1,800 research outputs found

    Flash Memory Devices

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    Flash memory devices have represented a breakthrough in storage since their inception in the mid-1980s, and innovation is still ongoing. The peculiarity of such technology is an inherent flexibility in terms of performance and integration density according to the architecture devised for integration. The NOR Flash technology is still the workhorse of many code storage applications in the embedded world, ranging from microcontrollers for automotive environment to IoT smart devices. Their usage is also forecasted to be fundamental in emerging AI edge scenario. On the contrary, when massive data storage is required, NAND Flash memories are necessary to have in a system. You can find NAND Flash in USB sticks, cards, but most of all in Solid-State Drives (SSDs). Since SSDs are extremely demanding in terms of storage capacity, they fueled a new wave of innovation, namely the 3D architecture. Today โ€œ3Dโ€ means that multiple layers of memory cells are manufactured within the same piece of silicon, easily reaching a terabit capacity. So far, Flash architectures have always been based on "floating gate," where the information is stored by injecting electrons in a piece of polysilicon surrounded by oxide. On the contrary, emerging concepts are based on "charge trap" cells. In summary, flash memory devices represent the largest landscape of storage devices, and we expect more advancements in the coming years. This will require a lot of innovation in process technology, materials, circuit design, flash management algorithms, Error Correction Code and, finally, system co-design for new applications such as AI and security enforcement

    Design, Modeling and Analysis of Non-classical Field Effect Transistors

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    Transistor scaling following per Moore\u27s Law slows down its pace when entering into nanometer regime where short channel effects (SCEs), including threshold voltage fluctuation, increased leakage current and mobility degradation, become pronounced in the traditional planar silicon MOSFET. In addition, as the demand of diversified functionalities rises, conventional silicon technologies cannot satisfy all non-digital applications requirements because of restrictions that stem from the fundamental material properties. Therefore, novel device materials and structures are desirable to fuel further evolution of semiconductor technologies. In this dissertation, I have proposed innovative device structures and addressed design considerations of those non-classical field effect transistors for digital, analog/RF and power applications with projected benefits. Considering device process difficulties and the dramatic fabrication cost, application-oriented device design and optimization are performed through device physics analysis and TCAD modeling methodology to develop design guidelines utilizing transistor\u27s improved characteristics toward application-specific circuit performance enhancement. Results support proposed device design methodologies that will allow development of novel transistors capable of overcoming limitation of planar nanoscale MOSFETs. In this work, both silicon and III-V compound devices are designed, optimized and characterized for digital and non-digital applications through calibrated 2-D and 3-D TCAD simulation. For digital functionalities, silicon and InGaAs MOSFETs have been investigated. Optimized 3-D silicon-on-insulator (SOI) and body-on-insulator (BOI) FinFETs are simulated to demonstrate their impact on the performance of volatile memory SRAM module with consideration of self-heating effects. Comprehensive simulation results suggest that the current drivability degradation due to increased device temperature is modest for both devices and corresponding digital circuits. However, SOI FinFET is recommended for the design of low voltage operation digital modules because of its faster AC response and better SCEs management than the BOI structure. The FinFET concept is also applied to the non-volatile memory cell at 22 nm technology node for low voltage operation with suppressed SCEs. In addition to the silicon technology, our TCAD estimation based on upper projections show that the InGaAs FinFET, with superior mobility and improved interface conditions, achieve tremendous drive current boost and aggressively suppressed SCEs and thereby a strong contender for low-power high-performance applications over the silicon counterpart. For non-digital functionalities, multi-fin FETs and GaN HEMT have been studied. Mixed-mode simulations along with developed optimization guidelines establish the realistic application potential of underlap design of silicon multi-Fin FETs for analog/RF operation. The device with underlap design shows compromised current drivability but improve analog intrinsic gain and high frequency performance. To investigate the potential of the novel N-polar GaN material, for the first time, I have provided calibrated TCAD modeling of E-mode N-polar GaN single-channel HEMT. In this work, I have also proposed a novel E-mode dual-channel hybrid MIS-HEMT showing greatly enhanced current carrying capability. The impact of GaN layer scaling has been investigated through extensive TCAD simulations and demonstrated techniques for device optimization

