Simple Atomic Quantum Memory Suitable for Semiconductor Quantum Dot Single Photons.

PubMed

Wolters, Janik; Buser, Gianni; Horsley, Andrew; Béguin, Lucas; Jöckel, Andreas; Jahn, Jan-Philipp; Warburton, Richard J; Treutlein, Philipp

2017-08-11

Quantum memories matched to single photon sources will form an important cornerstone of future quantum network technology. We demonstrate such a memory in warm Rb vapor with on-demand storage and retrieval, based on electromagnetically induced transparency. With an acceptance bandwidth of δf=0.66  GHz, the memory is suitable for single photons emitted by semiconductor quantum dots. In this regime, vapor cell memories offer an excellent compromise between storage efficiency, storage time, noise level, and experimental complexity, and atomic collisions have negligible influence on the optical coherences. Operation of the memory is demonstrated using attenuated laser pulses on the single photon level. For a 50 ns storage time, we measure η_{e2e}^{50  ns}=3.4(3)% end-to-end efficiency of the fiber-coupled memory, with a total intrinsic efficiency η_{int}=17(3)%. Straightforward technological improvements can boost the end-to-end-efficiency to η_{e2e}≈35%; beyond that, increasing the optical depth and exploiting the Zeeman substructure of the atoms will allow such a memory to approach near unity efficiency. In the present memory, the unconditional read-out noise level of 9×10^{-3} photons is dominated by atomic fluorescence, and for input pulses containing on average μ_{1}=0.27(4) photons, the signal to noise level would be unity.

Extreme Quantum Memory Advantage for Rare-Event Sampling

NASA Astrophysics Data System (ADS)

Aghamohammadi, Cina; Loomis, Samuel P.; Mahoney, John R.; Crutchfield, James P.

2018-02-01

We introduce a quantum algorithm for memory-efficient biased sampling of rare events generated by classical memoryful stochastic processes. Two efficiency metrics are used to compare quantum and classical resources for rare-event sampling. For a fixed stochastic process, the first is the classical-to-quantum ratio of required memory. We show for two example processes that there exists an infinite number of rare-event classes for which the memory ratio for sampling is larger than r , for any large real number r . Then, for a sequence of processes each labeled by an integer size N , we compare how the classical and quantum required memories scale with N . In this setting, since both memories can diverge as N →∞ , the efficiency metric tracks how fast they diverge. An extreme quantum memory advantage exists when the classical memory diverges in the limit N →∞ , but the quantum memory has a finite bound. We then show that finite-state Markov processes and spin chains exhibit memory advantage for sampling of almost all of their rare-event classes.

Improving attention control in dysphoria through cognitive training: transfer effects on working memory capacity and filtering efficiency.

PubMed

Owens, Max; Koster, Ernst H W; Derakshan, Nazanin

2013-03-01

Impaired filtering of irrelevant information from working memory is thought to underlie reduced working memory capacity for relevant information in dysphoria. The current study investigated whether training-related gains in working memory performance on the adaptive dual n-back task could result in improved inhibitory function. Efficacy of training was monitored in a change detection paradigm allowing measurement of a sustained event-related potential asymmetry sensitive to working memory capacity and the efficient filtering of irrelevant information. Dysphoric participants in the training group showed training-related gains in working memory that were accompanied by gains in working memory capacity and filtering efficiency compared to an active control group. Results provide important initial evidence that behavioral performance and neural function in dysphoria can be improved by facilitating greater attentional control. Copyright © 2013 Society for Psychophysiological Research.

Thermally efficient and highly scalable In2Se3 nanowire phase change memory

NASA Astrophysics Data System (ADS)

Jin, Bo; Kang, Daegun; Kim, Jungsik; Meyyappan, M.; Lee, Jeong-Soo

2013-04-01

The electrical characteristics of nonvolatile In2Se3 nanowire phase change memory are reported. Size-dependent memory switching behavior was observed in nanowires of varying diameters and the reduction in set/reset threshold voltage was as low as 3.45 V/6.25 V for a 60 nm nanowire, which is promising for highly scalable nanowire memory applications. Also, size-dependent thermal resistance of In2Se3 nanowire memory cells was estimated with values as high as 5.86×1013 and 1.04×106 K/W for a 60 nm nanowire memory cell in amorphous and crystalline phases, respectively. Such high thermal resistances are beneficial for improvement of thermal efficiency and thus reduction in programming power consumption based on Fourier's law. The evaluation of thermal resistance provides an avenue to develop thermally efficient memory cell architecture.

Does constraining memory maintenance reduce visual search efficiency?

PubMed

Buttaccio, Daniel R; Lange, Nicholas D; Thomas, Rick P; Dougherty, Michael R

2018-03-01

We examine whether constraining memory retrieval processes affects performance in a cued recall visual search task. In the visual search task, participants are first presented with a memory prompt followed by a search array. The memory prompt provides diagnostic information regarding a critical aspect of the target (its colour). We assume that upon the presentation of the memory prompt, participants retrieve and maintain hypotheses (i.e., potential target characteristics) in working memory in order to improve their search efficiency. By constraining retrieval through the manipulation of time pressure (Experiments 1A and 1B) or a concurrent working memory task (Experiments 2A, 2B, and 2C), we directly test the involvement of working memory in visual search. We find some evidence that visual search is less efficient under conditions in which participants were likely to be maintaining fewer hypotheses in working memory (Experiments 1A, 2A, and 2C), suggesting that the retrieval of representations from long-term memory into working memory can improve visual search. However, these results should be interpreted with caution, as the data from two experiments (Experiments 1B and 2B) did not lend support for this conclusion.

Intrinsic retrieval efficiency for quantum memories: A three-dimensional theory of light interaction with an atomic ensemble

NASA Astrophysics Data System (ADS)

Gujarati, Tanvi P.; Wu, Yukai; Duan, Luming

2018-03-01

Duan-Lukin-Cirac-Zoller quantum repeater protocol, which was proposed to realize long distance quantum communication, requires usage of quantum memories. Atomic ensembles interacting with optical beams based on off-resonant Raman scattering serve as convenient on-demand quantum memories. Here, a complete free space, three-dimensional theory of the associated read and write process for this quantum memory is worked out with the aim of understanding intrinsic retrieval efficiency. We develop a formalism to calculate the transverse mode structure for the signal and the idler photons and use the formalism to study the intrinsic retrieval efficiency under various configurations. The effects of atomic density fluctuations and atomic motion are incorporated by numerically simulating this system for a range of realistic experimental parameters. We obtain results that describe the variation in the intrinsic retrieval efficiency as a function of the memory storage time for skewed beam configuration at a finite temperature, which provides valuable information for optimization of the retrieval efficiency in experiments.

VOP memory management in MPEG-4

NASA Astrophysics Data System (ADS)

Vaithianathan, Karthikeyan; Panchanathan, Sethuraman

2001-03-01

MPEG-4 is a multimedia standard that requires Video Object Planes (VOPs). Generation of VOPs for any kind of video sequence is still a challenging problem that largely remains unsolved. Nevertheless, if this problem is treated by imposing certain constraints, solutions for specific application domains can be found. MPEG-4 applications in mobile devices is one such domain where the opposite goals namely low power and high throughput are required to be met. Efficient memory management plays a major role in reducing the power consumption. Specifically, efficient memory management for VOPs is difficult because the lifetimes of these objects vary and these life times may be overlapping. Varying life times of the objects requires dynamic memory management where memory fragmentation is a key problem that needs to be addressed. In general, memory management systems address this problem by following a combination of strategy, policy and mechanism. For MPEG4 based mobile devices that lack instruction processors, a hardware based memory management solution is necessary. In MPEG4 based mobile devices that have a RISC processor, using a Real time operating system (RTOS) for this memory management task is not expected to be efficient because the strategies and policies used by the ROTS is often tuned for handling memory segments of smaller sizes compared to object sizes. Hence, a memory management scheme specifically tuned for VOPs is important. In this paper, different strategies, policies and mechanisms for memory management are considered and an efficient combination is proposed for the case of VOP memory management along with a hardware architecture, which can handle the proposed combination.

High efficiency coherent optical memory with warm rubidium vapour

PubMed Central

Hosseini, M.; Sparkes, B.M.; Campbell, G.; Lam, P.K.; Buchler, B.C.

2011-01-01

By harnessing aspects of quantum mechanics, communication and information processing could be radically transformed. Promising forms of quantum information technology include optical quantum cryptographic systems and computing using photons for quantum logic operations. As with current information processing systems, some form of memory will be required. Quantum repeaters, which are required for long distance quantum key distribution, require quantum optical memory as do deterministic logic gates for optical quantum computing. Here, we present results from a coherent optical memory based on warm rubidium vapour and show 87% efficient recall of light pulses, the highest efficiency measured to date for any coherent optical memory suitable for quantum information applications. We also show storage and recall of up to 20 pulses from our system. These results show that simple warm atomic vapour systems have clear potential as a platform for quantum memory. PMID:21285952

High efficiency coherent optical memory with warm rubidium vapour.

PubMed

Hosseini, M; Sparkes, B M; Campbell, G; Lam, P K; Buchler, B C

2011-02-01

By harnessing aspects of quantum mechanics, communication and information processing could be radically transformed. Promising forms of quantum information technology include optical quantum cryptographic systems and computing using photons for quantum logic operations. As with current information processing systems, some form of memory will be required. Quantum repeaters, which are required for long distance quantum key distribution, require quantum optical memory as do deterministic logic gates for optical quantum computing. Here, we present results from a coherent optical memory based on warm rubidium vapour and show 87% efficient recall of light pulses, the highest efficiency measured to date for any coherent optical memory suitable for quantum information applications. We also show storage and recall of up to 20 pulses from our system. These results show that simple warm atomic vapour systems have clear potential as a platform for quantum memory.

A model of memory impairment in schizophrenia: cognitive and clinical factors associated with memory efficiency and memory errors.

PubMed

Brébion, Gildas; Bressan, Rodrigo A; Ohlsen, Ruth I; David, Anthony S

2013-12-01

Memory impairments in patients with schizophrenia have been associated with various cognitive and clinical factors. Hallucinations have been more specifically associated with errors stemming from source monitoring failure. We conducted a broad investigation of verbal memory and visual memory as well as source memory functioning in a sample of patients with schizophrenia. Various memory measures were tallied, and we studied their associations with processing speed, working memory span, and positive, negative, and depressive symptoms. Superficial and deep memory processes were differentially associated with processing speed, working memory span, avolition, depression, and attention disorders. Auditory/verbal and visual hallucinations were differentially associated with specific types of source memory error. We integrated all the results into a revised version of a previously published model of memory functioning in schizophrenia. The model describes the factors that affect memory efficiency, as well as the cognitive underpinnings of hallucinations within the source monitoring framework. © 2013.

Protection of Mission-Critical Applications from Untrusted Execution Environment: Resource Efficient Replication and Migration of Virtual Machines

DTIC Science & Technology

2015-09-28

the performance of log-and- replay can degrade significantly for VMs configured with multiple virtual CPUs, since the shared memory communication...whether based on checkpoint replication or log-and- replay , existing HA ap- proaches use in- memory backups. The backup VM sits in the memory of a...efficiently. 15. SUBJECT TERMS High-availability virtual machines, live migration, memory and traffic overheads, application suspension, Java

PIMS: Memristor-Based Processing-in-Memory-and-Storage.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cook, Jeanine

Continued progress in computing has augmented the quest for higher performance with a new quest for higher energy efficiency. This has led to the re-emergence of Processing-In-Memory (PIM) ar- chitectures that offer higher density and performance with some boost in energy efficiency. Past PIM work either integrated a standard CPU with a conventional DRAM to improve the CPU- memory link, or used a bit-level processor with Single Instruction Multiple Data (SIMD) control, but neither matched the energy consumption of the memory to the computation. We originally proposed to develop a new architecture derived from PIM that more effectively addressed energymore » efficiency for high performance scientific, data analytics, and neuromorphic applications. We also originally planned to implement a von Neumann architecture with arithmetic/logic units (ALUs) that matched the power consumption of an advanced storage array to maximize energy efficiency. Implementing this architecture in storage was our original idea, since by augmenting storage (in- stead of memory), the system could address both in-memory computation and applications that accessed larger data sets directly from storage, hence Processing-in-Memory-and-Storage (PIMS). However, as our research matured, we discovered several things that changed our original direc- tion, the most important being that a PIM that implements a standard von Neumann-type archi- tecture results in significant energy efficiency improvement, but only about a O(10) performance improvement. In addition to this, the emergence of new memory technologies moved us to propos- ing a non-von Neumann architecture, called Superstrider, implemented not in storage, but in a new DRAM technology called High Bandwidth Memory (HBM). HBM is a stacked DRAM tech- nology that includes a logic layer where an architecture such as Superstrider could potentially be implemented.« less

Comparing memory-efficient genome assemblers on stand-alone and cloud infrastructures.

PubMed

Kleftogiannis, Dimitrios; Kalnis, Panos; Bajic, Vladimir B

2013-01-01

A fundamental problem in bioinformatics is genome assembly. Next-generation sequencing (NGS) technologies produce large volumes of fragmented genome reads, which require large amounts of memory to assemble the complete genome efficiently. With recent improvements in DNA sequencing technologies, it is expected that the memory footprint required for the assembly process will increase dramatically and will emerge as a limiting factor in processing widely available NGS-generated reads. In this report, we compare current memory-efficient techniques for genome assembly with respect to quality, memory consumption and execution time. Our experiments prove that it is possible to generate draft assemblies of reasonable quality on conventional multi-purpose computers with very limited available memory by choosing suitable assembly methods. Our study reveals the minimum memory requirements for different assembly programs even when data volume exceeds memory capacity by orders of magnitude. By combining existing methodologies, we propose two general assembly strategies that can improve short-read assembly approaches and result in reduction of the memory footprint. Finally, we discuss the possibility of utilizing cloud infrastructures for genome assembly and we comment on some findings regarding suitable computational resources for assembly.

Spatial working memory load affects counting but not subitizing in enumeration.

PubMed

Shimomura, Tomonari; Kumada, Takatsune

2011-08-01

The present study investigated whether subitizing reflects capacity limitations associated with two types of working memory tasks. Under a dual-task situation, participants performed an enumeration task in conjunction with either a spatial (Experiment 1) or a nonspatial visual (Experiment 2) working memory task. Experiment 1 showed that spatial working memory load affected the slope of a counting function but did not affect subitizing performance or subitizing range. Experiment 2 showed that nonspatial visual working memory load affected neither enumeration efficiency nor subitizing range. Furthermore, in both spatial and nonspatial memory tasks, neither subitizing efficiency nor subitizing range was affected by amount of imposed memory load. In all the experiments, working memory load failed to influence slope, subitizing range, or overall reaction time. These findings suggest that subitizing is performed without either spatial or nonspatial working memory. A possible mechanism of subitizing with independent capacity of working memory is discussed.

Efficient High Performance Collective Communication for Distributed Memory Environments

ERIC Educational Resources Information Center

Ali, Qasim

2009-01-01

Collective communication allows efficient communication and synchronization among a collection of processes, unlike point-to-point communication that only involves a pair of communicating processes. Achieving high performance for both kernels and full-scale applications running on a distributed memory system requires an efficient implementation of…

Working memory capacity and redundant information processing efficiency.

PubMed

Endres, Michael J; Houpt, Joseph W; Donkin, Chris; Finn, Peter R

2015-01-01

Working memory capacity (WMC) is typically measured by the amount of task-relevant information an individual can keep in mind while resisting distraction or interference from task-irrelevant information. The current research investigated the extent to which differences in WMC were associated with performance on a novel redundant memory probes (RMP) task that systematically varied the amount of to-be-remembered (targets) and to-be-ignored (distractor) information. The RMP task was designed to both facilitate and inhibit working memory search processes, as evidenced by differences in accuracy, response time, and Linear Ballistic Accumulator (LBA) model estimates of information processing efficiency. Participants (N = 170) completed standard intelligence tests and dual-span WMC tasks, along with the RMP task. As expected, accuracy, response-time, and LBA model results indicated memory search and retrieval processes were facilitated under redundant-target conditions, but also inhibited under mixed target/distractor and redundant-distractor conditions. Repeated measures analyses also indicated that, while individuals classified as high (n = 85) and low (n = 85) WMC did not differ in the magnitude of redundancy effects, groups did differ in the efficiency of memory search and retrieval processes overall. Results suggest that redundant information reliably facilitates and inhibits the efficiency or speed of working memory search, and these effects are independent of more general limits and individual differences in the capacity or space of working memory.

Dynamic Forest: An Efficient Index Structure for NAND Flash Memory

NASA Astrophysics Data System (ADS)

Yang, Chul-Woong; Yong Lee, Ki; Ho Kim, Myoung; Lee, Yoon-Joon

In this paper, we present an efficient index structure for NAND flash memory, called the Dynamic Forest (D-Forest). Since write operations incur high overhead on NAND flash memory, D-Forest is designed to minimize write operations for index updates. The experimental results show that D-Forest significantly reduces write operations compared to the conventional B+-tree.

Energy-aware Thread and Data Management in Heterogeneous Multi-core, Multi-memory Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Su, Chun-Yi

By 2004, microprocessor design focused on multicore scaling—increasing the number of cores per die in each generation—as the primary strategy for improving performance. These multicore processors typically equip multiple memory subsystems to improve data throughput. In addition, these systems employ heterogeneous processors such as GPUs and heterogeneous memories like non-volatile memory to improve performance, capacity, and energy efficiency. With the increasing volume of hardware resources and system complexity caused by heterogeneity, future systems will require intelligent ways to manage hardware resources. Early research to improve performance and energy efficiency on heterogeneous, multi-core, multi-memory systems focused on tuning a single primitivemore » or at best a few primitives in the systems. The key limitation of past efforts is their lack of a holistic approach to resource management that balances the tradeoff between performance and energy consumption. In addition, the shift from simple, homogeneous systems to these heterogeneous, multicore, multi-memory systems requires in-depth understanding of efficient resource management for scalable execution, including new models that capture the interchange between performance and energy, smarter resource management strategies, and novel low-level performance/energy tuning primitives and runtime systems. Tuning an application to control available resources efficiently has become a daunting challenge; managing resources in automation is still a dark art since the tradeoffs among programming, energy, and performance remain insufficiently understood. In this dissertation, I have developed theories, models, and resource management techniques to enable energy-efficient execution of parallel applications through thread and data management in these heterogeneous multi-core, multi-memory systems. I study the effect of dynamic concurrent throttling on the performance and energy of multi-core, non-uniform memory access (NUMA) systems. I use critical path analysis to quantify memory contention in the NUMA memory system and determine thread mappings. In addition, I implement a runtime system that combines concurrent throttling and a novel thread mapping algorithm to manage thread resources and improve energy efficient execution in multi-core, NUMA systems.« less

The effect of nonadiabaticity on the efficiency of quantum memory based on an optical cavity

NASA Astrophysics Data System (ADS)

Veselkova, N. G.; Sokolov, I. V.

2017-07-01

Quantum efficiency is an important characteristic of quantum memory devices that are aimed at recording the quantum state of light signals and its storing and reading. In the case of memory based on an ensemble of cold atoms placed in an optical cavity, the efficiency is restricted, in particular, by relaxation processes in the system of active atomic levels. We show how the effect of the relaxation on the quantum efficiency can be determined in a regime of the memory usage in which the evolution of signals in time is not arbitrarily slow on the scale of the field lifetime in the cavity and when the frequently used approximation of the adiabatic elimination of the quantized cavity mode field cannot be applied. Taking into account the effect of the nonadiabaticity on the memory quality is of interest in view of the fact that, in order to increase the field-medium coupling parameter, a higher cavity quality factor is required, whereas storing and processing of sequences of many signals in the memory implies that their duration is reduced. We consider the applicability of the well-known efficiency estimates via the system cooperativity parameter and estimate a more general form. In connection with the theoretical description of the memory of the given type, we also discuss qualitative differences in the behavior of a random source introduced into the Heisenberg-Langevin equations for atomic variables in the cases of a large and a small number of atoms.

High-performance Raman memory with spatio-temporal reversal

NASA Astrophysics Data System (ADS)

Vernaz-Gris, Pierre; Tranter, Aaron D.; Everett, Jesse L.; Leung, Anthony C.; Paul, Karun V.; Campbell, Geoff T.; Lam, Ping Koy; Buchler, Ben C.

2018-05-01

A number of techniques exist to use an ensemble of atoms as a quantum memory for light. Many of these propose to use backward retrieval as a way to improve the storage and recall efficiency. We report on a demonstration of an off-resonant Raman memory that uses backward retrieval to achieve an efficiency of $65\\pm6\\%$ at a storage time of one pulse duration. The memory has a characteristic decay time of 60 $\\mu$s, corresponding to a delay-bandwidth product of $160$.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sancho Pitarch, Jose Carlos; Kerbyson, Darren; Lang, Mike

Increasing the core-count on current and future processors is posing critical challenges to the memory subsystem to efficiently handle concurrent memory requests. The current trend to cope with this challenge is to increase the number of memory channels available to the processor's memory controller. In this paper we investigate the effectiveness of this approach on the performance of parallel scientific applications. Specifically, we explore the trade-off between employing multiple memory channels per memory controller and the use of multiple memory controllers. Experiments conducted on two current state-of-the-art multicore processors, a 6-core AMD Istanbul and a 4-core Intel Nehalem-EP, for amore » wide range of production applications shows that there is a diminishing return when increasing the number of memory channels per memory controller. In addition, we show that this performance degradation can be efficiently addressed by increasing the ratio of memory controllers to channels while keeping the number of memory channels constant. Significant performance improvements can be achieved in this scheme, up to 28%, in the case of using two memory controllers with each with one channel compared with one controller with two memory channels.« less

A comparison of the Cray-2 performance before and after the installation of memory pseudo-banking

NASA Technical Reports Server (NTRS)

Schmickley, Ronald D.; Bailey, David H.

1987-01-01

A suite of 13 large Fortran benchmark codes were run on a Cray-2 configured with memory pseudo-banking circuits, and floating point operation rates were measured for each under a variety of system load configurations. These were compared with similar flop measurements taken on the same system before installation of the pseudo-banking. A useful memory access efficiency parameter was defined and calculated for both sets of performance rates, allowing a crude quantitative measure of the improvement in efficiency due to pseudo-banking. Programs were categorized as either highly scalar (S) or highly vectorized (V) and either memory-intensive or register-intensive, giving 4 categories: S-memory, S-register, V-memory, and V-register. Using flop rates as a simple quantifier of these 4 categories, a scatter plot of efficiency gain vs Mflops roughly illustrates the improvement in floating point processing speed due to pseudo-banking. On the Cray-2 system tested this improvement ranged from 1 percent for S-memory codes to about 12 percent for V-memory codes. No significant gains were made for V-register codes, which was to be expected.

Brain reserve and cognitive reserve protect against cognitive decline over 4.5 years in MS

PubMed Central

Rocca, Maria A.; Leavitt, Victoria M.; Dackovic, Jelena; Mesaros, Sarlota; Drulovic, Jelena; DeLuca, John; Filippi, Massimo

2014-01-01

Objective: Based on the theories of brain reserve and cognitive reserve, we investigated whether larger maximal lifetime brain growth (MLBG) and/or greater lifetime intellectual enrichment protect against cognitive decline over time. Methods: Forty patients with multiple sclerosis (MS) underwent baseline and 4.5-year follow-up evaluations of cognitive efficiency (Symbol Digit Modalities Test, Paced Auditory Serial Addition Task) and memory (Selective Reminding Test, Spatial Recall Test). Baseline and follow-up MRIs quantified disease progression: percentage brain volume change (cerebral atrophy), percentage change in T2 lesion volume. MLBG (brain reserve) was estimated with intracranial volume; intellectual enrichment (cognitive reserve) was estimated with vocabulary. We performed repeated-measures analyses of covariance to investigate whether larger MLBG and/or greater intellectual enrichment moderate/attenuate cognitive decline over time, controlling for disease progression. Results: Patients with MS declined in cognitive efficiency and memory (p < 0.001). MLBG moderated decline in cognitive efficiency (p = 0.031, ηp2 = 0.122), with larger MLBG protecting against decline. MLBG did not moderate memory decline (p = 0.234, ηp2 = 0.039). Intellectual enrichment moderated decline in cognitive efficiency (p = 0.031, ηp2 = 0.126) and memory (p = 0.037, ηp2 = 0.115), with greater intellectual enrichment protecting against decline. MS disease progression was more negatively associated with change in cognitive efficiency and memory among patients with lower vs higher MLBG and intellectual enrichment. Conclusion: We provide longitudinal support for theories of brain reserve and cognitive reserve in MS. Larger MLBG protects against decline in cognitive efficiency, and greater intellectual enrichment protects against decline in cognitive efficiency and memory. Consideration of these protective factors should improve prediction of future cognitive decline in patients with MS. PMID:24748670

Efficient entanglement distillation without quantum memory.

PubMed

Abdelkhalek, Daniela; Syllwasschy, Mareike; Cerf, Nicolas J; Fiurášek, Jaromír; Schnabel, Roman

2016-05-31

Entanglement distribution between distant parties is an essential component to most quantum communication protocols. Unfortunately, decoherence effects such as phase noise in optical fibres are known to demolish entanglement. Iterative (multistep) entanglement distillation protocols have long been proposed to overcome decoherence, but their probabilistic nature makes them inefficient since the success probability decays exponentially with the number of steps. Quantum memories have been contemplated to make entanglement distillation practical, but suitable quantum memories are not realised to date. Here, we present the theory for an efficient iterative entanglement distillation protocol without quantum memories and provide a proof-of-principle experimental demonstration. The scheme is applied to phase-diffused two-mode-squeezed states and proven to distil entanglement for up to three iteration steps. The data are indistinguishable from those that an efficient scheme using quantum memories would produce. Since our protocol includes the final measurement it is particularly promising for enhancing continuous-variable quantum key distribution.

Efficient entanglement distillation without quantum memory

PubMed Central

Abdelkhalek, Daniela; Syllwasschy, Mareike; Cerf, Nicolas J.; Fiurášek, Jaromír; Schnabel, Roman

2016-01-01

Entanglement distribution between distant parties is an essential component to most quantum communication protocols. Unfortunately, decoherence effects such as phase noise in optical fibres are known to demolish entanglement. Iterative (multistep) entanglement distillation protocols have long been proposed to overcome decoherence, but their probabilistic nature makes them inefficient since the success probability decays exponentially with the number of steps. Quantum memories have been contemplated to make entanglement distillation practical, but suitable quantum memories are not realised to date. Here, we present the theory for an efficient iterative entanglement distillation protocol without quantum memories and provide a proof-of-principle experimental demonstration. The scheme is applied to phase-diffused two-mode-squeezed states and proven to distil entanglement for up to three iteration steps. The data are indistinguishable from those that an efficient scheme using quantum memories would produce. Since our protocol includes the final measurement it is particularly promising for enhancing continuous-variable quantum key distribution. PMID:27241946

Asymmetric soft-error resistant memory

NASA Technical Reports Server (NTRS)

Buehler, Martin G. (Inventor); Perlman, Marvin (Inventor)

1991-01-01

A memory system is provided, of the type that includes an error-correcting circuit that detects and corrects, that more efficiently utilizes the capacity of a memory formed of groups of binary cells whose states can be inadvertently switched by ionizing radiation. Each memory cell has an asymmetric geometry, so that ionizing radiation causes a significantly greater probability of errors in one state than in the opposite state (e.g., an erroneous switch from '1' to '0' is far more likely than a switch from '0' to'1'. An asymmetric error correcting coding circuit can be used with the asymmetric memory cells, which requires fewer bits than an efficient symmetric error correcting code.

Scalable Motion Estimation Processor Core for Multimedia System-on-Chip Applications

NASA Astrophysics Data System (ADS)

Lai, Yeong-Kang; Hsieh, Tian-En; Chen, Lien-Fei

2007-04-01

In this paper, we describe a high-throughput and scalable motion estimation processor architecture for multimedia system-on-chip applications. The number of processing elements (PEs) is scalable according to the variable algorithm parameters and the performance required for different applications. Using the PE rings efficiently and an intelligent memory-interleaving organization, the efficiency of the architecture can be increased. Moreover, using efficient on-chip memories and a data management technique can effectively decrease the power consumption and memory bandwidth. Techniques for reducing the number of interconnections and external memory accesses are also presented. Our results demonstrate that the proposed scalable PE-ringed architecture is a flexible and high-performance processor core in multimedia system-on-chip applications.

Is less really more: Does a prefrontal efficiency genotype actually confer better performance when working memory becomes difficult?

