scholarly journals State-Transition-Aware Spilling Heuristic for MLC STT-RAM-Based Registers

VLSI Design ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Yuanhui Ni ◽  
Zhiyao Gong ◽  
Weiwen Chen ◽  
Chengmo Yang ◽  
Keni Qiu
Keyword(s):  
State Transition ◽  
Cost Minimization ◽  
Cost Model ◽  
Random Access ◽  
Spin Transfer Torque ◽  
Space Environment ◽  
State Transitions ◽  
Clear Understanding ◽  
Natural Immunity ◽  
The Impact

Multilevel Cell Spin-Transfer Torque Random Access Memory (MLC STT-RAM) is a promising nonvolatile memory technology to build registers for its natural immunity to electromagnetic radiation in rad-hard space environment. Unlike traditional SRAM-based registers, MLC STT-RAM exhibits unbalanced write state transitions due to the fact that the magnetization directions of hard and soft domains cannot be flipped independently. This feature leads to nonuniform costs of write states in terms of latency and energy. However, current SRAM-targeting register allocations do not have a clear understanding of the impact of the different write state-transition costs. As a result, those approaches heuristically select variables to be spilled without considering the spilling priority imposed by MLC STT-RAM. Aiming to address this limitation, this paper proposes a state-transition-aware spilling cost minimization (SSCM) policy, to save power when MLC STT-RAM is employed in register design. Specifically, the spilling cost model is first constructed according to the linear combination of different state-transition frequencies. Directed by the proposed cost model, the compiler picks up spilling candidates to achieve lower power and higher performance. Experimental results show that the proposed SSCM technique can save energy by 19.4% and improve the lifetime by 23.2% of MLC STT-RAM-based register design.

scholarly journals Viscoelasticity and cell jamming state transition

2021 ◽  
Author(s):  
Ivana Pajic-Lijakovic ◽  
Milan Milivojevic
Keyword(s):  
Residual Stress ◽  
Wound Healing ◽  
Cell Migration ◽  
State Transition ◽  
State Transitions ◽  
Collective Cell Migration ◽  
Biological Processes ◽  
Cell Mobility ◽  
Controversial Topic ◽  
The Impact

Although collective cell migration (CCM) is a highly coordinated migratory mode, perturbations in the form of jamming state transitions and vice versa often occur even in 2D. These perturbations are involved in various biological processes, such as embryogenesis, wound healing and cancer invasion. CCM induces accumulation of cell residual stress which has a feedback impact to cell packing density. Density-mediated change of cell mobility influences the state of viscoelasticity of multicellular systems and on that base the jamming state transition. Although a good comprehension of how cells collectively migrate by following molecular rules has been generated, the impact of cellular rearrangements on cell viscoelasticity remains less understood. Thus, considering the density driven evolution of viscoelasticity caused by reduction of cell mobility could result in a powerful tool in order to address the contribution of cell jamming state transition in CCM and help to understand this important but still controversial topic. In addition, five viscoelastic states gained within three regimes: (1) convective regime, (2) conductive regime, and (3) damped-conductive regime was discussed based on the modeling consideration with special emphasis of jamming and unjamming states.

scholarly journals Pre-Emphasis Pulse Design for Random-Access Memory

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1454
Author(s):  
Yoshihiro Sugiura ◽  
Toru Tanzawa
Keyword(s):  
Time Constant ◽  
Random Access ◽  
Memory Cell ◽  
Random Access Memory ◽  
Memory Access ◽  
Access Time ◽  
Access Memory ◽  
Delay Times ◽  
Cell Current ◽  
The Impact

This paper describes how one can reduce the memory access time with pre-emphasis (PE) pulses even in non-volatile random-access memory. Optimum PE pulse widths and resultant minimum word-line (WL) delay times are investigated as a function of column address. The impact of the process variation in the time constant of WL, the cell current, and the resistance of deciding path on optimum PE pulses are discussed. Optimum PE pulse widths and resultant minimum WL delay times are modeled with fitting curves as a function of column address of the accessed memory cell, which provides designers with the ability to set the optimum timing for WL and BL (bit-line) operations, reducing average memory access time.