    High-Density Solid-State Memory Devices and Technologies

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    This Special Issue aims to examine high-density solid-state memory devices and technologies from various standpoints in an attempt to foster their continuous success in the future. Considering that broadening of the range of applications will likely offer different types of solid-state memories their chance in the spotlight, the Special Issue is not focused on a specific storage solution but rather embraces all the most relevant solid-state memory devices and technologies currently on stage. Even the subjects dealt with in this Special Issue are widespread, ranging from process and design issues/innovations to the experimental and theoretical analysis of the operation and from the performance and reliability of memory devices and arrays to the exploitation of solid-state memories to pursue new computing paradigms

    Reliability of HfO2-Based Ferroelectric FETs: A Critical Review of Current and Future Challenges

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    Ferroelectric transistors (FeFETs) based on doped hafnium oxide (HfO2) have received much attention due to their technological potential in terms of scalability, highspeed, and low-power operation. Unfortunately, however, HfO2-FeFETs also suffer from persistent reliability challenges, specifically affecting retention, endurance, and variability. A deep understanding of the reliability physics of HfO2-FeFETs is an essential prerequisite for the successful commercialization of this promising technology. In this article, we review the literature about the relevant reliability aspects of HfO2-FeFETs. We initially focus on the reliability physics of ferroelectric capacitors, as a prelude to a comprehensive analysis of FeFET reliability. Then, we interpret key reliability metrics of the FeFET at the device level (i.e., retention, endurance, and variability) based on the physical mechanisms previously identified. Finally, we discuss the implications of device-level reliability metrics at both the circuit and system levels. Our integrative approach connects apparently unrelated reliability issues and suggests mitigation strategies at the device, circuit, or system level. We conclude this article by proposing a set of research opportunities to guide future development in this field

    Memristive Non-Volatile Memory Based on Graphene Materials

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    Resistive random access memory (RRAM), which is considered as one of the most promising next-generation non-volatile memory (NVM) devices and a representative of memristor technologies, demonstrated great potential in acting as an artificial synapse in the industry of neuromorphic systems and artificial intelligence (AI), due its advantages such as fast operation speed, low power consumption, and high device density. Graphene and related materials (GRMs), especially graphene oxide (GO), acting as active materials for RRAM devices, are considered as a promising alternative to other materials including metal oxides and perovskite materials. Herein, an overview of GRM-based RRAM devices is provided, with discussion about the properties of GRMs, main operation mechanisms for resistive switching (RS) behavior, figure of merit (FoM) summary, and prospect extension of GRM-based RRAM devices. With excellent physical and chemical advantages like intrinsic Youngโ€™s modulus (1.0 TPa), good tensile strength (130 GPa), excellent carrier mobility (2.0 ร— 105 cm2โˆ™Vโˆ’1โˆ™sโˆ’1), and high thermal (5000 Wmโˆ’1โˆ™Kโˆ’1) and superior electrical conductivity (1.0 ร— 106 Sโˆ™mโˆ’1), GRMs can act as electrodes and resistive switching media in RRAM devices. In addition, the GRM-based interface between electrode and dielectric can have an effect on atomic diffusion limitation in dielectric and surface effect suppression. Immense amounts of concrete research indicate that GRMs might play a significant role in promoting the large-scale commercialization possibility of RRAM devices

    A statistical study of time dependent reliability degradation of nanoscale MOSFET devices