PubMed

Ihne, Jessica L; Gallagher, Natalie M; Sullivan, Marie; Callicott, Joseph H; Green, Adam E

2016-01-01

Perhaps the most widely studied effect to emerge from the combination of neuroimaging and human genetics is the association of the COMT-Val(108/158)Met polymorphism with prefrontal activity during working memory. COMT-Val is a putative risk factor in schizophrenia, which is characterized by disordered prefrontal function. Work in healthy populations has sought to characterize mechanisms by which the valine (Val) allele may lead to disadvantaged prefrontal cognition. Lower activity in methionine (Met) carriers has been interpreted as advantageous neural efficiency. Notably, however, studies reporting COMT effects on neural efficiency have generally not reported working memory performance effects. Those studies have employed relatively low/easy working memory loads. Higher loads are known to elicit individual differences in working memory performance that are not visible at lower loads. If COMT-Met confers greater neural efficiency when working memory is easy, a reasonable prediction is that Met carriers will be better able to cope with increasing demand for neural resources when working memory becomes difficult. To our knowledge, this prediction has thus far gone untested. Here, we tested performance on three working memory tasks. Performance on each task was measured at multiple levels of load/difficulty, including loads more demanding than those used in prior studies. We found no genotype-by-load interactions or main effects of COMT genotype on accuracy or reaction time. Indeed, even testing for performance differences at each load of each task failed to find a single significant effect of COMT genotype. Thus, even if COMT genotype has the effects on prefrontal efficiency that prior work has suggested, such effects may not directly impact high-load working memory ability. The present findings accord with previous evidence that behavioral effects of COMT are small or nonexistent and, more broadly, with a growing consensus that substantial effects on phenotype will not emerge from candidate gene studies. Copyright © 2015 Elsevier Ltd. All rights reserved.

BLESS 2: accurate, memory-efficient and fast error correction method.

PubMed

Heo, Yun; Ramachandran, Anand; Hwu, Wen-Mei; Ma, Jian; Chen, Deming

2016-08-01

The most important features of error correction tools for sequencing data are accuracy, memory efficiency and fast runtime. The previous version of BLESS was highly memory-efficient and accurate, but it was too slow to handle reads from large genomes. We have developed a new version of BLESS to improve runtime and accuracy while maintaining a small memory usage. The new version, called BLESS 2, has an error correction algorithm that is more accurate than BLESS, and the algorithm has been parallelized using hybrid MPI and OpenMP programming. BLESS 2 was compared with five top-performing tools, and it was found to be the fastest when it was executed on two computing nodes using MPI, with each node containing twelve cores. Also, BLESS 2 showed at least 11% higher gain while retaining the memory efficiency of the previous version for large genomes. Freely available at https://sourceforge.net/projects/bless-ec dchen@illinois.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Efficiency of Energy Harvesting in Ni-Mn-Ga Shape Memory Alloys

NASA Astrophysics Data System (ADS)

Lindquist, Paul; Hobza, Tony; Patrick, Charles; Müllner, Peter

2018-03-01

Many researchers have reported on the voltage and power generated while energy harvesting using Ni-Mn-Ga shape memory alloys; few researchers report on the power conversion efficiency of energy harvesting. We measured the magneto-mechanical behavior and energy harvesting of Ni-Mn-Ga shape memory alloys to quantify the efficiency of energy harvesting using the inverse magneto-plastic effect. At low frequencies, less than 150 Hz, the power conversion efficiency is less than 0.1%. Power conversion efficiency increases with (i) increasing actuation frequency, (ii) increasing actuation stroke, and (iii) decreasing twinning stress. Extrapolating the results of low-frequency experiments to the kHz actuation regime yields a power conversion factor of about 20% for 3 kHz actuation frequency, 7% actuation strain, and 0.05 MPa twinning stress.

Design of a memory-access controller with 3.71-times-enhanced energy efficiency for Internet-of-Things-oriented nonvolatile microcontroller unit

NASA Astrophysics Data System (ADS)

Natsui, Masanori; Hanyu, Takahiro

2018-04-01

In realizing a nonvolatile microcontroller unit (MCU) for sensor nodes in Internet-of-Things (IoT) applications, it is important to solve the data-transfer bottleneck between the central processing unit (CPU) and the nonvolatile memory constituting the MCU. As one circuit-oriented approach to solving this problem, we propose a memory access minimization technique for magnetoresistive-random-access-memory (MRAM)-embedded nonvolatile MCUs. In addition to multiplexing and prefetching of memory access, the proposed technique realizes efficient instruction fetch by eliminating redundant memory access while considering the code length of the instruction to be fetched and the transition of the memory address to be accessed. As a result, the performance of the MCU can be improved while relaxing the performance requirement for the embedded MRAM, and compact and low-power implementation can be performed as compared with the conventional cache-based one. Through the evaluation using a system consisting of a general purpose 32-bit CPU and embedded MRAM, it is demonstrated that the proposed technique increases the peak efficiency of the system up to 3.71 times, while a 2.29-fold area reduction is achieved compared with the cache-based one.

Memory Efficient Sequence Analysis Using Compressed Data Structures (Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

ScienceCinema

Simpson, Jared

2018-01-24

Wellcome Trust Sanger Institute's Jared Simpson on Memory efficient sequence analysis using compressed data structures at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

Contribution of auditory working memory to speech understanding in mandarin-speaking cochlear implant users.

PubMed

Tao, Duoduo; Deng, Rui; Jiang, Ye; Galvin, John J; Fu, Qian-Jie; Chen, Bing

2014-01-01

To investigate how auditory working memory relates to speech perception performance by Mandarin-speaking cochlear implant (CI) users. Auditory working memory and speech perception was measured in Mandarin-speaking CI and normal-hearing (NH) participants. Working memory capacity was measured using forward digit span and backward digit span; working memory efficiency was measured using articulation rate. Speech perception was assessed with: (a) word-in-sentence recognition in quiet, (b) word-in-sentence recognition in speech-shaped steady noise at +5 dB signal-to-noise ratio, (c) Chinese disyllable recognition in quiet, (d) Chinese lexical tone recognition in quiet. Self-reported school rank was also collected regarding performance in schoolwork. There was large inter-subject variability in auditory working memory and speech performance for CI participants. Working memory and speech performance were significantly poorer for CI than for NH participants. All three working memory measures were strongly correlated with each other for both CI and NH participants. Partial correlation analyses were performed on the CI data while controlling for demographic variables. Working memory efficiency was significantly correlated only with sentence recognition in quiet when working memory capacity was partialled out. Working memory capacity was correlated with disyllable recognition and school rank when efficiency was partialled out. There was no correlation between working memory and lexical tone recognition in the present CI participants. Mandarin-speaking CI users experience significant deficits in auditory working memory and speech performance compared with NH listeners. The present data suggest that auditory working memory may contribute to CI users' difficulties in speech understanding. The present pattern of results with Mandarin-speaking CI users is consistent with previous auditory working memory studies with English-speaking CI users, suggesting that the lexical importance of voice pitch cues (albeit poorly coded by the CI) did not influence the relationship between working memory and speech perception.

Coherent spin control of a nanocavity-enhanced qubit in diamond

DOE PAGES

Li, Luozhou; Lu, Ming; Schroder, Tim; ...

2015-01-28

A central aim of quantum information processing is the efficient entanglement of multiple stationary quantum memories via photons. Among solid-state systems, the nitrogen-vacancy centre in diamond has emerged as an excellent optically addressable memory with second-scale electron spin coherence times. Recently, quantum entanglement and teleportation have been shown between two nitrogen-vacancy memories, but scaling to larger networks requires more efficient spin-photon interfaces such as optical resonators. Here we report such nitrogen-vacancy nanocavity systems in strong Purcell regime with optical quality factors approaching 10,000 and electron spin coherence times exceeding 200 µs using a silicon hard-mask fabrication process. This spin-photon interfacemore » is integrated with on-chip microwave striplines for coherent spin control, providing an efficient quantum memory for quantum networks.« less

Efficient and flexible memory architecture to alleviate data and context bandwidth bottlenecks of coarse-grained reconfigurable arrays

NASA Astrophysics Data System (ADS)

Yang, Chen; Liu, LeiBo; Yin, ShouYi; Wei, ShaoJun

2014-12-01

The computational capability of a coarse-grained reconfigurable array (CGRA) can be significantly restrained due to data and context memory bandwidth bottlenecks. Traditionally, two methods have been used to resolve this problem. One method loads the context into the CGRA at run time. This method occupies very small on-chip memory but induces very large latency, which leads to low computational efficiency. The other method adopts a multi-context structure. This method loads the context into the on-chip context memory at the boot phase. Broadcasting the pointer of a set of contexts changes the hardware configuration on a cycle-by-cycle basis. The size of the context memory induces a large area overhead in multi-context structures, which results in major restrictions on application complexity. This paper proposes a Predictable Context Cache (PCC) architecture to address the above context issues by buffering the context inside a CGRA. In this architecture, context is dynamically transferred into the CGRA. Utilizing a PCC significantly reduces the on-chip context memory and the complexity of the applications running on the CGRA is no longer restricted by the size of the on-chip context memory. Data preloading is the most frequently used approach to hide input data latency and speed up the data transmission process for the data bandwidth issue. Rather than fundamentally reducing the amount of input data, the transferred data and computations are processed in parallel. However, the data preloading method cannot work efficiently because data transmission becomes the critical path as the reconfigurable array scale increases. This paper also presents a Hierarchical Data Memory (HDM) architecture as a solution to the efficiency problem. In this architecture, high internal bandwidth is provided to buffer both reused input data and intermediate data. The HDM architecture relieves the external memory from the data transfer burden so that the performance is significantly improved. As a result of using PCC and HDM, experiments running mainstream video decoding programs achieved performance improvements of 13.57%-19.48% when there was a reasonable memory size. Therefore, 1080p@35.7fps for H.264 high profile video decoding can be achieved on PCC and HDM architecture when utilizing a 200 MHz working frequency. Further, the size of the on-chip context memory no longer restricted complex applications, which were efficiently executed on the PCC and HDM architecture.

Some comments on Hurst exponent and the long memory processes on capital markets

NASA Astrophysics Data System (ADS)

Sánchez Granero, M. A.; Trinidad Segovia, J. E.; García Pérez, J.

2008-09-01

The analysis of long memory processes in capital markets has been one of the topics in finance, since the existence of the market memory could implicate the rejection of an efficient market hypothesis. The study of these processes in finance is realized through Hurst exponent and the most classical method applied is R/S analysis. In this paper we will discuss the efficiency of this methodology as well as some of its more important modifications to detect the long memory. We also propose the application of a classical geometrical method with short modifications and we compare both approaches.

Motor Action and Emotional Memory

ERIC Educational Resources Information Center

Casasanto, Daniel; Dijkstra, Katinka

2010-01-01

Can simple motor actions affect how efficiently people retrieve emotional memories, and influence what they choose to remember? In Experiment 1, participants were prompted to retell autobiographical memories with either positive or negative valence, while moving marbles either upward or downward. They retrieved memories faster when the direction…

An extended continuum model considering optimal velocity change with memory and numerical tests

NASA Astrophysics Data System (ADS)

Qingtao, Zhai; Hongxia, Ge; Rongjun, Cheng

2018-01-01

In this paper, an extended continuum model of traffic flow is proposed with the consideration of optimal velocity changes with memory. The new model's stability condition and KdV-Burgers equation considering the optimal velocities change with memory are deduced through linear stability theory and nonlinear analysis, respectively. Numerical simulation is carried out to study the extended continuum model, which explores how optimal velocity changes with memory affected velocity, density and energy consumption. Numerical results show that when considering the effects of optimal velocity changes with memory, the traffic jams can be suppressed efficiently. Both the memory step and sensitivity parameters of optimal velocity changes with memory will enhance the stability of traffic flow efficiently. Furthermore, numerical results demonstrates that the effect of optimal velocity changes with memory can avoid the disadvantage of historical information, which increases the stability of traffic flow on road, and so it improve the traffic flow stability and minimize cars' energy consumptions.

User-Assisted Store Recycling for Dynamic Task Graph Schedulers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kurt, Mehmet Can; Krishnamoorthy, Sriram; Agrawal, Gagan

The emergence of the multi-core era has led to increased interest in designing effective yet practical parallel programming models. Models based on task graphs that operate on single-assignment data are attractive in several ways: they can support dynamic applications and precisely represent the available concurrency. However, they also require nuanced algorithms for scheduling and memory management for efficient execution. In this paper, we consider memory-efficient dynamic scheduling of task graphs. Specifically, we present a novel approach for dynamically recycling the memory locations assigned to data items as they are produced by tasks. We develop algorithms to identify memory-efficient store recyclingmore » functions by systematically evaluating the validity of a set of (user-provided or automatically generated) alternatives. Because recycling function can be input data-dependent, we have also developed support for continued correct execution of a task graph in the presence of a potentially incorrect store recycling function. Experimental evaluation demonstrates that our approach to automatic store recycling incurs little to no overheads, achieves memory usage comparable to the best manually derived solutions, often produces recycling functions valid across problem sizes and input parameters, and efficiently recovers from an incorrect choice of store recycling functions.« less

An Implicit Algorithm for the Numerical Simulation of Shape-Memory Alloys

DOE Office of Scientific and Technical Information (OSTI.GOV)

Becker, R; Stolken, J; Jannetti, C

Shape-memory alloys (SMA) have the potential to be used in a variety of interesting applications due to their unique properties of pseudoelasticity and the shape-memory effect. However, in order to design SMA devices efficiently, a physics-based constitutive model is required to accurately simulate the behavior of shape-memory alloys. The scope of this work is to extend the numerical capabilities of the SMA constitutive model developed by Jannetti et. al. (2003), to handle large-scale polycrystalline simulations. The constitutive model is implemented within the finite-element software ABAQUS/Standard using a user defined material subroutine, or UMAT. To improve the efficiency of the numericalmore » simulations, so that polycrystalline specimens of shape-memory alloys can be modeled, a fully implicit algorithm has been implemented to integrate the constitutive equations. Using an implicit integration scheme increases the efficiency of the UMAT over the previously implemented explicit integration method by a factor of more than 100 for single crystal simulations.« less

GPU-Accelerated Forward and Back-Projections with Spatially Varying Kernels for 3D DIRECT TOF PET Reconstruction.

PubMed

Ha, S; Matej, S; Ispiryan, M; Mueller, K

2013-02-01

We describe a GPU-accelerated framework that efficiently models spatially (shift) variant system response kernels and performs forward- and back-projection operations with these kernels for the DIRECT (Direct Image Reconstruction for TOF) iterative reconstruction approach. Inherent challenges arise from the poor memory cache performance at non-axis aligned TOF directions. Focusing on the GPU memory access patterns, we utilize different kinds of GPU memory according to these patterns in order to maximize the memory cache performance. We also exploit the GPU instruction-level parallelism to efficiently hide long latencies from the memory operations. Our experiments indicate that our GPU implementation of the projection operators has slightly faster or approximately comparable time performance than FFT-based approaches using state-of-the-art FFTW routines. However, most importantly, our GPU framework can also efficiently handle any generic system response kernels, such as spatially symmetric and shift-variant as well as spatially asymmetric and shift-variant, both of which an FFT-based approach cannot cope with.

GPU-Accelerated Forward and Back-Projections With Spatially Varying Kernels for 3D DIRECT TOF PET Reconstruction

NASA Astrophysics Data System (ADS)

Ha, S.; Matej, S.; Ispiryan, M.; Mueller, K.

2013-02-01

We describe a GPU-accelerated framework that efficiently models spatially (shift) variant system response kernels and performs forward- and back-projection operations with these kernels for the DIRECT (Direct Image Reconstruction for TOF) iterative reconstruction approach. Inherent challenges arise from the poor memory cache performance at non-axis aligned TOF directions. Focusing on the GPU memory access patterns, we utilize different kinds of GPU memory according to these patterns in order to maximize the memory cache performance. We also exploit the GPU instruction-level parallelism to efficiently hide long latencies from the memory operations. Our experiments indicate that our GPU implementation of the projection operators has slightly faster or approximately comparable time performance than FFT-based approaches using state-of-the-art FFTW routines. However, most importantly, our GPU framework can also efficiently handle any generic system response kernels, such as spatially symmetric and shift-variant as well as spatially asymmetric and shift-variant, both of which an FFT-based approach cannot cope with.

Successful Training of Filtering Mechanisms in Multiple Object Tracking Does Not Transfer to Filtering Mechanisms in a Visual Working Memory Task: Behavioral and Electrophysiological Evidence

ERIC Educational Resources Information Center

Arend, Anna M.; Zimmer, Hubert D.

2012-01-01

In this training study, we aimed to selectively train participants' filtering mechanisms to enhance visual working memory (WM) efficiency. The highly restricted nature of visual WM capacity renders efficient filtering mechanisms crucial for its successful functioning. Filtering efficiency in visual WM can be measured via the lateralized change…

Light storage in a cold atomic ensemble with a high optical depth

NASA Astrophysics Data System (ADS)

Park, Kwang-Kyoon; Chough, Young-Tak; Kim, Yoon-Ho

2017-06-01

A quantum memory with a high storage efficiency and a long coherence time is an essential element in quantum information applications. Here, we report our recent development of an optical quantum memory with a rubidium-87 cold atom ensemble. By increasing the optical depth of the medium, we have achieved a storage efficiency of 65% and a coherence time of 51 μs for a weak laser pulse. The result of a numerical analysis based on the Maxwell-Bloch equations agrees well with the experimental results. Our result paves the way toward an efficient optical quantum memory and may find applications in photonic quantum information processing.

The effects of two types of sleep deprivation on visual working memory capacity and filtering efficiency.

PubMed

Drummond, Sean P A; Anderson, Dane E; Straus, Laura D; Vogel, Edward K; Perez, Veronica B

2012-01-01

Sleep deprivation has adverse consequences for a variety of cognitive functions. The exact effects of sleep deprivation, though, are dependent upon the cognitive process examined. Within working memory, for example, some component processes are more vulnerable to sleep deprivation than others. Additionally, the differential impacts on cognition of different types of sleep deprivation have not been well studied. The aim of this study was to examine the effects of one night of total sleep deprivation and 4 nights of partial sleep deprivation (4 hours in bed/night) on two components of visual working memory: capacity and filtering efficiency. Forty-four healthy young adults were randomly assigned to one of the two sleep deprivation conditions. All participants were studied: 1) in a well-rested condition (following 6 nights of 9 hours in bed/night); and 2) following sleep deprivation, in a counter-balanced order. Visual working memory testing consisted of two related tasks. The first measured visual working memory capacity and the second measured the ability to ignore distractor stimuli in a visual scene (filtering efficiency). Results showed neither type of sleep deprivation reduced visual working memory capacity. Partial sleep deprivation also generally did not change filtering efficiency. Total sleep deprivation, on the other hand, did impair performance in the filtering task. These results suggest components of visual working memory are differentially vulnerable to the effects of sleep deprivation, and different types of sleep deprivation impact visual working memory to different degrees. Such findings have implications for operational settings where individuals may need to perform with inadequate sleep and whose jobs involve receiving an array of visual information and discriminating the relevant from the irrelevant prior to making decisions or taking actions (e.g., baggage screeners, air traffic controllers, military personnel, health care providers).

Anatomical Coupling between Distinct Metacognitive Systems for Memory and Visual Perception

PubMed Central

McCurdy, Li Yan; Maniscalco, Brian; Metcalfe, Janet; Liu, Ka Yuet; de Lange, Floris P.; Lau, Hakwan

2015-01-01

A recent study found that, across individuals, gray matter volume in the frontal polar region was correlated with visual metacognition capacity (i.e., how well one’s confidence ratings distinguish between correct and incorrect judgments). A question arises as to whether the putative metacognitive mechanisms in this region are also used in other metacognitive tasks involving, for example, memory. A novel psychophysical measure allowed us to assess metacognitive efficiency separately in a visual and a memory task, while taking variations in basic task performance capacity into account. We found that, across individuals, metacognitive efficiencies positively correlated between the two tasks. However, voxel-based morphometry analysis revealed distinct brain structures for the two kinds of metacognition. Replicating a previous finding, variation in visual metacognitive efficiency was correlated with volume of frontal polar regions. However, variation in memory metacognitive efficiency was correlated with volume of the precuneus. There was also a weak correlation between visual metacognitive efficiency and precuneus volume, which may account for the behavioral correlation between visual and memory metacognition (i.e., the precuneus may contain common mechanisms for both types of metacognition). However, we also found that gray matter volumes of the frontal polar and precuneus regions themselves correlated across individuals, and a formal model comparison analysis suggested that this structural covariation was sufficient to account for the behavioral correlation of metacognition in the two tasks. These results highlight the importance of the precuneus in higher-order memory processing and suggest that there may be functionally distinct metacognitive systems in the human brain. PMID:23365229

Exploration of depth modeling mode one lossless wedgelets storage strategies for 3D-high efficiency video coding

NASA Astrophysics Data System (ADS)

Sanchez, Gustavo; Marcon, César; Agostini, Luciano Volcan

2018-01-01

The 3D-high efficiency video coding has introduced tools to obtain higher efficiency in 3-D video coding, and most of them are related to the depth maps coding. Among these tools, the depth modeling mode-1 (DMM-1) focuses on better encoding edges regions of depth maps. The large memory required for storing all wedgelet patterns is one of the bottlenecks in the DMM-1 hardware design of both encoder and decoder since many patterns must be stored. Three algorithms to reduce the DMM-1 memory requirements and a hardware design targeting the most efficient among these algorithms are presented. Experimental results demonstrate that the proposed solutions surpass related works reducing up to 78.8% of the wedgelet memory, without degrading the encoding efficiency. Synthesis results demonstrate that the proposed algorithm reduces almost 75% of the power dissipation when compared to the standard approach.

Targeted Memory Reactivation during Sleep Adaptively Promotes the Strengthening or Weakening of Overlapping Memories.

PubMed

Oyarzún, Javiera P; Morís, Joaquín; Luque, David; de Diego-Balaguer, Ruth; Fuentemilla, Lluís

2017-08-09

System memory consolidation is conceptualized as an active process whereby newly encoded memory representations are strengthened through selective memory reactivation during sleep. However, our learning experience is highly overlapping in content (i.e., shares common elements), and memories of these events are organized in an intricate network of overlapping associated events. It remains to be explored whether and how selective memory reactivation during sleep has an impact on these overlapping memories acquired during awake time. Here, we test in a group of adult women and men the prediction that selective memory reactivation during sleep entails the reactivation of associated events and that this may lead the brain to adaptively regulate whether these associated memories are strengthened or pruned from memory networks on the basis of their relative associative strength with the shared element. Our findings demonstrate the existence of efficient regulatory neural mechanisms governing how complex memory networks are shaped during sleep as a function of their associative memory strength. SIGNIFICANCE STATEMENT Numerous studies have demonstrated that system memory consolidation is an active, selective, and sleep-dependent process in which only subsets of new memories become stabilized through their reactivation. However, the learning experience is highly overlapping in content and thus events are encoded in an intricate network of related memories. It remains to be explored whether and how memory reactivation has an impact on overlapping memories acquired during awake time. Here, we show that sleep memory reactivation promotes strengthening and weakening of overlapping memories based on their associative memory strength. These results suggest the existence of an efficient regulatory neural mechanism that avoids the formation of cluttered memory representation of multiple events and promotes stabilization of complex memory networks. Copyright © 2017 the authors 0270-6474/17/377748-11$15.00/0.

Memory for conversation and the development of common ground.

PubMed

McKinley, Geoffrey L; Brown-Schmidt, Sarah; Benjamin, Aaron S

2017-11-01

Efficient conversation is guided by the mutual knowledge, or common ground, that interlocutors form as a conversation progresses. Characterized from the perspective of commonly used measures of memory, efficient conversation should be closely associated with item memory-what was said-and context memory-who said what to whom. However, few studies have explicitly probed memory to evaluate what type of information is maintained following a communicative exchange. The current study examined how item and context memory relate to the development of common ground over the course of a conversation, and how these forms of memory vary as a function of one's role in a conversation as speaker or listener. The process of developing common ground was positively related to both item and context memory. In addition, content that was spoken was remembered better than content that was heard. Our findings illustrate how memory assessments can complement language measures by revealing the impact that basic conversational processes have on memory for what has been discussed. By taking this approach, we show that not only does the process of forming common ground facilitate communication in the present, but it also promotes an enduring record of that event, facilitating conversation into the future.

Optical storage with electromagnetically induced transparency in cold atoms at a high optical depth

NASA Astrophysics Data System (ADS)

Zhang, Shanchao; Zhou, Shuyu; Liu, Chang; Chen, J. F.; Wen, Jianming; Loy, M. M. T.; Wong, G. K. L.; Du, Shengwang

2012-06-01

We report experimental demonstration of efficient optical storage with electromagnetically induced transparency (EIT) in a dense cold ^85Rb atomic ensemble trapped in a two-dimensional magneto-optical trap. By varying the optical depth (OD) from 0 to 140, we observe that the optimal storage efficiency for coherent optical pulses has a saturation value of 50% as OD > 50. Our result is consistent with that obtained from hot vapor cell experiments which suggest that a four-wave mixing nonlinear process degrades the EIT storage coherence and efficiency. We apply this EIT quantum memory for narrow-band single photons with controllable waveforms, and obtain an optimal storage efficiency of 49±3% for single-photon wave packets. This is the highest single-photon storage efficiency reported up to today and brings the EIT atomic quantum memory close to practical application because an efficiency of above 50% is necessary to operate the memory within non-cloning regime and beat the classical limit.

High Storage Efficiency and Large Fractional Delay of EIT-Based Memory

NASA Astrophysics Data System (ADS)

Chen, Yi-Hsin; Lee, Meng-Jung; Wang, I.-Chung; Du, Shengwang; Chen, Yong-Fan; Chen, Ying-Cheng; Yu, Ite

2013-05-01

In long-distance quantum communication and optical quantum computation, an efficient and long-lived quantum memory is an important component. We first experimentally demonstrated that a time-space-reversing method plus the optimum pulse shape can improve the storage efficiency (SE) of light pulses to 78% in cold media based on the effect of electromagnetically induced transparency (EIT). We obtain a large fractional delay of 74 at 50% SE, which is the best record so far. The measured classical fidelity of the recalled pulse is higher than 90% and nearly independent of the storage time, implying that the optical memory maintains excellent phase coherence. Our results suggest the current result may be readily applied to single-photon quantum states due to quantum nature of the EIT light-matter inference. This study advances the EIT-based quantum memory in practical quantum information applications.

A Comprehensive Study on Energy Efficiency and Performance of Flash-based SSD

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, Seon-Yeon; Kim, Youngjae; Urgaonkar, Bhuvan

2011-01-01

Use of flash memory as a storage medium is becoming popular in diverse computing environments. However, because of differences in interface, flash memory requires a hard-disk-emulation layer, called FTL (flash translation layer). Although the FTL enables flash memory storages to replace conventional hard disks, it induces significant computational and space overhead. Despite the low power consumption of flash memory, this overhead leads to significant power consumption in an overall storage system. In this paper, we analyze the characteristics of flash-based storage devices from the viewpoint of power consumption and energy efficiency by using various methodologies. First, we utilize simulation tomore » investigate the interior operation of flash-based storage of flash-based storages. Subsequently, we measure the performance and energy efficiency of commodity flash-based SSDs by using microbenchmarks to identify the block-device level characteristics and macrobenchmarks to reveal their filesystem level characteristics.« less

Seizure Control and Memory Impairment Are Related to Disrupted Brain Functional Integration in Temporal Lobe Epilepsy.

PubMed

Park, Chang-Hyun; Choi, Yun Seo; Jung, A-Reum; Chung, Hwa-Kyoung; Kim, Hyeon Jin; Yoo, Jeong Hyun; Lee, Hyang Woon

2017-01-01

Brain functional integration can be disrupted in patients with temporal lobe epilepsy (TLE), but the clinical relevance of this disruption is not completely understood. The authors hypothesized that disrupted functional integration over brain regions remote from, as well as adjacent to, the seizure focus could be related to clinical severity in terms of seizure control and memory impairment. Using resting-state functional MRI data acquired from 48 TLE patients and 45 healthy controls, the authors mapped functional brain networks and assessed changes in a network parameter of brain functional integration, efficiency, to examine the distribution of disrupted functional integration within and between brain regions. The authors assessed whether the extent of altered efficiency was influenced by seizure control status and whether the degree of altered efficiency was associated with the severity of memory impairment. Alterations in the efficiency were observed primarily near the subcortical region ipsilateral to the seizure focus in TLE patients. The extent of regional involvement was greater in patients with poor seizure control: it reached the frontal, temporal, occipital, and insular cortices in TLE patients with poor seizure control, whereas it was limited to the limbic and parietal cortices in TLE patients with good seizure control. Furthermore, TLE patients with poor seizure control experienced more severe memory impairment, and this was associated with lower efficiency in the brain regions with altered efficiency. These findings indicate that the distribution of disrupted brain functional integration is clinically relevant, as it is associated with seizure control status and comorbid memory impairment.

Configurable memory system and method for providing atomic counting operations in a memory device

DOEpatents

Bellofatto, Ralph E.; Gara, Alan G.; Giampapa, Mark E.; Ohmacht, Martin

2010-09-14

A memory system and method for providing atomic memory-based counter operations to operating systems and applications that make most efficient use of counter-backing memory and virtual and physical address space, while simplifying operating system memory management, and enabling the counter-backing memory to be used for purposes other than counter-backing storage when desired. The encoding and address decoding enabled by the invention provides all this functionality through a combination of software and hardware.

A GPU-Accelerated Approach for Feature Tracking in Time-Varying Imagery Datasets.