scholarly journals Machine Learning for Statistical Modeling

2021 ◽  
Vol 26 (3) ◽  
pp. 1-17
Author(s):  
Urmimala Roy ◽  
Tanmoy Pramanik ◽  
Subhendu Roy ◽  
Avhishek Chatterjee ◽  
Leonard F. Register ◽  
...  
Keyword(s):  
Machine Learning ◽  
Time Distribution ◽  
Switching Time ◽  
A Priori ◽  
Random Access ◽  
Spin Transfer Torque ◽  
Support Vector ◽  
Micromagnetic Simulations ◽  
Physical Systems ◽  
Computational Resources

We propose a methodology to perform process variation-aware device and circuit design using fully physics-based simulations within limited computational resources, without developing a compact model. Machine learning (ML), specifically a support vector regression (SVR) model, has been used. The SVR model has been trained using a dataset of devices simulated a priori, and the accuracy of prediction by the trained SVR model has been demonstrated. To produce a switching time distribution from the trained ML model, we only had to generate the dataset to train and validate the model, which needed ∼500 hours of computation. On the other hand, if 10 6 samples were to be simulated using the same computation resources to generate a switching time distribution from micromagnetic simulations, it would have taken ∼250 days. Spin-transfer-torque random access memory (STTRAM) has been used to demonstrate the method. However, different physical systems may be considered, different ML models can be used for different physical systems and/or different device parameter sets, and similar ends could be achieved by training the ML model using measured device data.

scholarly journals Quantitative determination of organic adsorption capacity in the Palaeozoic shales from South China

2021 ◽  
pp. 014459872098303
Author(s):  
Sibo Wang ◽  
Zhiguang Song ◽  
Jia Xia ◽  
Yuan Gao ◽  
YaoPing Wang ◽  
...  
Keyword(s):  
Adsorption Capacity ◽  
Clear Understanding ◽  
Soluble Organic Matter ◽  
Maximum Increase ◽  
Immature Oil ◽  
Methane Sorption ◽  
Oil Shales ◽  
The Impact ◽  
Total Adsorption

In this study, the methane adsorption capacity of kerogen isolated from the Cambrian, Silurian, and Permian shales and the impact of soluble organic matter (SOM) on the adsorption capacity of these shales were investigated. The results reveal that 1) the adsorption capacity of kerogen varies in a broad range, from 14.48 to 23.22 cm3/g for the Cambrian kerogens, from 15.50 to 36.06 cm3/g for the Silurian kerogens, and from 10.71 to 11.15 cm3/g for the Permian kerogens; 2) the kerogen adsorption accounts for 33.67–70.23% of the total adsorption capacity of these Palaeozoic extracted shales, demonstrating that kerogen is the primary adsorbing substance in shales; 3) the adsorption isotherms of kerogen in highly mature Cambrian and Silurian shales are similar to those of Triassic coal, while the isotherms of kerogen in the relatively immature Permian shales are similar to those of the immature oil shales; and 4) the SOM demonstrates a significant impact on the adsorption capacity of shales as the removal of SOM can cause a maximum increase of 34.29% or a decrease of 23.36% in the total adsorption capacity of shales. However, there is no clear understanding of the impact of SOM on the methane sorption of shales.

Progress and Prospects of Spin Transfer Torque Random Access Memory

2012 ◽  
Vol 48 (11) ◽  
pp. 3025-3030 ◽  
Author(s):  
E. Chen ◽  
D. Apalkov ◽  
A. Driskill-Smith ◽  
A. Khvalkovskiy ◽  
D. Lottis ◽  
...  
Keyword(s):  
Random Access ◽  
Random Access Memory ◽  
Spin Transfer Torque ◽  
Spin Transfer ◽  
Access Memory