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    Charge trapping at the channel interface is a fundamental issue that adversely affects the reliability of metal-oxide semiconductor field effect transistor (MOSFET) devices. This effect represents a new source of statistical variability as these devices enter the nano-scale era. Recently, charge trapping has been identified as the dominant phenomenon leading to both random telegraph noise (RTN) and bias temperature instabilities (BTI). Thus, understanding the interplay between reliability and statistical variability in scaled transistors is essential to the implementation of a โ€˜reliability-awareโ€™ complementary metal oxide semiconductor (CMOS) circuit design. In order to investigate statistical reliability issues, a methodology based on a simulation flow has been developed in this thesis that allows a comprehensive and multi-scale study of charge-trapping phenomena and their impact on transistor and circuit performance. The proposed methodology is accomplished by using the Gold Standard Simulations (GSS) technology computer-aided design (TCAD)-based design tool chain co-optimization (DTCO) tool chain. The 70 nm bulk IMEC MOSFET and the 22 nm Intel fin-shape field effect transistor (FinFET) have been selected as targeted devices. The simulation flow starts by calibrating the device TCAD simulation decks against experimental measurements. This initial phase allows the identification of the physical structure and the doping distributions in the vertical and lateral directions based on the modulation in the inversion layerโ€™s depth as well as the modulation of short channel effects. The calibration is further refined by taking into account statistical variability to match the statistical distributions of the transistorsโ€™ figures of merit obtained by measurements. The TCAD simulation investigation of RTN and BTI phenomena is then carried out in the presence of several sources of statistical variability. The study extends further to circuit simulation level by extracting compact models from the statistical TCAD simulation results. These compact models are collected in libraries, which are then utilised to investigate the impact of the BTI phenomenon, and its interaction with statistical variability, in a six transistor-static random access memory (6T-SRAM) cell. At the circuit level figures of merit, such as the static noise margin (SNM), and their statistical distributions are evaluated. The focus of this thesis is to highlight the importance of accounting for the interaction between statistical variability and statistical reliability in the simulation of advanced CMOS devices and circuits, in order to maintain predictivity and obtain a quantitative agreement with a measured data. The main findings of this thesis can be summarised by the following points: Based on the analysis of the results, the dispersions of VT and ฮ”VT indicate that a change in device technology must be considered, from the planar MOSFET platform to a new device architecture such as FinFET or SOI. This result is due to the interplay between a single trap charge and statistical variability, which has a significant impact on device operation and intrinsic parameters as transistor dimensions shrink further. The ageing process of transistors can be captured by using the trapped charge density at the interface and observing the VT shift. Moreover, using statistical analysis one can highlight the extreme transistors and their probable effect on the circuit or system operation. The influence of the passgate (PG) transistor in a 6T-SRAM cell gives a different trend of the mean static noise margin

    Characterisation and mitigation of long-term degradation effects in programmable logic

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    Reliability has always been an issue in silicon device engineering, but until now it has been managed by the carefully tuned fabrication process. In the future the underlying physical limitations of silicon-based electronics, plus the practical challenges of manufacturing with such complexity at such a small scale, will lead to a crunch point where transistor-level reliability must be forfeited to continue achieving better productivity. Field-programmable gate arrays (FPGAs) are built on state-of-the-art silicon processes, but it has been recognised for some time that their distinctive characteristics put them in a favourable position over application-specific integrated circuits in the face of the reliability challenge. The literature shows how a regular structure, interchangeable resources and an ability to reconfigure can all be exploited to detect, locate, and overcome degradation and keep an FPGA application running. To fully exploit these characteristics, a better understanding is needed of the behavioural changes that are seen in the resources that make up an FPGA under ageing. Modelling is an attractive approach to this and in this thesis the causes and effects are explored of three important degradation mechanisms. All are shown to have an adverse affect on FPGA operation, but their characteristics show novel opportunities for ageing mitigation. Any modelling exercise is built on assumptions and so an empirical method is developed for investigating ageing on hardware with an accelerated-life test. Here, experiments show that timing degradation due to negative-bias temperature instability is the dominant process in the technology considered. Building on simulated and experimental results, this work also demonstrates a variety of methods for increasing the lifetime of FPGA lookup tables. The pre-emptive measure of wear-levelling is investigated in particular detail, and it is shown by experiment how di fferent reconfiguration algorithms can result in a significant reduction to the rate of degradation

    ์ดˆ๊ณ ์šฉ๋Ÿ‰ ์†”๋ฆฌ๋“œ ์Šคํ…Œ์ด๋“œ ๋“œ๋ผ์ด๋ธŒ๋ฅผ ์œ„ํ•œ ์‹ ๋ขฐ์„ฑ ํ–ฅ์ƒ ๋ฐ ์„ฑ๋Šฅ ์ตœ์ ํ™” ๊ธฐ์ˆ 

