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At least 829 records · Page 46

A petabyte size electronic library using the N-Gram memory engine

A model library containing petabytes of data is proposed by Triada, Ltd., Ann Arbor, Michigan. The library uses the newly patented N-Gram Memory Engine (Neurex), for storage, compression, and retrieval. Neurex splits data into two parts: a hierarchical network of associative memories that store 'information' from data and a permutation operator that preserves sequence. Neurex is expected to offer four advantages in mass storage systems. Neurex representations are dense, fully reversible, hence less expensive to store. Neurex becomes exponentially more stable with increasing data flow; thus its contents and the inverting algorithm may be mass produced for low cost distribution. Only a small permutation operator would be recalled from the library to recover data. Neurex may be enhanced to recall patterns using a partial pattern. Neurex nodes are measures of their pattern. Researchers might use nodes in statistical models to avoid costly sorting and counting procedures. Neurex subsumes a theory of learning and memory that the author believes extends information theory. Its first axiom is a symmetry principle: learning creates memory and memory evidences learning. The theory treats an information store that evolves from a null state to stationarity. A Neurex extracts information data without a priori knowledge; i.e., unlike neural networks, neither feedback nor training is required. The model consists of an energetically conservative field of uniformly distributed events with variable spatial and temporal scale, and an observer walking randomly through this field. A bank of band limited transducers (an 'eye'), each transducer in a bank being tuned to a sub-band, outputs signals upon registering events. Output signals are 'observed' by another transducer bank (a mid-brain), except the band limit of the second bank is narrower than the band limit of the first bank. The banks are arrayed as n 'levels' or 'time domains, td.' The banks are the hierarchical network (a cortex) and transducers are (associative) memories. A model Neurex was built and studied. Data were 50 MB to 10 GB samples of text, data base, and images: black/white, grey scale, and high resolution in several spectral bands. Memories at td, S(m(sub td)), were plotted against outputs of memories at td-1. S(m(sub td)) was Boltzman distributed, and memory frequencies exhibited self-organized criticality (SOC); i.e., 'l/f(sup beta)' after long exposures to data. Whereas output signals from level n may be encoded with B(sub output) = O(-log(2)f(sup beta)) bits, and input data encoded with B(sub input) = O((S(td)/S(td-1))(sup n)), B(sup output)/B(sub input) is much less than 1 always, the Neurex determines a canonical code for data and it is a lossless data compressor. Further tests are underway to confirm these results with more data types and larger samples.

Bugajski, Joseph M.↗

The Application of Beowulf-Class Computing to Computational Electromagnetics

Current computational developments at the Jet Propulsion Laboratory (JPL) are motivated by the NASA/JPL goal of reducing payload in future space missions while increasing mission capability through miniaturization of active and passive sensors, analytical instruments and communication systems.

beowulf-class↗

High-performance ultra-low power VLSI analog processor for data compression

An apparatus for data compression employing a parallel analog processor. The apparatus includes an array of processor cells with N columns and M rows wherein the processor cells have an input device, memory device, and processor device. The input device is used for inputting a series of input vectors. Each input vector is simultaneously input into each column of the array of processor cells in a pre-determined sequential order. An input vector is made up of M components, ones of which are input into ones of M processor cells making up a column of the array. The memory device is used for providing ones of M components of a codebook vector to ones of the processor cells making up a column of the array. A different codebook vector is provided to each of the N columns of the array. The processor device is used for simultaneously comparing the components of each input vector to corresponding components of each codebook vector, and for outputting a signal representative of the closeness between the compared vector components. A combination device is used to combine the signal output from each processor cell in each column of the array and to output a combined signal. A closeness determination device is then used for determining which codebook vector is closest to an input vector from the combined signals, and for outputting a codebook vector index indicating which of the N codebook vectors was the closest to each input vector input into the array.

