105 resultados para Memory Awareness


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Programming for parallel architectures that do not have a shared address space is extremely difficult due to the need for explicit communication between memories of different compute devices. A heterogeneous system with CPUs and multiple GPUs, or a distributed-memory cluster are examples of such systems. Past works that try to automate data movement for distributed-memory architectures can lead to excessive redundant communication. In this paper, we propose an automatic data movement scheme that minimizes the volume of communication between compute devices in heterogeneous and distributed-memory systems. We show that by partitioning data dependences in a particular non-trivial way, one can generate data movement code that results in the minimum volume for a vast majority of cases. The techniques are applicable to any sequence of affine loop nests and works on top of any choice of loop transformations, parallelization, and computation placement. The data movement code generated minimizes the volume of communication for a particular configuration of these. We use a combination of powerful static analyses relying on the polyhedral compiler framework and lightweight runtime routines they generate, to build a source-to-source transformation tool that automatically generates communication code. We demonstrate that the tool is scalable and leads to substantial gains in efficiency. On a heterogeneous system, the communication volume is reduced by a factor of 11X to 83X over state-of-the-art, translating into a mean execution time speedup of 1.53X. On a distributed-memory cluster, our scheme reduces the communication volume by a factor of 1.4X to 63.5X over state-of-the-art, resulting in a mean speedup of 1.55X. In addition, our scheme yields a mean speedup of 2.19X over hand-optimized UPC codes.

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Wing morphing is one of the emerging methodology towards improving aerodynamic efficiency of flight vehicle structures. In this paper a morphing structural element is designed and studied which has its origin in the well known chiral structures. The new aspect of design and functionality explored in this paper is that the chiral cell is actuated using thermal Shape Memory Alloy (SMA) actuator wires to provide directional motion. Such structure utilizes the potential of different actuations concepts based on actuator embedded in the chiral structure skin. This paper describes a new class of chiral cell structure with integrated SMA wire for actuation. Chiral topological constructs are obtained by considering passive and active load path decoupling and sub-optimal shape changes. Single cell of chiral honeycomb with actuators are analyzed using finite element simulation results and experiments. To this end, a multi-cell plan-form is characterized showing interesting possibilities in structural morphing applications. The applicability of the developed chiral cell to flexible wing skin, variable stiffness based design and controlling longitudinal-to-transverse stiffness ratio are discussed.

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Debonding of Shape Memory Alloy (SMA) wires in SMA reinforced polymer matrix composites is a complex phenomenon compared to other fabric fiber debonding in similar matrix composites. This paper focuses on experimental study and analytical correlation of stress required for debonding of thermal SMA actuator wire reinforced composites. Fiber pull-out tests are carried out on thermal SMA actuator at parent state to understand the effect of stress induced detwinned martensites. An ASTM standard is followed as benchmark method for fiber pull-out test. Debonding stress is derived with the help of non-local shear-lag theory applied to elasto-plastic interface. Furthermore, experimental investigations are carried out to study the effect of Laser shot peening on SMA surface to improve the interfacial strength. Variation in debonding stress due to length of SMA wire reinforced in epoxy are investigated for non-peened and peened SMA wires. Experimental results of interfacial strength variation due to various L/d ratio for non-peened and peened SMA actuator wires in epoxy matrix are discussed.

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Ni-Fe-Ga-based alloys form a new class of ferromagnetic shape memory alloys (FSMAs) that show considerable formability because of the presence of a disordered fcc gamma-phase. The current study explores the deformation processing of this alloy using an off-stoichiometric Ni55Fe59Ga26 alloy that contains the ductile gamma-phase. The hot deformation behavior of this alloy has been characterized on the basis of its flow stress variation obtained by isothermal constant true strain rate compression tests in the 1123-1323 K temperature range and strain rate range of 10(-3)-10 s(-1) and using a combination of constitutive modeling and processing map. The dynamic recrystallization (DRX) regime for thermomechanical processing has been identified for this Heusler alloy on the basis of the processing maps and the deformed microstructures. This alloy also shows evidence of dynamic strain-aging (DSA) effect which has not been reported so far for any Heusler FSMAs. Similar effect is also noticed in a Ni-Mn-Ga-based Heusler alloy which is devoid of any gamma-phase. (C) 2014 Elsevier Ltd. All rights reserved.