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2021.8. ๊น€์ง€ํ™.The development of ultra-large NAND flash storage devices (SSDs) is recently made possible by NAND flash memory semiconductor process scaling and multi-leveling techniques, and NAND package technology, which enables continuous increasing of storage capacity by mounting many NAND flash memory dies in an SSD. As the capacity of an SSD increases, the total cost of ownership of the storage system can be reduced very effectively, however due to limitations of ultra-large SSDs in reliability and performance, there exists some obstacles for ultra-large SSDs to be widely adopted. In order to take advantage of an ultra-large SSD, it is necessary to develop new techniques to improve these reliability and performance issues. In this dissertation, we propose various optimization techniques to solve the reliability and performance issues of ultra-large SSDs. In order to overcome the optimization limitations of the existing approaches, our techniques were designed based on various characteristic evaluation results of NAND flash devices and field failure characteristics analysis results of real SSDs. We first propose a low-stress erase technique for the purpose of reducing the characteristic deviation between wordlines (WLs) in a NAND flash block. By reducing the erase stress on weak WLs, it effectively slows down NAND degradation and improves NAND endurance. From the NAND evaluation results, the conditions that can most effectively guard the weak WLs are defined as the gerase mode. In addition, considering the user workload characteristics, we propose a technique to dynamically select the optimal gerase mode that can maximize the lifetime of the SSD. Secondly, we propose an integrated approach that maximizes the efficiency of copyback operations to improve performance while not compromising data reliability. Based on characterization using real 3D TLC flash chips, we propose a novel per-block error propagation model under consecutive copyback operations. Our model significantly increases the number of successive copybacks by exploiting the aging characteristics of NAND blocks. Furthermore, we devise a resource-efficient