Tawel, Raoul↗

Performance Evaluation of an Intel Haswell- and Ivy Bridge-Based Supercomputer Using Scientific and Engineering Applications

We present a performance evaluation conducted on a production supercomputer of the Intel Xeon Processor E5- 2680v3, a twelve-core implementation of the fourth-generation Haswell architecture, and compare it with Intel Xeon Processor E5-2680v2, an Ivy Bridge implementation of the third-generation Sandy Bridge architecture. Several new architectural features have been incorporated in Haswell including improvements in all levels of the memory hierarchy as well as improvements to vector instructions and power management. We critically evaluate these new features of Haswell and compare with Ivy Bridge using several low-level benchmarks including subset of HPCC, HPCG and four full-scale scientific and engineering applications. We also present a model to predict the performance of HPCG and Cart3D within 5%, and Overflow within 10% accuracy.

Ivy Bridge↗

Designing a High Performance OpenSHMEM Implementation using Universal Common Communication Substrate as a Communication Middleware

OpenSHMEM is an effort to standardize the well-known SHMEM parallel programming library. The project aims to produce an open-source and portable SHMEM API and is led by ORNL and UH. In this paper, we optimize the current OpenSHMEM reference implementa- tion, based on GASNet, to achieve higher performance characteristics. To achieve these desired performance characteristics, we have redesigned an important component of the OpenSHMEM implementation, the network layer, to leverage a low-level communication library designed for imple- menting parallel programming models called UCCS. In particular, UCCS provides an interface and semantics such as native atomic operations and remote memory operations to better support PGAS programming models, including OpenSHMEM. Through the use of microbenchmarks, we evaluate this new OpenSHMEM implementation on various network metrics, including the latency of point-to-point and collective operations. Furthermore, we compare the performance of our OpenSHMEM imple- mentation with the state-of-the-art SGI SHMEM. Our results show that the atomic operations of our OpenSHMEM implementation outperform SGI s SHMEM implementation by 3%. Its RMA operations outperform both SGI s SHMEM and the original OpenSHMEM reference implemen- tation by as much as 18% and 12% for gets, and as much as 83% and 53% for puts.

Welch, Donald A↗

Influence of boron on the microstructural and mechanical properties of Ni{sub 53.5}Mn{sub 26.0}Ga{sub 20.5} shape memory alloy

Boron addition to Ni{sub 53.5}Mn{sub 26.0}Ga{sub 20.5} alloy is found to modify the microstructure and mechanical properties substantially. Studies on (Ni{sub 53.5}Mn{sub 26.0}Ga{sub 20.5})B{sub x} alloys reveal that boron addition causes grain refinement which led to an increase in compressive strength in x=0.5 alloy which also retained multimode twinning. Substantial second phase segregation rich in Ni was seen at grain boundaries, the extent of which increased with boron content. This led to a compositional shift in the matrix phase which resulted in a reduction in the martensitic transformation temperature and which in turn caused an easy deformation at low stresses and suppression of multimode twinning in x=1.0 alloy.

36 MATERIALS SCIENCE↗

Conceptual design of a 10 to the 8th power bit magnetic bubble domain mass storage unit and fabrication, test and delivery of a feasibility model

The conceptual design of a highly reliable 10 to the 8th power-bit bubble domain memory for the space program is described. The memory has random access to blocks of closed-loop shift registers, and utilizes self-contained bubble domain chips with on-chip decoding. Trade-off studies show that the highest reliability and lowest power dissipation is obtained when the memory is organized on a bit-per-chip basis. The final design has 800 bits/register, 128 registers/chip, 16 chips/plane, and 112 planes, of which only seven are activated at a time. A word has 64 data bits +32 checkbits, used in a 16-adjacent code to provide correction of any combination of errors in one plane. 100 KHz maximum rotational frequency keeps power low (equal to or less than, 25 watts) and also allows asynchronous operation. Data rate is 6.4 megabits/sec, access time is 200 msec to an 800-word block and an additional 4 msec (average) to a word. The fabrication and operation are also described for a 64-bit bubble domain memory chip designed to test the concept of on-chip magnetic decoding. Access to one of the chip's four shift registers for the read, write, and clear functions is by means of bubble domain decoders utilizing the interaction between a conductor line and a bubble.