Debris/Micrometeoroid Impacts and Synergistic Effects on Spacecraft Materials

MRS Bulletin ◽  
2010 ◽  
Vol 35 (1) ◽  
pp. 41-47 ◽  
Author(s):  
E. Grossman ◽  
I. Gouzman ◽  
R. Verker
Keyword(s):  
Space Debris ◽  
Synergistic Effects ◽  
Degradation Mechanism ◽  
Space Environment ◽  
Materials Properties ◽  
Gas Gun ◽  
Naturally Occurring ◽  
Space Activity ◽  
The Impact ◽  
Debris Impact

AbstractIn the last 40 years, the increased space activity created a new form of space environment of hypervelocity objects—space debris—that have no functional use. The space debris, together with naturally occurring ultrahigh velocity meteoroids, presents a significant hazard to spacecraft. Collision with space debris or meteoroids might result in disfunction of external units such as solar cells, affecting materials properties, contaminating optical devices, or destroying satellites. The collision normally results in the formation of additional debris, increasing the hazard for future missions. The hypervelocity debris effect is studied by retrieving materials from space or by using ground simulation facilities. Simulation facilities, which include the light gas gun and Laser Driven Flyer methods, are used for studying the materials degradation due to debris impact. The impact effect could be accelerated when occurring simultaneously with other space environment components, such as atomic oxygen, ultraviolet, or x-ray radiation. Understanding the degradation mechanism might help in developing materials that will withstand the increasing hazard from the space debris, allowing for longer space missions. The large increase in space debris population and the associated risk to space activity requires significant measures to mitigate this hazard. Most current efforts are being devoted to prevention of collisions by keeping track of the larger debris and avoiding formation of new debris.

scholarly journals The Impact of Long-Term Exposure to Space Environment on Adult Mammalian Organisms: A Study on Mouse Thyroid and Testis

PLoS ONE ◽  
2012 ◽  
Vol 7 (4) ◽  
pp. e35418 ◽  
Author(s):  
Maria Angela Masini ◽  
Elisabetta Albi ◽  
Cristina Barmo ◽  
Tommaso Bonfiglio ◽  
Lara Bruni ◽  
...  
Keyword(s):  
Space Environment ◽  
The Impact ◽  
Mouse Thyroid

scholarly journals Water Accounting Plus (WA+) – a water accounting procedure for complex river basins based on satellite measurements

2013 ◽  
Vol 17 (7) ◽  
pp. 2459-2472 ◽  
Author(s):  
P. Karimi ◽  
W. G. M. Bastiaanssen ◽  
D. Molden
Keyword(s):  
Water Management ◽  
Land Use ◽  
Spatial Information ◽  
River Basins ◽  
Clear Understanding ◽  
Satellite Measurements ◽  
Resource Base ◽  
Water Depletion ◽  
Water Accounting ◽  
The Impact

Abstract. Coping with water scarcity and growing competition for water among different sectors requires proper water management strategies and decision processes. A pre-requisite is a clear understanding of the basin hydrological processes, manageable and unmanageable water flows, the interaction with land use and opportunities to mitigate the negative effects and increase the benefits of water depletion on society. Currently, water professionals do not have a common framework that links depletion to user groups of water and their benefits. The absence of a standard hydrological and water management summary is causing confusion and wrong decisions. The non-availability of water flow data is one of the underpinning reasons for not having operational water accounting systems for river basins in place. In this paper, we introduce Water Accounting Plus (WA+), which is a new framework designed to provide explicit spatial information on water depletion and net withdrawal processes in complex river basins. The influence of land use and landscape evapotranspiration on the water cycle is described explicitly by defining land use groups with common characteristics. WA+ presents four sheets including (i) a resource base sheet, (ii) an evapotranspiration sheet, (iii) a productivity sheet, and (iv) a withdrawal sheet. Every sheet encompasses a set of indicators that summarise the overall water resources situation. The impact of external (e.g., climate change) and internal influences (e.g., infrastructure building) can be estimated by studying the changes in these WA+ indicators. Satellite measurements can be used to acquire a vast amount of required data but is not a precondition for implementing WA+ framework. Data from hydrological models and water allocation models can also be used as inputs to WA+.

Sign in / Sign up

Export Citation Format

Share Document