Electrical switching in chalcogenide glasses - Some newer insights

The recent studies on the switching. behavior of several chalcogenide semiconductors indicate that there exists a close relation between the electrical switching and structural effects in these materials; the two network topological Thresholds, namely the Rigidity Percolation and the Chemical Threshold are found to influence considerably the composition dependence of the switching voltages/fields of many memory and threshold switching glasses. Further, changes in the coordination of constituent atoms are found to effect a change in the switching behavior (memory to threshold), Also, an interesting relation has been established between the type of switching exhibited and the thermal diffusivity of the material.

Scalable Context-Sensitive Points-To Analysis Using Multi-Dimensional Bloom Filters

Context-sensitive points-to analysis is critical for several program optimizations. However, as the number of contexts grows exponentially, storage requirements for the analysis increase tremendously for large programs, making the analysis non-scalable. We propose a scalable flow-insensitive context-sensitive inclusion-based points-to analysis that uses a specially designed multi-dimensional bloom filter to store the points-to information. Two key observations motivate our proposal: (i) points-to information (between pointer-object and between pointer-pointer) is sparse, and (ii) moving from an exact to an approximate representation of points-to information only leads to reduced precision without affecting correctness of the (may-points-to) analysis. By using an approximate representation a multi-dimensional bloom filter can significantly reduce the memory requirements with a probabilistic bound on loss in precision. Experimental evaluation on SPEC 2000 benchmarks and two large open source programs reveals that with an average storage requirement of 4MB, our approach achieves almost the same precision (98.6%) as the exact implementation. By increasing the average memory to 27MB, it achieves precision upto 99.7% for these benchmarks. Using Mod/Ref analysis as the client, we find that the client analysis is not affected that often even when there is some loss of precision in the points-to representation. We find that the NoModRef percentage is within 2% of the exact analysis while requiring 4MB (maximum 15MB) memory and less than 4 minutes on average for the points-to analysis. Another major advantage of our technique is that it allows to trade off precision for memory usage of the analysis.

MODLEX: A Multi Objective Data Layout EXploration Framework for Embedded Systems-on-Chip

The memory subsystem is a major contributor to the performance, power, and area of complex SoCs used in feature rich multimedia products. Hence, memory architecture of the embedded DSP is complex and usually custom designed with multiple banks of single-ported or dual ported on-chip scratch pad memory and multiple banks of off-chip memory. Building software for such large complex memories with many of the software components as individually optimized software IPs is a big challenge. In order to obtain good performance and a reduction in memory stalls, the data buffers of the application need to be placed carefully in different types of memory. In this paper we present a unified framework (MODLEX) that combines different data layout optimizations to address the complex DSP memory architectures. Our method models the data layout problem as multi-objective genetic algorithm (GA) with performance and power being the objectives and presents a set of solution points which is attractive from a platform design viewpoint. While most of the work in the literature assumes that performance and power are non-conflicting objectives, our work demonstrates that there is significant trade-off (up to 70%) that is possible between power and performance.

VLSI Implementation of Spatial prediction Based Image Compression Scheme

We propose the design and implementation of hardware architecture for spatial prediction based image compression scheme, which consists of prediction phase and quantization phase. In prediction phase, the hierarchical tree structure obtained from the test image is used to predict every central pixel of an image by its four neighboring pixels. The prediction scheme generates an error image, to which the wavelet/sub-band coding algorithm can be applied to obtain efficient compression. The software model is tested for its performance in terms of entropy, standard deviation. The memory and silicon area constraints play a vital role in the realization of the hardware for hand-held devices. The hardware architecture is constructed for the proposed scheme, which involves the aspects of parallelism in instructions and data. The processor consists of pipelined functional units to obtain the maximum throughput and higher speed of operation. The hardware model is analyzed for performance in terms throughput, speed and power. The results of hardware model indicate that the proposed architecture is suitable for power constrained implementations with higher data rate