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A discrete-time dynamics of a non-Markovian random walker is analyzed using a minimal model where memory of the past drives the present dynamics. In recent work N. Kumar et al., Phys. Rev. E 82, 021101 (2010)] we proposed a model that exhibits asymptotic superdiffusion, normal diffusion, and subdiffusion with the sweep of a single parameter. Here we propose an even simpler model, with minimal options for the walker: either move forward or stay at rest. We show that this model can also give rise to diffusive, subdiffusive, and superdiffusive dynamics at long times as a single parameter is varied. We show that in order to have subdiffusive dynamics, the memory of the rest states must be perfectly correlated with the present dynamics. We show explicitly that if this condition is not satisfied in a unidirectional walk, the dynamics is only either diffusive or superdiffusive (but not subdiffusive) at long times.

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Introduction: Immunomodulators are agents, which can modulate the immune response to specific antigens, while causing least toxicity to the host system. Being part of the modern vaccine formulations, these compounds have contributed remarkably to the field of therapeutics. Despite the successful record maintained by these agents, the requirement of novel immunomodulators keeps increasing due to the increasing severity of diseases. Hence, research regarding the same holds great importance. Areas covered: In this review, we discuss the role of immunomodulators in improving performance of various vaccines used for counteracting most threatening infectious diseases, mechanisms behind their action and criteria for development of novel immunomodulators. Expert opinion: Understanding the molecular mechanisms underlying immune response is a prerequisite for development of effective therapeutics as these are often exploited by pathogens for their own propagation. Keeping this in mind, the present research in the field of immunotherapy focuses on developing immunomodulators that would not only enhance the protection against pathogen, but also generate a long-term memory response. With the introduction of advanced formulations including combination of different kinds of immunomodulators, one can expect tremendous success in near future.

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Investigations on the electrical switching, structural, optical and photoacoustic analysis have been undertaken on chalcogenide GeSe1.5S0.5 thin films of various thicknesses prepared by vacuum evaporation technique. The decrease of band gap energy with increase in film thickness has been explained using the `density of states model'. The structural units of the films are characterized using Raman spectroscopy and the deconvoluted Raman peaks obtained from Gaussian fit around 188 cm(-1), 204 cm(-1) and 214 cm(-1) favors Ge-chalcogen tetrahedral units forming corner and edge sharing tetrahedra. All the thin films samples have been exhibited memory-type electrical switching behavior. An enhancement in the threshold voltages of GeSe1.5S0.5 thin films have been observed with increase in film thickness. The thickness dependence of switching voltages provide an insight into the switching mechanism and it is explained by the Joule heating effect. (C) 2014 Elsevier B.V. All rights reserved.

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As rapid brain development occurs during the neonatal period, environmental manipulation during this period may have a significant impact on sleep and memory functions. Moreover, rapid eye movement (REM) sleep plays an important role in integrating new information with the previously stored emotional experience. Hence, the impact of early maternal separation and isolation stress (MS) during the stress hyporesponsive period (SHRP) on fear memory retention and sleep in rats were studied. The neonatal rats were subjected to maternal separation and isolation stress during postnatal days 5-7 (6 h daily/3 d). Polysomnographic recordings and differential fear conditioning was carried out in two different sets of rats aged 2 months. The neuronal replay during REM sleep was analyzed using different parameters. MS rats showed increased time in REM stage and total sleep period also increased. MS rats showed fear generalization with increased fear memory retention than normal control (NC). The detailed analysis of the local field potentials across different time periods of REM sleep showed increased theta oscillations in the hippocampus, amygdala and cortical circuits. Our findings suggest that stress during SHRP has sensitized the hippocampus amygdala cortical loops which could be due to increased release of corticosterone that generally occurs during REM sleep. These rats when subjected to fear conditioning exhibit increased fear memory and increased, fear generalization. The development of helplessness, anxiety and sleep changes in human patients, thus, could be related to the reduced thermal, tactile and social stimulation during SHRP on brain plasticity and fear memory functions. (C) 2014 Elsevier B.V. All rights reserved.