PubMed

Peng, Chao; Sahani, Sandip; Rushing, John

2017-10-01

We propose a novel parallel connected component labeling (CCL) algorithm along with efficient out-of-core data management to detect and track feature regions of large time-varying imagery datasets. Our approach contributes to the big data field with parallel algorithms tailored for GPU architectures. We remove the data dependency between frames and achieve pixel-level parallelism. Due to the large size, the entire dataset cannot fit into cached memory. Frames have to be streamed through the memory hierarchy (disk to CPU main memory and then to GPU memory), partitioned, and processed as batches, where each batch is small enough to fit into the GPU. To reconnect the feature regions that are separated due to data partitioning, we present a novel batch merging algorithm to extract the region connection information across multiple batches in a parallel fashion. The information is organized in a memory-efficient structure and supports fast indexing on the GPU. Our experiment uses a commodity workstation equipped with a single GPU. The results show that our approach can efficiently process a weather dataset composed of terabytes of time-varying radar images. The advantages of our approach are demonstrated by comparing to the performance of an efficient CPU cluster implementation which is being used by the weather scientists.

Route selection by rats and humans in a navigational traveling salesman problem.

PubMed

Blaser, Rachel E; Ginchansky, Rachel R

2012-03-01

Spatial cognition is typically examined in non-human animals from the perspective of learning and memory. For this reason, spatial tasks are often constrained by the time necessary for training or the capacity of the animal's short-term memory. A spatial task with limited learning and memory demands could allow for more efficient study of some aspects of spatial cognition. The traveling salesman problem (TSP), used to study human visuospatial problem solving, is a simple task with modifiable learning and memory requirements. In the current study, humans and rats were characterized in a navigational version of the TSP. Subjects visited each of 10 baited targets in any sequence from a set starting location. Unlike similar experiments, the roles of learning and memory were purposely minimized; all targets were perceptually available, no distracters were used, and each configuration was tested only once. The task yielded a variety of behavioral measures, including target revisits and omissions, route length, and frequency of transitions between each pair of targets. Both humans and rats consistently chose routes that were more efficient than chance, but less efficient than optimal, and generally less efficient than routes produced by the nearest-neighbor strategy. We conclude that the TSP is a useful and flexible task for the study of spatial cognition in human and non-human animals.

Representational Constraints on the Development of Memory and Metamemory: A Developmental-Representational Theory

ERIC Educational Resources Information Center

Ceci, Stephen J.; Fitneva, Stanka A.; Williams, Wendy M.

2010-01-01

Traditional accounts of memory development suggest that maturation of prefrontal cortex (PFC) enables efficient metamemory, which enhances memory. An alternative theory is described, in which changes in early memory and metamemory are mediated by representational changes, independent of PFC maturation. In a pilot study and Experiment 1, younger…

[Serotonin receptor (5-HTR2A) and dysbindin (DTNBP1) genes and component process variables of short-term verbal memory in schizophrenia].

PubMed

Alfimova, M V; Monakhov, M V; Abramova, L I; Golubev, S A; Golimbet, V E

2009-01-01

An association study of variations in the DTNBP1 (P1763 and P1578) and 5-HTR2A (T102C and A-1438G) genes with short-term verbal memory efficiency and its component process variables was carried out in 405 patients with schizophrenia and 290 healthy controls. All subjects were asked to recall immediately two sets of 10 words. Total recall, List 1 recall, immediate recall or attention span, proactive interference and a number of intrusions were measured. Patients significantly differed from controls by all memory variables. The efficiency of test performance, efficiency of immediate memory, effect of proactive interference as well as number of intrusions were decreased in the group of patients. Both 5-HTR2A polymorphisms were associated with short-term verbal memory efficiency in the combined sample, with the worst performance observed in carriers of homozygous CC (T102C) and GG (A-1438G) genotypes. The significant effect of the P1763 (DTNBP1) marker on the component process variables (proactive interference and intrusions) was found while its effect on the total recall was non-significant. The homozygotes for GG (P1763) had the worst scores. Overall, the data obtained are in line with the conception of DTNBP1 and 5-HTR2A involvement in different component process variables of memory in healthy subjects and patients with schizophrenia.

Optimizing NEURON Simulation Environment Using Remote Memory Access with Recursive Doubling on Distributed Memory Systems.

PubMed

Shehzad, Danish; Bozkuş, Zeki

2016-01-01

Increase in complexity of neuronal network models escalated the efforts to make NEURON simulation environment efficient. The computational neuroscientists divided the equations into subnets amongst multiple processors for achieving better hardware performance. On parallel machines for neuronal networks, interprocessor spikes exchange consumes large section of overall simulation time. In NEURON for communication between processors Message Passing Interface (MPI) is used. MPI_Allgather collective is exercised for spikes exchange after each interval across distributed memory systems. The increase in number of processors though results in achieving concurrency and better performance but it inversely affects MPI_Allgather which increases communication time between processors. This necessitates improving communication methodology to decrease the spikes exchange time over distributed memory systems. This work has improved MPI_Allgather method using Remote Memory Access (RMA) by moving two-sided communication to one-sided communication, and use of recursive doubling mechanism facilitates achieving efficient communication between the processors in precise steps. This approach enhanced communication concurrency and has improved overall runtime making NEURON more efficient for simulation of large neuronal network models.

Optimizing NEURON Simulation Environment Using Remote Memory Access with Recursive Doubling on Distributed Memory Systems

PubMed Central

Bozkuş, Zeki

2016-01-01

Increase in complexity of neuronal network models escalated the efforts to make NEURON simulation environment efficient. The computational neuroscientists divided the equations into subnets amongst multiple processors for achieving better hardware performance. On parallel machines for neuronal networks, interprocessor spikes exchange consumes large section of overall simulation time. In NEURON for communication between processors Message Passing Interface (MPI) is used. MPI_Allgather collective is exercised for spikes exchange after each interval across distributed memory systems. The increase in number of processors though results in achieving concurrency and better performance but it inversely affects MPI_Allgather which increases communication time between processors. This necessitates improving communication methodology to decrease the spikes exchange time over distributed memory systems. This work has improved MPI_Allgather method using Remote Memory Access (RMA) by moving two-sided communication to one-sided communication, and use of recursive doubling mechanism facilitates achieving efficient communication between the processors in precise steps. This approach enhanced communication concurrency and has improved overall runtime making NEURON more efficient for simulation of large neuronal network models. PMID:27413363

Brain oscillatory substrates of visual short-term memory capacity.

PubMed

Sauseng, Paul; Klimesch, Wolfgang; Heise, Kirstin F; Gruber, Walter R; Holz, Elisa; Karim, Ahmed A; Glennon, Mark; Gerloff, Christian; Birbaumer, Niels; Hummel, Friedhelm C

2009-11-17

The amount of information that can be stored in visual short-term memory is strictly limited to about four items. Therefore, memory capacity relies not only on the successful retention of relevant information but also on efficient suppression of distracting information, visual attention, and executive functions. However, completely separable neural signatures for these memory capacity-limiting factors remain to be identified. Because of its functional diversity, oscillatory brain activity may offer a utile solution. In the present study, we show that capacity-determining mechanisms, namely retention of relevant information and suppression of distracting information, are based on neural substrates independent of each other: the successful maintenance of relevant material in short-term memory is associated with cross-frequency phase synchronization between theta (rhythmical neural activity around 5 Hz) and gamma (> 50 Hz) oscillations at posterior parietal recording sites. On the other hand, electroencephalographic alpha activity (around 10 Hz) predicts memory capacity based on efficient suppression of irrelevant information in short-term memory. Moreover, repetitive transcranial magnetic stimulation at alpha frequency can modulate short-term memory capacity by influencing the ability to suppress distracting information. Taken together, the current study provides evidence for a double dissociation of brain oscillatory correlates of visual short-term memory capacity.

The cost of misremembering: Inferring the loss function in visual working memory.

PubMed

Sims, Chris R

2015-03-04

Visual working memory (VWM) is a highly limited storage system. A basic consequence of this fact is that visual memories cannot perfectly encode or represent the veridical structure of the world. However, in natural tasks, some memory errors might be more costly than others. This raises the intriguing possibility that the nature of memory error reflects the costs of committing different kinds of errors. Many existing theories assume that visual memories are noise-corrupted versions of afferent perceptual signals. However, this additive noise assumption oversimplifies the problem. Implicit in the behavioral phenomena of visual working memory is the concept of a loss function: a mathematical entity that describes the relative cost to the organism of making different types of memory errors. An optimally efficient memory system is one that minimizes the expected loss according to a particular loss function, while subject to a constraint on memory capacity. This paper describes a novel theoretical framework for characterizing visual working memory in terms of its implicit loss function. Using inverse decision theory, the empirical loss function is estimated from the results of a standard delayed recall visual memory experiment. These results are compared to the predicted behavior of a visual working memory system that is optimally efficient for a previously identified natural task, gaze correction following saccadic error. Finally, the approach is compared to alternative models of visual working memory, and shown to offer a superior account of the empirical data across a range of experimental datasets. © 2015 ARVO.

Working memory load predicts visual search efficiency: Evidence from a novel pupillary response paradigm.

PubMed

Attar, Nada; Schneps, Matthew H; Pomplun, Marc

2016-10-01

An observer's pupil dilates and constricts in response to variables such as ambient and focal luminance, cognitive effort, the emotional stimulus content, and working memory load. The pupil's memory load response is of particular interest, as it might be used for estimating observers' memory load while they are performing a complex task, without adding an interruptive and confounding memory test to the protocol. One important task in which working memory's involvement is still being debated is visual search, and indeed a previous experiment by Porter, Troscianko, and Gilchrist (Quarterly Journal of Experimental Psychology, 60, 211-229, 2007) analyzed observers' pupil sizes during search to study this issue. These authors found that pupil size increased over the course of the search, and they attributed this finding to accumulating working memory load. However, since the pupil response is slow and does not depend on memory load alone, this conclusion is rather speculative. In the present study, we estimated working memory load in visual search during the presentation of intermittent fixation screens, thought to induce a low, stable level of arousal and cognitive effort. Using standard visual search and control tasks, we showed that this paradigm reduces the influence of non-memory-related factors on pupil size. Furthermore, we found an early increase in working memory load to be associated with more efficient search, indicating a significant role of working memory in the search process.

Efficient accesses of data structures using processing near memory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jayasena, Nuwan S.; Zhang, Dong Ping; Diez, Paula Aguilera

Systems, apparatuses, and methods for implementing efficient queues and other data structures. A queue may be shared among multiple processors and/or threads without using explicit software atomic instructions to coordinate access to the queue. System software may allocate an atomic queue and corresponding queue metadata in system memory and return, to the requesting thread, a handle referencing the queue metadata. Any number of threads may utilize the handle for accessing the atomic queue. The logic for ensuring the atomicity of accesses to the atomic queue may reside in a management unit in the memory controller coupled to the memory wheremore » the atomic queue is allocated.« less

A generalized memory test algorithm

NASA Technical Reports Server (NTRS)

Milner, E. J.

1982-01-01

A general algorithm for testing digital computer memory is presented. The test checks that (1) every bit can be cleared and set in each memory work, and (2) bits are not erroneously cleared and/or set elsewhere in memory at the same time. The algorithm can be applied to any size memory block and any size memory word. It is concise and efficient, requiring the very few cycles through memory. For example, a test of 16-bit-word-size memory requries only 384 cycles through memory. Approximately 15 seconds were required to test a 32K block of such memory, using a microcomputer having a cycle time of 133 nanoseconds.

Concurrent Memory Load Can Make RSVP Search More Efficient

ERIC Educational Resources Information Center

Gil-Gomez de Liano, Beatriz; Botella, Juan

2011-01-01

The detrimental effect of increased memory load on selective attention has been demonstrated in many situations. However, in search tasks over time using RSVP methods, it is not clear how memory load affects attentional processes; no effects as well as beneficial and detrimental effects of memory load have been found in these types of tasks. The…

Genetic algorithms with memory- and elitism-based immigrants in dynamic environments.

PubMed

Yang, Shengxiang

2008-01-01

In recent years the genetic algorithm community has shown a growing interest in studying dynamic optimization problems. Several approaches have been devised. The random immigrants and memory schemes are two major ones. The random immigrants scheme addresses dynamic environments by maintaining the population diversity while the memory scheme aims to adapt genetic algorithms quickly to new environments by reusing historical information. This paper investigates a hybrid memory and random immigrants scheme, called memory-based immigrants, and a hybrid elitism and random immigrants scheme, called elitism-based immigrants, for genetic algorithms in dynamic environments. In these schemes, the best individual from memory or the elite from the previous generation is retrieved as the base to create immigrants into the population by mutation. This way, not only can diversity be maintained but it is done more efficiently to adapt genetic algorithms to the current environment. Based on a series of systematically constructed dynamic problems, experiments are carried out to compare genetic algorithms with the memory-based and elitism-based immigrants schemes against genetic algorithms with traditional memory and random immigrants schemes and a hybrid memory and multi-population scheme. The sensitivity analysis regarding some key parameters is also carried out. Experimental results show that the memory-based and elitism-based immigrants schemes efficiently improve the performance of genetic algorithms in dynamic environments.

MIROS: A Hybrid Real-Time Energy-Efficient Operating System for the Resource-Constrained Wireless Sensor Nodes

PubMed Central

Liu, Xing; Hou, Kun Mean; de Vaulx, Christophe; Shi, Hongling; Gholami, Khalid El

2014-01-01

Operating system (OS) technology is significant for the proliferation of the wireless sensor network (WSN). With an outstanding OS; the constrained WSN resources (processor; memory and energy) can be utilized efficiently. Moreover; the user application development can be served soundly. In this article; a new hybrid; real-time; memory-efficient; energy-efficient; user-friendly and fault-tolerant WSN OS MIROS is designed and implemented. MIROS implements the hybrid scheduler and the dynamic memory allocator. Real-time scheduling can thus be achieved with low memory consumption. In addition; it implements a mid-layer software EMIDE (Efficient Mid-layer Software for User-Friendly Application Development Environment) to decouple the WSN application from the low-level system. The application programming process can consequently be simplified and the application reprogramming performance improved. Moreover; it combines both the software and the multi-core hardware techniques to conserve the energy resources; improve the node reliability; as well as achieve a new debugging method. To evaluate the performance of MIROS; it is compared with the other WSN OSes (TinyOS; Contiki; SOS; openWSN and mantisOS) from different OS concerns. The final evaluation results prove that MIROS is suitable to be used even on the tight resource-constrained WSN nodes. It can support the real-time WSN applications. Furthermore; it is energy efficient; user friendly and fault tolerant. PMID:25248069

MIROS: a hybrid real-time energy-efficient operating system for the resource-constrained wireless sensor nodes.

PubMed

Liu, Xing; Hou, Kun Mean; de Vaulx, Christophe; Shi, Hongling; El Gholami, Khalid

2014-09-22

Operating system (OS) technology is significant for the proliferation of the wireless sensor network (WSN). With an outstanding OS; the constrained WSN resources (processor; memory and energy) can be utilized efficiently. Moreover; the user application development can be served soundly. In this article; a new hybrid; real-time; memory-efficient; energy-efficient; user-friendly and fault-tolerant WSN OS MIROS is designed and implemented. MIROS implements the hybrid scheduler and the dynamic memory allocator. Real-time scheduling can thus be achieved with low memory consumption. In addition; it implements a mid-layer software EMIDE (Efficient Mid-layer Software for User-Friendly Application Development Environment) to decouple the WSN application from the low-level system. The application programming process can consequently be simplified and the application reprogramming performance improved. Moreover; it combines both the software and the multi-core hardware techniques to conserve the energy resources; improve the node reliability; as well as achieve a new debugging method. To evaluate the performance of MIROS; it is compared with the other WSN OSes (TinyOS; Contiki; SOS; openWSN and mantisOS) from different OS concerns. The final evaluation results prove that MIROS is suitable to be used even on the tight resource-constrained WSN nodes. It can support the real-time WSN applications. Furthermore; it is energy efficient; user friendly and fault tolerant.

Encoding: The Keystone to Efficient Functioning of Verbal Short-Term Memory

ERIC Educational Resources Information Center

Barry, Johanna G.; Sabisch, Beate; Friederici, Angela D.; Brauer, Jens

2011-01-01

Verbal short-term memory (VSTM) is thought to play a critical role in language learning. It is indexed by the nonword repetition task where listeners are asked to repeat meaningless words like "blonterstaping". The present study investigated the effect on nonword repetition performance of differences in efficiency of functioning of some part of…

High speed finite element simulations on the graphics card

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huthwaite, P.; Lowe, M. J. S.

A software package is developed to perform explicit time domain finite element simulations of ultrasonic propagation on the graphical processing unit, using Nvidia’s CUDA. Of critical importance for this problem is the arrangement of nodes in memory, allowing data to be loaded efficiently and minimising communication between the independently executed blocks of threads. The initial stage of memory arrangement is partitioning the mesh; both a well established ‘greedy’ partitioner and a new, more efficient ‘aligned’ partitioner are investigated. A method is then developed to efficiently arrange the memory within each partition. The technique is compared to a commercial CPU equivalent,more » demonstrating an overall speedup of at least 100 for a non-destructive testing weld model.« less

Performance analysis and comparison of a minimum interconnections direct storage model with traditional neural bidirectional memories.

PubMed

Bhatti, A Aziz

2009-12-01

This study proposes an efficient and improved model of a direct storage bidirectional memory, improved bidirectional associative memory (IBAM), and emphasises the use of nanotechnology for efficient implementation of such large-scale neural network structures at a considerable lower cost reduced complexity, and less area required for implementation. This memory model directly stores the X and Y associated sets of M bipolar binary vectors in the form of (MxN(x)) and (MxN(y)) memory matrices, requires O(N) or about 30% of interconnections with weight strength ranging between +/-1, and is computationally very efficient as compared to sequential, intraconnected and other bidirectional associative memory (BAM) models of outer-product type that require O(N(2)) complex interconnections with weight strength ranging between +/-M. It is shown that it is functionally equivalent to and possesses all attributes of a BAM of outer-product type, and yet it is simple and robust in structure, very large scale integration (VLSI), optical and nanotechnology realisable, modular and expandable neural network bidirectional associative memory model in which the addition or deletion of a pair of vectors does not require changes in the strength of interconnections of the entire memory matrix. The analysis of retrieval process, signal-to-noise ratio, storage capacity and stability of the proposed model as well as of the traditional BAM has been carried out. Constraints on and characteristics of unipolar and bipolar binaries for improved storage and retrieval are discussed. The simulation results show that it has log(e) N times higher storage capacity, superior performance, faster convergence and retrieval time, when compared to traditional sequential and intraconnected bidirectional memories.

Coherent Optical Memory with High Storage Efficiency and Large Fractional Delay

NASA Astrophysics Data System (ADS)

Chen, Yi-Hsin; Lee, Meng-Jung; Wang, I.-Chung; Du, Shengwang; Chen, Yong-Fan; Chen, Ying-Cheng; Yu, Ite A.

2013-02-01

A high-storage efficiency and long-lived quantum memory for photons is an essential component in long-distance quantum communication and optical quantum computation. Here, we report a 78% storage efficiency of light pulses in a cold atomic medium based on the effect of electromagnetically induced transparency. At 50% storage efficiency, we obtain a fractional delay of 74, which is the best up-to-date record. The classical fidelity of the recalled pulse is better than 90% and nearly independent of the storage time, as confirmed by the direct measurement of phase evolution of the output light pulse with a beat-note interferometer. Such excellent phase coherence between the stored and recalled light pulses suggests that the current result may be readily applied to single photon wave packets. Our work significantly advances the technology of electromagnetically induced transparency-based optical memory and may find practical applications in long-distance quantum communication and optical quantum computation.

Coherent optical memory with high storage efficiency and large fractional delay.

PubMed

Chen, Yi-Hsin; Lee, Meng-Jung; Wang, I-Chung; Du, Shengwang; Chen, Yong-Fan; Chen, Ying-Cheng; Yu, Ite A

2013-02-22

A high-storage efficiency and long-lived quantum memory for photons is an essential component in long-distance quantum communication and optical quantum computation. Here, we report a 78% storage efficiency of light pulses in a cold atomic medium based on the effect of electromagnetically induced transparency. At 50% storage efficiency, we obtain a fractional delay of 74, which is the best up-to-date record. The classical fidelity of the recalled pulse is better than 90% and nearly independent of the storage time, as confirmed by the direct measurement of phase evolution of the output light pulse with a beat-note interferometer. Such excellent phase coherence between the stored and recalled light pulses suggests that the current result may be readily applied to single photon wave packets. Our work significantly advances the technology of electromagnetically induced transparency-based optical memory and may find practical applications in long-distance quantum communication and optical quantum computation.

The Development of Memory Efficiency and Value-Directed Remembering Across the Lifespan: A Cross-Sectional Study of Memory and Selectivity

PubMed Central

Castel, Alan D.; Humphreys, Kathryn L.; Lee, Steve S.; Galván, Adriana; Balota, David A.; McCabe, David P.

2012-01-01

Although attentional control and memory change considerably across the lifespan, no research has examined how the ability to strategically remember important information (i.e., value-directed remembering) changes from childhood to old age. The present study examined this in different age groups across the lifespan (N=320, 5 to 96 years old). We employed a selectivity task where participants were asked to study and recall items worth different point values in order to maximize their point score. This procedure allowed for measures of memory quantity/capacity (number of words recalled) and memory efficiency/selectivity (the recall of high-value items relative to low-value items). Age-related differences were found for memory capacity, as young adults recalled more words than the other groups. However, in terms of selectivity, younger and older adults were more selective than adolescents and children. The dissociation between these measures across the lifespan illustrates important age-related differences in terms of memory capacity and the ability to selectively remember high-value information. PMID:21942664

The development of memory efficiency and value-directed remembering across the life span: a cross-sectional study of memory and selectivity.

PubMed

Castel, Alan D; Humphreys, Kathryn L; Lee, Steve S; Galván, Adriana; Balota, David A; McCabe, David P

2011-11-01

Although attentional control and memory change considerably across the life span, no research has examined how the ability to strategically remember important information (i.e., value-directed remembering) changes from childhood to old age. The present study examined this in different age groups across the life span (N = 320, 5-96 years old). A selectivity task was used in which participants were asked to study and recall items worth different point values in order to maximize their point score. This procedure allowed for measures of memory quantity/capacity (number of words recalled) and memory efficiency/selectivity (the recall of high-value items relative to low-value items). Age-related differences were found for memory capacity, as young adults recalled more words than the other groups. However, in terms of selectivity, younger and older adults were more selective than adolescents and children. The dissociation between these measures across the life span illustrates important age-related differences in terms of memory capacity and the ability to selectively remember high-value information.

Blanket Gate Would Address Blocks Of Memory

NASA Technical Reports Server (NTRS)

Lambe, John; Moopenn, Alexander; Thakoor, Anilkumar P.

1988-01-01

Circuit-chip area used more efficiently. Proposed gate structure selectively allows and restricts access to blocks of memory in electronic neural-type network. By breaking memory into independent blocks, gate greatly simplifies problem of reading from and writing to memory. Since blocks not used simultaneously, share operational amplifiers that prompt and read information stored in memory cells. Fewer operational amplifiers needed, and chip area occupied reduced correspondingly. Cost per bit drops as result.

Memory Efficient Ranking.

ERIC Educational Resources Information Center

Moffat, Alistair; And Others

1994-01-01

Describes an approximate document ranking process that uses a compact array of in-memory, low-precision approximations for document length. Combined with another rule for reducing the memory required by partial similarity accumulators, the approximation heuristic allows the ranking of large document collections using less than one byte of memory…

Molecular Mechanisms Underlying Formation of Long-Term Reward Memories and Extinction Memories in the Honeybee ("Apis Mellifera")

ERIC Educational Resources Information Center

Eisenhardt, Dorothea

2014-01-01

The honeybee ("Apis mellifera") has long served as an invertebrate model organism for reward learning and memory research. Its capacity for learning and memory formation is rooted in the ecological need to efficiently collect nectar and pollen during summer to ensure survival of the hive during winter. Foraging bees learn to associate a…

Efficiency at rest: magnetoencephalographic resting-state connectivity and individual differences in verbal working memory.

PubMed

del Río, David; Cuesta, Pablo; Bajo, Ricardo; García-Pacios, Javier; López-Higes, Ramón; del-Pozo, Francisco; Maestú, Fernando

2012-11-01

Inter-individual differences in cognitive performance are based on an efficient use of task-related brain resources. However, little is known yet on how these differences might be reflected on resting-state brain networks. Here we used Magnetoencephalography resting-state recordings to assess the relationship between a behavioral measurement of verbal working memory and functional connectivity as measured through Mutual Information. We studied theta (4-8 Hz), low alpha (8-10 Hz), high alpha (10-13 Hz), low beta (13-18 Hz) and high beta (18-30 Hz) frequency bands. A higher verbal working memory capacity was associated with a lower mutual information in the low alpha band, prominently among right-anterior and left-lateral sensors. The results suggest that an efficient brain organization in the domain of verbal working memory might be related to a lower resting-state functional connectivity across large-scale brain networks possibly involving right prefrontal and left perisylvian areas. Copyright © 2012 Elsevier B.V. All rights reserved.

Generalized enhanced suffix array construction in external memory.

PubMed

Louza, Felipe A; Telles, Guilherme P; Hoffmann, Steve; Ciferri, Cristina D A

2017-01-01

Suffix arrays, augmented by additional data structures, allow solving efficiently many string processing problems. The external memory construction of the generalized suffix array for a string collection is a fundamental task when the size of the input collection or the data structure exceeds the available internal memory. In this article we present and analyze [Formula: see text] [introduced in CPM (External memory generalized suffix and [Formula: see text] arrays construction. In: Proceedings of CPM. pp 201-10, 2013)], the first external memory algorithm to construct generalized suffix arrays augmented with the longest common prefix array for a string collection. Our algorithm relies on a combination of buffers, induced sorting and a heap to avoid direct string comparisons. We performed experiments that covered different aspects of our algorithm, including running time, efficiency, external memory access, internal phases and the influence of different optimization strategies. On real datasets of size up to 24 GB and using 2 GB of internal memory, [Formula: see text] showed a competitive performance when compared to [Formula: see text] and [Formula: see text], which are efficient algorithms for a single string according to the related literature. We also show the effect of disk caching managed by the operating system on our algorithm. The proposed algorithm was validated through performance tests using real datasets from different domains, in various combinations, and showed a competitive performance. Our algorithm can also construct the generalized Burrows-Wheeler transform of a string collection with no additional cost except by the output time.

A wearable multiplexed silicon nonvolatile memory array using nanocrystal charge confinement

PubMed Central

Kim, Jaemin; Son, Donghee; Lee, Mincheol; Song, Changyeong; Song, Jun-Kyul; Koo, Ja Hoon; Lee, Dong Jun; Shim, Hyung Joon; Kim, Ji Hoon; Lee, Minbaek; Hyeon, Taeghwan; Kim, Dae-Hyeong

2016-01-01

Strategies for efficient charge confinement in nanocrystal floating gates to realize high-performance memory devices have been investigated intensively. However, few studies have reported nanoscale experimental validations of charge confinement in closely packed uniform nanocrystals and related device performance characterization. Furthermore, the system-level integration of the resulting devices with wearable silicon electronics has not yet been realized. We introduce a wearable, fully multiplexed silicon nonvolatile memory array with nanocrystal floating gates. The nanocrystal monolayer is assembled over a large area using the Langmuir-Blodgett method. Efficient particle-level charge confinement is verified with the modified atomic force microscopy technique. Uniform nanocrystal charge traps evidently improve the memory window margin and retention performance. Furthermore, the multiplexing of memory devices in conjunction with the amplification of sensor signals based on ultrathin silicon nanomembrane circuits in stretchable layouts enables wearable healthcare applications such as long-term data storage of monitored heart rates. PMID:26763827

A wearable multiplexed silicon nonvolatile memory array using nanocrystal charge confinement.

PubMed

Kim, Jaemin; Son, Donghee; Lee, Mincheol; Song, Changyeong; Song, Jun-Kyul; Koo, Ja Hoon; Lee, Dong Jun; Shim, Hyung Joon; Kim, Ji Hoon; Lee, Minbaek; Hyeon, Taeghwan; Kim, Dae-Hyeong

2016-01-01

Strategies for efficient charge confinement in nanocrystal floating gates to realize high-performance memory devices have been investigated intensively. However, few studies have reported nanoscale experimental validations of charge confinement in closely packed uniform nanocrystals and related device performance characterization. Furthermore, the system-level integration of the resulting devices with wearable silicon electronics has not yet been realized. We introduce a wearable, fully multiplexed silicon nonvolatile memory array with nanocrystal floating gates. The nanocrystal monolayer is assembled over a large area using the Langmuir-Blodgett method. Efficient particle-level charge confinement is verified with the modified atomic force microscopy technique. Uniform nanocrystal charge traps evidently improve the memory window margin and retention performance. Furthermore, the multiplexing of memory devices in conjunction with the amplification of sensor signals based on ultrathin silicon nanomembrane circuits in stretchable layouts enables wearable healthcare applications such as long-term data storage of monitored heart rates.