Direct hexagonal transition of amorphous (Ge2Sb2Te5)(0.9)Se-0.1 thin films

Ge2Sb2Te5 (GST) is well known for its phase change properties and applications in memory and data storage. Efforts are being made to improve its thermal stability and transition between amorphous and crystalline phases. Various elements are doped to GST to improve these properties. In this work, Se has been doped to GST to study its effect on phase change properties. Amorphous GST film crystallized in to rock salt (NaCl) type structure at 150 degrees C and then transformed to hexagonal structure at 250 degrees C. Interestingly, Se doped GST ((GST)(0.9)Se-0.1) film crystallized directly into hexagonal phase and the intermediate phase of NaCl is not observed. The crystallization temperature (T-c) of (GST)(0.9)Se-0.1 is around 200 degrees C, which is 50 degrees C higher than the T-c of GST. For (GST)(0.9)Se-0.1, the threshold switching occurs at about 4.5V which is higher than GST (3 V). Band gap (E-opt) values of as deposited films are calculated from Tauc plot which are 0.63 eV for GST and 0.66 eV for (GST)(0.9)Se-0.1. The E-opt decreases for the films annealed at higher temperatures. The increased T-c, E-opt, the contrast in resistance and the direct transition to hexagonal phase may improve the data readability and thermal stability in the Se doped GST film. (C) 2014 AIP Publishing LLC.

Approximation of Spatio-Temporal Random Processes Using Tensor Decomposition

A new representation of spatio-temporal random processes is proposed in this work. In practical applications, such processes are used to model velocity fields, temperature distributions, response of vibrating systems, to name a few. Finding an efficient representation for any random process leads to encapsulation of information which makes it more convenient for a practical implementations, for instance, in a computational mechanics problem. For a single-parameter process such as spatial or temporal process, the eigenvalue decomposition of the covariance matrix leads to the well-known Karhunen-Loeve (KL) decomposition. However, for multiparameter processes such as a spatio-temporal process, the covariance function itself can be defined in multiple ways. Here the process is assumed to be measured at a finite set of spatial locations and a finite number of time instants. Then the spatial covariance matrix at different time instants are considered to define the covariance of the process. This set of square, symmetric, positive semi-definite matrices is then represented as a third-order tensor. A suitable decomposition of this tensor can identify the dominant components of the process, and these components are then used to define a closed-form representation of the process. The procedure is analogous to the KL decomposition for a single-parameter process, however, the decompositions and interpretations vary significantly. The tensor decompositions are successfully applied on (i) a heat conduction problem, (ii) a vibration problem, and (iii) a covariance function taken from the literature that was fitted to model a measured wind velocity data. It is observed that the proposed representation provides an efficient approximation to some processes. Furthermore, a comparison with KL decomposition showed that the proposed method is computationally cheaper than the KL, both in terms of computer memory and execution time.

Interface-assisted molecular spintronics

Molecular spintronics, a field that utilizes the spin state of organic molecules to develop magneto-electronic devices, has shown an enormous scientific activity for more than a decade. But, in the last couple of years, new insights in understanding the fundamental phenomena of molecular interaction on magnetic surfaces, forming a hybrid interface, are presenting a new pathway for developing the subfield of interface-assisted molecular spintronics. The recent exploration of such hybrid interfaces involving carbon based aromatic molecules shows a significant excitement and promise over the previously studied single molecular magnets. In the above new scenario, hybridization of the molecular orbitals with the spin-polarized bands of the surface creates new interface states with unique electronic and magnetic character. This study opens up a molecular-genome initiative in designing new handles to functionalize the spin dependent electronic properties of the hybrid interface to construct spin-functional tailor-made devices. Through this article, we review this subject by presenting a fundamental understanding of the interface spin-chemistry and spin-physics by taking support of advanced computational and spectroscopy tools to investigate molecular spin responses with demonstration of new interface phenomena. Spin-polarized scanning tunneling spectroscopy is favorably considered to be an important tool to investigate these hybrid interfaces with intra-molecular spatial resolution. Finally, by addressing some of the recent findings, we propose novel device schemes towards building interface tailored molecular spintronic devices for applications in sensor, memory, and quantum computing.

Do gamma oscillations play a role in cerebral cortex?

Gamma rhythm (which has a center frequency between 30 and 80 Hz) is modulated by cognitive mechanisms such as attention and memory, and has been hypothesized to play a role in mediating these processes by supporting communication channels between cortical areas or encoding information in its phase. We highlight several issues related to gamma rhythms, such as low and inconsistent power, its dependence on low-level stimulus features, problems due to conduction delays, and contamination due to spike-related activity that makes accurate estimation of gamma phase difficult. Gamma rhythm could be a potentially useful signature of excitation-inhibition interactions in the brain, but whether it also provides a mechanism for information processing or coding remains an open question.