error management scheme that can handle successive copybacks where pages move around multiple blocks with different reliability. By utilizing proposed copyback operation for internal data movement, SSD performance can be effectively improved without any reliability issues. Finally, we propose a new recovery scheme, called reparo, for a RAID storage system with ultra-large SSDs. Unlike the existing RAID recovery schemes, reparo repairs a failed SSD at the NAND die granularity without replacing it with a new SSD, thus avoiding most of the inter-SSD data copies during a RAID recovery step. When a NAND die of an SSD fails, reparo exploits a multi-core processor of the SSD controller to identify failed LBAs from the failed NAND die and to recover data from the failed LBAs. Furthermore, reparo ensures no negative post-recovery impact on the performance and lifetime of the repaired SSD. In order to evaluate the effectiveness of the proposed techniques, we implemented them in a storage device prototype, an open NAND flash storage device development environment, and a real SSD environment. And their usefulness was verified using various benchmarks and I/O traces collected the from real-world applications. The experiment results show that the reliability and performance of the ultra-large SSD can be effectively improved through the proposed techniques.๋ฐ˜๋„์ฒด ๊ณต์ •์˜ ๋ฏธ์„ธํ™”, ๋‹ค์น˜ํ™” ๊ธฐ์ˆ ์— ์˜ํ•ด์„œ ์ง€์†์ ์œผ๋กœ ์šฉ๋Ÿ‰์ด ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๋Š” ๋‹จ์œ„ ๋‚ธ๋“œ ํ”Œ๋ž˜์‰ฌ ๋ฉ”๋ชจ๋ฆฌ์™€ ํ•˜๋‚˜์˜ ๋‚ธ๋“œ ํ”Œ๋ž˜์‰ฌ ๊ธฐ๋ฐ˜ ์Šคํ† ๋ฆฌ์ง€ ์‹œ์Šคํ…œ ๋‚ด์— ์ˆ˜ ๋งŽ์€ ๋‚ธ๋“œ ํ”Œ๋ž˜์‰ฌ ๋ฉ”๋ชจ๋ฆฌ ๋‹ค์ด๋ฅผ ์‹ค์žฅํ•  ์ˆ˜ ์žˆ๊ฒŒํ•˜๋Š” ๋‚ธ๋“œ ํŒจํ‚ค์ง€ ๊ธฐ์ˆ ๋กœ ์ธํ•ด ํ•˜๋“œ๋””์Šคํฌ๋ณด๋‹ค ํ›จ์”ฌ ๋” ํฐ ์ดˆ๊ณ ์šฉ๋Ÿ‰์˜ ๋‚ธ๋“œ ํ”Œ๋ž˜์‰ฌ ์ €์žฅ์žฅ์น˜์˜ ๊ฐœ๋ฐœ์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ–ˆ๋‹ค. ํ”Œ๋ž˜์‰ฌ ์ €์žฅ์žฅ์น˜์˜ ์šฉ๋Ÿ‰์ด ์ฆ๊ฐ€ํ•  ์ˆ˜๋ก ์Šคํ† ๋ฆฌ์ง€ ์‹œ์Šคํ…œ์˜ ์ด ์†Œ์œ ๋น„์šฉ์„ ์ค„์ด๋Š”๋ฐ ๋งค์šฐ ํšจ๊ณผ์ ์ธ ์žฅ์ ์„ ๊ฐ€์ง€๊ณ  ์žˆ์œผ๋‚˜, ์‹ ๋ขฐ์„ฑ ๋ฐ ์„ฑ๋Šฅ์˜ ์ธก๋ฉด์—์„œ์˜ ํ•œ๊ณ„๋กœ ์ธํ•ด์„œ ์ดˆ๊ณ ์šฉ๋Ÿ‰ ๋‚ธ๋“œ ํ”Œ๋ž˜์‰ฌ ์ €์žฅ์žฅ์น˜๊ฐ€ ๋„๋ฆฌ ์‚ฌ์šฉ๋˜๋Š”๋ฐ ์žˆ์–ด์„œ ์žฅ์• ๋ฌผ๋กœ ์ž‘์šฉํ•˜๊ณ  ์žˆ๋‹ค. ์ดˆ๊ณ ์šฉ๋Ÿ‰ ์ €์žฅ์žฅ์น˜์˜ ์žฅ์ ์„ ํ™œ์šฉํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์ด๋Ÿฌํ•œ ์‹ ๋ขฐ์„ฑ ๋ฐ ์„ฑ๋Šฅ์„ ๊ฐœ์„ ํ•˜๊ธฐ ์œ„ํ•œ ์ƒˆ๋กœ์šด ๊ธฐ๋ฒ•์˜ ๊ฐœ๋ฐœ์ด ํ•„์š”ํ•˜๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ดˆ๊ณ ์šฉ๋Ÿ‰ ๋‚ธ๋“œ๊ธฐ๋ฐ˜ ์ €์žฅ์žฅ์น˜(SSD)์˜ ๋ฌธ์ œ์ ์ธ ์„ฑ๋Šฅ ๋ฐ ์‹ ๋ขฐ์„ฑ์„ ๊ฐœ์„ ํ•˜๊ธฐ ์œ„ํ•œ ๋‹ค์–‘ํ•œ ์ตœ์ ํ™” ๊ธฐ์ˆ ์„ ์ œ์•ˆํ•œ๋‹ค. ๊ธฐ์กด ๊ธฐ๋ฒ•๋“ค์˜ ์ตœ์ ํ™” ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•ด์„œ, ์šฐ๋ฆฌ์˜ ๊ธฐ์ˆ ์€ ์‹ค์ œ ๋‚ธ๋“œ ํ”Œ๋ž˜์‰ฌ ์†Œ์ž์— ๋Œ€ํ•œ ๋‹ค์–‘ํ•œ ํŠน์„ฑ ํ‰๊ฐ€ ๊ฒฐ๊ณผ์™€ SSD์˜ ํ˜„์žฅ ๋ถˆ๋Ÿ‰ ํŠน์„ฑ ๋ถ„์„๊ฒฐ๊ณผ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ๊ณ ์•ˆ๋˜์—ˆ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด์„œ ๋‚ธ๋“œ์˜ ํ”Œ๋ž˜์‰ฌ ํŠน์„ฑ๊ณผ SSD, ๊ทธ๋ฆฌ๊ณ  ํ˜ธ์ŠคํŠธ ์‹œ์Šคํ…œ์˜ ๋™์ž‘ ํŠน์„ฑ์„ ๊ณ ๋ คํ•œ ์„ฑ๋Šฅ ๋ฐ ์‹ ๋ขฐ์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚ค๋Š” ์ตœ์ ํ™” ๋ฐฉ๋ฒ•๋ก ์„ ์ œ์‹œํ•œ๋‹ค. ์ฒซ์งธ๋กœ, ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๋‚ธ๋“œ ํ”Œ๋ž˜์‰ฌ ๋ถˆ๋ก๋‚ด์˜ ํŽ˜์ด์ง€๋“ค๊ฐ„์˜ ํŠน์„ฑํŽธ์ฐจ๋ฅผ ์ค„์ด๊ธฐ ์œ„ํ•ด์„œ ๋™์ ์ธ ์†Œ๊ฑฐ ์ŠคํŠธ๋ ˆ์Šค ๊ฒฝ๊ฐ ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์€ ๋‚ธ๋“œ ๋ธ”๋ก์˜ ๋‚ด๊ตฌ์„ฑ์„ ๋Š˜๋ฆฌ๊ธฐ ์œ„ํ•ด์„œ ํŠน์„ฑ์ด ์•ฝํ•œ ํŽ˜์ด์ง€๋“ค์— ๋Œ€ํ•ด์„œ ๋” ์ ์€ ์†Œ๊ฑฐ ์ŠคํŠธ๋ ˆ์Šค๊ฐ€ ์ธ๊ฐ€ํ•  ์ˆ˜ ์žˆ๋„๋ก ๋‚ธ๋“œ ํ‰๊ฐ€ ๊ฒฐ๊ณผ๋กœ ๋ถ€ํ„ฐ ์†Œ๊ฑฐ ์ŠคํŠธ๋ ˆ์Šค ๊ฒฝ๊ฐ ๋ชจ๋ธ์„ ๊ตฌ์ถ•ํ•œ๋‹ค. ๋˜ํ•œ ์‚ฌ์šฉ์ž ์›Œํฌ๋กœ๋“œ ํŠน์„ฑ์„ ๊ณ ๋ คํ•˜์—ฌ, ์†Œ๊ฑฐ ์ŠคํŠธ๋ ˆ์Šค ๊ฒฝ๊ฐ ๊ธฐ๋ฒ•์˜ ํšจ๊ณผ๊ฐ€ ์ตœ๋Œ€ํ™” ๋  ์ˆ˜ ์žˆ๋Š” ์ตœ์ ์˜ ๊ฒฝ๊ฐ ์ˆ˜์ค€์„ ๋™์ ์œผ๋กœ ํŒ๋‹จํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•œ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด์„œ ๋‚ธ๋“œ ๋ธ”๋ก์„ ์—ดํ™”์‹œํ‚ค๋Š” ์ฃผ์š” ์›์ธ์ธ ์†Œ๊ฑฐ ๋™์ž‘์„ ํšจ์œจ์ ์œผ๋กœ ์ œ์–ดํ•จ์œผ๋กœ์จ ์ €์žฅ์žฅ์น˜์˜ ์ˆ˜๋ช…์„ ํšจ๊ณผ์ ์œผ๋กœ ํ–ฅ์ƒ์‹œํ‚จ๋‹ค. ๋‘˜์งธ๋กœ, ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๊ณ ์šฉ๋Ÿ‰ SSD์—์„œ์˜ ๋‚ด๋ถ€ ๋ฐ์ดํ„ฐ ์ด๋™์œผ๋กœ ์ธํ•œ ์„ฑ๋Šฅ ์ €ํ•˜๋ฌธ์ œ๋ฅผ ๊ฐœ์„ ํ•˜๊ธฐ ์œ„ํ•ด์„œ ๋‚ธ๋“œ ํ”Œ๋ž˜์‰ฌ์˜ ์ œํ•œ๋œ ์นดํ”ผ๋ฐฑ(copyback) ๋ช…๋ น์„ ํ™œ์šฉํ•˜๋Š” ์ ์‘ํ˜• ๊ธฐ๋ฒ•์ธ rCPB์„ ์ œ์•ˆํ•œ๋‹ค. rCPB์€ Copyback ๋ช…๋ น์˜ ํšจ์œจ์„ฑ์„ ๊ทน๋Œ€ํ™” ํ•˜๋ฉด์„œ๋„ ๋ฐ์ดํ„ฐ ์‹ ๋ขฐ์„ฑ์— ๋ฌธ์ œ๊ฐ€ ์—†๋„๋ก ๋‚ธ๋“œ์˜ ๋ธ”๋Ÿญ์˜ ๋…ธํ™”ํŠน์„ฑ์„ ๋ฐ˜์˜ํ•œ ์ƒˆ๋กœ์šด copyback ์˜ค๋ฅ˜ ์ „ํŒŒ ๋ชจ๋ธ์„ ๊ธฐ๋ฐ˜์œผ๋กœํ•œ๋‹ค. ์ด์—๋”ํ•ด, ์‹ ๋ขฐ์„ฑ์ด ๋‹ค๋ฅธ ๋ธ”๋Ÿญ๊ฐ„์˜ copyback ๋ช…๋ น์„ ํ™œ์šฉํ•œ ๋ฐ์ดํ„ฐ ์ด๋™์„ ๋ฌธ์ œ์—†์ด ๊ด€๋ฆฌํ•˜๊ธฐ ์œ„ํ•ด์„œ ์ž์› ํšจ์œจ์ ์ธ ์˜ค๋ฅ˜ ๊ด€๋ฆฌ ์ฒด๊ณ„๋ฅผ ์ œ์•ˆํ•œ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด์„œ ์‹ ๋ขฐ์„ฑ์— ๋ฌธ์ œ๋ฅผ ์ฃผ์ง€ ์•Š๋Š” ์ˆ˜์ค€์—์„œ copyback์„ ์ตœ๋Œ€ํ•œ ํ™œ์šฉํ•˜์—ฌ ๋‚ด๋ถ€ ๋ฐ์ดํ„ฐ ์ด๋™์„ ์ตœ์ ํ™” ํ•จ์œผ๋กœ์จ SSD์˜ ์„ฑ๋Šฅํ–ฅ์ƒ์„ ๋‹ฌ์„ฑํ•  ์ˆ˜ ์žˆ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ดˆ๊ณ ์šฉ๋Ÿ‰ SSD์—์„œ ๋‚ธ๋“œ ํ”Œ๋ž˜์‰ฌ์˜ ๋‹ค์ด(die) ๋ถˆ๋Ÿ‰์œผ๋กœ ์ธํ•œ ๋ ˆ์ด๋“œ(redundant array of independent disks, RAID) ๋ฆฌ๋นŒ๋“œ ์˜ค๋ฒ„ํ—ค๋“œ๋ฅผ ์ตœ์†Œํ™” ํ•˜๊ธฐ์œ„ํ•œ ์ƒˆ๋กœ์šด RAID ๋ณต๊ตฌ ๊ธฐ๋ฒ•์ธ reparo๋ฅผ ์ œ์•ˆํ•œ๋‹ค. Reparo๋Š” SSD์— ๋Œ€ํ•œ ๊ต์ฒด์—†์ด SSD์˜ ๋ถˆ๋Ÿ‰ die์— ๋Œ€ํ•ด์„œ๋งŒ ๋ณต๊ตฌ๋ฅผ ์ˆ˜ํ–‰ํ•จ์œผ๋กœ์จ ๋ณต๊ตฌ ์˜ค๋ฒ„ํ—ค๋“œ๋ฅผ ์ตœ์†Œํ™”ํ•œ๋‹ค. ๋ถˆ๋Ÿ‰์ด ๋ฐœ์ƒํ•œ die์˜ ๋ฐ์ดํ„ฐ๋งŒ ์„ ๋ณ„์ ์œผ๋กœ ๋ณต๊ตฌํ•จ์œผ๋กœ์จ ๋ณต๊ตฌ ๊ณผ์ •์˜ ๋ฆฌ๋นŒ๋“œ ํŠธ๋ž˜ํ”ฝ์„ ์ตœ์†Œํ™”ํ•˜๋ฉฐ, SSD ๋‚ด๋ถ€์˜ ๋ณ‘๋ ฌ๊ตฌ์กฐ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๋ถˆ๋Ÿ‰ die ๋ณต๊ตฌ ์‹œ๊ฐ„์„ ํšจ๊ณผ์ ์œผ๋กœ ๋‹จ์ถ•ํ•œ๋‹ค. ๋˜ํ•œ die ๋ถˆ๋Ÿ‰์œผ๋กœ ์ธํ•œ ๋ฌผ๋ฆฌ์  ๊ณต๊ฐ„๊ฐ์†Œ์˜ ๋ถ€์ž‘์šฉ์„ ์ตœ์†Œํ™” ํ•จ์œผ๋กœ์จ ๋ณต๊ตฌ ์ดํ›„์˜ ์„ฑ๋Šฅ ์ €ํ•˜ ๋ฐ ์ˆ˜๋ช…์˜ ๊ฐ์†Œ ๋ฌธ์ œ๊ฐ€ ์—†๋„๋ก ํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ ์ œ์•ˆํ•œ ๊ธฐ๋ฒ•๋“ค์€ ์ €์žฅ์žฅ์น˜ ํ”„๋กœํ† ํƒ€์ž… ๋ฐ ๊ณต๊ฐœ ๋‚ธ๋“œ ํ”Œ๋ž˜์‰ฌ ์ €์žฅ์žฅ์น˜ ๊ฐœ๋ฐœํ™˜๊ฒฝ, ๊ทธ๋ฆฌ๊ณ  ์‹ค์žฅ SSDํ™˜๊ฒฝ์— ๊ตฌํ˜„๋˜์—ˆ์œผ๋ฉฐ, ์‹ค์ œ ์‘์šฉ ํ”„๋กœ๊ทธ๋žจ์„ ๋ชจ์‚ฌํ•œ ๋‹ค์–‘ํ•œ ๋ฒคํŠธ๋งˆํฌ ๋ฐ ์‹ค์ œ I/O ํŠธ๋ ˆ์ด์Šค๋“ค์„ ์ด์šฉํ•˜์—ฌ ๊ทธ ์œ ์šฉ์„ฑ์„ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ์‹คํ—˜ ๊ฒฐ๊ณผ, ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•๋“ค์„ ํ†ตํ•ด์„œ ์ดˆ๊ณ ์šฉ๋Ÿ‰ SSD์˜ ์‹ ๋ขฐ์„ฑ ๋ฐ ์„ฑ๋Šฅ์„ ํšจ๊ณผ์ ์œผ๋กœ ๊ฐœ์„ ํ•  ์ˆ˜ ์žˆ์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค.I Introduction 1 1.1 Motivation 1 1.2 Dissertation Goals 3 1.3 Contributions 5 1.4 Dissertation Structure 8 II Background 11 2.1 Overview of 3D NAND Flash Memory 11 2.2 Reliability Management in NAND Flash Memory 14 2.3 UL SSD architecture 15 2.4 Related Work 17 2.4.1 NAND endurance optimization by utilizing page characteristics difference 17 2.4.2 Performance optimizations using copyback operation 18 2.4.3 