Efficiency Enhancement in DC Pulsed Gas Discharge Memory Panel

NASA Astrophysics Data System (ADS)

Okamoto, Yukio

1983-01-01

Much improvement in the luminous efficiency of a dc pulsed gas discharge memory panel for color TV display was achieved by shortening the sustaining pulse duration. High energy electrons can thus be produced in the pulsed discharge with fast rise times. Calculated optimum value of E/P in a Xe gas discharge is 7-8 V/cm\\cdotTorr.

On the predictability of extreme events in records with linear and nonlinear long-range memory: Efficiency and noise robustness

NASA Astrophysics Data System (ADS)

Bogachev, Mikhail I.; Bunde, Armin

2011-06-01

We study the predictability of extreme events in records with linear and nonlinear long-range memory in the presence of additive white noise using two different approaches: (i) the precursory pattern recognition technique (PRT) that exploits solely the information about short-term precursors, and (ii) the return interval approach (RIA) that exploits long-range memory incorporated in the elapsed time after the last extreme event. We find that the PRT always performs better when only linear memory is present. In the presence of nonlinear memory, both methods demonstrate comparable efficiency in the absence of white noise. When additional white noise is present in the record (which is the case in most observational records), the efficiency of the PRT decreases monotonously with increasing noise level. In contrast, the RIA shows an abrupt transition between a phase of low level noise where the prediction is as good as in the absence of noise, and a phase of high level noise where the prediction becomes poor. In the phase of low and intermediate noise the RIA predicts considerably better than the PRT, which explains our recent findings in physiological and financial records.

Incidental recall on WAIS-R digit symbol discriminates Alzheimer's and Parkinson's diseases.

PubMed

Demakis, G J; Sawyer, T P; Fritz, D; Sweet, J J

2001-03-01

The purpose of this study was to examine how Alzheimer's (n = 37) and Parkinson's (n = 21) patients perform on the incidental recall adaptation to the Digit Symbol of the Wechsler Adult Intelligence Scale-Revised (WAIS-R) and how such performance is related to established cognitive efficiency and memory measures. This adaptation requires the examinee to complete the entire subtest and then, without warning, to immediately recall the symbols associated with each number. Groups did not differ significantly on standard Digit Symbol administration (90 seconds), but on recall Parkinson's patients recalled significantly more symbols and symbol-number pairs than Alzheimer's patients. Using only the number of symbols recalled, discriminate function analysis correctly classified 76% of these patients. Correlations between age-corrected scaled score, symbols incidentally recalled, and established measures of cognitive efficiency and memory provided evidence of convergent and divergent validity. Age-corrected scaled scores were more consistently and strongly related to cognitive efficiency, whereas symbols recalled were more consistently and strongly related to memory measures. These findings suggest that the Digit Symbol recall adaptation is actually assessing memory and that it can be another useful way to detect memory impairment. Copyright 2001 John Wiley & Sons, Inc.

Simple and Efficient Single Photon Filter for a Rb-based Quantum Memory

NASA Astrophysics Data System (ADS)

Stack, Daniel; Li, Xiao; Quraishi, Qudsia

2015-05-01

Distribution of entangled quantum states over significant distances is important to the development of future quantum technologies such as long-distance cryptography, networks of atomic clocks, distributed quantum computing, etc. Long-lived quantum memories and single photons are building blocks for systems capable of realizing such applications. The ability to store and retrieve quantum information while filtering unwanted light signals is critical to the operation of quantum memories based on neutral-atom ensembles. We report on an efficient frequency filter which uses a glass cell filled with 85Rb vapor to attenuate noise photons by an order of magnitude with little loss to the single photons associated with the operation of our cold 87Rb quantum memory. An Ar buffer gas is required to differentiate between signal and noise photons or similar statement. Our simple, passive filter requires no optical pumping or external frequency references and provides an additional 18 dB attenuation of our pump laser for every 1 dB loss of the single photon signal. We observe improved non-classical correlations and our data shows that the addition of a frequency filter increases the non-classical correlations and readout efficiency of our quantum memory by ~ 35%.

Aging, Memory Efficiency and the Strategic Control of Attention at Encoding: Impairments of Value-Directed Remembering in Alzheimer's Disease

PubMed Central

Castel, Alan D.; Balota, David A.; McCabe, David P.

2009-01-01

Selecting what is important to remember, attending to this information, and then later recalling it can be thought of in terms of the strategic control of attention and the efficient use of memory. In order to examine whether aging and Alzheimer's disease (AD) influenced this ability, the present study used a selectivity task, where studied items were worth various point values and participants were asked to maximize the value of the items they recalled. Relative to younger adults (N=35) and healthy older adults (N=109), individuals with very mild AD (N=41) and mild AD (N=13) showed impairments in the strategic and efficient encoding and recall of high value items. Although individuals with AD recalled more high value items than low value items, they did not efficiently maximize memory performance (as measured by a selectivity index) relative to healthy older adults. Performance on complex working memory span tasks was related to the recall of the high value items but not low value items. This pattern suggests that relative to healthy aging, AD leads to impairments in strategic control at encoding and value-directed remembering. PMID:19413444

DANoC: An Efficient Algorithm and Hardware Codesign of Deep Neural Networks on Chip.

PubMed

Zhou, Xichuan; Li, Shengli; Tang, Fang; Hu, Shengdong; Lin, Zhi; Zhang, Lei

2017-07-18

Deep neural networks (NNs) are the state-of-the-art models for understanding the content of images and videos. However, implementing deep NNs in embedded systems is a challenging task, e.g., a typical deep belief network could exhaust gigabytes of memory and result in bandwidth and computational bottlenecks. To address this challenge, this paper presents an algorithm and hardware codesign for efficient deep neural computation. A hardware-oriented deep learning algorithm, named the deep adaptive network, is proposed to explore the sparsity of neural connections. By adaptively removing the majority of neural connections and robustly representing the reserved connections using binary integers, the proposed algorithm could save up to 99.9% memory utility and computational resources without undermining classification accuracy. An efficient sparse-mapping-memory-based hardware architecture is proposed to fully take advantage of the algorithmic optimization. Different from traditional Von Neumann architecture, the deep-adaptive network on chip (DANoC) brings communication and computation in close proximity to avoid power-hungry parameter transfers between on-board memory and on-chip computational units. Experiments over different image classification benchmarks show that the DANoC system achieves competitively high accuracy and efficiency comparing with the state-of-the-art approaches.

Age Differences in the Effects of Domain Knowledge on Reading Efficiency

PubMed Central

Miller, Lisa M. Soederberg

2009-01-01

The present study investigated age differences in the effects of knowledge on the efficiency with which information is processed while reading. Individuals between 18 and 85 years of age, with varying levels of cooking knowledge, read and recalled a series of short passages within the domain of cooking. Reading efficiency was operationalized as time spent reading divided by the amount recalled for each passage. Results showed that reading efficiency increased with increasing levels of knowledge among older but not younger adults. Similarly, those with smaller working memory capacities showed increasing efficiency with increasing knowledge. These findings suggest that knowledge promotes a more efficient allocation policy which is particularly helpful in later life, perhaps due to age-related declines in working memory capacity. PMID:19290738

Learning and memory performance in a cohort of clinically referred breast cancer survivors: the role of attention versus forgetting in patient-reported memory complaints.

PubMed

Root, James C; Ryan, Elizabeth; Barnett, Gregory; Andreotti, Charissa; Bolutayo, Kemi; Ahles, Tim

2015-05-01

While forgetfulness is widely reported by breast cancer survivors, studies documenting objective memory performance yield mixed, largely inconsistent, results. Failure to find consistent, objective memory issues may be due to the possibility that cancer survivors misattribute their experience of forgetfulness to primary memory issues rather than to difficulties in attention at the time of learning. To clarify potential attention issues, factor scores for Attention Span, Learning Efficiency, Delayed Memory, and Inaccurate Memory were analyzed for the California Verbal Learning Test-Second Edition (CVLT-II) in 64 clinically referred breast cancer survivors with self-reported cognitive complaints; item analysis was conducted to clarify specific contributors to observed effects, and contrasts between learning and recall trials were compared with normative data. Performance on broader cognitive domains is also reported. The Attention Span factor, but not Learning Efficiency, Delayed Memory, or Inaccurate Memory factors, was significantly affected in this clinical sample. Contrasts between trials were consistent with normative data and did not indicate greater loss of information over time than in the normative sample. Results of this analysis suggest that attentional dysfunction may contribute to subjective and objective memory complaints in breast cancer survivors. These results are discussed in the context of broader cognitive effects following treatment for clinicians who may see cancer survivors for assessment. Copyright © 2014 John Wiley & Sons, Ltd.

Training of Attentional Filtering, but Not of Memory Storage, Enhances Working Memory Efficiency by Strengthening the Neuronal Gatekeeper Network.

PubMed

Schmicker, Marlen; Schwefel, Melanie; Vellage, Anne-Katrin; Müller, Notger G

2016-04-01

Memory training (MT) in older adults with memory deficits often leads to frustration and, therefore, is usually not recommended. Here, we pursued an alternative approach and looked for transfer effects of 1-week attentional filter training (FT) on working memory performance and its neuronal correlates in young healthy humans. The FT effects were compared with pure MT, which lacked the necessity to filter out irrelevant information. Before and after training, all participants performed an fMRI experiment that included a combined task in which stimuli had to be both filtered based on color and stored in memory. We found that training induced processing changes by biasing either filtering or storage. FT induced larger transfer effects on the untrained cognitive function than MT. FT increased neuronal activity in frontal parts of the neuronal gatekeeper network, which is proposed to hinder irrelevant information from being unnecessarily stored in memory. MT decreased neuronal activity in the BG part of the gatekeeper network but enhanced activity in the parietal storage node. We take these findings as evidence that FT renders working memory more efficient by strengthening the BG-prefrontal gatekeeper network. MT, on the other hand, simply stimulates storage of any kind of information. These findings illustrate a tight connection between working memory and attention, and they may open up new avenues for ameliorating memory deficits in patients with cognitive impairments.

Prevalence of impaired memory in hospitalized adults and associations with in-hospital sleep loss.

PubMed

Calev, Hila; Spampinato, Lisa M; Press, Valerie G; Meltzer, David O; Arora, Vineet M

2015-07-01

Effective inpatient teaching requires intact patient memory, but studies suggest hospitalized adults may have memory deficits. Sleep loss among inpatients could contribute to memory impairment. To assess memory in older hospitalized adults, and to test the association between sleep quantity, sleep quality, and memory, in order to identify a possible contributor to memory deficits in these patients. Prospective cohort study. General medicine and hematology/oncology inpatient wards. Fifty-nine hospitalized adults at least 50 years of age with no diagnosed sleep disorder. Immediate memory and memory after a 24-hour delay were assessed using a word recall and word recognition task from the University of Southern California Repeatable Episodic Memory Test. A vignette-based memory task was piloted as an alternative test more closely resembling discharge instructions. Sleep duration and efficiency overnight in the hospital were measured using actigraphy. Mean immediate recall was 3.8 words out of 15 (standard deviation = 2.1). Forty-nine percent of subjects had poor memory, defined as immediate recall score of 3 or lower. Median immediate recognition was 11 words out of 15 (interquartile range [IQR] = 9-13). Median delayed recall score was 1 word, and median delayed recognition was 10 words (IQR = 8-12). In-hospital sleep duration and efficiency were not significantly associated with memory. The medical vignette score was correlated with immediate recall (r = 0.49, P < 0.01). About half of the inpatients studied had poor memory while in the hospital, signaling that hospitalization might not be an ideal teachable moment. In-hospital sleep was not associated with memory scores. © 2015 Society of Hospital Medicine.

Prevalence of Impaired Memory in Hospitalized Adults and Associations with In-Hospital Sleep Loss

PubMed Central

Calev, Hila; Spampinato, Lisa M; Press, Valerie G; Meltzer, David O; Arora, Vineet M

2015-01-01

Background Effective inpatient teaching requires intact patient memory, but studies suggest hospitalized adults may have memory deficits. Sleep loss among inpatients could contribute to memory impairment. Objective To assess memory in older hospitalized adults, and to test the association between sleep quantity, sleep quality and memory, in order to identify a possible contributor to memory deficits in these patients. Design Prospective cohort study Setting General medicine and hematology/oncology inpatient wards Patients 59 hospitalized adults at least 50 years of age with no diagnosed sleep disorder. Measurements Immediate memory and memory after a 24-hour delay were assessed using a word recall and word recognition task from the University of Southern California Repeatable Episodic Memory Test (USC-REMT). A vignette-based memory task was piloted as an alternative test more closely resembling discharge instructions. Sleep duration and efficiency overnight in the hospital were measured using actigraphy. Results Mean immediate recall was 3.8 words out of 15 (SD=2.1). Forty-nine percent of subjects had poor memory, defined as immediate recall score of 3 or lower. Median immediate recognition was 11 words out of 15 (IQR=9, 13). Median delayed recall score was 1 word and median delayed recognition was 10 words (IQR= 8–12). In-hospital sleep duration and efficiency were not significantly associated with memory. The medical vignette score was correlated with immediate recall (r=0.49, p<0.01) Conclusions About half of inpatients studied had poor memory while in the hospital, signaling that hospitalization might not be an ideal teachable moment. In-hospital sleep was not associated with memory scores. PMID:25872763

Recurrent Neural Networks With Auxiliary Memory Units.

PubMed

Wang, Jianyong; Zhang, Lei; Guo, Quan; Yi, Zhang

2018-05-01

Memory is one of the most important mechanisms in recurrent neural networks (RNNs) learning. It plays a crucial role in practical applications, such as sequence learning. With a good memory mechanism, long term history can be fused with current information, and can thus improve RNNs learning. Developing a suitable memory mechanism is always desirable in the field of RNNs. This paper proposes a novel memory mechanism for RNNs. The main contributions of this paper are: 1) an auxiliary memory unit (AMU) is proposed, which results in a new special RNN model (AMU-RNN), separating the memory and output explicitly and 2) an efficient learning algorithm is developed by employing the technique of error flow truncation. The proposed AMU-RNN model, together with the developed learning algorithm, can learn and maintain stable memory over a long time range. This method overcomes both the learning conflict problem and gradient vanishing problem. Unlike the traditional method, which mixes the memory and output with a single neuron in a recurrent unit, the AMU provides an auxiliary memory neuron to maintain memory in particular. By separating the memory and output in a recurrent unit, the problem of learning conflicts can be eliminated easily. Moreover, by using the technique of error flow truncation, each auxiliary memory neuron ensures constant error flow during the learning process. The experiments demonstrate good performance of the proposed AMU-RNNs and the developed learning algorithm. The method exhibits quite efficient learning performance with stable convergence in the AMU-RNN learning and outperforms the state-of-the-art RNN models in sequence generation and sequence classification tasks.

Working Memory Capacity and Recall from Long-Term Memory: Examining the Influences of Encoding Strategies, Study Time Allocation, Search Efficiency, and Monitoring Abilities

ERIC Educational Resources Information Center

Unsworth, Nash

2016-01-01

The relation between working memory capacity (WMC) and recall from long-term memory (LTM) was examined in the current study. Participants performed multiple measures of delayed free recall varying in presentation duration and self-reported their strategy usage after each task. Participants also performed multiple measures of WMC. The results…

Working Memory Intervention: A Reading Comprehension Approach

ERIC Educational Resources Information Center

Perry, Tracy L.; Malaia, Evguenia

2013-01-01

For any complex mental task, people rely on working memory. Working memory capacity (WMC) is one predictor of success in learning. Historically, attempts to improve verbal WM through training have not been effective. This study provided elementary students with WM consolidation efficiency training to answer the question, Can reading comprehension…

Neural Correlates of Prospective Memory across the Lifespan

ERIC Educational Resources Information Center

Zollig, Jacqueline; West, Robert; Martin, Mike; Altgassen, Mareike; Lemke, Ulrike; Kliegel, Matthias

2007-01-01

Overview: Behavioural data reveal an inverted U-shaped function in the efficiency of prospective memory from childhood to young adulthood to later adulthood. However, prior research has not directly compared processes contributing to age-related variation in prospective memory across the lifespan, hence it is unclear whether the same factors…

Selective scanpath repetition during memory-guided visual search.

PubMed

Wynn, Jordana S; Bone, Michael B; Dragan, Michelle C; Hoffman, Kari L; Buchsbaum, Bradley R; Ryan, Jennifer D

2016-01-02

Visual search efficiency improves with repetition of a search display, yet the mechanisms behind these processing gains remain unclear. According to Scanpath Theory, memory retrieval is mediated by repetition of the pattern of eye movements or "scanpath" elicited during stimulus encoding. Using this framework, we tested the prediction that scanpath recapitulation reflects relational memory guidance during repeated search events. Younger and older subjects were instructed to find changing targets within flickering naturalistic scenes. Search efficiency (search time, number of fixations, fixation duration) and scanpath similarity (repetition) were compared across age groups for novel (V1) and repeated (V2) search events. Younger adults outperformed older adults on all efficiency measures at both V1 and V2, while the search time benefit for repeated viewing (V1-V2) did not differ by age. Fixation-binned scanpath similarity analyses revealed repetition of initial and final (but not middle) V1 fixations at V2, with older adults repeating more initial V1 fixations than young adults. In young adults only, early scanpath similarity correlated negatively with search time at test, indicating increased efficiency, whereas the similarity of V2 fixations to middle V1 fixations predicted poor search performance. We conclude that scanpath compression mediates increased search efficiency by selectively recapitulating encoding fixations that provide goal-relevant input. Extending Scanpath Theory, results suggest that scanpath repetition varies as a function of time and memory integrity.

Memory capacity, selective control, and value-directed remembering in children with and without attention-deficit/hyperactivity disorder (ADHD).

PubMed

Castel, Alan D; Lee, Steve S; Humphreys, Kathryn L; Moore, Amy N

2011-01-01

The ability to select what is important to remember, to attend to this information, and to recall high-value items leads to the efficient use of memory. The present study examined how children with and without attention-deficit/hyperactivity disorder (ADHD) performed on an incentive-based selectivity task in which to-be-remembered items were worth different point values. Participants were 6-9 year old children with ADHD (n = 57) and without ADHD (n = 59). Using a selectivity task, participants studied words paired with point values and were asked to maximize their score, which was the overall value of the items they recalled. This task allows for measures of memory capacity and the ability to selectively remember high-value items. Although there were no significant between-groups differences in the number of words recalled (memory capacity), children with ADHD were less selective than children in the control group in terms of the value of the items they recalled (control of memory). All children recalled more high-value items than low-value items and showed some learning with task experience, but children with ADHD Combined type did not efficiently maximize memory performance (as measured by a selectivity index) relative to children with ADHD Inattentive type and healthy controls, who did not differ significantly from one another. Children with ADHD Combined type exhibit impairments in the strategic and efficient encoding and recall of high-value items. The findings have implications for theories of memory dysfunction in childhood ADHD and the key role of metacognition, cognitive control, and value-directed remembering when considering the strategic use of memory. (c) 2010 APA, all rights reserved

Large efficiency at telecom wavelength for optical quantum memories.

PubMed

Dajczgewand, Julián; Le Gouët, Jean-Louis; Louchet-Chauvet, Anne; Chanelière, Thierry

2014-05-01

We implement the ROSE protocol in an erbium-doped solid, compatible with the telecom range. The ROSE scheme is an adaptation of the standard two-pulse photon echo to make it suitable for a quantum memory. We observe a retrieval efficiency of 40% for a weak laser pulse in the forward direction by using specific orientations of the light polarizations, magnetic field, and crystal axes.

Feasibility study of current pulse induced 2-bit/4-state multilevel programming in phase-change memory

NASA Astrophysics Data System (ADS)

Liu, Yan; Fan, Xi; Chen, Houpeng; Wang, Yueqing; Liu, Bo; Song, Zhitang; Feng, Songlin

2017-08-01

In this brief, multilevel data storage for phase-change memory (PCM) has attracted more attention in the memory market to implement high capacity memory system and reduce cost-per-bit. In this work, we present a universal programing method of SET stair-case current pulse in PCM cells, which can exploit the optimum programing scheme to achieve 2-bit/ 4state resistance-level with equal logarithm interval. SET stair-case waveform can be optimized by TCAD real time simulation to realize multilevel data storage efficiently in an arbitrary phase change material. Experimental results from 1 k-bit PCM test-chip have validated the proposed multilevel programing scheme. This multilevel programming scheme has improved the information storage density, robustness of resistance-level, energy efficient and avoiding process complexity.

Enabling the High Level Synthesis of Data Analytics Accelerators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Minutoli, Marco; Castellana, Vito G.; Tumeo, Antonino

Conventional High Level Synthesis (HLS) tools mainly tar- get compute intensive kernels typical of digital signal pro- cessing applications. We are developing techniques and ar- chitectural templates to enable HLS of data analytics appli- cations. These applications are memory intensive, present fine-grained, unpredictable data accesses, and irregular, dy- namic task parallelism. We discuss an architectural tem- plate based around a distributed controller to efficiently ex- ploit thread level parallelism. We present a memory in- terface that supports parallel memory subsystems and en- ables implementing atomic memory operations. We intro- duce a dynamic task scheduling approach to efficiently ex- ecute heavilymore » unbalanced workload. The templates are val- idated by synthesizing queries from the Lehigh University Benchmark (LUBM), a well know SPARQL benchmark.« less

Research about Memory Detection Based on the Embedded Platform

NASA Astrophysics Data System (ADS)

Sun, Hao; Chu, Jian

As is known to us all, the resources of memory detection of the embedded systems are very limited. Taking the Linux-based embedded arm as platform, this article puts forward two efficient memory detection technologies according to the characteristics of the embedded software. Especially for the programs which need specific libraries, the article puts forwards portable memory detection methods to help program designers to reduce human errors,improve programming quality and therefore make better use of the valuable embedded memory resource.

Memory management in genome-wide association studies

PubMed Central

2009-01-01

Genome-wide association is a powerful tool for the identification of genes that underlie common diseases. Genome-wide association studies generate billions of genotypes and pose significant computational challenges for most users including limited computer memory. We applied a recently developed memory management tool to two analyses of North American Rheumatoid Arthritis Consortium studies and measured the performance in terms of central processing unit and memory usage. We conclude that our memory management approach is simple, efficient, and effective for genome-wide association studies. PMID:20018047

The Cognitive Bases of Intelligence Analysis.

DTIC Science & Technology

1984-01-01

the truth of a single proposition or to discriminate among several propositions. Indicators represent the potentially observable events that form the ...serves as a checklist against which to evaluate an actual Intelligance product. * If the Ideal product Is specified In sufficient detail for a particular...34 Interf’arence In accessing memory occurs for both recognition and recall. Memory retrieval is most efficient when the memories are discriminable . Memories for

Representational constraints on the development of memory and metamemory: a developmental-representational theory.

PubMed

Ceci, Stephen J; Fitneva, Stanka A; Williams, Wendy M

2010-04-01

Traditional accounts of memory development suggest that maturation of prefrontal cortex (PFC) enables efficient metamemory, which enhances memory. An alternative theory is described, in which changes in early memory and metamemory are mediated by representational changes, independent of PFC maturation. In a pilot study and Experiment 1, younger children failed to recognize previously presented pictures, yet the children could identify the context in which they occurred, suggesting these failures resulted from inefficient metamemory. Older children seldom exhibited such failure. Experiment 2 established that this was not due to retrieval-time recoding. Experiment 3 suggested that young children's representation of a picture's attributes explained their metamemory failure. Experiment 4 demonstrated that metamemory is age-invariant when representational quality is controlled: When stimuli were equivalently represented, age differences in memory and metamemory declined. These findings do not support the traditional view that as children develop, neural maturation permits more efficient monitoring, which leads to improved memory. These findings support a theory based on developmental-representational synthesis, in which constraints on metamemory are independent of neurological development; representational features drive early memory to a greater extent than previously acknowledged, suggesting that neural maturation has been overimputed as a source of early metamemory and memory failure. PsycINFO Database Record (c) 2010 APA, all rights reserved.

Processing efficiency theory in children: working memory as a mediator between trait anxiety and academic performance.

PubMed

Owens, Matthew; Stevenson, Jim; Norgate, Roger; Hadwin, Julie A

2008-10-01

Working memory skills are positively associated with academic performance. In contrast, high levels of trait anxiety are linked with educational underachievement. Based on Eysenck and Calvo's (1992) processing efficiency theory (PET), the present study investigated whether associations between anxiety and educational achievement were mediated via poor working memory performance. Fifty children aged 11-12 years completed verbal (backwards digit span; tapping the phonological store/central executive) and spatial (Corsi blocks; tapping the visuospatial sketchpad/central executive) working memory tasks. Trait anxiety was measured using the State-Trait Anxiety Inventory for Children. Academic performance was assessed using school administered tests of reasoning (Cognitive Abilities Test) and attainment (Standard Assessment Tests). The results showed that the association between trait anxiety and academic performance was significantly mediated by verbal working memory for three of the six academic performance measures (math, quantitative and non-verbal reasoning). Spatial working memory did not significantly mediate the relationship between trait anxiety and academic performance. On average verbal working memory accounted for 51% of the association between trait anxiety and academic performance, while spatial working memory only accounted for 9%. The findings indicate that PET is a useful framework to assess the impact of children's anxiety on educational achievement.

Efficient Parallelization of a Dynamic Unstructured Application on the Tera MTA

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Biswas, Rupak

1999-01-01

The success of parallel computing in solving real-life computationally-intensive problems relies on their efficient mapping and execution on large-scale multiprocessor architectures. Many important applications are both unstructured and dynamic in nature, making their efficient parallel implementation a daunting task. This paper presents the parallelization of a dynamic unstructured mesh adaptation algorithm using three popular programming paradigms on three leading supercomputers. We examine an MPI message-passing implementation on the Cray T3E and the SGI Origin2OOO, a shared-memory implementation using cache coherent nonuniform memory access (CC-NUMA) of the Origin2OOO, and a multi-threaded version on the newly-released Tera Multi-threaded Architecture (MTA). We compare several critical factors of this parallel code development, including runtime, scalability, programmability, and memory overhead. Our overall results demonstrate that multi-threaded systems offer tremendous potential for quickly and efficiently solving some of the most challenging real-life problems on parallel computers.

Statistical Learning Induces Discrete Shifts in the Allocation of Working Memory Resources

ERIC Educational Resources Information Center

Umemoto, Akina; Scolari, Miranda; Vogel, Edward K.; Awh, Edward

2010-01-01

Observers can voluntarily select which items are encoded into working memory, and the efficiency of this process strongly predicts memory capacity. Nevertheless, the present work suggests that voluntary intentions do not exclusively determine what is encoded into this online workspace. Observers indicated whether any items from a briefly stored…

NAS Applications and Advanced Algorithms

NASA Technical Reports Server (NTRS)

Bailey, David H.; Biswas, Rupak; VanDerWijngaart, Rob; Kutler, Paul (Technical Monitor)

1997-01-01

This paper examines the applications most commonly run on the supercomputers at the Numerical Aerospace Simulation (NAS) facility. It analyzes the extent to which such applications are fundamentally oriented to vector computers, and whether or not they can be efficiently implemented on hierarchical memory machines, such as systems with cache memories and highly parallel, distributed memory systems.

Aging Memory Is "Not" a Limiting Factor for Lifelong Learning

ERIC Educational Resources Information Center

Lalovic, Dejan; Gvozdenovic, Vasilije

2015-01-01

Efficient memory is one of the necessary cognitive potentials required for virtually every form of lifelong learning. In this contribution we first briefly review and summarize state of the art of knowledge on memory and related cognitive functions in normal aging. Then we critically discuss a relatively short inventory of clinical, psychometric,…

Cache write generate for parallel image processing on shared memory architectures.

PubMed

Wittenbrink, C M; Somani, A K; Chen, C H

1996-01-01

We investigate cache write generate, our cache mode invention. We demonstrate that for parallel image processing applications, the new mode improves main memory bandwidth, CPU efficiency, cache hits, and cache latency. We use register level simulations validated by the UW-Proteus system. Many memory, cache, and processor configurations are evaluated.

Kinetic energy classification and smoothing for compact B-spline basis sets in quantum Monte Carlo

DOE PAGES

Krogel, Jaron T.; Reboredo, Fernando A.

2018-01-25

Quantum Monte Carlo calculations of defect properties of transition metal oxides have become feasible in recent years due to increases in computing power. As the system size has grown, availability of on-node memory has become a limiting factor. Saving memory while minimizing computational cost is now a priority. The main growth in memory demand stems from the B-spline representation of the single particle orbitals, especially for heavier elements such as transition metals where semi-core states are present. Despite the associated memory costs, splines are computationally efficient. In this paper, we explore alternatives to reduce the memory usage of splined orbitalsmore » without significantly affecting numerical fidelity or computational efficiency. We make use of the kinetic energy operator to both classify and smooth the occupied set of orbitals prior to splining. By using a partitioning scheme based on the per-orbital kinetic energy distributions, we show that memory savings of about 50% is possible for select transition metal oxide systems. Finally, for production supercells of practical interest, our scheme incurs a performance penalty of less than 5%.« less

Kinetic energy classification and smoothing for compact B-spline basis sets in quantum Monte Carlo

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krogel, Jaron T.; Reboredo, Fernando A.