Source record↗

On the Feasibility of 1T Ferroelectric FET Memory Array

To fully exploit the ferroelectric field effect transistor (FeFET) as compact embedded nonvolatile memory for various computing and storage applications, it is desirable to use a single FeFET (1T) as a unit cell and arrange the cells into an array. However, many write mechanisms for an 1T FeFET array reported in the literature are yet to be validated experimentally. In this work, we performed a comprehensive experimental characterization on the write operations in an 1T- NOR and 1T- AND array using n-channel bulk FeFETs. We discovered that: 1) the source/drain contact can only supply minority carriers (i.e., electrons) to the channel for polarization screening during the low- V TH state programming; 2) the body contact can not only supply majority carriers (i.e., holes) for efficient high- V TH state write, but also depletion charge for low- V TH state programming, though with lower efficiency; and 3) during the low/high- V TH programming, only the path that can supply negative/positive screening charges, respectively, need to respond, which necessitates the application of proper write biases on the corresponding terminal. Based on the understanding of these write mechanisms, we show the importance of localized body contact or column-wise body contact for the successful high- V TH state programming. We also show that the previously proposed C- AND write scheme fails to program the FeFET to the low- V TH state for our devices. Finally, we propose several write schemes for both 1T- AND and 1T- NOR arrays for various scenarios providing insights for choosing the appropriate write scheme, which will facilitate the adoption of 1T FeFET memory arrays for emerging applications.

FeFET↗

A dynamic solvent chamber propagation estimation framework using RNN for warm solvent injection in heterogeneous reservoirs

Warm solvent injection (WSI), injecting low-temperature solvent into formations to reduce the viscosity of heavy oil, is a clean technology for heavy oil production through reducing greenhouse gas emissions and water usage. The success of WSI operation depends on the uniform development and propagation of solvent chambers in reservoirs. However, reservoir heterogeneity stemming from shale barriers plays a detrimental role in the conformance of solvent chamber development and oil production rate. In this work, we developed a novel recurrent neural network (RNN)-based framework with the capability of efficiently tracking and estimating the solvent chamber positions in heterogeneous reservoirs based on only production time-series data. The developed estimation model utilizes the “sequence-to-sequence" mapping methodology to correlate observed production time-series sequence and solvent chamber edge sequence via a long short-term memory (LSTM) algorithm. The trained RNN models exhibit high accuracy, evidenced by the predicted dynamic solvent chamber locations match the corresponding true locations from numerical simulation, with a high coefficient of determination (R 2 ) and a low mean squared error. Specifically, the achieved R 2 values exceed 0.98 on both the training and testing data. The developed RNN-based workflow was tested via several cases from both regularly- and irregularly-shaped shale barriers, and the results were promising. The predicted solvent chambers showed strong agreement with those obtained from numerical simulations. The major benefits of this workflow include reducing computational time and saving overall monitoring and tracking costs for conventional techniques. In conclusion, the present work would provide a good demonstration of the capability of practical integration of machine learning methods in solving engineering problems.

