177 resultados para processing platform


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How the brain maintains perceptual continuity across eye movements that yield discontinuous snapshots of the world is still poorly understood. In this study, we adapted a framework from the dual-task paradigm, well suited to reveal bottlenecks in mental processing, to study how information is processed across sequential saccades. The pattern of RTs allowed us to distinguish among three forms of trans-saccadic processing (no trans-saccadic processing, trans-saccadic visual processing and trans-saccadic visual processing and saccade planning models). Using a cued double-step saccade task, we show that even though saccade execution is a processing bottleneck, limiting access to incoming visual information, partial visual and motor processing that occur prior to saccade execution is used to guide the next eye movement. These results provide insights into how the oculomotor system is designed to process information across multiple fixations that occur during natural scanning.

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Numerical Linear Algebra (NLA) kernels are at the heart of all computational problems. These kernels require hardware acceleration for increased throughput. NLA Solvers for dense and sparse matrices differ in the way the matrices are stored and operated upon although they exhibit similar computational properties. While ASIC solutions for NLA Solvers can deliver high performance, they are not scalable, and hence are not commercially viable. In this paper, we show how NLA kernels can be accelerated on REDEFINE, a scalable runtime reconfigurable hardware platform. Compared to a software implementation, Direct Solver (Modified Faddeev's algorithm) on REDEFINE shows a 29X improvement on an average and Iterative Solver (Conjugate Gradient algorithm) shows a 15-20% improvement. We further show that solution on REDEFINE is scalable over larger problem sizes without any notable degradation in performance.

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In the world of high performance computing huge efforts have been put to accelerate Numerical Linear Algebra (NLA) kernels like QR Decomposition (QRD) with the added advantage of reconfigurability and scalability. While popular custom hardware solution in form of systolic arrays can deliver high performance, they are not scalable, and hence not commercially viable. In this paper, we show how systolic solutions of QRD can be realized efficiently on REDEFINE, a scalable runtime reconfigurable hardware platform. We propose various enhancements to REDEFINE to meet the custom need of accelerating NLA kernels. We further do the design space exploration of the proposed solution for any arbitrary application of size n × n. We determine the right size of the sub-array in accordance with the optimal pipeline depth of the core execution units and the number of such units to be used per sub-array.

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The design and operation of the minimum cost classifier, where the total cost is the sum of the measurement cost and the classification cost, is computationally complex. Noting the difficulties associated with this approach, decision tree design directly from a set of labelled samples is proposed in this paper. The feature space is first partitioned to transform the problem to one of discrete features. The resulting problem is solved by a dynamic programming algorithm over an explicitly ordered state space of all outcomes of all feature subsets. The solution procedure is very general and is applicable to any minimum cost pattern classification problem in which each feature has a finite number of outcomes. These techniques are applied to (i) voiced, unvoiced, and silence classification of speech, and (ii) spoken vowel recognition. The resulting decision trees are operationally very efficient and yield attractive classification accuracies.

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Editors' note:Flexible, large-area display and sensor arrays are finding growing applications in multimedia and future smart homes. This article first analyzes and compares current flexible devices, then discusses the implementation, requirements, and testing of flexible sensor arrays.—Jiun-Lang Huang (National Taiwan University) and Kwang-Ting (Tim) Cheng (University of California, Santa Barbara)

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Reaction wheel assemblies (RWAs) are momentum exchange devices used in fine pointing control of spacecrafts. Even though the spinning rotor of the reaction wheel is precisely balanced to minimize emitted vibration due to static and dynamic imbalances, precision instrument payloads placed in the neighborhood can always be severely impacted by residual vibration forces emitted by reaction wheel assemblies. The reduction of the vibration level at sensitive payloads can be achieved by placing the RWA on appropriate mountings. A low frequency flexible space platform consisting of folded continuous beams has been designed to serve as a mount for isolating a disturbance source in precision payloads equipped spacecrafts. Analytical and experimental investigations have been carried out to test the usefulness of the low frequency flexible platform as a vibration isolator for RWAs. Measurements and tests have been conducted at varying wheel speeds, to quantify and characterize the amount of isolation obtained from the reaction wheel generated vibration. These tests are further extended to other variants of similar design in order to bring out the best isolation for given disturbance loads. Both time and frequency domain analysis of test data show that the flexible beam platform as a mount for reaction wheels is quite effective and can be used in spacecrafts for passive vibration control. (C) 2011 Elsevier Ltd. All rights reserved.

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Instruction reuse is a microarchitectural technique that improves the execution time of a program by removing redundant computations at run-time. Although this is the job of an optimizing compiler, they do not succeed many a time due to limited knowledge of run-time data. In this paper we examine instruction reuse of integer ALU and load instructions in network processing applications. Specifically, this paper attempts to answer the following questions: (1) How much of instruction reuse is inherent in network processing applications?, (2) Can reuse be improved by reducing interference in the reuse buffer?, (3) What characteristics of network applications can be exploited to improve reuse?, and (4) What is the effect of reuse on resource contention and memory accesses? We propose an aggregation scheme that combines the high-level concept of network traffic i.e. "flows" with a low level microarchitectural feature of programs i.e. repetition of instructions and data along with an architecture that exploits temporal locality in incoming packet data to improve reuse. We find that for the benchmarks considered, 1% to 50% of instructions are reused while the speedup achieved varies between 1% and 24%. As a side effect, instruction reuse reduces memory traffic and can therefore be considered as a scheme for low power.

