Data Pattern Aware Reliability Enhancement Scheme for 3D Solid-State Drives

2021 ◽  
Vol 20 (5s) ◽  
pp. 1-20
Author(s):  
Shiqiang Nie ◽  
Weiguo Wu ◽  
Chi Zhang
Keyword(s):  
Low Cost ◽  
Coarse Grained ◽  
Nand Flash ◽  
Program Optimization ◽  
Solid State Drives ◽  
Fine Grained ◽  
Trade Offs ◽  
Program Step ◽  
Reliability Enhancement ◽  
Incremental Step

3D charge-trap (CT) NAND flash-based SSD has been used widely for its large capacity, low cost per bit, and high endurance. One-shot program (OSP) scheme, as a variation of incremental step pulse programming (ISPP) scheme, has been employed to program data for CT flash, whose program unit is the Word-Line (WL) instead of the page. The existing program optimization schemes either make trade-offs among program latency and reliability by adjusting the program step voltage on demand; or remap the most error-prone cell states to others by re-encoding programmed data. However, the data pattern, which represents the ratio of 1s in data values, has not been thoroughly studied. In this paper, we observe that most small files do not contain uniform 1s and 0s among these common file types (i.e., image, audio, text, executable file), leading to programming WL cells in different states unevenly. Some cell states dominate over the WL, while others are not. Based on this observation, we propose a flexible reliability enhancement scheme based on the OSP scheme. This scheme programs the cells into different states with varied , i.e., these cells in one state, whose number is the largest in one WL, are programmed with a fine-grained (namely slow write). In contrast, the minority are programmed with a coarse-grained (namely fast write). So the reliability is improved due to averaging the major enhanced cells with the minor degraded cells without program latency overhead. A series of experiments have been conducted, and the results indicate that the proposed scheme achieves 34% read performance improvement and 16% lifetime elongation on average.

Correlation between dislocation, grain boundary and interface of duplex SS in stress corrosion cracking(SCC)

1990 ◽  
Vol 48 (4) ◽  
pp. 928-929
Author(s):  
Wang Zheng-fang ◽  
Z.F. Wang
Keyword(s):  
Stainless Steel ◽  
Thermal Cycle ◽  
Secondary Phase ◽  
Corrosion Cracking ◽  
Coarse Grained ◽  
Test Environment ◽  
Fine Grained ◽  
Evaluation Test ◽  
Welding Thermal Cycle ◽  
Micro Analysis

The main purpose of this study highlights on the evaluation of chloride SCC resistance of the material,duplex stainless steel,OOCr18Ni5Mo3Si2 (18-5Mo) and its welded coarse grained zone(CGZ).18-5Mo is a dual phases (A+F) stainless steel with yield strength:512N/mm2 .The proportion of secondary Phase(A phase) accounts for 30-35% of the total with fine grained and homogeneously distributed A and F phases(Fig.1).After being welded by a specific welding thermal cycle to the material,i.e. Tmax=1350°C and t8/5=20s,microstructure may change from fine grained morphology to coarse grained morphology and from homogeneously distributed of A phase to a concentration of A phase(Fig.2).Meanwhile,the proportion of A phase reduced from 35% to 5-10°o.For this reason it is known as welded coarse grained zone(CGZ).In association with difference of microstructure between base metal and welded CGZ,so chloride SCC resistance also differ from each other.Test procedures:Constant load tensile test(CLTT) were performed for recording Esce-t curve by which corrosion cracking growth can be described, tf,fractured time,can also be recorded by the test which is taken as a electrochemical behavior and mechanical property for SCC resistance evaluation. Test environment:143°C boiling 42%MgCl2 solution is used.Besides, micro analysis were conducted with light microscopy(LM),SEM,TEM,and Auger energy spectrum(AES) so as to reveal the correlation between the data generated by the CLTT results and micro analysis.

Are Public Bureaucracies Supposed to Be High Reliability Organizations?