Quantum Monte Carlo calculations of defect properties of transition metal oxides have become feasible in recent years due to increases in computing power. As the system size has grown, availability of on-node memory has become a limiting factor. Saving memory while minimizing computational cost is now a priority. The main growth in memory demand stems from the B-spline representation of the single particle orbitals, especially for heavier elements such as transition metals where semi-core states are present. Despite the associated memory costs, splines are computationally efficient. In this paper, we explore alternatives to reduce the memory usage of splined orbitalsmore » without significantly affecting numerical fidelity or computational efficiency. We make use of the kinetic energy operator to both classify and smooth the occupied set of orbitals prior to splining. By using a partitioning scheme based on the per-orbital kinetic energy distributions, we show that memory savings of about 50% is possible for select transition metal oxide systems. Finally, for production supercells of practical interest, our scheme incurs a performance penalty of less than 5%.« less

Kinetic energy classification and smoothing for compact B-spline basis sets in quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Krogel, Jaron T.; Reboredo, Fernando A.

2018-01-01

Quantum Monte Carlo calculations of defect properties of transition metal oxides have become feasible in recent years due to increases in computing power. As the system size has grown, availability of on-node memory has become a limiting factor. Saving memory while minimizing computational cost is now a priority. The main growth in memory demand stems from the B-spline representation of the single particle orbitals, especially for heavier elements such as transition metals where semi-core states are present. Despite the associated memory costs, splines are computationally efficient. In this work, we explore alternatives to reduce the memory usage of splined orbitals without significantly affecting numerical fidelity or computational efficiency. We make use of the kinetic energy operator to both classify and smooth the occupied set of orbitals prior to splining. By using a partitioning scheme based on the per-orbital kinetic energy distributions, we show that memory savings of about 50% is possible for select transition metal oxide systems. For production supercells of practical interest, our scheme incurs a performance penalty of less than 5%.

Noise reduction in optically controlled quantum memory

NASA Astrophysics Data System (ADS)

Ma, Lijun; Slattery, Oliver; Tang, Xiao

2018-05-01

Quantum memory is an essential tool for quantum communications systems and quantum computers. An important category of quantum memory, called optically controlled quantum memory, uses a strong classical beam to control the storage and re-emission of a single-photon signal through an atomic ensemble. In this type of memory, the residual light from the strong classical control beam can cause severe noise and degrade the system performance significantly. Efficiently suppressing this noise is a requirement for the successful implementation of optically controlled quantum memories. In this paper, we briefly introduce the latest and most common approaches to quantum memory and review the various noise-reduction techniques used in implementing them.

On the practical efficiency of shape memory engines

NASA Astrophysics Data System (ADS)

McCormick, P. G.

1987-02-01

The effects of non-ideal behavior, i.e., thermal efficiencies less than perfect, on the efficiency of shape memory (SME) engines are analyzed. Account is taken of the temperature hysteresis between the forward and reverse transformation and the finite elastic compliance of the SM element and the engine. The temperature difference produced by a particular stress cycle and necessary to complete the cycle is quantified, along with the temperature penalty which arises from non-ideal behavior. The hysteresis, elastic compliance and low working strains in cycled materials are shown to yield low thermal efficiencies, e.g., 1.95 pct instead of 6.74 pct in the case of a 20 k hysteresis. Heat recycling can theoretically improve the efficiency to about 3.23 pct.

Minimizing the Disruptive Effects of Prospective Memory in Simulated Air Traffic Control

PubMed Central

Loft, Shayne; Smith, Rebekah E.; Remington, Roger

2015-01-01

Prospective memory refers to remembering to perform an intended action in the future. Failures of prospective memory can occur in air traffic control. In two experiments, we examined the utility of external aids for facilitating air traffic management in a simulated air traffic control task with prospective memory requirements. Participants accepted and handed-off aircraft and detected aircraft conflicts. The prospective memory task involved remembering to deviate from a routine operating procedure when accepting target aircraft. External aids that contained details of the prospective memory task appeared and flashed when target aircraft needed acceptance. In Experiment 1, external aids presented either adjacent or non-adjacent to each of the 20 target aircraft presented over the 40min test phase reduced prospective memory error by 11% compared to a condition without external aids. In Experiment 2, only a single target aircraft was presented a significant time (39min–42min) after presentation of the prospective memory instruction, and the external aids reduced prospective memory error by 34%. In both experiments, costs to the efficiency of non-prospective memory air traffic management (non-target aircraft acceptance response time, conflict detection response time) were reduced by non-adjacent aids compared to no aids or adjacent aids. In contrast, in both experiments, the efficiency of the prospective memory air traffic management (target aircraft acceptance response time) was facilitated by adjacent aids compared to non-adjacent aids. Together, these findings have potential implications for the design of automated alerting systems to maximize multi-task performance in work settings where operators monitor and control demanding perceptual displays. PMID:24059825

Progress towards broadband Raman quantum memory in Bose-Einstein condensates

NASA Astrophysics Data System (ADS)

Saglamyurek, Erhan; Hrushevskyi, Taras; Smith, Benjamin; Leblanc, Lindsay

2017-04-01

Optical quantum memories are building blocks for quantum information technologies. Efficient and long-lived storage in combination with high-speed (broadband) operation are key features required for practical applications. While the realization has been a great challenge, Raman memory in Bose-Einstein condensates (BECs) is a promising approach, due to negligible decoherence from diffusion and collisions that leads to seconds-scale memory times, high efficiency due to large atomic density, the possibility for atom-chip integration with micro photonics, and the suitability of the far off-resonant Raman approach with storage of broadband photons (over GHz) [5]. Here we report our progress towards Raman memory in a BEC. We describe our apparatus recently built for producing BEC with 87Rb atoms, and present the observation of nearly pure BEC with 5x105 atoms at 40 nK. After showing our initial characterizations, we discuss the suitability of our system for Raman-based light storage in our BEC.

Distributed Saturation

NASA Technical Reports Server (NTRS)

Chung, Ming-Ying; Ciardo, Gianfranco; Siminiceanu, Radu I.

2007-01-01

The Saturation algorithm for symbolic state-space generation, has been a recent break-through in the exhaustive veri cation of complex systems, in particular globally-asyn- chronous/locally-synchronous systems. The algorithm uses a very compact Multiway Decision Diagram (MDD) encoding for states and the fastest symbolic exploration algo- rithm to date. The distributed version of Saturation uses the overall memory available on a network of workstations (NOW) to efficiently spread the memory load during the highly irregular exploration. A crucial factor in limiting the memory consumption during the symbolic state-space generation is the ability to perform garbage collection to free up the memory occupied by dead nodes. However, garbage collection over a NOW requires a nontrivial communication overhead. In addition, operation cache policies become critical while analyzing large-scale systems using the symbolic approach. In this technical report, we develop a garbage collection scheme and several operation cache policies to help on solving extremely complex systems. Experiments show that our schemes improve the performance of the original distributed implementation, SmArTNow, in terms of time and memory efficiency.

Sleep-Dependent Memory Consolidation and Reconsolidation

PubMed Central

Stickgold, Robert; Walker, Matthew P.

2009-01-01

Molecular, cellular, and systems-level processes convert initial, labile memory representations into more permanent ones, available for continued reactivation and recall over extended periods of time. These processes of memory consolidation and reconsolidation are not all-or-none phenomena, but rather a continuing series of biological adjustments that enhance both the efficiency and utility of stored memories over time. In this chapter, we review the role of sleep in supporting these disparate but related processes. PMID:17470412

A fast sequence assembly method based on compressed data structures.

PubMed

Liang, Peifeng; Zhang, Yancong; Lin, Kui; Hu, Jinglu

2014-01-01

Assembling a large genome using next generation sequencing reads requires large computer memory and a long execution time. To reduce these requirements, a memory and time efficient assembler is presented from applying FM-index in JR-Assembler, called FMJ-Assembler, where FM stand for FMR-index derived from the FM-index and BWT and J for jumping extension. The FMJ-Assembler uses expanded FM-index and BWT to compress data of reads to save memory and jumping extension method make it faster in CPU time. An extensive comparison of the FMJ-Assembler with current assemblers shows that the FMJ-Assembler achieves a better or comparable overall assembly quality and requires lower memory use and less CPU time. All these advantages of the FMJ-Assembler indicate that the FMJ-Assembler will be an efficient assembly method in next generation sequencing technology.

Memory effect, resolution, and efficiency measurements of an Al2O3 coated plastic scintillator used for radioxenon detection

NASA Astrophysics Data System (ADS)

Bläckberg, L.; Fritioff, T.; Mårtensson, L.; Nielsen, F.; Ringbom, A.; Sjöstrand, H.; Klintenberg, M.

2013-06-01

A cylindrical plastic scintillator cell, used for radioxenon monitoring within the verification regime of the Comprehensive Nuclear-Test-Ban Treaty, has been coated with 425 nm Al2O3 using low temperature Atomic Layer Deposition, and its performance has been evaluated. The motivation is to reduce the memory effect caused by radioxenon diffusing into the plastic scintillator material during measurements, resulting in an elevated detection limit. Measurements with the coated detector show both energy resolution and efficiency comparable to uncoated detectors, and a memory effect reduction of a factor of 1000. Provided that the quality of the detector is maintained for a longer period of time, Al2O3 coatings are believed to be a viable solution to the memory effect problem in question.

Multithreaded implicitly dealiased convolutions

NASA Astrophysics Data System (ADS)

Roberts, Malcolm; Bowman, John C.

2018-03-01

Implicit dealiasing is a method for computing in-place linear convolutions via fast Fourier transforms that decouples work memory from input data. It offers easier memory management and, for long one-dimensional input sequences, greater efficiency than conventional zero-padding. Furthermore, for convolutions of multidimensional data, the segregation of data and work buffers can be exploited to reduce memory usage and execution time significantly. This is accomplished by processing and discarding data as it is generated, allowing work memory to be reused, for greater data locality and performance. A multithreaded implementation of implicit dealiasing that accepts an arbitrary number of input and output vectors and a general multiplication operator is presented, along with an improved one-dimensional Hermitian convolution that avoids the loop dependency inherent in previous work. An alternate data format that can accommodate a Nyquist mode and enhance cache efficiency is also proposed.

Hi-Corrector: a fast, scalable and memory-efficient package for normalizing large-scale Hi-C data.

PubMed

Li, Wenyuan; Gong, Ke; Li, Qingjiao; Alber, Frank; Zhou, Xianghong Jasmine

2015-03-15

Genome-wide proximity ligation assays, e.g. Hi-C and its variant TCC, have recently become important tools to study spatial genome organization. Removing biases from chromatin contact matrices generated by such techniques is a critical preprocessing step of subsequent analyses. The continuing decline of sequencing costs has led to an ever-improving resolution of the Hi-C data, resulting in very large matrices of chromatin contacts. Such large-size matrices, however, pose a great challenge on the memory usage and speed of its normalization. Therefore, there is an urgent need for fast and memory-efficient methods for normalization of Hi-C data. We developed Hi-Corrector, an easy-to-use, open source implementation of the Hi-C data normalization algorithm. Its salient features are (i) scalability-the software is capable of normalizing Hi-C data of any size in reasonable times; (ii) memory efficiency-the sequential version can run on any single computer with very limited memory, no matter how little; (iii) fast speed-the parallel version can run very fast on multiple computing nodes with limited local memory. The sequential version is implemented in ANSI C and can be easily compiled on any system; the parallel version is implemented in ANSI C with the MPI library (a standardized and portable parallel environment designed for solving large-scale scientific problems). The package is freely available at http://zhoulab.usc.edu/Hi-Corrector/. © The Author 2014. Published by Oxford University Press.

Working Memory and Processing Efficiency in Children's Reasoning.

ERIC Educational Resources Information Center

Halford, Graeme S.; And Others

A series of studies was conducted to determine whether children's reasoning is capacity-limited and whether any such capacity, if it exists, is based on the working memory system. An N-term series (transitive inference) was used as the primary task in an interference paradigm. A concurrent short-term memory load was employed as the secondary task.…

The Development of Strategy Use in Elementary School Children: Working Memory and Individual Differences

ERIC Educational Resources Information Center

Imbo, Ineke; Vandierendonck, Andre

2007-01-01

The current study tested the development of working memory involvement in children's arithmetic strategy selection and strategy efficiency. To this end, an experiment in which the dual-task method and the choice/no-choice method were combined was administered to 10- to 12-year-olds. Working memory was needed in retrieval, transformation, and…

Compression in Visual Working Memory: Using Statistical Regularities to Form More Efficient Memory Representations

ERIC Educational Resources Information Center

Brady, Timothy F.; Konkle, Talia; Alvarez, George A.

2009-01-01

The information that individuals can hold in working memory is quite limited, but researchers have typically studied this capacity using simple objects or letter strings with no associations between them. However, in the real world there are strong associations and regularities in the input. In an information theoretic sense, regularities…

Word-Decoding Skill Interacts with Working Memory Capacity to Influence Inference Generation during Reading

ERIC Educational Resources Information Center

Hamilton, Stephen; Freed, Erin; Long, Debra L.

2016-01-01

The aim of this study was to examine predictions derived from a proposal about the relation between word-decoding skill and working memory capacity, called verbal efficiency theory. The theory states that poor word representations and slow decoding processes consume resources in working memory that would otherwise be used to execute high-level…

Effects of cacheing on multitasking efficiency and programming strategy on an ELXSI 6400

DOE Office of Scientific and Technical Information (OSTI.GOV)

Montry, G.R.; Benner, R.E.

1985-12-01

The impact of a cache/shared memory architecture, and, in particular, the cache coherency problem, upon concurrent algorithm and program development is discussed. In this context, a simple set of programming strategies are proposed which streamline code development and improve code performance when multitasking in a cache/shared memory or distributed memory environment.

How Quickly They Forget: The Relationship between Forgetting and Working Memory Performance

ERIC Educational Resources Information Center

Bayliss, Donna M.; Jarrold, Christopher

2015-01-01

This study examined the contribution of individual differences in rate of forgetting to variation in working memory performance in children. One hundred and twelve children (mean age 9 years 4 months) completed 2 tasks designed to measure forgetting, as well as measures of working memory, processing efficiency, and short-term storage ability.…

Seven-Year-Olds Allocate Attention Like Adults Unless Working Memory Is Overloaded

ERIC Educational Resources Information Center

Cowan, Nelson; Morey, Candice C.; AuBuchon, Angela M.; Zwilling, Christopher E.; Gilchrist, Amanda L.

2010-01-01

Previous studies have indicated that visual working memory performance increases with age in childhood, but it is not clear why. One main hypothesis has been that younger children are less efficient in their attention; specifically, they are less able to exclude irrelevant items from working memory to make room for relevant items. We examined this…

Appearance of the two-way shape-memory effect in a nitinol spring subjected to temperature and deformation cycling

NASA Astrophysics Data System (ADS)

Manjavidze, A. G.; Barnov, V. A.; Jorjishvili, L. I.; Sobolevskaya, S. V.

2008-03-01

The properties of a cylindrical spiral spring of nitinol (shape-memory alloy) are studied. When this spring is used as a working element in a rotary martensitic engine, the appearance of the two-way shape-memory effect in it is shown to decrease the engine operation efficiency.

Implementation of a parallel unstructured Euler solver on shared and distributed memory architectures

NASA Technical Reports Server (NTRS)

Mavriplis, D. J.; Das, Raja; Saltz, Joel; Vermeland, R. E.

1992-01-01

An efficient three dimensional unstructured Euler solver is parallelized on a Cray Y-MP C90 shared memory computer and on an Intel Touchstone Delta distributed memory computer. This paper relates the experiences gained and describes the software tools and hardware used in this study. Performance comparisons between two differing architectures are made.

Spermidine boosts autophagy to protect from synapse aging.

PubMed

Bhukel, Anuradha; Madeo, Frank; Sigrist, Stephan J

2017-02-01

All animals form memories to adapt their behavior in a context-dependent manner. With increasing age, however, forming new memories becomes less efficient. While synaptic plasticity promotes memory formation, the etiology of age-induced memory formation remained enigmatic. Previous work showed that simple feeding of polyamine spermidine protects from age-induced memory impairment in Drosophila. Most recent work now shows that spermidine operates directly at synapses, allowing for an autophagy-dependent homeostatic regulation of presynaptic specializations. How exactly autophagic regulations intersect with synaptic plasticity should be an interesting subject for future research.

A Memory Efficient Network Encryption Scheme

NASA Astrophysics Data System (ADS)

El-Fotouh, Mohamed Abo; Diepold, Klaus

In this paper, we studied the two widely used encryption schemes in network applications. Shortcomings have been found in both schemes, as these schemes consume either more memory to gain high throughput or low memory with low throughput. The need has aroused for a scheme that has low memory requirements and in the same time possesses high speed, as the number of the internet users increases each day. We used the SSM model [1], to construct an encryption scheme based on the AES. The proposed scheme possesses high throughput together with low memory requirements.

Selective scanpath repetition during memory-guided visual search

PubMed Central

Wynn, Jordana S.; Bone, Michael B.; Dragan, Michelle C.; Hoffman, Kari L.; Buchsbaum, Bradley R.; Ryan, Jennifer D.

2016-01-01

ABSTRACT Visual search efficiency improves with repetition of a search display, yet the mechanisms behind these processing gains remain unclear. According to Scanpath Theory, memory retrieval is mediated by repetition of the pattern of eye movements or “scanpath” elicited during stimulus encoding. Using this framework, we tested the prediction that scanpath recapitulation reflects relational memory guidance during repeated search events. Younger and older subjects were instructed to find changing targets within flickering naturalistic scenes. Search efficiency (search time, number of fixations, fixation duration) and scanpath similarity (repetition) were compared across age groups for novel (V1) and repeated (V2) search events. Younger adults outperformed older adults on all efficiency measures at both V1 and V2, while the search time benefit for repeated viewing (V1–V2) did not differ by age. Fixation-binned scanpath similarity analyses revealed repetition of initial and final (but not middle) V1 fixations at V2, with older adults repeating more initial V1 fixations than young adults. In young adults only, early scanpath similarity correlated negatively with search time at test, indicating increased efficiency, whereas the similarity of V2 fixations to middle V1 fixations predicted poor search performance. We conclude that scanpath compression mediates increased search efficiency by selectively recapitulating encoding fixations that provide goal-relevant input. Extending Scanpath Theory, results suggest that scanpath repetition varies as a function of time and memory integrity. PMID:27570471

Factors affecting reorganisation of memory encoding networks in temporal lobe epilepsy

PubMed Central

Sidhu, M.K.; Stretton, J.; Winston, G.P.; Symms, M.; Thompson, P.J.; Koepp, M.J.; Duncan, J.S.

2015-01-01

Summary Aims In temporal lobe epilepsy (TLE) due to hippocampal sclerosis reorganisation in the memory encoding network has been consistently described. Distinct areas of reorganisation have been shown to be efficient when associated with successful subsequent memory formation or inefficient when not associated with successful subsequent memory. We investigated the effect of clinical parameters that modulate memory functions: age at onset of epilepsy, epilepsy duration and seizure frequency in a large cohort of patients. Methods We studied 53 patients with unilateral TLE and hippocampal sclerosis (29 left). All participants performed a functional magnetic resonance imaging memory encoding paradigm of faces and words. A continuous regression analysis was used to investigate the effects of age at onset of epilepsy, epilepsy duration and seizure frequency on the activation patterns in the memory encoding network. Results Earlier age at onset of epilepsy was associated with left posterior hippocampus activations that were involved in successful subsequent memory formation in left hippocampal sclerosis patients. No association of age at onset of epilepsy was seen with face encoding in right hippocampal sclerosis patients. In both left hippocampal sclerosis patients during word encoding and right hippocampal sclerosis patients during face encoding, shorter duration of epilepsy and lower seizure frequency were associated with medial temporal lobe activations that were involved in successful memory formation. Longer epilepsy duration and higher seizure frequency were associated with contralateral extra-temporal activations that were not associated with successful memory formation. Conclusion Age at onset of epilepsy influenced verbal memory encoding in patients with TLE due to hippocampal sclerosis in the speech-dominant hemisphere. Shorter duration of epilepsy and lower seizure frequency were associated with less disruption of the efficient memory encoding network whilst longer duration and higher seizure frequency were associated with greater, inefficient, extra-temporal reorganisation. PMID:25616449

Cross talk and diffraction efficiency in angular multiplexed memories using improved polypeptide

NASA Astrophysics Data System (ADS)

Ramenah, Harry K.; Bertrand, Paul; Soubari, E. H.; Meyrueis, Patrick

1996-12-01

We studied energy coupling between gratings and angularly multiplexed 20 gratings with a uniform diffraction efficiency within 25 micrometer layer thickness of dichromated gelatin. The dependence of diffraction efficiency on beam ratio is given. We recorded a matrix form memory of nxmxp elements, where n and m are the rows and columns and p the number of multiplexes. For indication only, n equals m equals 10, p equals 20, the surface area of the matrix is 1 cm2. Color diffractive images and digital data are illustrated as well as video, cartography and medical applications.

A Case Study on Neural Inspired Dynamic Memory Management Strategies for High Performance Computing.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vineyard, Craig Michael; Verzi, Stephen Joseph

As high performance computing architectures pursue more computational power there is a need for increased memory capacity and bandwidth as well. A multi-level memory (MLM) architecture addresses this need by combining multiple memory types with different characteristics as varying levels of the same architecture. How to efficiently utilize this memory infrastructure is an unknown challenge, and in this research we sought to investigate whether neural inspired approaches can meaningfully help with memory management. In particular we explored neurogenesis inspired re- source allocation, and were able to show a neural inspired mixed controller policy can beneficially impact how MLM architectures utilizemore » memory.« less

Carbon nanomaterials for non-volatile memories

NASA Astrophysics Data System (ADS)

Ahn, Ethan C.; Wong, H.-S. Philip; Pop, Eric

2018-03-01

Carbon can create various low-dimensional nanostructures with remarkable electronic, optical, mechanical and thermal properties. These features make carbon nanomaterials especially interesting for next-generation memory and storage devices, such as resistive random access memory, phase-change memory, spin-transfer-torque magnetic random access memory and ferroelectric random access memory. Non-volatile memories greatly benefit from the use of carbon nanomaterials in terms of bit density and energy efficiency. In this Review, we discuss sp2-hybridized carbon-based low-dimensional nanostructures, such as fullerene, carbon nanotubes and graphene, in the context of non-volatile memory devices and architectures. Applications of carbon nanomaterials as memory electrodes, interfacial engineering layers, resistive-switching media, and scalable, high-performance memory selectors are investigated. Finally, we compare the different memory technologies in terms of writing energy and time, and highlight major challenges in the manufacturing, integration and understanding of the physical mechanisms and material properties.

Memory-efficient table look-up optimized algorithm for context-based adaptive variable length decoding in H.264/advanced video coding

NASA Astrophysics Data System (ADS)

Wang, Jianhua; Cheng, Lianglun; Wang, Tao; Peng, Xiaodong

2016-03-01

Table look-up operation plays a very important role during the decoding processing of context-based adaptive variable length decoding (CAVLD) in H.264/advanced video coding (AVC). However, frequent table look-up operation can result in big table memory access, and then lead to high table power consumption. Aiming to solve the problem of big table memory access of current methods, and then reduce high power consumption, a memory-efficient table look-up optimized algorithm is presented for CAVLD. The contribution of this paper lies that index search technology is introduced to reduce big memory access for table look-up, and then reduce high table power consumption. Specifically, in our schemes, we use index search technology to reduce memory access by reducing the searching and matching operations for code_word on the basis of taking advantage of the internal relationship among length of zero in code_prefix, value of code_suffix and code_lengh, thus saving the power consumption of table look-up. The experimental results show that our proposed table look-up algorithm based on index search can lower about 60% memory access consumption compared with table look-up by sequential search scheme, and then save much power consumption for CAVLD in H.264/AVC.

Compression in visual working memory: using statistical regularities to form more efficient memory representations.

PubMed

Brady, Timothy F; Konkle, Talia; Alvarez, George A

2009-11-01

The information that individuals can hold in working memory is quite limited, but researchers have typically studied this capacity using simple objects or letter strings with no associations between them. However, in the real world there are strong associations and regularities in the input. In an information theoretic sense, regularities introduce redundancies that make the input more compressible. The current study shows that observers can take advantage of these redundancies, enabling them to remember more items in working memory. In 2 experiments, covariance was introduced between colors in a display so that over trials some color pairs were more likely to appear than other color pairs. Observers remembered more items from these displays than from displays where the colors were paired randomly. The improved memory performance cannot be explained by simply guessing the high-probability color pair, suggesting that observers formed more efficient representations to remember more items. Further, as observers learned the regularities, their working memory performance improved in a way that is quantitatively predicted by a Bayesian learning model and optimal encoding scheme. These results suggest that the underlying capacity of the individuals' working memory is unchanged, but the information they have to remember can be encoded in a more compressed fashion. Copyright 2009 APA

Efficient computation of aerodynamic influence coefficients for aeroelastic analysis on a transputer network

NASA Technical Reports Server (NTRS)

Janetzke, David C.; Murthy, Durbha V.

1991-01-01

Aeroelastic analysis is multi-disciplinary and computationally expensive. Hence, it can greatly benefit from parallel processing. As part of an effort to develop an aeroelastic capability on a distributed memory transputer network, a parallel algorithm for the computation of aerodynamic influence coefficients is implemented on a network of 32 transputers. The aerodynamic influence coefficients are calculated using a 3-D unsteady aerodynamic model and a parallel discretization. Efficiencies up to 85 percent were demonstrated using 32 processors. The effect of subtask ordering, problem size, and network topology are presented. A comparison to results on a shared memory computer indicates that higher speedup is achieved on the distributed memory system.

High efficiency Raman memory by suppressing radiation trapping

NASA Astrophysics Data System (ADS)

Thomas, S. E.; Munns, J. H. D.; Kaczmarek, K. T.; Qiu, C.; Brecht, B.; Feizpour, A.; Ledingham, P. M.; Walmsley, I. A.; Nunn, J.; Saunders, D. J.

2017-06-01

Raman interactions in alkali vapours are used in applications such as atomic clocks, optical signal processing, generation of squeezed light and Raman quantum memories for temporal multiplexing. To achieve a strong interaction the alkali ensemble needs both a large optical depth and a high level of spin-polarisation. We implement a technique known as quenching using a molecular buffer gas which allows near-perfect spin-polarisation of over 99.5 % in caesium vapour at high optical depths of up to ˜ 2× {10}5; a factor of 4 higher than can be achieved without quenching. We use this system to explore efficient light storage with high gain in a GHz bandwidth Raman memory.

Memory and Learning: A Case Study.

ERIC Educational Resources Information Center

Webster, Raymond E.

1986-01-01

The usefulness of the Learning Efficency Test (LET), an approach to assessing the learning efficiency and short-term memory recall capacity in children, is described via a case study demonstrating the test's use to develop instructional strategies. (CL)

Face classification using electronic synapses

NASA Astrophysics Data System (ADS)

Yao, Peng; Wu, Huaqiang; Gao, Bin; Eryilmaz, Sukru Burc; Huang, Xueyao; Zhang, Wenqiang; Zhang, Qingtian; Deng, Ning; Shi, Luping; Wong, H.-S. Philip; Qian, He

2017-05-01

Conventional hardware platforms consume huge amount of energy for cognitive learning due to the data movement between the processor and the off-chip memory. Brain-inspired device technologies using analogue weight storage allow to complete cognitive tasks more efficiently. Here we present an analogue non-volatile resistive memory (an electronic synapse) with foundry friendly materials. The device shows bidirectional continuous weight modulation behaviour. Grey-scale face classification is experimentally demonstrated using an integrated 1024-cell array with parallel online training. The energy consumption within the analogue synapses for each iteration is 1,000 × (20 ×) lower compared to an implementation using Intel Xeon Phi processor with off-chip memory (with hypothetical on-chip digital resistive random access memory). The accuracy on test sets is close to the result using a central processing unit. These experimental results consolidate the feasibility of analogue synaptic array and pave the way toward building an energy efficient and large-scale neuromorphic system.

Modulation of selective attention by polarity-specific tDCS effects.

PubMed

Pecchinenda, Anna; Ferlazzo, Fabio; Lavidor, Michal

2015-02-01

Selective attention relies on working memory to maintain an attention set of task priorities. Consequently, selective attention is more efficient when working memory resources are not depleted. However, there is some evidence that distractors are processed even when working memory load is low. We used tDCS to assess whether boosting the activity of the Dorsolateral Prefrontal Cortex (DLPFC), involved in selective attention and working memory, would reduce interference from emotional distractors. Findings showed that anodal tDCS over the DLPFC was not sufficient to reduce interference from angry distractors. In contrast, cathodal tDCS over the DLPFC reduced interference from happy distractors. These findings show that altering the DLPFC activity is not sufficient to establish top-down control and increase selective attention efficiency. Although, when the neural signal in the DLPFC is altered by cathodal tDCS, interference from emotional distractors is reduced, leading to an improved performance. Copyright © 2014 Elsevier Ltd. All rights reserved.

Face classification using electronic synapses.

