958 resultados para Memory space


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It has been shown that active control of locomotion increases accuracy and precision of nonvisual space perception, but psychological mechanisms of this enhancement are poorly understood. The present study explored a hypothesis that active control of locomotion enhances space perception by facilitating crossmodal interaction between visual and nonvisual spatial information. In an experiment, blindfolded participants walked along a linear path under one of the following two conditions: (1) They walked by themselves following a guide rope; and (2) they were led by an experimenter. Subsequently, they indicated the walked distance by tossing a beanbag to the origin of locomotion. The former condition gave participants greater control of their locomotion, and thus represented a more active walking condition. In addition, before each trial, half the participants viewed the room in which they performed the distance perception task. The other half remained blindfolded throughout the experiment. Results showed that although the room was devoid of any particular cues for walked distances, visual knowledge of the surroundings improved the precision of nonvisual distance perception. Importantly, however, the benefit of preview was observed only when participants walked more actively. This indicates that active control of locomotion allowed participants to better utilize their visual memory of the environment for perceiving nonvisually encoded distance, suggesting that active control of locomotion served as a catalyst for integrating visual and nonvisual information to derive spatial representations of higher quality.

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This practice-led research project examined the audience experience of immersive environments in participatory performance. Drawing upon the work of artist Ilya Kabakov, Gaston Bachelard's Poetics of Space (1964) and Leibniz's theory of the monad, the study investigated how an immersive space can be constructed to evoke emotion and memory recall in participants. The research consisted of two cycles of creative experimentation resulting in the presentation of a final piece entitled Dulcet. The research contributes new terminology to the discourse surrounding the participant experience in immersive environments, specifically space-as-memory, the role of ambiguity in spatial design and the construct of the monadic environment.

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The triangular space between memory, narrative and pictorial representation is the terrain on which this article is developed. Taking the art of memory developed by Giordano Bruno (1548 – 1600) and the art of painting subtly revolutionised by Adam Elsheimer (1578 – 1610) as test-cases, it is shown how both subvert the norms of mimesis and narration prevalent throughout the Renaissance, how disrupted memory creates “incoherent” narratives, and how perspective and the notion of “place” are questioned in a corollary way. Two paintings by Elsheimer are analysed and shown to include, in spite of their supposed “realism”, numerous incoherencies, aporias and strange elements – often overlooked. Thus, they do not conform to two of the basic rules governing both the classical art of memory and the humanist art of painting: well-defined places and the exhaustive translatability of words into images (and vice-versa). In the work of Bruno, both his philosophical claims and the literary devices he uses are analysed as hints for a similar (and contemporaneous) undermining of conventions about the transparency and immediacy of representation.

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Polycrystalline strontium titanate (SrTiO3) films were prepared by a pulsed laser deposition technique on p-type silicon and platinum-coated silicon substrates. The films exhibited good structural and dielectric properties which were sensitive to the processing conditions. The small signal dielectric constant and dissipation factor at a frequency of 100 kHz were about 225 and 0.03 respectively. The capacitance-voltage (C-V) characteristics in metal-insulator-semiconductor structures exhibited anomalous frequency dispersion behavior and a hysteresis effect. The hysteresis in the C-V curve was found to be about 1 V and of a charge injection type. The density of interface states was about 1.79 x 10(12) cm(-2). The charge storage density was found to be 40 fC mu m(-2) at an applied electric field of 200 kV cm(-1). Studies on current-voltage characteristics indicated an ohmic nature at lower voltages and space charge conduction at higher voltages. The films also exhibited excellent time-dependent dielectric breakdown behavior.

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Lead-lanthanum-titanate (Pb0.72La0.28)TiO3 (PLT) is one of the interesting materials for DRAM applications due to its room temperature paraelectric nature and its higher dielectric permittivity. PLT thin films of different thickness ranging from 0.54- 0.9 mum were deposited on Pt coated Si substrates by excimer laser ablation technique. We have measured the voltage (field) dependence, the thickness dependence, temperature dependence of dc leakage currents and analysis is done on these PLT thin films. Current- voltage characteristics were measured at different temperatures for different thick films and the thickness dependence of leakage current has been explained by considering space charge limited conduction mechanism. The charge transport phenomena were studied in detail for films of different thicknesses for dynamic random access memory applications.

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Sensor network nodes exhibit characteristics of both embedded systems and general-purpose systems.A sensor network operating system is a kind of embedded operating system, but unlike a typical embedded operating system, sensor network operatin g system may not be real time, and is constrained by memory and energy constraints. Most sensor network operating systems are based on event-driven approach. Event-driven approach is efficient in terms of time and space.Also this approach does not require a separate stack for each execution context. But using this model, it is difficult to implement long running tasks, like cryptographic operations. A thread based computation requires a separate stack for each execution context, and is less efficient in terms of time and space. In this paper, we propose a thread based execution model that uses only a fixed number of stacks. In this execution model, the number of stacks at each priority level are fixed. It minimizes the stack requirement for multi-threading environment and at the same time provides ease of programming. We give an implementation of this model in Contiki OS by separating thread implementation from protothread implementation completely. We have tested our OS by implementing a clock synchronization protocol using it.