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Wolfgang Seibel
Keyword(s):  
Child Protection ◽  
Organization Theory ◽  
Goal Attainment ◽  
High Reliability ◽  
Human Action ◽  
High Reliability Organizations ◽  
Fine Grained ◽  
Trade Offs ◽  
Public Bureaucracy ◽  
Account Standard

This article addresses the question of to what extent conventional theories of high reliability organizations and normal accidents theory are applicable to public bureaucracy. Empirical evidence suggests precisely this. Relevant cases are, for instance, collapsing buildings and bridges due to insufficient supervision of engineering by the relevant authorities, infants dying at the hands of their own parents due to misperceptions and neglect on the part of child protection agencies, uninterrupted serial killings due to a lack of coordination among police services, or improper planning and risk assessment in the preparation of mass events such as soccer games or street parades. The basic argument is that conceptualizing distinct and differentiated causal mechanisms is useful for developing more fine-grained variants of both normal accident theory and high reliability organization theory that take into account standard pathologies of public bureaucracies and inevitable trade-offs connected to their political embeddedness in democratic and rule-of-law-based systems to which belong the tensions between responsiveness and responsibility and between goal attainment and system maintenance. This, the article argues, makes it possible to identify distinct points of intervention at which permissive conditions with the potential to trigger risk-generating human action can be neutralized while the threshold that separates risk-generating human action from actual disaster can be raised to a level that makes disastrous outcomes less probable.

scholarly journals Balanced Sparsity for Efficient DNN Inference on GPU

2019 ◽  
Vol 33 ◽  
pp. 5676-5683 ◽  
Author(s):  
Zhuliang Yao ◽  
Shijie Cao ◽  
Wencong Xiao ◽  
Chen Zhang ◽  
Lanshun Nie
Keyword(s):  
Deep Neural Networks ◽  
General Purpose ◽  
Coarse Grained ◽  
Efficient Computation ◽  
Model Accuracy ◽  
Sparse Model ◽  
Model Inference ◽  
Fine Grained ◽  
Practical Inference ◽  
Speed Up

In trained deep neural networks, unstructured pruning can reduce redundant weights to lower storage cost. However, it requires the customization of hardwares to speed up practical inference. Another trend accelerates sparse model inference on general-purpose hardwares by adopting coarse-grained sparsity to prune or regularize consecutive weights for efficient computation. But this method often sacrifices model accuracy. In this paper, we propose a novel fine-grained sparsity approach, Balanced Sparsity, to achieve high model accuracy with commercial hardwares efficiently. Our approach adapts to high parallelism property of GPU, showing incredible potential for sparsity in the widely deployment of deep learning services. Experiment results show that Balanced Sparsity achieves up to 3.1x practical speedup for model inference on GPU, while retains the same high model accuracy as finegrained sparsity.

scholarly journals A Machine Vision Approach for Bioreactor Foam Sensing

2021 ◽  
pp. 247263032110088
Author(s):  
Jonas Austerjost ◽  
Robert Söldner ◽  
Christoffer Edlund ◽  
Johan Trygg ◽  
David Pollard ◽  
...  
Keyword(s):  
Machine Learning ◽  
Machine Vision ◽  
State Of The Art ◽  
Low Cost ◽  
High Accuracy ◽  
Consumer Electronics ◽  
Learning System ◽  
Automotive Applications ◽  
Fine Grained

Machine vision is a powerful technology that has become increasingly popular and accurate during the last decade due to rapid advances in the field of machine learning. The majority of machine vision applications are currently found in consumer electronics, automotive applications, and quality control, yet the potential for bioprocessing applications is tremendous. For instance, detecting and controlling foam emergence is important for all upstream bioprocesses, but the lack of robust foam sensing often leads to batch failures from foam-outs or overaddition of antifoam agents. Here, we report a new low-cost, flexible, and reliable foam sensor concept for bioreactor applications. The concept applies convolutional neural networks (CNNs), a state-of-the-art machine learning system for image processing. The implemented method shows high accuracy for both binary foam detection (foam/no foam) and fine-grained classification of foam levels.