PubMed

Yao, Peng; Wu, Huaqiang; Gao, Bin; Eryilmaz, Sukru Burc; Huang, Xueyao; Zhang, Wenqiang; Zhang, Qingtian; Deng, Ning; Shi, Luping; Wong, H-S Philip; Qian, He

2017-05-12

Conventional hardware platforms consume huge amount of energy for cognitive learning due to the data movement between the processor and the off-chip memory. Brain-inspired device technologies using analogue weight storage allow to complete cognitive tasks more efficiently. Here we present an analogue non-volatile resistive memory (an electronic synapse) with foundry friendly materials. The device shows bidirectional continuous weight modulation behaviour. Grey-scale face classification is experimentally demonstrated using an integrated 1024-cell array with parallel online training. The energy consumption within the analogue synapses for each iteration is 1,000 × (20 ×) lower compared to an implementation using Intel Xeon Phi processor with off-chip memory (with hypothetical on-chip digital resistive random access memory). The accuracy on test sets is close to the result using a central processing unit. These experimental results consolidate the feasibility of analogue synaptic array and pave the way toward building an energy efficient and large-scale neuromorphic system.

Non-tables look-up search algorithm for efficient H.264/AVC context-based adaptive variable length coding decoding

NASA Astrophysics Data System (ADS)

Han, Yishi; Luo, Zhixiao; Wang, Jianhua; Min, Zhixuan; Qin, Xinyu; Sun, Yunlong

2014-09-01

In general, context-based adaptive variable length coding (CAVLC) decoding in H.264/AVC standard requires frequent access to the unstructured variable length coding tables (VLCTs) and significant memory accesses are consumed. Heavy memory accesses will cause high power consumption and time delays, which are serious problems for applications in portable multimedia devices. We propose a method for high-efficiency CAVLC decoding by using a program instead of all the VLCTs. The decoded codeword from VLCTs can be obtained without any table look-up and memory access. The experimental results show that the proposed algorithm achieves 100% memory access saving and 40% decoding time saving without degrading video quality. Additionally, the proposed algorithm shows a better performance compared with conventional CAVLC decoding, such as table look-up by sequential search, table look-up by binary search, Moon's method, and Kim's method.

Broadband multiresonator quantum memory-interface.

PubMed

Moiseev, S A; Gerasimov, K I; Latypov, R R; Perminov, N S; Petrovnin, K V; Sherstyukov, O N

2018-03-05

In this paper we experimentally demonstrated a broadband scheme of the multiresonator quantum memory-interface. The microwave photonic scheme consists of the system of mini-resonators strongly interacting with a common broadband resonator coupled with the external waveguide. We have implemented the impedance matched quantum storage in this scheme via controllable tuning of the mini-resonator frequencies and coupling of the common resonator with the external waveguide. Proof-of-principal experiment has been demonstrated for broadband microwave pulses when the quantum efficiency of 16.3% was achieved at room temperature. By using the obtained experimental spectroscopic data, the dynamics of the signal retrieval has been simulated and promising results were found for high-Q mini-resonators in microwave and optical frequency ranges. The results pave the way for the experimental implementation of broadband quantum memory-interface with quite high efficiency η > 0.99 on the basis of modern technologies, including optical quantum memory at room temperature.

Interactive Effects of Working Memory Self-Regulatory Ability and Relevance Instructions on Text Processing

ERIC Educational Resources Information Center

Hamilton, Nancy Jo

2012-01-01

Reading is a process that requires the enactment of many cognitive processes. Each of these processes uses a certain amount of working memory resources, which are severely constrained by biology. More efficiency in the function of working memory may mediate the biological limits of same. Reading relevancy instructions may be one such method to…

A system-level approach for embedded memory robustness

NASA Astrophysics Data System (ADS)

Mariani, Riccardo; Boschi, Gabriele

2005-11-01

New ultra-deep submicron technologies are bringing not only new advantages such extraordinary transistor densities or unforeseen performances, but also new uncertainties such soft-error susceptibility, modelling complexity, coupling effects, leakage contribution and increased sensitivity to internal and external disturbs. Nowadays, embedded memories are taking profit of such new technologies and they are more and more used in systems: therefore as robustness and reliability requirement increase, memory systems must be protected against different kind of faults (permanent and transient) and that should be done in an efficient way. It means that reliability and costs, such overhead and performance degradation, must be efficiently tuned based on the system and on the application. Moreover, the new emerging norms for safety-critical applications such IEC 61508 are requiring precise answers in terms of robustness also in the case of memory systems. In this paper, classical protection techniques for error detection and correction are enriched with a system-aware approach, where the memory system is analyzed based on its role in the application. A configurable memory protection system is presented, together with the results of its application to a proof-of-concept architecture. This work has been developed in the framework of MEDEA+ T126 project called BLUEBERRIES.

Boosting the FM-Index on the GPU: Effective Techniques to Mitigate Random Memory Access.

PubMed

Chacón, Alejandro; Marco-Sola, Santiago; Espinosa, Antonio; Ribeca, Paolo; Moure, Juan Carlos

2015-01-01

The recent advent of high-throughput sequencing machines producing big amounts of short reads has boosted the interest in efficient string searching techniques. As of today, many mainstream sequence alignment software tools rely on a special data structure, called the FM-index, which allows for fast exact searches in large genomic references. However, such searches translate into a pseudo-random memory access pattern, thus making memory access the limiting factor of all computation-efficient implementations, both on CPUs and GPUs. Here, we show that several strategies can be put in place to remove the memory bottleneck on the GPU: more compact indexes can be implemented by having more threads work cooperatively on larger memory blocks, and a k-step FM-index can be used to further reduce the number of memory accesses. The combination of those and other optimisations yields an implementation that is able to process about two Gbases of queries per second on our test platform, being about 8 × faster than a comparable multi-core CPU version, and about 3 × to 5 × faster than the FM-index implementation on the GPU provided by the recently announced Nvidia NVBIO bioinformatics library.

A 12-Week Physical and Cognitive Exercise Program Can Improve Cognitive Function and Neural Efficiency in Community-Dwelling Older Adults: A Randomized Controlled Trial.

PubMed

Nishiguchi, Shu; Yamada, Minoru; Tanigawa, Takanori; Sekiyama, Kaoru; Kawagoe, Toshikazu; Suzuki, Maki; Yoshikawa, Sakiko; Abe, Nobuhito; Otsuka, Yuki; Nakai, Ryusuke; Aoyama, Tomoki; Tsuboyama, Tadao

2015-07-01

To investigate whether a 12-week physical and cognitive exercise program can improve cognitive function and brain activation efficiency in community-dwelling older adults. Randomized controlled trial. Kyoto, Japan. Community-dwelling older adults (N = 48) were randomized into an exercise group (n = 24) and a control group (n = 24). Exercise group participants received a weekly dual task-based multimodal exercise class in combination with pedometer-based daily walking exercise during the 12-week intervention phase. Control group participants did not receive any intervention and were instructed to spend their time as usual during the intervention phase. The outcome measures were global cognitive function, memory function, executive function, and brain activation (measured using functional magnetic resonance imaging) associated with visual short-term memory. Exercise group participants had significantly greater postintervention improvement in memory and executive functions than the control group (P < .05). In addition, after the intervention, less activation was found in several brain regions associated with visual short-term memory, including the prefrontal cortex, in the exercise group (P < .001, uncorrected). A 12-week physical and cognitive exercise program can improve the efficiency of brain activation during cognitive tasks in older adults, which is associated with improvements in memory and executive function. © 2015, Copyright the Authors Journal compilation © 2015, The American Geriatrics Society.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mittal, Sparsh; Zhang, Zhao

With each CMOS technology generation, leakage energy consumption has been dramatically increasing and hence, managing leakage power consumption of large last-level caches (LLCs) has become a critical issue in modern processor design. In this paper, we present EnCache, a novel software-based technique which uses dynamic profiling-based cache reconfiguration for saving cache leakage energy. EnCache uses a simple hardware component called profiling cache, which dynamically predicts energy efficiency of an application for 32 possible cache configurations. Using these estimates, system software reconfigures the cache to the most energy efficient configuration. EnCache uses dynamic cache reconfiguration and hence, it does not requiremore » offline profiling or tuning the parameter for each application. Furthermore, EnCache optimizes directly for the overall memory subsystem (LLC and main memory) energy efficiency instead of the LLC energy efficiency alone. The experiments performed with an x86-64 simulator and workloads from SPEC2006 suite confirm that EnCache provides larger energy saving than a conventional energy saving scheme. For single core and dual-core system configurations, the average savings in memory subsystem energy over a shared baseline configuration are 30.0% and 27.3%, respectively.« less

Causal evidence for mnemonic metacognition in human precuneus.

PubMed

Ye 叶群, Qun; Zou 邹富渟, Futing; Lau 劉克頑, Hakwan; Hu 胡谊, Yi; Kwok 郭思齊, Sze Chai

2018-06-19

Metacognition is the capacity to introspectively monitor and control one's own cognitive processes. Previous anatomical and functional neuroimaging findings implicated the important role of the precuneus in metacognition processing, especially during mnemonic tasks. However, the issue of whether this medial parietal cortex is a domain-specific region that supports mnemonic metacognition remains controversial. Here, we focally disrupted this parietal area with repetitive transcranial magnetic stimulation in healthy human participants of both sexes, seeking to ascertain its functional necessity for metacognition in memory versus perceptual decisions. Perturbing precuneal activity selectively impaired metacognitive efficiency of temporal-order memory judgement, but not perceptual discrimination. Moreover, the correlation in individuals' metacognitive efficiency between domains disappeared when the precuneus was perturbed. Taken together, these findings provide evidence reinforcing the notion that the precuneal region plays an important role in mediating metacognition of episodic memory retrieval. SIGNIFICANCE STATEMENT Theories on the neural basis of metacognition have thus far been largely centered on the role of the prefrontal cortex. Here we refined the theoretical framework through characterizing a unique precuneal involvement in mnemonic metacognition with a noninvasive but inferentially powerful method: transcranial magnetic stimulation. By quantifying meta-cognitive efficiency across two distinct domains (memory vs. perception) that are matched for stimulus characteristics, we reveal an instrumental role of the precuneus in mnemonic metacognition. This causal evidence corroborates ample clinical reports that parietal lobe lesions often produce inaccurate self-reports of confidence in memory recollection and establish the precuneus as a nexus for the introspective ability to evaluate the success of memory judgment in humans. Copyright © 2018 the authors.

The effect of interference on temporal order memory for random and fixed sequences in nondemented older adults.

PubMed

Tolentino, Jerlyn C; Pirogovsky, Eva; Luu, Trinh; Toner, Chelsea K; Gilbert, Paul E

2012-05-21

Two experiments tested the effect of temporal interference on order memory for fixed and random sequences in young adults and nondemented older adults. The results demonstrate that temporal order memory for fixed and random sequences is impaired in nondemented older adults, particularly when temporal interference is high. However, temporal order memory for fixed sequences is comparable between older adults and young adults when temporal interference is minimized. The results suggest that temporal order memory is less efficient and more susceptible to interference in older adults, possibly due to impaired temporal pattern separation.

Processing-in-Memory Enabled Graphics Processors for 3D Rendering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xie, Chenhao; Song, Shuaiwen; Wang, Jing

2017-02-06

The performance of 3D rendering of Graphics Processing Unit that convents 3D vector stream into 2D frame with 3D image effects significantly impact users’ gaming experience on modern computer systems. Due to the high texture throughput in 3D rendering, main memory bandwidth becomes a critical obstacle for improving the overall rendering performance. 3D stacked memory systems such as Hybrid Memory Cube (HMC) provide opportunities to significantly overcome the memory wall by directly connecting logic controllers to DRAM dies. Based on the observation that texel fetches significantly impact off-chip memory traffic, we propose two architectural designs to enable Processing-In-Memory based GPUmore » for efficient 3D rendering.« less

BLACKCOMB2: Hardware-software co-design for non-volatile memory in exascale systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mudge, Trevor

This work was part of a larger project, Blackcomb2, centered at Oak Ridge National Labs (Jeff Vetter PI) to investigate the opportunities for replacing or supplementing DRAM main memory with nonvolatile memory (NVmemory) in Exascale memory systems. The goal was to reduce the energy consumed by in future supercomputer memory systems and to improve their resiliency. Building on the accomplishments of the original Blackcomb Project, funded in 2010, the goal for Blackcomb2 was to identify, evaluate, and optimize the most promising emerging memory technologies, architecture hardware and software technologies, which are essential to provide the necessary memory capacity, performance, resilience,more » and energy efficiency in Exascale systems. Capacity and energy are the key drivers.« less

Optical mass memories

NASA Technical Reports Server (NTRS)

Bailey, G. A.

1976-01-01

Optical and magnetic variants in the design of trillion-bit read/write memories are compared and tabulated. Components and materials suitable for a random access read/write nonmoving memory system are examined, with preference given to holography and photoplastic materials. Advantages and deficiencies of photoplastics are reviewed. Holographic page composer design, essential features of an optical memory with no moving parts, fiche-oriented random access memory design, and materials suitable for an efficient photoplastic fiche are considered. The optical variants offer advantages in lower volume and weight at data transfer rates near 1 Mbit/sec, but power drain is of the same order as for the magnetic variants (tape memory, disk memory). The mechanical properties of photoplastic film materials still leave much to be desired.

Memory dynamics under stress.

PubMed

Quaedflieg, Conny W E M; Schwabe, Lars

2018-03-01

Stressful events have a major impact on memory. They modulate memory formation in a time-dependent manner, closely linked to the temporal profile of action of major stress mediators, in particular catecholamines and glucocorticoids. Shortly after stressor onset, rapidly acting catecholamines and fast, non-genomic glucocorticoid actions direct cognitive resources to the processing and consolidation of the ongoing threat. In parallel, control of memory is biased towards rather rigid systems, promoting habitual forms of memory allowing efficient processing under stress, at the expense of "cognitive" systems supporting memory flexibility and specificity. In this review, we discuss the implications of this shift in the balance of multiple memory systems for the dynamics of the memory trace. Specifically, stress appears to hinder the incorporation of contextual details into the memory trace, to impede the integration of new information into existing knowledge structures, to impair the flexible generalisation across past experiences, and to hamper the modification of memories in light of new information. Delayed, genomic glucocorticoid actions might reverse the control of memory, thus restoring homeostasis and "cognitive" control of memory again.

Adaptive efficient compression of genomes

PubMed Central

2012-01-01

Modern high-throughput sequencing technologies are able to generate DNA sequences at an ever increasing rate. In parallel to the decreasing experimental time and cost necessary to produce DNA sequences, computational requirements for analysis and storage of the sequences are steeply increasing. Compression is a key technology to deal with this challenge. Recently, referential compression schemes, storing only the differences between a to-be-compressed input and a known reference sequence, gained a lot of interest in this field. However, memory requirements of the current algorithms are high and run times often are slow. In this paper, we propose an adaptive, parallel and highly efficient referential sequence compression method which allows fine-tuning of the trade-off between required memory and compression speed. When using 12 MB of memory, our method is for human genomes on-par with the best previous algorithms in terms of compression ratio (400:1) and compression speed. In contrast, it compresses a complete human genome in just 11 seconds when provided with 9 GB of main memory, which is almost three times faster than the best competitor while using less main memory. PMID:23146997

Long-term moderate elevation of corticosterone facilitates avian food-caching behaviour and enhances spatial memory.

PubMed

Pravosudov, Vladimir V

2003-12-22

It is widely assumed that chronic stress and corresponding chronic elevations of glucocorticoid levels have deleterious effects on animals' brain functions such as learning and memory. Some animals, however, appear to maintain moderately elevated levels of glucocorticoids over long periods of time under natural energetically demanding conditions, and it is not clear whether such chronic but moderate elevations may be adaptive. I implanted wild-caught food-caching mountain chickadees (Poecile gambeli), which rely at least in part on spatial memory to find their caches, with 90-day continuous time-release corticosterone pellets designed to approximately double the baseline corticosterone levels. Corticosterone-implanted birds cached and consumed significantly more food and showed more efficient cache recovery and superior spatial memory performance compared with placebo-implanted birds. Thus, contrary to prevailing assumptions, long-term moderate elevations of corticosterone appear to enhance spatial memory in food-caching mountain chickadees. These results suggest that moderate chronic elevation of corticosterone may serve as an adaptation to unpredictable environments by facilitating feeding and food-caching behaviour and by improving cache-retrieval efficiency in food-caching birds.

Accessing sparse arrays in parallel memories

DOE Office of Scientific and Technical Information (OSTI.GOV)

Banerjee, U.; Gajski, D.; Kuck, D.

The concept of dense and sparse execution of arrays is introduced. Arrays themselves can be stored in a dense or sparse manner in a parallel memory with m memory modules. The paper proposes hardware for speeding up the execution of array operations of the form c(c/sub 0/+ci)=a(a/sub 0/+ai) op b(b/sub 0/+bi), where a/sub 0/, a, b/sub 0/, b, c/sub 0/, c are integer constants and i is an index variable. The hardware handles 'sparse execution', in which the operation op is not executed for every value of i. The hardware also makes provision for 'sparse storage', in which memory spacemore » is not provided for every array element. It is shown how to access array elements of the above form without conflict in an efficient way. The efficiency is obtained by using some specialised units which are basically smart memories with priority detection, one's counting or associative searching. Generalisation to multidimensional arrays is shown possible under restrictions defined in the paper. 12 references.« less

The relationship between dominance, corticosterone, memory, and food caching in mountain chickadees (Poecile gambeli).

PubMed

Pravosudov, Vladimir V; Mendoza, Sally P; Clayton, Nicola S

2003-08-01

It has been hypothesized that in avian social groups subordinate individuals should maintain more energy reserves than dominants, as an insurance against increased perceived risk of starvation. Subordinates might also have elevated baseline corticosterone levels because corticosterone is known to facilitate fattening in birds. Recent experiments showed that moderately elevated corticosterone levels resulting from unpredictable food supply are correlated with enhanced cache retrieval efficiency and more accurate performance on a spatial memory task. Given the correlation between corticosterone and memory, a further prediction is that subordinates might be more efficient at cache retrieval and show more accurate performance on spatial memory tasks. We tested these predictions in dominant-subordinate pairs of mountain chickadees (Poecile gambeli). Each pair was housed in the same cage but caching behavior was tested individually in an adjacent aviary to avoid the confounding effects of small spaces in which birds could unnaturally and directly influence each other's behavior. In sharp contrast to our hypothesis, we found that subordinate chickadees cached less food, showed less efficient cache retrieval, and performed significantly worse on the spatial memory task than dominants. Although the behavioral differences could have resulted from social stress of subordination, and dominant birds reached significantly higher levels of corticosterone during their response to acute stress compared to subordinates, there were no significant differences between dominants and subordinates in baseline levels or in the pattern of adrenocortical stress response. We find no evidence, therefore, to support the hypothesis that subordinate mountain chickadees maintain elevated baseline corticosterone levels whereas lower caching rates and inferior cache retrieval efficiency might contribute to reduced survival of subordinates commonly found in food-caching parids.

Fast Magnetoresistive Random-Access Memory

NASA Technical Reports Server (NTRS)

Wu, Jiin-Chuan; Stadler, Henry L.; Katti, Romney R.

1991-01-01

Magnetoresistive binary digital memories of proposed new type expected to feature high speed, nonvolatility, ability to withstand ionizing radiation, high density, and low power. In memory cell, magnetoresistive effect exploited more efficiently by use of ferromagnetic material to store datum and adjacent magnetoresistive material to sense datum for readout. Because relative change in sensed resistance between "zero" and "one" states greater, shorter sampling and readout access times achievable.

Cache directory look-up re-use as conflict check mechanism for speculative memory requests

DOEpatents

Ohmacht, Martin

2013-09-10

In a cache memory, energy and other efficiencies can be realized by saving a result of a cache directory lookup for sequential accesses to a same memory address. Where the cache is a point of coherence for speculative execution in a multiprocessor system, with directory lookups serving as the point of conflict detection, such saving becomes particularly advantageous.

The Development of Memory Efficiency and Value-Directed Remembering across the Life Span: A Cross-Sectional Study of Memory and Selectivity

ERIC Educational Resources Information Center

Castel, Alan D.; Humphreys, Kathryn L.; Lee, Steve S.; Galvan, Adriana; Balota, David A.; McCabe, David P.

2011-01-01

Although attentional control and memory change considerably across the life span, no research has examined how the ability to strategically remember important information (i.e., value-directed remembering) changes from childhood to old age. The present study examined this in different age groups across the life span (N = 320, 5-96 years old). A…

A Case for Tamper-Resistant and Tamper-Evident Computer Systems

DTIC Science & Technology

2007-02-01

such as Kerberos is hard to apply [2] B . Gassend, G. Sub, D. Clarke, M. Dijk, and S. Devadas . Caches and Hash Trees for Efficient Memory Integrity...the block’s data from DRAM. For authentication, Merkle [14] G. Suh, D. Clarke, B . Gassend, M. van Dijk, and S. Devadas . Efficient Memory Integrity...wwi4serverwatch.com/news/article.php/ tion where a data block is encrypted or decrypted through an XOR 1399451, 2000. [11] B . Rogers, Y. Solihin

Efficient detection of dangling pointer error for C/C++ programs

NASA Astrophysics Data System (ADS)

Zhang, Wenzhe

2017-08-01

Dangling pointer error is pervasive in C/C++ programs and it is very hard to detect. This paper introduces an efficient detector to detect dangling pointer error in C/C++ programs. By selectively leave some memory accesses unmonitored, our method could reduce the memory monitoring overhead and thus achieves better performance over previous methods. Experiments show that our method could achieve an average speed up of 9% over previous compiler instrumentation based method and more than 50% over previous page protection based method.

Aging and Memory as Discrimination: Influences of Encoding Specificity, Cue Overload, and Prior Knowledge

PubMed Central

2016-01-01

From the perspective of memory-as-discrimination, whether a cue leads to correct retrieval simultaneously depends on the cue’s relationship to (a) the memory target and (b) the other retrieval candidates. A corollary of the view is that increasing encoding-retrieval match may only help memory if it improves the cue’s capacity to discriminate the target from competitors. Here, age differences in this discrimination process were assessed by manipulating the overlap between cues present at encoding and retrieval orthogonally with cue–target distinctiveness. In Experiment 1, associative memory differences for cue–target sets between young and older adults were minimized through training and retrieval efficiency was assessed through response time. In Experiment 2, age-group differences in associative memory were left to vary and retrieval efficiency was assessed through accuracy. Both experiments showed age-invariance in memory-as-discrimination: cues increasing encoding-retrieval match did not benefit memory unless they also improved discrimination between the target and competitors. Predictions based on the age-related associative deficit were also supported: prior knowledge alleviated age-related associative deficits (Experiment 1), and increasing encoding-retrieval match benefited older more than young adults (Experiment 2). We suggest that the latter occurred because older adults’ associative memory deficits reduced the impact of competing retrieval candidates—hence the age-related benefit was not attributable to encoding-retrieval match per se, but rather it was a joint function of an increased probability of the cue connecting to the target combined with a decrease in competing retrieval candidates. PMID:27831714

The Control of Single-color and Multiple-color Visual Search by Attentional Templates in Working Memory and in Long-term Memory.

PubMed

Grubert, Anna; Carlisle, Nancy B; Eimer, Martin

2016-12-01

The question whether target selection in visual search can be effectively controlled by simultaneous attentional templates for multiple features is still under dispute. We investigated whether multiple-color attentional guidance is possible when target colors remain constant and can thus be represented in long-term memory but not when they change frequently and have to be held in working memory. Participants searched for one, two, or three possible target colors that were specified by cue displays at the start of each trial. In constant-color blocks, the same colors remained task-relevant throughout. In variable-color blocks, target colors changed between trials. The contralateral delay activity (CDA) to cue displays increased in amplitude as a function of color memory load in variable-color blocks, which indicates that cued target colors were held in working memory. In constant-color blocks, the CDA was much smaller, suggesting that color representations were primarily stored in long-term memory. N2pc components to targets were measured as a marker of attentional target selection. Target N2pcs were attenuated and delayed during multiple-color search, demonstrating less efficient attentional deployment to color-defined target objects relative to single-color search. Importantly, these costs were the same in constant-color and variable-color blocks. These results demonstrate that attentional guidance by multiple-feature as compared with single-feature templates is less efficient both when target features remain constant and can be represented in long-term memory and when they change across trials and therefore have to be maintained in working memory.

The effects of aging on ERP correlates of source memory retrieval for self-referential information.

PubMed

Dulas, Michael R; Newsome, Rachel N; Duarte, Audrey

2011-03-04

Numerous behavioral studies have suggested that normal aging negatively affects source memory accuracy for various kinds of associations. Neuroimaging evidence suggests that less efficient retrieval processing (temporally delayed and attenuated) may contribute to these impairments. Previous aging studies have not compared source memory accuracy and corresponding neural activity for different kinds of source details; namely, those that have been encoded via a more or less effective strategy. Thus, it is not yet known whether encoding source details in a self-referential manner, a strategy suggested to promote successful memory in the young and old, may enhance source memory accuracy and reduce the commonly observed age-related changes in neural activity associated with source memory retrieval. Here, we investigated these issues by using event-related potentials (ERPs) to measure the effects of aging on the neural correlates of successful source memory retrieval ("old-new effects") for objects encoded either self-referentially or self-externally. Behavioral results showed that both young and older adults demonstrated better source memory accuracy for objects encoded self-referentially. ERP results showed that old-new effects onsetted earlier for self-referentially encoded items in both groups and that age-related differences in the onset latency of these effects were reduced for self-referentially, compared to self-externally, encoded items. These results suggest that the implementation of an effective encoding strategy, like self-referential processing, may lead to more efficient retrieval, which in turn may improve source memory accuracy in both young and older adults. Published by Elsevier B.V.

Aging and memory as discrimination: Influences of encoding specificity, cue overload, and prior knowledge.

PubMed

Badham, Stephen P; Poirier, Marie; Gandhi, Navina; Hadjivassiliou, Anna; Maylor, Elizabeth A

2016-11-01

From the perspective of memory-as-discrimination, whether a cue leads to correct retrieval simultaneously depends on the cue's relationship to (a) the memory target and (b) the other retrieval candidates. A corollary of the view is that increasing encoding-retrieval match may only help memory if it improves the cue's capacity to discriminate the target from competitors. Here, age differences in this discrimination process were assessed by manipulating the overlap between cues present at encoding and retrieval orthogonally with cue-target distinctiveness. In Experiment 1, associative memory differences for cue-target sets between young and older adults were minimized through training and retrieval efficiency was assessed through response time. In Experiment 2, age-group differences in associative memory were left to vary and retrieval efficiency was assessed through accuracy. Both experiments showed age-invariance in memory-as-discrimination: cues increasing encoding-retrieval match did not benefit memory unless they also improved discrimination between the target and competitors. Predictions based on the age-related associative deficit were also supported: prior knowledge alleviated age-related associative deficits (Experiment 1), and increasing encoding-retrieval match benefited older more than young adults (Experiment 2). We suggest that the latter occurred because older adults' associative memory deficits reduced the impact of competing retrieval candidates-hence the age-related benefit was not attributable to encoding-retrieval match per se, but rather it was a joint function of an increased probability of the cue connecting to the target combined with a decrease in competing retrieval candidates. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Multipulse addressing of a Raman quantum memory: configurable beam splitting and efficient readout.

PubMed

Reim, K F; Nunn, J; Jin, X-M; Michelberger, P S; Champion, T F M; England, D G; Lee, K C; Kolthammer, W S; Langford, N K; Walmsley, I A

2012-06-29

Quantum memories are vital to the scalability of photonic quantum information processing (PQIP), since the storage of photons enables repeat-until-success strategies. On the other hand, the key element of all PQIP architectures is the beam splitter, which allows us to coherently couple optical modes. Here, we show how to combine these crucial functionalities by addressing a Raman quantum memory with multiple control pulses. The result is a coherent optical storage device with an extremely large time bandwidth product, that functions as an array of dynamically configurable beam splitters, and that can be read out with arbitrarily high efficiency. Networks of such devices would allow fully scalable PQIP, with applications in quantum computation, long distance quantum communications and quantum metrology.

Three-dimensional optical memory systems based on photochromic materials: polarization control of two-color data writing and the possibility of nondestructive data reading

NASA Astrophysics Data System (ADS)

Akimov, D. A.; Fedotov, Andrei B.; Koroteev, Nikolai I.; Magnitskii, S. A.; Naumov, A. N.; Sidorov-Biryukov, Dmitri A.; Sokoluk, N. T.; Zheltikov, Alexei M.

1998-04-01

The possibilities of optimizing data writing and reading in devices of 3D optical memory using photochromic materials are discussed. We quantitatively analyze linear and nonlinear optical properties of induline spiropyran molecules, which allows us to estimate the efficiency of using such materials for implementing 3D optical-memory devices. It is demonstrated that, with an appropriate choice of polarization vectors of laser beams, one can considerably improve the efficiency of two-photon writing in photochromic materials. The problem of reading the data stored in a photochromic material is analyzed. The possibilities of data reading methods with the use of fluorescence and four-photon techniques are compared.