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Today's feature-rich multimedia products require embedded system solution with complex System-on-Chip (SoC) to meet market expectations of high performance at a low cost and lower energy consumption. The memory architecture of the embedded system strongly influences critical system design objectives like area, power and performance. Hence the embedded system designer performs a complete memory architecture exploration to custom design a memory architecture for a given set of applications. Further, the designer would be interested in multiple optimal design points to address various market segments. However, tight time-to-market constraints enforces short design cycle time. In this paper we address the multi-level multi-objective memory architecture exploration problem through a combination of exhaustive-search based memory exploration at the outer level and a two step based integrated data layout for SPRAM-Cache based architectures at the inner level. We present a two step integrated approach for data layout for SPRAM-Cache based hybrid architectures with the first step as data-partitioning that partitions data between SPRAM and Cache, and the second step is the cache conscious data layout. We formulate the cache-conscious data layout as a graph partitioning problem and show that our approach gives up to 34% improvement over an existing approach and also optimizes the off-chip memory address space. We experimented our approach with 3 embedded multimedia applications and our approach explores several hundred memory configurations for each application, yielding several optimal design points in a few hours of computation on a standard desktop.

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Prediction of the Sun's magnetic activity is important because of its effect on space environment and climate. However, recent efforts to predict the amplitude of the solar cycle have resulted in diverging forecasts with no consensus. Yeates et al. have shown that the dynamical memory of the solar dynamo mechanism governs predictability, and this memory is different for advection- and diffusion-dominated solar convection zones. By utilizing stochastically forced, kinematic dynamo simulations, we demonstrate that the inclusion of downward turbulent pumping of magnetic flux reduces the memory of both advection- and diffusion-dominated solar dynamos to only one cycle; stronger pumping degrades this memory further. Thus, our results reconcile the diverging dynamo-model-based forecasts for the amplitude of solar cycle 24. We conclude that reliable predictions for the maximum of solar activity can be made only at the preceding minimum-allowing about five years of advance planning for space weather. For more accurate predictions, sequential data assimilation would be necessary in forecasting models to account for the Sun's short memory.

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Fast content addressable data access mechanisms have compelling applications in today's systems. Many of these exploit the powerful wildcard matching capabilities provided by ternary content addressable memories. For example, TCAM based implementations of important algorithms in data mining been developed in recent years; these achieve an an order of magnitude speedup over prevalent techniques. However, large hardware TCAMs are still prohibitively expensive in terms of power consumption and cost per bit. This has been a barrier to extending their exploitation beyond niche and special purpose systems. We propose an approach to overcome this barrier by extending the traditional virtual memory hierarchy to scale up the user visible capacity of TCAMs while mitigating the power consumption overhead. By exploiting the notion of content locality (as opposed to spatial locality), we devise a novel combination of software and hardware techniques to provide an abstraction of a large virtual ternary content addressable space. In the long run, such abstractions enable applications to disassociate considerations of spatial locality and contiguity from the way data is referenced. If successful, ideas for making content addressability a first class abstraction in computing systems can open up a radical shift in the way applications are optimized for memory locality, just as storage class memories are soon expected to shift away from the way in which applications are typically optimized for disk access locality.

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We demonstrate the possibility of accelerated identification of potential compositions for high-temperature shape memory alloys (SMAs) through a combinatorial material synthesis and analysis approach, wherein we employ the combination of diffusion couple and indentation techniques. The former was utilized to generate smooth and compositionally graded inter-diffusion zones (IDZs) in the Ni-Ti-Pd ternary alloy system of varying IDZ thickness, depending on the annealing time at high temperature. The IDZs thus produced were then impressed with an indenter with a spherical tip so as to inscribe a predetermined indentation strain. Subsequent annealing of the indented samples at various elevated temperatures, T-a, ranging between 150 and 550 degrees C allows for partial to full relaxation of the strain imposed due to the shape memory effect. If T-a is above the austenite finish temperature, A(f), the relaxation will be complete. By measuring the depth recovery, which serves as a proxy for the shape recovery characteristic of the SMA, a three-dimensional map in the recovery temperature composition space is constructed. A comparison of the published Af data for different compositions with the Ta data shows good agreement when the depth recovery is between 70% and 80%, indicating that the methodology proposed in this paper can be utilized for the identification of promising compositions. Advantages and further possibilities of this methodology are discussed.

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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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In this paper, the architecture of a vector-matrix multiplier (MVM) is simulated. The optical design can be made compact by the use of GRIN lenses for the optical fan-in. The intended application area was in storage area networks (SANs) but the concept can be applied to a neural network. © 2011 Allerton Press, Inc.