scholarly journals Submarine lava deltas of the 2018 eruption of Kīlauea volcano

2021 ◽  
Vol 83 (4) ◽  
Author(s):  
S. Adam Soule ◽  
Michael Zoeller ◽  
Carolyn Parcheta
Keyword(s):  
Grain Size ◽  
Pore Pressure ◽  
Mechanistic Model ◽  
Large Fraction ◽  
Volcanic Hazards ◽  
Lava Flows ◽  
Coarse Grained ◽  
Fine Grained ◽  
Fine Grain ◽  
Delta Formation

AbstractHawaiian and other ocean island lava flows that reach the coastline can deposit significant volumes of lava in submarine deltas. The catastrophic collapse of these deltas represents one of the most significant, but least predictable, volcanic hazards at ocean islands. The volume of lava deposited below sea level in delta-forming eruptions and the mechanisms of delta construction and destruction are rarely documented. Here, we report on bathymetric surveys and ROV observations following the Kīlauea 2018 eruption that, along with a comparison to the deltas formed at Pu‘u ‘Ō‘ō over the past decade, provide new insight into delta formation. Bathymetric differencing reveals that the 2018 deltas contain more than half of the total volume of lava erupted. In addition, we find that the 2018 deltas are comprised largely of coarse-grained volcanic breccias and intact lava flows, which contrast with those at Pu‘u ‘Ō‘ō that contain a large fraction of fine-grained hyaloclastite. We attribute this difference to less efficient fragmentation of the 2018 ‘a‘ā flows leading to fragmentation by collapse rather than hydrovolcanic explosion. We suggest a mechanistic model where the characteristic grain size influences the form and stability of the delta with fine grain size deltas (Pu‘u ‘Ō‘ō) experiencing larger landslides with greater run-out supported by increased pore pressure and with coarse grain size deltas (Kīlauea 2018) experiencing smaller landslides that quickly stop as the pore pressure rapidly dissipates. This difference, if validated for other lava deltas, would provide a means to assess potential delta stability in future eruptions.

scholarly journals A cooperative DDoS attack detection scheme based on entropy and ensemble learning in SDN

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Shanshan Yu ◽  
Jicheng Zhang ◽  
Ju Liu ◽  
Xiaoqing Zhang ◽  
Yafeng Li ◽  
...  
Keyword(s):  
Ensemble Learning ◽  
Denial Of Service ◽  
Attack Detection ◽  
Coarse Grained ◽  
Communication Overhead ◽  
Detection Scheme ◽  
Fine Grained ◽  
Ddos Attack ◽  
Network Status ◽  
Ddos Attack Detection

AbstractIn order to solve the problem of distributed denial of service (DDoS) attack detection in software-defined network, we proposed a cooperative DDoS attack detection scheme based on entropy and ensemble learning. This method sets up a coarse-grained preliminary detection module based on entropy in the edge switch to monitor the network status in real time and report to the controller if any abnormality is found. Simultaneously, a fine-grained precise attack detection module is designed in the controller, and a ensemble learning-based algorithm is utilized to further identify abnormal traffic accurately. In this framework, the idle computing capability of edge switches is fully utilized with the design idea of edge computing to offload part of the detection task from the control plane to the data plane innovatively. Simulation results of two common DDoS attack methods, ICMP and SYN, show that the system can effectively detect DDoS attacks and greatly reduce the southbound communication overhead and the burden of the controller as well as the detection delay of the attacks.

Rheology of hydrocarbon gels

1950 ◽  
Vol 200 (1061) ◽  
pp. 183-188 ◽  
Keyword(s):  
Mechanical Properties ◽  
Experimental Measurement ◽  
Theoretical Basis ◽  
Continuous Media ◽  
Point Of View ◽  
Coarse Grained ◽  
Testing Instrument ◽  
Fine Grained ◽  
Mineral Oils ◽  
Space And Time

Hydrocarbon gels contain a number of materials, such as rubber, greases, saponified mineral oils, etc., of great interest for various engineering purposes. Specific requirements in mechanical properties have been met by producing gels in appropriately chosen patterns of constituent components of visible, colloidal, molecular and atomic sizes, ranging from coarse-grained aggregates, represented by sponges, foams, emulsions, etc.; to fine-grained and apparently homogeneous ones, represented by optically clear compounds. The engineer who has to deal with the whole range of such materials will adopt a macroscopic point of view, based on an apparent continuity of all the material structures and of the distributions in space and time of the displacements and forces occurring under mechanical actions. It has been possible to determine these distributions in the framework of a comprehensive scheme in which the fundamental principles of the mechanics of continuous media provide the theoretical basis, and a testing instrument of new design, termed Rheogoniometer, the means of experimental measurement (Weissenberg 1931, 1934, 1946, 1947, 1948).