58 GEOSCIENCES↗

Summary of Test Results of MQXFS1—The First Short Model 150 mm Aperture Nb 3 Sn Quadrupole for the High-Luminosity LHC Upgrade

The development of Nb 3 Sn quadrupole magnets for the High-Luminosity LHC upgrade is a joint venture between the US LHC Accelerator Research Program (LARP)* and CERN with the goal of fabricating large aperture quadrupoles for the LHC interaction regions (IR). The inner triplet (low-β) NbTi quadrupoles in the IR will be replaced by the stronger Nb3Sn magnets boosting the LHC program of having 10-fold increase in integrated luminosity after the foreseen upgrades. Previously, LARP conducted successful tests of short and long models with up to 120 mm aperture. The first short 150 mm aperture quadrupole model MQXFS1 was assembled with coils fabricated by both CERN and LARP. The magnet demonstrated a strong performance at Fermilab's vertical magnet test facility reaching the LHC operating limits. This paper presents the latest results from MQXFS1 tests with changed prestress levels. The overall magnet performance, including quench training and memory, ramp rate, and temperature dependence, is also summarized.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Thin film memory matrix using amorphous and high resistive layers

Memory cells in a matrix are provided by a thin film of amorphous semiconductor material overlayed by a thin film of resistive material. An array of parallel conductors on one side perpendicular to an array of parallel conductors on the other side enable the amorphous semiconductor material to be switched in addressed areas to be switched from a high resistance state to a low resistance state with a predetermined level of electrical energy applied through selected conductors, and thereafter to be read out with a lower level of electrical energy. Each cell may be fabricated in the channel of an MIS field-effect transistor with a separate common gate over each section to enable the memory matrix to be selectively blanked in sections during storing or reading out of data. This allows for time sharing of addressing circuitry for storing and reading out data in a synaptic network, which may be under control of a microprocessor.

Thakoor, Anilkumar P.↗

Kinetics of Domain Switching by Mechanical and Electrical Stimulation in Relaxor-Based Ferroelectrics

Ferroelectric materials have been extensively explored for applications in high-density nonvolatile memory devices because of their ferroelectric-ferroelastic domain-switching behavior under electric loading or mechanical stress. However, the existence of ferroelectric and ferroelastic backswitching would cause significant data loss, which affects the reliability of data storage. In this work, we apply in situ transmission electron microscopy and phase-field modeling to explore the unique ferroelastic domain-switching kinetics and the origin of this in relaxor-based Pb(Mg 1/3 Nb 2/3 )O 3 -33%PbTiO 3 single-crystal pillars under electrical and mechanical stimulations. Results showed that the electric-mechanical hysteresis loop shifted for relaxor-based single-crystal pillars because of the low energy levels of domains in the material and the constraint on the pillars, resulting in various mechanically reversible and irreversible domain-switching states. The phenomenon can potentially be used for advanced bit writing and reading in nonvolatile memories, which effectively overcomes the backswitching problem and broadens the types of ferroelectric materials for nonvolatile memory applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Non-convex Multi-species Hopfield Models

In this work we introduce a multi-species generalization of the Hopfield model for associative memory, where neurons are divided into groups and both inter-groups and intra-groups pair-wise interactions are considered, with different intensities. Thus, this system contains two of the main ingredients of modern deep neural-network architectures: Hebbian interactions to store patterns of information and multiple layers coding different levels of correlations. The model is completely solvable in the low-load regime with a suitable generalization of the Hamilton–Jacobi technique, despite the Hamiltonian can be a non-definite quadratic form of the Mattis magnetizations. The family of multi-species Hopfield model includes, as special cases, the 3-layers Restricted Boltzmann Machine with Gaussian hidden layer and the Bidirectional Associative Memory model.

97 MATHEMATICS AND COMPUTING↗

Efficient Temperature-Dependent Green’s Functions Methods for Realistic Systems: Compact Grids for Orthogonal Polynomial Transforms

The Matsubara Green’s function that is used to describe temperature-dependent behavior is expressed on a numerical grid. While such a grid usually has a couple of hundred points for low-energy model systems, for realistic systems with large basis sets the size of an accurate grid can be tens of thousands of points, constituting a severe computational and memory bottleneck. In this paper, we determine efficient imaginary time grids for the temperature-dependent Matsubara Green’s function formalism that can be used for calculations on realistic systems. Here we show that, because of the use of an orthogonal polynomial transform, we can restrict the imaginary time grid to a few hundred points and reach micro-Hartree accuracy in the electronic energy evaluation. Moreover, we show that only a limited number of orthogonal polynomial expansion coefficients are necessary to preserve accuracy when working with a dual representation of the Green’s function or self-energy and transforming between the imaginary time and frequency domain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Voltage-controlled low-energy switching of nanomagnets through Ruderman-Kittel-Kasuya-Yosida interactions for magnetoelectric device applications