Optimizations for RAID Rebuild 19 2.4.4 Reliability improvement using internal RAID 20 III GuardedErase: Extending SSD Lifetimes by Protecting Weak Wordlines 22 3.1 Reliability Characterization of a 3D NAND Flash Block 22 3.1.1 Large Reliability Variations Among WLs 22 3.1.2 Erase Stress on Flash Reliability 26 3.2 GuardedErase: Design Overview and its Endurance Model 28 3.2.1 Basic Idea 28 3.2.2 Per-WL Low-Stress Erase Mode 31 3.2.3 Per-Block Erase Modes 35 3.3 Design and Implementation of LongFTL 39 3.3.1 Overview 39 3.3.2 Weak WL Detector 40 3.3.3 WAF Monitor 42 3.3.4 GErase Mode Selector 43 3.4 Experimental Results 46 3.4.1 Experimental Settings 46 3.4.2 Lifetime Improvement 47 3.4.3 Performance Overhead 49 3.4.4 Effectiveness of Lowest Erase Relief Ratio 50 IV Improving SSD Performance Using Adaptive Restricted- Copyback Operations 52 4.1 Motivations 52 4.1.1 Data Migration in Modern SSD 52 4.1.2 Need for Block Aging-Aware Copyback 53 4.2 RCPB: Copyback with a Limit 55 4.2.1 Error-Propagation Characteristics 55 4.2.2 RCPB Operation Model 58 4.3 Design and Implementation of rcFTL 59 4.3.1 EPM module 60 4.3.2 Data Migration Mode Selection 64 4.4 Experimental Results 65 4.4.1 Experimental Setup 65 4.4.2 Evaluation Results 66 V Reparo: A Fast RAID Recovery Scheme for Ultra- Large SSDs 70 5.1 SSD Failures: Causes and Characteristics 70 5.1.1 SSD Failure Types 70 5.1.2 SSD Failure Characteristics 72 5.2 Impact of UL SSDs on RAID Reliability 74 5.3 RAID Recovery using Reparo 77 5.3.1 Overview of Reparo 77 5.4 Cooperative Die Recovery 82 5.4.1 Identifier: Parallel Search of Failed LBAs 82 5.4.2 Handler: Per-Core Space Utilization Adjustment 83 5.5 Identifier Acceleration Using P2L Mapping Information 89 5.5.1 Page-level P2L Entrustment to Neighboring Die 90 5.5.2 Block-level P2L Entrustment to Neighboring Die 92 5.5.3 Additional Considerations for P2L Entrustment 94 5.6 Experimental Results 95 5.6.1 Experimental Settings 95 5.6.2 Experimental Results 97 VI Conclusions 109 6.1 Summary 109 6.2 Future Work 111 6.2.1 Optimization with Accurate WAF Prediction 111 6.2.2 Maximizing Copyback Threshold 111 6.2.3 Pre-failure Detection 112๋ฐ•
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