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Rapid solidification, mechanical alloying and devitrificaiton of precursor metallic glasses are all possible routes for the synthesis of nanocrystals and nanocomposites, though their efficacy is system dependent. In a comprehensive study of alloys across the Ti-Ni phase diagram, nanocrystals of Ti and Ni and nanocomposites of alpha -Ti and Ti sub 2 Ni, Ti sub 2 Ni and TiNi and beta -Ti and glass have been produced. By the addition of Al, devitrification of metallic glasses created by mechanical alloying led to nanocrystalline intermetallic compounds. The evolution of these nanocrystalline microstructures has been rationalized on the basis of thermodynamic and kinetic considerations involving the metastable phase diagram for this system.

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A new scheme for minimizing handover failure probability in mobile cellular communication systems is presented. The scheme involves a reassignment of priorities for handover requests enqueued in adjacent cells to release a channel for a handover request which is about to fail. Performance evaluation of the new scheme carried out by computer simulation of a four-cell highway cellular system has shown a considerable reduction in handover failure probability

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In an effort to design efficient platform for siRNA delivery, we combine all atom classical and quantum simulations to study the binding of small interfering RNA (siRNA) by pristine single wall carbon nanotube (SWCNT). Our results show that siRNA strongly binds to SWCNT surface via unzipping its base-pairs and the propensity of unzipping increases with the increase in the diameter of the SWCNTs. The unzipping and subsequent wrapping events are initiated and driven by van der Waals interactions between the aromatic rings of siRNA nucleobases and the SWCNT surface. However, molecular dynamics (MD) simulations of double strand DNA (dsDNA) of the same sequence show that the dsDNA undergoes much less unzipping and wrapping on the SWCNT in the simulation time scale of 70 ns. This interesting difference is due to smaller interaction energy of thymidine of dsDNA with the SWCNT compared to that of uridine of siRNA, as calculated by dispersion corrected density functional theory (DFT) methods. After the optimal binding of siRNA to SWCNT, the complex is very stable which serves as one of the major mechanisms of siRNA delivery for biomedical applications. Since siRNA has to undergo unwinding process with the effect of RNA-induced silencing complex, our proposed delivery mechanism by SWCNT possesses potential advantages in achieving RNA interference. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.3682780]

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Sesbania mosaic virus (SeMV) is a positive stranded RNA virus belonging to the genus Sobemovirus. Construction of an infectious clone is an essential step for deciphering the virus gene functions in vivo. Using Agrobacterium based transient expression system we show that SeMV icDNA is infectious on Sesbania grandiflora and Cyamopsis tetragonoloba plants. The efficiency of icDNA infection was found to be significantly high on Cyamopsis plants when compared to that on Sesbania grandiflora. The coat protein could be detected within 6 days post infiltration in the infiltrated leaves. Different species of viral RNA (double stranded and single stranded genomic and subgenomic RNA) could be detected upon northern analysis, suggesting that complete replication had taken place. Based on the analysis of the sequences at the genomic termini of progeny RNA from SeMV icDNA infiltrated leaves and those of its 3' and 5' terminal deletion mutants, we propose a possible mechanism for 3' and 5' end repair in vivo. Mutation of the cleavage sites in the polyproteins encoded by ORF 2 resulted in complete loss of infection by the icDNA, suggesting the importance of correct polyprotein processing at all the four cleavage sites for viral replication. Complementation analysis suggested that ORF 2 gene products can act in trans. However, the trans acting ability of ORF 2 gene products was abolished upon deletion of the N-terminal hydrophobic domain of polyprotein 2a and 2ab, suggesting that these products necessarily function at the replication site, where they are anchored to membranes.

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Carbon nanotubes dispersed in polymer matrix have been aligned in the form of fibers and interconnects and cured electrically and by UV light. Conductivity and effective semiconductor tunneling against reverse to forward bias field have been designed to have differentiable current-voltage response of each of the fiber/channel. The current-voltage response is a function of the strain applied to the fibers along axial direction. Biaxial and shear strains are correlated by differentiating signals from the aligned fibers/channels. Using a small doping of magnetic nanoparticles in these composite fibers, magneto-resistance properties are realized which are strong enough to use the resulting magnetostriction as a state variable for signal processing and computing. Various basic analog signal processing tasks such as addition, convolution and filtering etc. can be performed. These preliminary study shows promising application of the concept in combined analog-digital computation in carbon nanotube based fibers. Various dynamic effects such as relaxation, electric field dependent nonlinearities and hysteresis on the output signals are studied using experimental data and analytical model.