In this article, we consider through simulation low-energy switching of nanomagnets via electrostatically gated inter-magnet Ruderman-Kittel-Kasuya-Yosida (RKKY) interactions on the surface of three-dimensional topological insulators, for possible memory and nonvolatile logic applications. We model the possibility and dynamics of RKKY-based switching of one nanomagnet by coupling to one or more nanomagnets of set orientation. Potential applications to both memory and nonvolatile logic are illustrated. Sub-attojoule switching energies, far below conventional spin transfer torque (STT)-based memories and even below CMOS logic appear possible. Switching times on the order of a few nanoseconds, comparable to times for STT switching, are estimated for ferromagnetic nanomagnets, but the approach also appears compatible with the use of antiferromagnets which may allow for faster switching.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Empowering 2D nanoelectronics via ferroelectricity

Introducing ferroelectricity to two-dimensional (2D) van der Waals (vdW) materials such as graphene, transition metal dichalcogenides, and black phosphorous presents a promising route for developing high-speed and low-power nanoelectronics. This Perspective reviews two actively pursued materials strategies, ferroelectric/vdW heterostructures and vdW ferroelectric materials. Finally, the topics discussed include their application potential and performance limitations as memory, logic, sensing, and optical devices, as well as the challenges and outlook of the field.

2D materials↗

Effective Landau-type model of a Hf x Zr 1 - x O 2 -graphene nanostructure

Here, to describe the charge-polarization coupling in the nanostructure formed by a thin Hf x Zr 1-x O 2 film with a single-layer graphene as a top electrode, we develop the “effective” Landau-Ginzburg-Devonshire model. This approach is based on the parametrization of the Landau expansion coefficients for the polar (FE) and antipolar (AFE) orderings in thin Hf 1-x Zr x O 2 films from a limited number of polarization-field curves and hysteresis loops. The Landau expansion coefficients are nonlinearly dependent on the film thickness h and Zr/[Hf+Zr] ratio x, in contrast to h-independent and linearly x-dependent expansion coefficients of a classical Landau energy. We explain the dependence of the Landau expansion coefficients by the strong nonmonotonic dependence of the Hf 1-x Zr x O 2 film polar properties on the film thickness, grain size and surface energy. The proposed Landau free energy with five “effective” expansion coefficients, which are interpolation functions of x and h, describes the continuous transformation of polarization dependences on applied electric field and hysteresis loop shapes induced by the changes of x and h in the range 0 < x < 1 and 5 nm < h < 35 nm. Using the effective free energy, we demonstrated that the polarization of Hf 1-x Zr x O 2 film influences strongly on the graphene conductivity, and the full correlation between the distribution of polarization and charge carriers in graphene is revealed. In accordance with our modeling, the polarization of the (5 – 25) nm thick Hf 1-x Zr x O 2 films, which are in the ferroelectric-like or antiferroelectric-like states for the chemical compositions 0.35 ≤ x ≤ 0.95, determine the concentration of carriers in graphene and can control its field dependence. The result can be promising for creation of next generation Si-compatible nonvolatile memories and graphene-ferroelectric FETs, because the working voltages applied to the Hf 1-x Zr x O 2 film (which acts as a gate) can be relatively low (less than 2 V). These low voltages are sufficient to induce the pronounced hysteresis of ferroelectric polarization in the Hf 1-x Zr x O 2 gate, which, due to the strong electric coupling, induces the hysteresis of the graphene charge.

36 MATERIALS SCIENCE↗