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Modulus variation of NiTi shape memory alloy has been investigated at microstructural level through nano dynamical mechanical analysis and compared with bulk experimental measurements. The differences between the modulus values at the macro and micro level as well as within the micro level are discussed and the corresponding variations have been explained based on the crystal structure, orientation and misorientation. The experimental results confirm a higher modulus value for the martensite phase that is in agreement with the theoretical predictions. (C) 2015 Elsevier B. V. All rights reserved.

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This paper presents a low energy memory decoder architecture for ultra-low-voltage systems containing multiple voltage domains. Due to limitations in scalability of memory supply voltages, these systems typically contain a core operating at subthreshold voltages and memories operating at a higher voltage. This difference in voltage provides a timing slack on the memory path as the core supply is scaled. The paper analyzes the feasibility and trade-offs in utilizing this timing slack to operate a greater section of memory decoder circuitry at the lower supply. A 256x16-bit SRAM interface has been designed in UMC 65nm low-leakage process to evaluate the above technique with the core and memory operating at 280 mV and 500 mV respectively. The technique provides a reduction of up to 20% in energy/cycle of the row decoder without any penalty in area and system-delay.

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Interfacial properties of Shape Memory Alloy (SMA) reinforced polymer matrix composites can be enhanced by improving the interfacial bonding. This paper focuses on studying the interfacial stresses developed in the SMA-epoxy interface due to various laser shot penning conditions. Fiber-pull test-setup is designed to understand the role of mechanical bias stress cycling and thermal actuation cycling. Phase transformation is tracked over mechanical and thermal fatigue cycles. A micromechanics based model developed earlier based on shear lag in SMA and energy based consistent homogenization is extended here to incorporate the stress-temperature phase diagram parameters for modeling fatigue.

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Coarse Grained Reconfigurable Architectures (CGRA) are emerging as embedded application processing units in computing platforms for Exascale computing. Such CGRAs are distributed memory multi- core compute elements on a chip that communicate over a Network-on-chip (NoC). Numerical Linear Algebra (NLA) kernels are key to several high performance computing applications. In this paper we propose a systematic methodology to obtain the specification of Compute Elements (CE) for such CGRAs. We analyze block Matrix Multiplication and block LU Decomposition algorithms in the context of a CGRA, and obtain theoretical bounds on communication requirements, and memory sizes for a CE. Support for high performance custom computations common to NLA kernels are met through custom function units (CFUs) in the CEs. We present results to justify the merits of such CFUs.

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Thin films of different thicknesses in the range of 200-720 nm have been deposited on glass substrates at room temperature using thermal evaporation technique. The structural investigations revealed that the as-deposited films are amorphous in nature. The surface roughness of the films shows an increasing trend at higher thickness of the films. The surface roughness of the films shows an increasing trend at higher thickness of the films. Interference fringes in the transmission spectra of these films suggest that the films are fairly smooth and uniform. The optical absorption in Sb2Se3 film is described using indirect transition and the variation in band gaps is explained on the basis of defects and disorders in the chalcogenide systems. Raman spectrum confirms the increase of orderliness with film thickness. From the I-V characteristics, a memory type switching is observed whose threshold voltage increases with film thickness. (C) 2015 Elsevier B.V. All rights reserved.

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Quantum cellular automata (QCA) is a new technology in the nanometer scale and has been considered as one of the alternative to CMOS technology. In this paper, we describe the design and layout of a serial memory and parallel memory, showing the layout of individual memory cells. Assuming that we can fabricate cells which are separated by 10nm, memory capacities of over 1.6 Gbit/cm2 can be achieved. Simulations on the proposed memories were carried out using QCADesigner, a layout and simulation tool for QCA. During the design, we have tried to reduce the number of cells as well as to reduce the area which is found to be 86.16sq mm and 0.12 nm2 area with the QCA based memory cell. We have also achieved an increase in efficiency by 40%.These circuits are the building block of nano processors and provide us to understand the nano devices of the future.

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We demonstrate all inorganic, robust, cost-effective, spin-coated, two-terminal capacitive memory metal-oxide nanoparticle-oxide-semiconductor devices with cadmium telluride nanoparticles sandwiched between aluminum oxide phosphate layers to form the dielectric memory stack. Using a novel high-speed circuit to decouple reading and writing, experimentally measured memory windows, programming voltages, retention times, and endurance are comparable with or better than the two-terminal memory devices realized using other fabrication techniques.