Sex, estradiol, and spatial memory in a food-caching corvid.

PubMed

Rensel, Michelle A; Ellis, Jesse M S; Harvey, Brigit; Schlinger, Barney A

2015-09-01

Estrogens significantly impact spatial memory function in mammalian species. Songbirds express the estrogen synthetic enzyme aromatase at relatively high levels in the hippocampus and there is evidence from zebra finches that estrogens facilitate performance on spatial learning and/or memory tasks. It is unknown, however, whether estrogens influence hippocampal function in songbirds that naturally exhibit memory-intensive behaviors, such as cache recovery observed in many corvid species. To address this question, we examined the impact of estradiol on spatial memory in non-breeding Western scrub-jays, a species that routinely participates in food caching and retrieval in nature and in captivity. We also asked if there were sex differences in performance or responses to estradiol. Utilizing a combination of an aromatase inhibitor, fadrozole, with estradiol implants, we found that while overall cache recovery rates were unaffected by estradiol, several other indices of spatial memory, including searching efficiency and efficiency to retrieve the first item, were impaired in the presence of estradiol. In addition, males and females differed in some performance measures, although these differences appeared to be a consequence of the nature of the task as neither sex consistently out-performed the other. Overall, our data suggest that a sustained estradiol elevation in a food-caching bird impairs some, but not all, aspects of spatial memory on an innate behavioral task, at times in a sex-specific manner. Copyright © 2015 Elsevier Inc. All rights reserved.

SEX, ESTRADIOL, AND SPATIAL MEMORY IN A FOOD-CACHING CORVID

PubMed Central

Rensel, Michelle A.; Ellis, Jesse M.S.; Harvey, Brigit; Schlinger, Barney A.

2015-01-01

Estrogens significantly impact spatial memory function in mammalian species. Songbirds express the estrogen synthetic enzyme aromatase at relatively high levels in the hippocampus and there is evidence from zebra finches that estrogens facilitate performance on spatial learning and/or memory tasks. It is unknown, however, whether estrogens influence hippocampal function in songbirds that naturally exhibit memory-intensive behaviors, such as cache recovery observed in many corvid species. To address this question, we examined the impact of estradiol on spatial memory in non-breeding Western scrub-jays, a species that routinely participates in food caching and retrieval in nature and in captivity. We also asked if there were sex differences in performance or responses to estradiol. Utilizing a combination of an aromatase inhibitor, fadrozole, with estradiol implants, we found that while overall cache recovery rates were unaffected by estradiol, several other indices of spatial memory, including searching efficiency and efficiency to retrieve the first item, were impaired in the presence of estradiol. In addition, males and females differed in some performance measures, although these differences appeared to be a consequence of the nature of the task as neither sex consistently out-performed the other. Overall, our data suggest that a sustained estradiol elevation in a food-caching bird impairs some, but not all, aspects of spatial memory on an innate behavioral task, at times in a sex-specific manner. PMID:26232613

Power and Performance Trade-offs for Space Time Adaptive Processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gawande, Nitin A.; Manzano Franco, Joseph B.; Tumeo, Antonino

Computational efficiency – performance relative to power or energy – is one of the most important concerns when designing RADAR processing systems. This paper analyzes power and performance trade-offs for a typical Space Time Adaptive Processing (STAP) application. We study STAP implementations for CUDA and OpenMP on two computationally efficient architectures, Intel Haswell Core I7-4770TE and NVIDIA Kayla with a GK208 GPU. We analyze the power and performance of STAP’s computationally intensive kernels across the two hardware testbeds. We also show the impact and trade-offs of GPU optimization techniques. We show that data parallelism can be exploited for efficient implementationmore » on the Haswell CPU architecture. The GPU architecture is able to process large size data sets without increase in power requirement. The use of shared memory has a significant impact on the power requirement for the GPU. A balance between the use of shared memory and main memory access leads to an improved performance in a typical STAP application.« less

A highly efficient silole-containing dithienylethene with excellent thermal stability and fatigue resistance: a promising candidate for optical memory storage materials.

PubMed

Chan, Jacky Chi-Hung; Lam, Wai Han; Yam, Vivian Wing-Wah

2014-12-10

Diarylethene compounds are potential candidates for applications in optical memory storage systems and photoswitchable molecular devices; however, they usually show low photocycloreversion quantum yields, which result in ineffective erasure processes. Here, we present the first highly efficient photochromic silole-containing dithienylethene with excellent thermal stability and fatigue resistance. The photochemical quantum yields for photocyclization and photocycloreversion of the compound are found to be high and comparable to each other; the latter of which is rarely found in diarylethene compounds. These would give rise to highly efficient photoswitchable material with effective writing and erasure processes. Incorporation of the silole moiety as a photochromic dithienylethene backbone also was demonstrated to enhance the thermal stability of the closed form, in which the thermal backward reaction to the open form was found to be negligible even at 100 °C, which leads to a promising candidate for use as photoswitchable materials and optical memory storage.

AQUAdexIM: highly efficient in-memory indexing and querying of astronomy time series images

NASA Astrophysics Data System (ADS)

Hong, Zhi; Yu, Ce; Wang, Jie; Xiao, Jian; Cui, Chenzhou; Sun, Jizhou

2016-12-01

Astronomy has always been, and will continue to be, a data-based science, and astronomers nowadays are faced with increasingly massive datasets, one key problem of which is to efficiently retrieve the desired cup of data from the ocean. AQUAdexIM, an innovative spatial indexing and querying method, performs highly efficient on-the-fly queries under users' request to search for Time Series Images from existing observation data on the server side and only return the desired FITS images to users, so users no longer need to download entire datasets to their local machines, which will only become more and more impractical as the data size keeps increasing. Moreover, AQUAdexIM manages to keep a very low storage space overhead and its specially designed in-memory index structure enables it to search for Time Series Images of a given area of the sky 10 times faster than using Redis, a state-of-the-art in-memory database.

Comparison of memory and meta-memory abilities of children with cochlear implant and normal hearing peers.

PubMed

Engel-Yeger, Batya; Durr, Doris H; Josman, Naomi

2011-01-01

This study aimed (1) to compare visual memory and meta-memory abilities, including the use of strategies as context, of children with cochlear implant (CI) and children with normal hearing; (2) to examine the concurrent and construct validity of 'The Contextual Memory Test for Children' (CMT-CH). Twenty children with CI and 20 children with normal hearing, aged 8-10 years, participated in this study. Memory abilities were measured by two subtests of the Children's Memory Scale (CMS) and by CMT-CH, which also measures meta-memory abilities. Children with CI scored significantly lower in both tests of memory and meta-memory and showed less efficient use of context to memorise. Significant positive correlations were found between CMS and CMT-CH memory tests in both groups. Visual memory and meta-memory abilities may be impaired in children with CI. Evaluation and intervention for children with CI should refer to their memory and meta-memory abilities in order to measure the outcomes of CIs, and enhance language development academic achievements. Although more studies on CMT-CH should be performed, the CMT-CH may be used for the evaluation of visual memory of children with CI.

Nanophotonic rare-earth quantum memory with optically controlled retrieval

NASA Astrophysics Data System (ADS)

Zhong, Tian; Kindem, Jonathan M.; Bartholomew, John G.; Rochman, Jake; Craiciu, Ioana; Miyazono, Evan; Bettinelli, Marco; Cavalli, Enrico; Verma, Varun; Nam, Sae Woo; Marsili, Francesco; Shaw, Matthew D.; Beyer, Andrew D.; Faraon, Andrei

2017-09-01

Optical quantum memories are essential elements in quantum networks for long-distance distribution of quantum entanglement. Scalable development of quantum network nodes requires on-chip qubit storage functionality with control of the readout time. We demonstrate a high-fidelity nanophotonic quantum memory based on a mesoscopic neodymium ensemble coupled to a photonic crystal cavity. The nanocavity enables >95% spin polarization for efficient initialization of the atomic frequency comb memory and time bin-selective readout through an enhanced optical Stark shift of the comb frequencies. Our solid-state memory is integrable with other chip-scale photon source and detector devices for multiplexed quantum and classical information processing at the network nodes.

Design and DSP implementation of star image acquisition and star point fast acquiring and tracking

NASA Astrophysics Data System (ADS)

Zhou, Guohui; Wang, Xiaodong; Hao, Zhihang

2006-02-01

Star sensor is a special high accuracy photoelectric sensor. Attitude acquisition time is an important function index of star sensor. In this paper, the design target is to acquire 10 samples per second dynamic performance. On the basis of analyzing CCD signals timing and star image processing, a new design and a special parallel architecture for improving star image processing are presented in this paper. In the design, the operation moving the data in expanded windows including the star to the on-chip memory of DSP is arranged in the invalid period of CCD frame signal. During the CCD saving the star image to memory, DSP processes the data in the on-chip memory. This parallelism greatly improves the efficiency of processing. The scheme proposed here results in enormous savings of memory normally required. In the scheme, DSP HOLD mode and CPLD technology are used to make a shared memory between CCD and DSP. The efficiency of processing is discussed in numerical tests. Only in 3.5ms is acquired the five lightest stars in the star acquisition stage. In 43us, the data in five expanded windows including stars are moved into the internal memory of DSP, and in 1.6ms, five star coordinates are achieved in the star tracking stage.

Coherence time of over a second in a telecom-compatible quantum memory storage material

NASA Astrophysics Data System (ADS)

Rančić, Miloš; Hedges, Morgan P.; Ahlefeldt, Rose L.; Sellars, Matthew J.

2018-01-01

Quantum memories for light will be essential elements in future long-range quantum communication networks. These memories operate by reversibly mapping the quantum state of light onto the quantum transitions of a material system. For networks, the quantum coherence times of these transitions must be long compared to the network transmission times, approximately 100 ms for a global communication network. Due to a lack of a suitable storage material, a quantum memory that operates in the 1,550 nm optical fibre communication band with a storage time greater than 1 μs has not been demonstrated. Here we describe the spin dynamics of 167Er3+: Y2SiO5 in a high magnetic field and demonstrate that this material has the characteristics for a practical quantum memory in the 1,550 nm communication band. We observe a hyperfine coherence time of 1.3 s. We also demonstrate efficient spin pumping of the entire ensemble into a single hyperfine state, a requirement for broadband spin-wave storage. With an absorption of 70 dB cm-1 at 1,538 nm and Λ transitions enabling spin-wave storage, this material is the first candidate identified for an efficient, broadband quantum memory at telecommunication wavelengths.

Cognitive correlates of verbal memory and verbal fluency in schizophrenia, and differential effects of various clinical symptoms between male and female patients.

PubMed

Brébion, Gildas; Villalta-Gil, Victoria; Autonell, Jaume; Cervilla, Jorge; Dolz, Montserrat; Foix, Alexandrina; Haro, Josep Maria; Usall, Judith; Vilaplana, Miriam; Ochoa, Susana

2013-06-01

Impairment of higher cognitive functions in patients with schizophrenia might stem from perturbation of more basic functions, such as processing speed. Various clinical symptoms might affect cognitive efficiency as well. Notably, previous research has revealed the role of affective symptoms on memory performance in this population, and suggested sex-specific effects. We conducted a post-hoc analysis of an extensive neuropsychological study of 88 patients with schizophrenia. Regression analyses were conducted on verbal memory and verbal fluency data to investigate the contribution of semantic organisation and processing speed to performance. The role of negative and affective symptoms and of attention disorders in verbal memory and verbal fluency was investigated separately in male and female patients. Semantic clustering contributed to verbal recall, and a measure of reading speed contributed to verbal recall as well as to phonological and semantic fluency. Negative symptoms affected verbal recall and verbal fluency in the male patients, whereas attention disorders affected these abilities in the female patients. Furthermore, depression affected verbal recall in women, whereas anxiety affected it in men. These results confirm the association of processing speed with cognitive efficiency in patients with schizophrenia. They also confirm the previously observed sex-specific associations of depression and anxiety with memory performance in these patients, and suggest that negative symptoms and attention disorders likewise are related to cognitive efficiency differently in men and women. Copyright © 2013 Elsevier B.V. All rights reserved.

Hierarchically clustered adaptive quantization CMAC and its learning convergence.

PubMed

Teddy, S D; Lai, E M K; Quek, C

2007-11-01

The cerebellar model articulation controller (CMAC) neural network (NN) is a well-established computational model of the human cerebellum. Nevertheless, there are two major drawbacks associated with the uniform quantization scheme of the CMAC network. They are the following: (1) a constant output resolution associated with the entire input space and (2) the generalization-accuracy dilemma. Moreover, the size of the CMAC network is an exponential function of the number of inputs. Depending on the characteristics of the training data, only a small percentage of the entire set of CMAC memory cells is utilized. Therefore, the efficient utilization of the CMAC memory is a crucial issue. One approach is to quantize the input space nonuniformly. For existing nonuniformly quantized CMAC systems, there is a tradeoff between memory efficiency and computational complexity. Inspired by the underlying organizational mechanism of the human brain, this paper presents a novel CMAC architecture named hierarchically clustered adaptive quantization CMAC (HCAQ-CMAC). HCAQ-CMAC employs hierarchical clustering for the nonuniform quantization of the input space to identify significant input segments and subsequently allocating more memory cells to these regions. The stability of the HCAQ-CMAC network is theoretically guaranteed by the proof of its learning convergence. The performance of the proposed network is subsequently benchmarked against the original CMAC network, as well as two other existing CMAC variants on two real-life applications, namely, automated control of car maneuver and modeling of the human blood glucose dynamics. The experimental results have demonstrated that the HCAQ-CMAC network offers an efficient memory allocation scheme and improves the generalization and accuracy of the network output to achieve better or comparable performances with smaller memory usages. Index Terms-Cerebellar model articulation controller (CMAC), hierarchical clustering, hierarchically clustered adaptive quantization CMAC (HCAQ-CMAC), learning convergence, nonuniform quantization.

An abstraction layer for efficient memory management of tabulated chemistry and flamelet solutions

NASA Astrophysics Data System (ADS)

Weise, Steffen; Messig, Danny; Meyer, Bernd; Hasse, Christian

2013-06-01

A large number of methods for simulating reactive flows exist, some of them, for example, directly use detailed chemical kinetics or use precomputed and tabulated flame solutions. Both approaches couple the research fields computational fluid dynamics and chemistry tightly together using either an online or offline approach to solve the chemistry domain. The offline approach usually involves a method of generating databases or so-called Lookup-Tables (LUTs). As these LUTs are extended to not only contain material properties but interactions between chemistry and turbulent flow, the number of parameters and thus dimensions increases. Given a reasonable discretisation, file sizes can increase drastically. The main goal of this work is to provide methods that handle large database files efficiently. A Memory Abstraction Layer (MAL) has been developed that handles requested LUT entries efficiently by splitting the database file into several smaller blocks. It keeps the total memory usage at a minimum using thin allocation methods and compression to minimise filesystem operations. The MAL has been evaluated using three different test cases. The first rather generic one is a sequential reading operation on an LUT to evaluate the runtime behaviour as well as the memory consumption of the MAL. The second test case is a simulation of a non-premixed turbulent flame, the so-called HM1 flame, which is a well-known test case in the turbulent combustion community. The third test case is a simulation of a non-premixed laminar flame as described by McEnally in 1996 and Bennett in 2000. Using the previously developed solver 'flameletFoam' in conjunction with the MAL, memory consumption and the performance penalty introduced were studied. The total memory used while running a parallel simulation was reduced significantly while the CPU time overhead associated with the MAL remained low.

Memory-related brain lateralisation in birds and humans.

PubMed

Moorman, Sanne; Nicol, Alister U

2015-03-01

Visual imprinting in chicks and song learning in songbirds are prominent model systems for the study of the neural mechanisms of memory. In both systems, neural lateralisation has been found to be involved in memory formation. Although many processes in the human brain are lateralised--spatial memory and musical processing involves mostly right hemisphere dominance, whilst language is mostly left hemisphere dominant--it is unclear what the function of lateralisation is. It might enhance brain capacity, make processing more efficient, or prevent occurrence of conflicting signals. In both avian paradigms we find memory-related lateralisation. We will discuss avian lateralisation findings and propose that birds provide a strong model for studying neural mechanisms of memory-related lateralisation. Copyright © 2014. Published by Elsevier Ltd.

LOD-based clustering techniques for efficient large-scale terrain storage and visualization

NASA Astrophysics Data System (ADS)

Bao, Xiaohong; Pajarola, Renato

2003-05-01

Large multi-resolution terrain data sets are usually stored out-of-core. To visualize terrain data at interactive frame rates, the data needs to be organized on disk, loaded into main memory part by part, then rendered efficiently. Many main-memory algorithms have been proposed for efficient vertex selection and mesh construction. Organization of terrain data on disk is quite difficult because the error, the triangulation dependency and the spatial location of each vertex all need to be considered. Previous terrain clustering algorithms did not consider the per-vertex approximation error of individual terrain data sets. Therefore, the vertex sequences on disk are exactly the same for any terrain. In this paper, we propose a novel clustering algorithm which introduces the level-of-detail (LOD) information to terrain data organization to map multi-resolution terrain data to external memory. In our approach the LOD parameters of the terrain elevation points are reflected during clustering. The experiments show that dynamic loading and paging of terrain data at varying LOD is very efficient and minimizes page faults. Additionally, the preprocessing of this algorithm is very fast and works from out-of-core.

Intelligence and working memory systems: evidence of neural efficiency in alpha band ERD.

PubMed

Grabner, R H; Fink, A; Stipacek, A; Neuper, C; Neubauer, A C

2004-07-01

Starting from the well-established finding that brighter individuals display a more efficient brain function when performing cognitive tasks (i.e., neural efficiency), we investigated the relationship between intelligence and cortical activation in the context of working memory (WM) tasks. Fifty-five male (n=28) and female (n=27) participants worked on (1) a classical forward digit span task demanding only short-term memory (STM), (2) an attention-switching task drawing on the central executive (CE) of WM and (3) a WM task involving both STM storage and CE processes. During performance of these three types of tasks, cortical activation was quantified by the extent of Event-Related Desynchronization (ERD) in the alpha band of the human EEG. Correlational analyses revealed associations between the amount of ERD in the upper alpha band and intelligence in several brain regions. In all tasks, the males were more likely to display the negative intelligence-cortical activation relationship. Furthermore, stronger associations between ERD and intelligence were found for fluid rather than crystallized intelligence. Analyses also point to topographical differences in neural efficiency depending on sex, task type and the associated cognitive subsystems engaged during task performance.

Contextual knowledge reduces demands on working memory during reading.

PubMed

Miller, Lisa M Soederberg; Cohen, Jason A; Wingfield, Arthur

2006-09-01

An experiment is reported in which young, middle-aged, and older adults read and recalled ambiguous texts either with or without the topic title that supplied contextual knowledge. Within each of the age groups, the participants were divided into those with high or low working memory (WM) spans, with available WM capacity further manipulated by the presence or absence of an auditory target detection task concurrent with the reading task. Differences in reading efficiency (reading time per proposition recalled) between low WM span and high WM span groups were greater among readers who had access to contextual knowledge relative to those who did not, suggesting that contextual knowledge reduces demands on WM capacity. This position was further supported by the finding that increased age and attentional demands, two factors associated with reduced WM capacity, exaggerated the benefits of contextual knowledge on reading efficiency. The relative strengths of additional potential predictors of reading efficiency (e.g., interest, effort, and memory beliefs), along with knowledge, WM span, and age, are reported. Findings showed that contextual knowledge was the strongest predictor of reading efficiency even after controlling for the effects of all of the other predictors.

Strategic search from long-term memory: an examination of semantic and autobiographical recall.

PubMed

Unsworth, Nash; Brewer, Gene A; Spillers, Gregory J

2014-01-01

Searching long-term memory is theoretically driven by both directed (search strategies) and random components. In the current study we conducted four experiments evaluating strategic search in semantic and autobiographical memory. Participants were required to generate either exemplars from the category of animals or the names of their friends for several minutes. Self-reported strategies suggested that participants typically relied on visualization strategies for both tasks and were less likely to rely on ordered strategies (e.g., alphabetic search). When participants were instructed to use particular strategies, the visualization strategy resulted in the highest levels of performance and the most efficient search, whereas ordered strategies resulted in the lowest levels of performance and fairly inefficient search. These results are consistent with the notion that retrieval from long-term memory is driven, in part, by search strategies employed by the individual, and that one particularly efficient strategy is to visualize various situational contexts that one has experienced in the past in order to constrain the search and generate the desired information.

Working memory capacity and recall from long-term memory: Examining the influences of encoding strategies, study time allocation, search efficiency, and monitoring abilities.

PubMed

Unsworth, Nash

2016-01-01

The relation between working memory capacity (WMC) and recall from long-term memory (LTM) was examined in the current study. Participants performed multiple measures of delayed free recall varying in presentation duration and self-reported their strategy usage after each task. Participants also performed multiple measures of WMC. The results suggested that WMC and LTM recall were related, and part of this relation was due to effective strategy use. However, adaptive changes in strategy use and study time allocation were not related to WMC. Examining multiple variables with structural equation modeling suggested that the relation between WMC and LTM recall was due to variation in effective strategy use, search efficiency, and monitoring abilities. Furthermore, all variables were shown to account for individual differences in LTM recall. These results suggest that the relation between WMC and recall from LTM is due to multiple strategic factors operating at both encoding and retrieval. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Intelligence as the efficiency of cue-driven retrieval from secondary memory.

PubMed

Liesefeld, Heinrich René; Hoffmann, Eugenia; Wentura, Dirk

2016-01-01

Complex-span (working-memory-capacity) tasks are among the most successful predictors of intelligence. One important contributor to this relationship is the ability to efficiently employ cues for the retrieval from secondary memory. Presumably, intelligent individuals can considerably restrict their memory search sets by using such cues and can thereby improve recall performance. We here test this assumption by experimentally manipulating the validity of retrieval cues. When memoranda are drawn from the same semantic category on two successive trials of a verbal complex-span task, the category is a very strong retrieval cue on its first occurrence (strong-cue trial) but loses some of its validity on its second occurrence (weak-cue trial). If intelligent individuals make better use of semantic categories as retrieval cues, their recall accuracy suffers more from this loss of cue validity. Accordingly, our results show that less variance in intelligence is explained by recall accuracy on weak-cue compared with strong-cue trials.

Efficient ICCG on a shared memory multiprocessor

NASA Technical Reports Server (NTRS)

Hammond, Steven W.; Schreiber, Robert

1989-01-01

Different approaches are discussed for exploiting parallelism in the ICCG (Incomplete Cholesky Conjugate Gradient) method for solving large sparse symmetric positive definite systems of equations on a shared memory parallel computer. Techniques for efficiently solving triangular systems and computing sparse matrix-vector products are explored. Three methods for scheduling the tasks in solving triangular systems are implemented on the Sequent Balance 21000. Sample problems that are representative of a large class of problems solved using iterative methods are used. We show that a static analysis to determine data dependences in the triangular solve can greatly improve its parallel efficiency. We also show that ignoring symmetry and storing the whole matrix can reduce solution time substantially.

Neuroanatomical and Cognitive Mediators of Age-Related Differences in Episodic Memory

PubMed Central

Head, Denise; Rodrigue, Karen M.; Kennedy, Kristen M.; Raz, Naftali

2009-01-01

Aging is associated with declines in episodic memory. In this study, the authors used a path analysis framework to explore the mediating role of differences in brain structure, executive functions, and processing speed in age-related differences in episodic memory. Measures of regional brain volume (prefrontal gray and white matter, caudate, hippocampus, visual cortex), executive functions (working memory, inhibitory control, task switching, temporal processing), processing speed, and episodic memory were obtained in a sample of young and older adults. As expected, age was linked to reduction in regional brain volumes and cognitive performance. Moreover, neural and cognitive factors completely mediated age differences in episodic memory. Whereas hippocampal shrinkage directly affected episodic memory, prefrontal volumetric reductions influenced episodic memory via limitations in working memory and inhibitory control. Age-related slowing predicted reduced efficiency in temporal processing, working memory, and inhibitory control. Lastly, poorer temporal processing directly affected episodic memory. No direct effects of age on episodic memory remained once these factors were taken into account. These analyses highlight the value of a multivariate approach with the understanding of complex relationships in cognitive and brain aging. PMID:18590361

A novel binary shape context for 3D local surface description

NASA Astrophysics Data System (ADS)

Dong, Zhen; Yang, Bisheng; Liu, Yuan; Liang, Fuxun; Li, Bijun; Zang, Yufu

2017-08-01

3D local surface description is now at the core of many computer vision technologies, such as 3D object recognition, intelligent driving, and 3D model reconstruction. However, most of the existing 3D feature descriptors still suffer from low descriptiveness, weak robustness, and inefficiency in both time and memory. To overcome these challenges, this paper presents a robust and descriptive 3D Binary Shape Context (BSC) descriptor with high efficiency in both time and memory. First, a novel BSC descriptor is generated for 3D local surface description, and the performance of the BSC descriptor under different settings of its parameters is analyzed. Next, the descriptiveness, robustness, and efficiency in both time and memory of the BSC descriptor are evaluated and compared to those of several state-of-the-art 3D feature descriptors. Finally, the performance of the BSC descriptor for 3D object recognition is also evaluated on a number of popular benchmark datasets, and an urban-scene dataset is collected by a terrestrial laser scanner system. Comprehensive experiments demonstrate that the proposed BSC descriptor obtained high descriptiveness, strong robustness, and high efficiency in both time and memory and achieved high recognition rates of 94.8%, 94.1% and 82.1% on the considered UWA, Queen, and WHU datasets, respectively.

Twin Neurons for Efficient Real-World Data Distribution in Networks of Neural Cliques: Applications in Power Management in Electronic Circuits.

PubMed

Boguslawski, Bartosz; Gripon, Vincent; Seguin, Fabrice; Heitzmann, Frédéric

2016-02-01

Associative memories are data structures that allow retrieval of previously stored messages given part of their content. They, thus, behave similarly to the human brain's memory that is capable, for instance, of retrieving the end of a song, given its beginning. Among different families of associative memories, sparse ones are known to provide the best efficiency (ratio of the number of bits stored to that of the bits used). Recently, a new family of sparse associative memories achieving almost optimal efficiency has been proposed. Their structure, relying on binary connections and neurons, induces a direct mapping between input messages and stored patterns. Nevertheless, it is well known that nonuniformity of the stored messages can lead to a dramatic decrease in performance. In this paper, we show the impact of nonuniformity on the performance of this recent model, and we exploit the structure of the model to improve its performance in practical applications, where data are not necessarily uniform. In order to approach the performance of networks with uniformly distributed messages presented in theoretical studies, twin neurons are introduced. To assess the adapted model, twin neurons are used with the real-world data to optimize power consumption of electronic circuits in practical test cases.

Memory protection

NASA Technical Reports Server (NTRS)

Denning, Peter J.

1988-01-01

Accidental overwriting of files or of memory regions belonging to other programs, browsing of personal files by superusers, Trojan horses, and viruses are examples of breakdowns in workstations and personal computers that would be significantly reduced by memory protection. Memory protection is the capability of an operating system and supporting hardware to delimit segments of memory, to control whether segments can be read from or written into, and to confine accesses of a program to its segments alone. The absence of memory protection in many operating systems today is the result of a bias toward a narrow definition of performance as maximum instruction-execution rate. A broader definition, including the time to get the job done, makes clear that cost of recovery from memory interference errors reduces expected performance. The mechanisms of memory protection are well understood, powerful, efficient, and elegant. They add to performance in the broad sense without reducing instruction execution rate.

Extending the BEAGLE library to a multi-FPGA platform.

PubMed

Jin, Zheming; Bakos, Jason D

2013-01-19

Maximum Likelihood (ML)-based phylogenetic inference using Felsenstein's pruning algorithm is a standard method for estimating the evolutionary relationships amongst a set of species based on DNA sequence data, and is used in popular applications such as RAxML, PHYLIP, GARLI, BEAST, and MrBayes. The Phylogenetic Likelihood Function (PLF) and its associated scaling and normalization steps comprise the computational kernel for these tools. These computations are data intensive but contain fine grain parallelism that can be exploited by coprocessor architectures such as FPGAs and GPUs. A general purpose API called BEAGLE has recently been developed that includes optimized implementations of Felsenstein's pruning algorithm for various data parallel architectures. In this paper, we extend the BEAGLE API to a multiple Field Programmable Gate Array (FPGA)-based platform called the Convey HC-1. The core calculation of our implementation, which includes both the phylogenetic likelihood function (PLF) and the tree likelihood calculation, has an arithmetic intensity of 130 floating-point operations per 64 bytes of I/O, or 2.03 ops/byte. Its performance can thus be calculated as a function of the host platform's peak memory bandwidth and the implementation's memory efficiency, as 2.03 × peak bandwidth × memory efficiency. Our FPGA-based platform has a peak bandwidth of 76.8 GB/s and our implementation achieves a memory efficiency of approximately 50%, which gives an average throughput of 78 Gflops. This represents a ~40X speedup when compared with BEAGLE's CPU implementation on a dual Xeon 5520 and 3X speedup versus BEAGLE's GPU implementation on a Tesla T10 GPU for very large data sizes. The power consumption is 92 W, yielding a power efficiency of 1.7 Gflops per Watt. The use of data parallel architectures to achieve high performance for likelihood-based phylogenetic inference requires high memory bandwidth and a design methodology that emphasizes high memory efficiency. To achieve this objective, we integrated 32 pipelined processing elements (PEs) across four FPGAs. For the design of each PE, we developed a specialized synthesis tool to generate a floating-point pipeline with resource and throughput constraints to match the target platform. We have found that using low-latency floating-point operators can significantly reduce FPGA area and still meet timing requirement on the target platform. We found that this design methodology can achieve performance that exceeds that of a GPU-based coprocessor.

