account and container servers for object metadata management. For this, the proposed system consists of locality-based dynamic page buffer, write buffer, and nonvolatile memory modules. Experimental results show that the proposed system improves the hit rate by 5.5% compared to the conventional system.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.23 no.3
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• pp.1-8
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• 2018

In this paper, we propose a new page replacement policy using recency and frequency on hybrid main memory. The proposal has two features. First, when a page fault occurs in the main memory, the proposal allocates it to DRAM, regardless of operation types such as read or write. The page allocated by the page fault is likely to be high probability of re-reference in the near future. Our allocation can reduce the frequency of write operations in PCM. Second, if the write operations are frequently performed on pages of PCM, the pages are migrated from PCM to DRAM. Otherwise, the pages are maintained in PCM, to reduce the number of unnecessary page migrations from PCM. In our experiments, the proposal reduced the number of page migrations from PCM about 32.12% on average and reduced the number of write operations in PCM about 44.64% on average, compared to CLOCK-DWF. Moreover, the proposal reduced the energy consumption about 15.61%, and 3.04%, compared to other page replacement policies.

• ETRI Journal
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• v.36 no.6
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• pp.988-998
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• 2014

For memory-based big data storage, using hybrid memories consisting of both dynamic random-access memory (DRAM) and non-volatile random-access memories (NVRAMs) is a promising approach. DRAM supports low access time but consumes much energy, whereas NVRAMs have high access time but do not need energy to retain data. In this paper, we propose a new data migration method that can dynamically move data pages into the most appropriate memories to exploit their strengths and alleviate their weaknesses. We predict the access frequency values of the data pages and then measure comprehensively the gains and costs of each placement choice based on these predicted values. Next, we compute the potential benefits of all choices for each candidate page to make page migration decisions. Extensive experiments show that our method improves over the existing ones the access response time by as much as a factor of four, with similar rates of energy consumption.

• Journal of KIISE
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• v.42 no.2
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• pp.183-189
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• 2015

Recently, computer systems have encountered difficulties in making further progress due to the technical limitations of DRAM based main memory technologies. This has motivated the development of next generation memory technologies that have high density and non-volatility. However, these new memory technologies also have their own intrinsic limitations, making it difficult for them to currently be used as main memory. In order to overcome these problems, we propose a hybrid main memory system, namely HyMN, which utilizes the merits of next generation memory technologies by combining two types of memory: Write-Affable RAM(WAM) and Read-Affable RAM(ReAM). In so doing, we analyze the appropriate WAM size for HyMN, at which we can avoid the performance degradation. Further, we show that the execution time performance of HyMN, which provides an additional benefit of durability against unexpected blackouts, is almost comparable to legacy DRAM systems under normal operations.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.12-15
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• 2020

Data access characteristics can directly affect the efficiency of the system execution. This research is to design an accurate predictor by using historical memory access information, where highly accessible data can be migrated from low-speed storage (SSD/HHD) to high-speed memory (Memory/CPU Cache) in advance, thereby reducing data access latency and further improving overall performance. For this goal, we design a locally weighted linear regression prefetch scheme to cope with irregular access patterns in large graph processing applications for a DARM-PCM hybrid memory structure. By analyzing the testing result, the appropriate structural parameters can be selected, which greatly improves the cache prefetching performance, resulting in overall performance improvement.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.7
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• pp.789-793
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• 2010

Recently, flash memory-based non-volatile cache (NVC) is emerging as an effective solution to enhance both I/O performance and energy consumption of storage systems. To get significant performance and energy gains by NVC, it would be better to use multi-level-cell (MLC) flash memories since it can provide a large capacity of NVC with low cost. However, the number of available program/erase cycles of MLC flash memory is smaller than that of single-level-cell (SLC) flash memory limiting the lifespan of NVC. To overcome such a limitation, SLC/MLC combined flash memory is a promising solution for NVC. In this paper, we propose an effective management scheme for heterogeneous SLC and MLC regions of the combined flash memory.

• ETRI Journal
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• v.40 no.6
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• pp.759-773
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• 2018

Uncore components such as on-chip memory systems and on-chip interconnects consume a large amount of energy in emerging embedded applications. Few studies have focused on next-generation analytical models for future chip-multiprocessors (CMPs) that simultaneously consider the impacts of the power consumption of core and uncore components. In this paper, we propose a convex-optimization approach to design heterogeneous uncore architectures for embedded CMPs. Our convex approach optimizes the number and placement of memory banks with different technologies on the memory layer. In parallel with hybrid memory architecting, optimizing the number and placement of through silicon vias as a viable solution in building three-dimensional (3D) CMPs is another important target of the proposed approach. Experimental results show that the proposed method outperforms 3D CMP designs with hybrid and traditional memory architectures in terms of both energy delay products (EDPs) and performance parameters. The proposed method improves the EDPs by an average of about 43% compared with SRAM design. In addition, it improves the throughput by about 7% compared with dynamic RAM (DRAM) design.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.440-440
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• 2011

We report on the non-volatile memory characteristics of a bistable organic memory (BOM) device with Au nanoparticles (NPs) embedded in a conducting poly N-vinylcarbazole (PVK) colloids hybrid layer deposited on flexible polyethylene terephthalate (PET) substrates. Transmission electron microscopy (TEM) images show the Au nanoparticles distributed isotropically around the surface of a PVK colloid. The average induced charge on Au nanoparticles, estimated using the C-V hysteresis curve, was large, as much as 5 holes/NP at a sweeping voltage of ${\pm}3$ V. The maximum ON/OFF ratio of the current bistability in the BOM devices was as large as $1{\times}105$. The cycling endurance tests of the ON/OFF switching exhibited a high endurance of above $1.5{\times}105$ cycles and a high ON/OFF ratio of ~105 could be achieved consistently even after quite a long retention time of more than $1{\times}106$ s.