Microstructural Refinement in a Commercial Aluminum Alloy Processed by ECAP Using a Die Channel Angle of 110 Degrees

2015 ◽  
Vol 1114 ◽  
pp. 3-8
Author(s):  
Nicolae Şerban ◽  
Doina Răducanu ◽  
Nicolae Ghiban ◽  
Vasile Dănuţ Cojocaru
Keyword(s):  
Grain Refinement ◽  
Cross Section ◽  
High Strength ◽  
Secondary Phase ◽  
Coarse Grained ◽  
Metallographic Analysis ◽  
Second Phase ◽  
Channel Angle ◽  
Ambient Temperatures ◽  
Fine Grained

The properties of ultra-fine grained materials are superior to those of corresponding conventional coarse grained materials, being significantly improved as a result of grain refinement. Equal channel angular pressing (ECAP) is an efficient method for modifying the microstructure by refining grain size via severe plastic deformation (SPD) in producing ultra-fine grained materials (UFG) and nanomaterials (NM). The grain sizes produced by ECAP processing are typically in the submicrometer range and this leads to high strength at ambient temperatures. ECAP is performed by pressing test samples through a die containing two channels, equal in cross-section and intersecting at a certain angle. The billet experiences simple shear deformation at the intersection, without any precipitous change in the cross-section area because the die prevents lateral expansion and therefore the billet can be pressed more than once and it can be rotated around its pressing axis during subsequent passes. After ECAP significant grain refinement occurs together with dislocation strengthening, resulting in a considerable enhancement in the strength of the alloys. A commercial AlMgSi alloy (AA6063) was investigated in this study. The specimens were processed for a number of passes up to nine, using a die channel angle of 110°, applying the ECAP route BC. After ECAP, samples were cut from each specimen and prepared for metallographic analysis. The microstructure of the ECAP-ed and as-received material was investigated using optical (OLYMPUS – BX60M) and SEM microscopy (TESCAN VEGA II – XMU). It was determined that for the as-received material the microstructure shows a rough appearance, with large grains of dendritic or seaweed aspect and with a secondary phase at grain boundaries (continuous casting structure). For the ECAP processed samples, the microstructure shows a finished aspect, with refined, elongated grains, also with crumbled and uniformly distributed second phase particles after a typical ECAP texture.

Conditional Belief and the Ramsey Test

2002 ◽  
Vol 51 ◽  
pp. 215-232
Author(s):  
Scott Sturgeon
Keyword(s):  
Everyday Life ◽  
Common Sense ◽  
The Other ◽  
Coarse Grained ◽  
Degrees Of Belief ◽  
Conditional Belief ◽  
Ramsey Test ◽  
Fine Grained

Consider the frameS believes that—.Fill it with a conditional, sayIf you eat an Apple, you'll drink a Coke.what makes the result true? More generally, what facts are marked by instances ofS believes (A→C)?In a sense the answer is obious: beliefs are so marked. Yet that bromide leads directly to competing schools of thought. And the reason is simple.Common-sense thinks of belief two ways. Sometimes it sees it as a three-part affair. When so viewed either you believe, disbelieve, or suspend judgment. This take on belief is coarse-grained. It says belief has three flavours: acceptance, rejection, neither. But it's not the only way common-sense thinks of belief. Sometimes it's more subtle: ‘How strong is your faith?’ can be apposite between believers. That signals an important fact. Ordinary practice also treats belief as a fine-grained affair. It speaks of levels of confidence. It admits degrees of belief. It contains a fine-grained take as well. There are two ways belief is seen in everyday life. One is coarse-grained. The other is fine-grained.

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