Disrupted rapid eye movement sleep predicts poor declarative memory performance in post-traumatic stress disorder.

PubMed

Lipinska, Malgorzata; Timol, Ridwana; Kaminer, Debra; Thomas, Kevin G F

2014-06-01

Successful memory consolidation during sleep depends on healthy slow-wave and rapid eye movement sleep, and on successful transition across sleep stages. In post-traumatic stress disorder, sleep is disrupted and memory is impaired, but relations between these two variables in the psychiatric condition remain unexplored. We examined whether disrupted sleep, and consequent disrupted memory consolidation, is a mechanism underlying declarative memory deficits in post-traumatic stress disorder. We recruited three matched groups of participants: post-traumatic stress disorder (n = 16); trauma-exposed non-post-traumatic stress disorder (n = 15); and healthy control (n = 14). They completed memory tasks before and after 8 h of sleep. We measured sleep variables using sleep-adapted electroencephalography. Post-traumatic stress disorder-diagnosed participants experienced significantly less sleep efficiency and rapid eye movement sleep percentage, and experienced more awakenings and wake percentage in the second half of the night than did participants in the other two groups. After sleep, post-traumatic stress disorder-diagnosed participants retained significantly less information on a declarative memory task than controls. Rapid eye movement percentage, wake percentage and sleep efficiency correlated with retention of information over the night. Furthermore, lower rapid eye movement percentage predicted poorer retention in post-traumatic stress disorder-diagnosed individuals. Our results suggest that declarative memory consolidation is disrupted during sleep in post-traumatic stress disorder. These data are consistent with theories suggesting that sleep benefits memory consolidation via predictable neurobiological mechanisms, and that rapid eye movement disruption is more than a symptom of post-traumatic stress disorder. © 2014 European Sleep Research Society.

Elevated stress is associated with prefrontal cortex dysfunction during a verbal memory task in women with HIV

PubMed Central

Rubin, Leah H.; Wu, Minjie; Sundermann, Erin E.; Meyer, Vanessa J.; Smith, Rachael; Weber, Kathleen M.; Cohen, Mardge H.; Little, Deborah M.; Maki, Pauline M.

2016-01-01

HIV-infected women may be particularly vulnerable to verbal learning and memory deficits. One factor contributing to these deficits is high perceived stress, which is associated with prefrontal cortical (PFC) atrophy and memory outcomes sensitive to PFC function, including retrieval and semantic clustering. We examined the association between stress and PFC activation during a verbal memory task in 36 HIV-infected women from the Chicago Consortium of the Women’s Interagency HIV Study (WIHS) to better understand the role of the PFC in this stress-related impairment. Participants completed standardized measures of verbal learning and memory and stress (Perceived Stress Scale-10). We used functional magnetic resonance imaging to assess brain function while participants completed encoding and recognition phases of a verbal memory task. HIV-infected women with higher stress (scores in top tertile) performed worse on all verbal memory outcomes including strategic encoding (p’s<0.05) compared to HIV-infected women with lower stress (scores in lower two tertiles). Patterns of brain activation during recognition (but not encoding) differed between women with higher versus lower stress. During recognition, women with higher stress demonstrated greater deactivation in medial PFC and posterior cingulate cortex compared to women with lower stress (p’s<0.05). Greater deactivation in medial PFC marginally related to less efficient strategic retrieval (p=0.06). Similar results were found in analyses focusing on PTSD symptoms. Results suggest that stress might alter the function of the medial PFC in HIV-infected women resulting in less efficient strategic retrieval and deficits in verbal memory. PMID:27094924

Elevated stress is associated with prefrontal cortex dysfunction during a verbal memory task in women with HIV.

PubMed

Rubin, Leah H; Wu, Minjie; Sundermann, Erin E; Meyer, Vanessa J; Smith, Rachael; Weber, Kathleen M; Cohen, Mardge H; Little, Deborah M; Maki, Pauline M

2016-12-01

HIV-infected women may be particularly vulnerable to verbal learning and memory deficits. One factor contributing to these deficits is high perceived stress, which is associated with prefrontal cortical (PFC) atrophy and memory outcomes sensitive to PFC function, including retrieval and semantic clustering. We examined the association between stress and PFC activation during a verbal memory task in 36 HIV-infected women from the Chicago Consortium of the Women's Interagency HIV Study (WIHS) to better understand the role of the PFC in this stress-related impairment. Participants completed standardized measures of verbal learning and memory and stress (perceived stress scale-10). We used functional magnetic resonance imaging to assess brain function while participants completed encoding and recognition phases of a verbal memory task. HIV-infected women with higher stress (scores in top tertile) performed worse on all verbal memory outcomes including strategic encoding (p < 0.05) compared to HIV-infected women with lower stress (scores in lower two tertiles). Patterns of brain activation during recognition (but not encoding) differed between women with higher vs. lower stress. During recognition, women with higher stress demonstrated greater deactivation in medial PFC and posterior cingulate cortex compared to women with lower stress (p < 0.05). Greater deactivation in medial PFC marginally related to less efficient strategic retrieval (p = 0.06). Similar results were found in analyses focusing on PTSD symptoms. Results suggest that stress might alter the function of the medial PFC in HIV-infected women resulting in less efficient strategic retrieval and deficits in verbal memory.

Efficient Graph Based Assembly of Short-Read Sequences on Hybrid Core Architecture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sczyrba, Alex; Pratap, Abhishek; Canon, Shane

2011-03-22

Advanced architectures can deliver dramatically increased throughput for genomics and proteomics applications, reducing time-to-completion in some cases from days to minutes. One such architecture, hybrid-core computing, marries a traditional x86 environment with a reconfigurable coprocessor, based on field programmable gate array (FPGA) technology. In addition to higher throughput, increased performance can fundamentally improve research quality by allowing more accurate, previously impractical approaches. We will discuss the approach used by Convey?s de Bruijn graph constructor for short-read, de-novo assembly. Bioinformatics applications that have random access patterns to large memory spaces, such as graph-based algorithms, experience memory performance limitations on cache-based x86more » servers. Convey?s highly parallel memory subsystem allows application-specific logic to simultaneously access 8192 individual words in memory, significantly increasing effective memory bandwidth over cache-based memory systems. Many algorithms, such as Velvet and other de Bruijn graph based, short-read, de-novo assemblers, can greatly benefit from this type of memory architecture. Furthermore, small data type operations (four nucleotides can be represented in two bits) make more efficient use of logic gates than the data types dictated by conventional programming models.JGI is comparing the performance of Convey?s graph constructor and Velvet on both synthetic and real data. We will present preliminary results on memory usage and run time metrics for various data sets with different sizes, from small microbial and fungal genomes to very large cow rumen metagenome. For genomes with references we will also present assembly quality comparisons between the two assemblers.« less

Combined Cognitive Training vs. Memory Strategy Training in Healthy Older Adults.

PubMed

Li, Bing; Zhu, Xinyi; Hou, Jianhua; Chen, Tingji; Wang, Pengyun; Li, Juan

2016-01-01

As mnemonic utilization deficit in older adults associates with age-related decline in executive function, we hypothesized that memory strategy training combined with executive function training might induce larger training effect in memory and broader training effects in non-memory outcomes than pure memory training. The present study compared the effects of combined cognitive training (executive function training plus memory strategy training) to pure memory strategy training. Forty healthy older adults were randomly assigned to a combined cognitive training group or a memory strategy training group. A control group receiving no training was also included. Combined cognitive training group received 16 sessions of training (eight sessions of executive function training followed by eight sessions of memory strategy training). Memory training group received 16 sessions of memory strategy training. The results partly supported our hypothesis in that indeed improved performance on executive function was only found in combined training group, whereas memory performance increased less in combined training compared to memory strategy group. Results suggest that combined cognitive training may be less efficient than pure memory training in memory outcomes, though the influences from insufficient training time and less closeness between trained executive function and working memory could not be excluded; however it has broader training effects in non-memory outcomes. www.chictr.org.cn, identifier ChiCTR-OON-16007793.

Energy-efficient writing scheme for magnetic domain-wall motion memory

NASA Astrophysics Data System (ADS)

Kim, Kab-Jin; Yoshimura, Yoko; Ham, Woo Seung; Ernst, Rick; Hirata, Yuushou; Li, Tian; Kim, Sanghoon; Moriyama, Takahiro; Nakatani, Yoshinobu; Ono, Teruo

2017-04-01

We present an energy-efficient magnetic domain-writing scheme for domain wall (DW) motion-based memory devices. A cross-shaped nanowire is employed to inject a domain into the nanowire through current-induced DW propagation. The energy required for injecting the magnetic domain is more than one order of magnitude lower than that for the conventional field-based writing scheme. The proposed scheme is beneficial for device miniaturization because the threshold current for DW propagation scales with the device size, which cannot be achieved in the conventional field-based technique.

Compiling for Application Specific Computational Acceleration in Reconfigurable Architectures Final Report CRADA No. TSB-2033-01

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Supinski, B.; Caliga, D.

2017-09-28

The primary objective of this project was to develop memory optimization technology to efficiently deliver data to, and distribute data within, the SRC-6's Field Programmable Gate Array- ("FPGA") based Multi-Adaptive Processors (MAPs). The hardware/software approach was to explore efficient MAP configurations and generate the compiler technology to exploit those configurations. This memory accessing technology represents an important step towards making reconfigurable symmetric multi-processor (SMP) architectures that will be a costeffective solution for large-scale scientific computing.

The Focus of Attention in Visual Working Memory: Protection of Focused Representations and Its Individual Variation.

PubMed

Heuer, Anna; Schubö, Anna

2016-01-01

Visual working memory can be modulated according to changes in the cued task relevance of maintained items. Here, we investigated the mechanisms underlying this modulation. In particular, we studied the consequences of attentional selection for selected and unselected items, and the role of individual differences in the efficiency with which attention is deployed. To this end, performance in a visual working memory task as well as the CDA/SPCN and the N2pc, ERP components associated with visual working memory and attentional processes, were analysed. Selection during the maintenance stage was manipulated by means of two successively presented retrocues providing spatial information as to which items were most likely to be tested. Results show that attentional selection serves to robustly protect relevant representations in the focus of attention while unselected representations which may become relevant again still remain available. Individuals with larger retrocueing benefits showed higher efficiency of attentional selection, as indicated by the N2pc, and showed stronger maintenance-associated activity (CDA/SPCN). The findings add to converging evidence that focused representations are protected, and highlight the flexibility of visual working memory, in which information can be weighted according its relevance.

Efficient Bayesian inference for natural time series using ARFIMA processes

NASA Astrophysics Data System (ADS)

Graves, T.; Gramacy, R. B.; Franzke, C. L. E.; Watkins, N. W.

2015-11-01

Many geophysical quantities, such as atmospheric temperature, water levels in rivers, and wind speeds, have shown evidence of long memory (LM). LM implies that these quantities experience non-trivial temporal memory, which potentially not only enhances their predictability, but also hampers the detection of externally forced trends. Thus, it is important to reliably identify whether or not a system exhibits LM. In this paper we present a modern and systematic approach to the inference of LM. We use the flexible autoregressive fractional integrated moving average (ARFIMA) model, which is widely used in time series analysis, and of increasing interest in climate science. Unlike most previous work on the inference of LM, which is frequentist in nature, we provide a systematic treatment of Bayesian inference. In particular, we provide a new approximate likelihood for efficient parameter inference, and show how nuisance parameters (e.g., short-memory effects) can be integrated over in order to focus on long-memory parameters and hypothesis testing more directly. We illustrate our new methodology on the Nile water level data and the central England temperature (CET) time series, with favorable comparison to the standard estimators. For CET we also extend our method to seasonal long memory.

Spin-transfer torque switched magnetic tunnel junctions in magnetic random access memory

NASA Astrophysics Data System (ADS)

Sun, Jonathan Z.

2016-10-01

Spin-transfer torque (or spin-torque, or STT) based magnetic tunnel junction (MTJ) is at the heart of a new generation of magnetism-based solid-state memory, the so-called spin-transfer-torque magnetic random access memory, or STT-MRAM. Over the past decades, STT-based switchable magnetic tunnel junction has seen progress on many fronts, including the discovery of (001) MgO as the most favored tunnel barrier, which together with (bcc) Fe or FeCo alloy are yielding best demonstrated tunnel magneto-resistance (TMR); the development of perpendicularly magnetized ultrathin CoFeB-type of thin films sufficient to support high density memories with junction sizes demonstrated down to 11nm in diameter; and record-low spin-torque switching threshold current, giving best reported switching efficiency over 5 kBT/μA. Here we review the basic device properties focusing on the perpendicularly magnetized MTJs, both in terms of switching efficiency as measured by sub-threshold, quasi-static methods, and of switching speed at super-threshold, forced switching. We focus on device behaviors important for memory applications that are rooted in fundamental device physics, which highlights the trade-off of device parameters for best suitable system integration.

Efficient Machine Learning Approach for Optimizing Scientific Computing Applications on Emerging HPC Architectures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arumugam, Kamesh

Efficient parallel implementations of scientific applications on multi-core CPUs with accelerators such as GPUs and Xeon Phis is challenging. This requires - exploiting the data parallel architecture of the accelerator along with the vector pipelines of modern x86 CPU architectures, load balancing, and efficient memory transfer between different devices. It is relatively easy to meet these requirements for highly structured scientific applications. In contrast, a number of scientific and engineering applications are unstructured. Getting performance on accelerators for these applications is extremely challenging because many of these applications employ irregular algorithms which exhibit data-dependent control-ow and irregular memory accesses. Furthermore,more » these applications are often iterative with dependency between steps, and thus making it hard to parallelize across steps. As a result, parallelism in these applications is often limited to a single step. Numerical simulation of charged particles beam dynamics is one such application where the distribution of work and memory access pattern at each time step is irregular. Applications with these properties tend to present significant branch and memory divergence, load imbalance between different processor cores, and poor compute and memory utilization. Prior research on parallelizing such irregular applications have been focused around optimizing the irregular, data-dependent memory accesses and control-ow during a single step of the application independent of the other steps, with the assumption that these patterns are completely unpredictable. We observed that the structure of computation leading to control-ow divergence and irregular memory accesses in one step is similar to that in the next step. It is possible to predict this structure in the current step by observing the computation structure of previous steps. In this dissertation, we present novel machine learning based optimization techniques to address the parallel implementation challenges of such irregular applications on different HPC architectures. In particular, we use supervised learning to predict the computation structure and use it to address the control-ow and memory access irregularities in the parallel implementation of such applications on GPUs, Xeon Phis, and heterogeneous architectures composed of multi-core CPUs with GPUs or Xeon Phis. We use numerical simulation of charged particles beam dynamics simulation as a motivating example throughout the dissertation to present our new approach, though they should be equally applicable to a wide range of irregular applications. The machine learning approach presented here use predictive analytics and forecasting techniques to adaptively model and track the irregular memory access pattern at each time step of the simulation to anticipate the future memory access pattern. Access pattern forecasts can then be used to formulate optimization decisions during application execution which improves the performance of the application at a future time step based on the observations from earlier time steps. In heterogeneous architectures, forecasts can also be used to improve the memory performance and resource utilization of all the processing units to deliver a good aggregate performance. We used these optimization techniques and anticipation strategy to design a cache-aware, memory efficient parallel algorithm to address the irregularities in the parallel implementation of charged particles beam dynamics simulation on different HPC architectures. Experimental result using a diverse mix of HPC architectures shows that our approach in using anticipation strategy is effective in maximizing data reuse, ensuring workload balance, minimizing branch and memory divergence, and in improving resource utilization.« less

Neural Bases of Automaticity

ERIC Educational Resources Information Center

Servant, Mathieu; Cassey, Peter; Woodman, Geoffrey F.; Logan, Gordon D.

2018-01-01

Automaticity allows us to perform tasks in a fast, efficient, and effortless manner after sufficient practice. Theories of automaticity propose that across practice processing transitions from being controlled by working memory to being controlled by long-term memory retrieval. Recent event-related potential (ERP) studies have sought to test this…

Optimal Recall from Bounded Metaplastic Synapses: Predicting Functional Adaptations in Hippocampal Area CA3

PubMed Central

Savin, Cristina; Dayan, Peter; Lengyel, Máté

2014-01-01

A venerable history of classical work on autoassociative memory has significantly shaped our understanding of several features of the hippocampus, and most prominently of its CA3 area, in relation to memory storage and retrieval. However, existing theories of hippocampal memory processing ignore a key biological constraint affecting memory storage in neural circuits: the bounded dynamical range of synapses. Recent treatments based on the notion of metaplasticity provide a powerful model for individual bounded synapses; however, their implications for the ability of the hippocampus to retrieve memories well and the dynamics of neurons associated with that retrieval are both unknown. Here, we develop a theoretical framework for memory storage and recall with bounded synapses. We formulate the recall of a previously stored pattern from a noisy recall cue and limited-capacity (and therefore lossy) synapses as a probabilistic inference problem, and derive neural dynamics that implement approximate inference algorithms to solve this problem efficiently. In particular, for binary synapses with metaplastic states, we demonstrate for the first time that memories can be efficiently read out with biologically plausible network dynamics that are completely constrained by the synaptic plasticity rule, and the statistics of the stored patterns and of the recall cue. Our theory organises into a coherent framework a wide range of existing data about the regulation of excitability, feedback inhibition, and network oscillations in area CA3, and makes novel and directly testable predictions that can guide future experiments. PMID:24586137

Evaluating architecture impact on system energy efficiency

PubMed Central

Yu, Shijie; Wang, Rui; Luan, Zhongzhi; Qian, Depei

2017-01-01

As the energy consumption has been surging in an unsustainable way, it is important to understand the impact of existing architecture designs from energy efficiency perspective, which is especially valuable for High Performance Computing (HPC) and datacenter environment hosting tens of thousands of servers. One obstacle hindering the advance of comprehensive evaluation on energy efficiency is the deficient power measuring approach. Most of the energy study relies on either external power meters or power models, both of these two methods contain intrinsic drawbacks in their practical adoption and measuring accuracy. Fortunately, the advent of Intel Running Average Power Limit (RAPL) interfaces has promoted the power measurement ability into next level, with higher accuracy and finer time resolution. Therefore, we argue it is the exact time to conduct an in-depth evaluation of the existing architecture designs to understand their impact on system energy efficiency. In this paper, we leverage representative benchmark suites including serial and parallel workloads from diverse domains to evaluate the architecture features such as Non Uniform Memory Access (NUMA), Simultaneous Multithreading (SMT) and Turbo Boost. The energy is tracked at subcomponent level such as Central Processing Unit (CPU) cores, uncore components and Dynamic Random-Access Memory (DRAM) through exploiting the power measurement ability exposed by RAPL. The experiments reveal non-intuitive results: 1) the mismatch between local compute and remote memory node caused by NUMA effect not only generates dramatic power and energy surge but also deteriorates the energy efficiency significantly; 2) for multithreaded application such as the Princeton Application Repository for Shared-Memory Computers (PARSEC), most of the workloads benefit a notable increase of energy efficiency using SMT, with more than 40% decline in average power consumption; 3) Turbo Boost is effective to accelerate the workload execution and further preserve the energy, however it may not be applicable on system with tight power budget. PMID:29161317

Evaluating architecture impact on system energy efficiency.

PubMed

Yu, Shijie; Yang, Hailong; Wang, Rui; Luan, Zhongzhi; Qian, Depei

2017-01-01

As the energy consumption has been surging in an unsustainable way, it is important to understand the impact of existing architecture designs from energy efficiency perspective, which is especially valuable for High Performance Computing (HPC) and datacenter environment hosting tens of thousands of servers. One obstacle hindering the advance of comprehensive evaluation on energy efficiency is the deficient power measuring approach. Most of the energy study relies on either external power meters or power models, both of these two methods contain intrinsic drawbacks in their practical adoption and measuring accuracy. Fortunately, the advent of Intel Running Average Power Limit (RAPL) interfaces has promoted the power measurement ability into next level, with higher accuracy and finer time resolution. Therefore, we argue it is the exact time to conduct an in-depth evaluation of the existing architecture designs to understand their impact on system energy efficiency. In this paper, we leverage representative benchmark suites including serial and parallel workloads from diverse domains to evaluate the architecture features such as Non Uniform Memory Access (NUMA), Simultaneous Multithreading (SMT) and Turbo Boost. The energy is tracked at subcomponent level such as Central Processing Unit (CPU) cores, uncore components and Dynamic Random-Access Memory (DRAM) through exploiting the power measurement ability exposed by RAPL. The experiments reveal non-intuitive results: 1) the mismatch between local compute and remote memory node caused by NUMA effect not only generates dramatic power and energy surge but also deteriorates the energy efficiency significantly; 2) for multithreaded application such as the Princeton Application Repository for Shared-Memory Computers (PARSEC), most of the workloads benefit a notable increase of energy efficiency using SMT, with more than 40% decline in average power consumption; 3) Turbo Boost is effective to accelerate the workload execution and further preserve the energy, however it may not be applicable on system with tight power budget.

Cache and energy efficient algorithms for Nussinov's RNA Folding.

PubMed

Zhao, Chunchun; Sahni, Sartaj

2017-12-06

An RNA folding/RNA secondary structure prediction algorithm determines the non-nested/pseudoknot-free structure by maximizing the number of complementary base pairs and minimizing the energy. Several implementations of Nussinov's classical RNA folding algorithm have been proposed. Our focus is to obtain run time and energy efficiency by reducing the number of cache misses. Three cache-efficient algorithms, ByRow, ByRowSegment and ByBox, for Nussinov's RNA folding are developed. Using a simple LRU cache model, we show that the Classical algorithm of Nussinov has the highest number of cache misses followed by the algorithms Transpose (Li et al.), ByRow, ByRowSegment, and ByBox (in this order). Extensive experiments conducted on four computational platforms-Xeon E5, AMD Athlon 64 X2, Intel I7 and PowerPC A2-using two programming languages-C and Java-show that our cache efficient algorithms are also efficient in terms of run time and energy. Our benchmarking shows that, depending on the computational platform and programming language, either ByRow or ByBox give best run time and energy performance. The C version of these algorithms reduce run time by as much as 97.2% and energy consumption by as much as 88.8% relative to Classical and by as much as 56.3% and 57.8% relative to Transpose. The Java versions reduce run time by as much as 98.3% relative to Classical and by as much as 75.2% relative to Transpose. Transpose achieves run time and energy efficiency at the expense of memory as it takes twice the memory required by Classical. The memory required by ByRow, ByRowSegment, and ByBox is the same as that of Classical. As a result, using the same amount of memory, the algorithms proposed by us can solve problems up to 40% larger than those solvable by Transpose.

A review of emerging non-volatile memory (NVM) technologies and applications

NASA Astrophysics Data System (ADS)

Chen, An

2016-11-01

This paper will review emerging non-volatile memory (NVM) technologies, with the focus on phase change memory (PCM), spin-transfer-torque random-access-memory (STTRAM), resistive random-access-memory (RRAM), and ferroelectric field-effect-transistor (FeFET) memory. These promising NVM devices are evaluated in terms of their advantages, challenges, and applications. Their performance is compared based on reported parameters of major industrial test chips. Memory selector devices and cell structures are discussed. Changing market trends toward low power (e.g., mobile, IoT) and data-centric applications create opportunities for emerging NVMs. High-performance and low-cost emerging NVMs may simplify memory hierarchy, introduce non-volatility in logic gates and circuits, reduce system power, and enable novel architectures. Storage-class memory (SCM) based on high-density NVMs could fill the performance and density gap between memory and storage. Some unique characteristics of emerging NVMs can be utilized for novel applications beyond the memory space, e.g., neuromorphic computing, hardware security, etc. In the beyond-CMOS era, emerging NVMs have the potential to fulfill more important functions and enable more efficient, intelligent, and secure computing systems.

An efficient spectral crystal plasticity solver for GPU architectures

NASA Astrophysics Data System (ADS)

Malahe, Michael

2018-03-01

We present a spectral crystal plasticity (CP) solver for graphics processing unit (GPU) architectures that achieves a tenfold increase in efficiency over prior GPU solvers. The approach makes use of a database containing a spectral decomposition of CP simulations performed using a conventional iterative solver over a parameter space of crystal orientations and applied velocity gradients. The key improvements in efficiency come from reducing global memory transactions, exposing more instruction-level parallelism, reducing integer instructions and performing fast range reductions on trigonometric arguments. The scheme also makes more efficient use of memory than prior work, allowing for larger problems to be solved on a single GPU. We illustrate these improvements with a simulation of 390 million crystal grains on a consumer-grade GPU, which executes at a rate of 2.72 s per strain step.

Supporting shared data structures on distributed memory architectures

NASA Technical Reports Server (NTRS)

Koelbel, Charles; Mehrotra, Piyush; Vanrosendale, John

1990-01-01

Programming nonshared memory systems is more difficult than programming shared memory systems, since there is no support for shared data structures. Current programming languages for distributed memory architectures force the user to decompose all data structures into separate pieces, with each piece owned by one of the processors in the machine, and with all communication explicitly specified by low-level message-passing primitives. A new programming environment is presented for distributed memory architectures, providing a global name space and allowing direct access to remote parts of data values. The analysis and program transformations required to implement this environment are described, and the efficiency of the resulting code on the NCUBE/7 and IPSC/2 hypercubes are described.

Immune memory: the basics and how to trigger an efficient long-term immune memory.

PubMed

Beverley, P C L

2010-01-01

Immunological memory consists of expanded clones of T and B lymphocytes that show an increased rate of cell division and shortened telomeres compared with naïve cells. However, exhaustion of clones is delayed by kinetic heterogeneity within clones and altered survival and up-regulation of telomerase. Prolonged maintenance of protective B-cell immunity is T-cell dependent and requires a balance between plasma cells and memory B cells. Protective T-cell immunity also requires correct quality of T cells and that they are located appropriately. Copyright 2009 Elsevier Ltd. All rights reserved.

Memory monitoring by animals and humans

NASA Technical Reports Server (NTRS)

Smith, J. D.; Shields, W. E.; Allendoerfer, K. R.; Washburn, D. A.; Rumbaugh, D. M. (Principal Investigator)

1998-01-01

The authors asked whether animals and humans would use similarly an uncertain response to escape indeterminate memories. Monkeys and humans performed serial probe recognition tasks that produced differential memory difficulty across serial positions (e.g., primacy and recency effects). Participants were given an escape option that let them avoid any trials they wished and receive a hint to the trial's answer. Across species, across tasks, and even across conspecifics with sharper or duller memories, monkeys and humans used the escape option selectively when more indeterminate memory traces were probed. Their pattern of escaping always mirrored the pattern of their primary memory performance across serial positions. Signal-detection analyses confirm the similarity of the animals' and humans' performances. Optimality analyses assess their efficiency. Several aspects of monkeys' performance suggest the cognitive sophistication of their decisions to escape.

Microprogramming Handbook. Second Edition.

ERIC Educational Resources Information Center

Microdata Corp., Santa Ana, CA.

Instead of instructions residing in the main memory as in a fixed instruction computer, a micro-programable computer has a separete read-only memory which is alterable so that the system can be efficiently adapted to the application at hand. Microprogramable computers are faster than fixed instruction computers for several reasons: instruction…

Basic and Exceptional Calculation Abilities in a Calculating Prodigy: A Case Study.

ERIC Educational Resources Information Center

Pesenti, Mauro; Seron, Xavier; Samson, Dana; Duroux, Bruno

1999-01-01

Describes the basic and exceptional calculation abilities of a calculating prodigy whose performances were investigated in single- and multi-digit number multiplication, numerical comparison, raising of powers, and short-term memory tasks. Shows how his highly efficient long-term memory storage and retrieval processes, knowledge of calculation…

Efficiency of the Prefrontal Cortex during Working Memory in Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Sheridan, Margaret A.; Hinshaw, Stephen; D'Esposito, Mark

2007-01-01

Objective: Previous research has demonstrated that during task conditions requiring an increase in inhibitory function or working memory, children and adults with attention-deficit/hyperactivity disorder (ADHD) exhibit greater and more varied prefrontal cortical(PFC) activation compared to age-matched control participants. This pattern may reflect…

Adult Word Recognition and Visual Sequential Memory

ERIC Educational Resources Information Center

Holmes, V. M.

2012-01-01

Two experiments were conducted investigating the role of visual sequential memory skill in the word recognition efficiency of undergraduate university students. Word recognition was assessed in a lexical decision task using regularly and strangely spelt words, and nonwords that were either standard orthographically legal strings or items made from…

Differential effects of ADORA2A gene variations in pre-attentive visual sensory memory subprocesses.

PubMed

Beste, Christian; Stock, Ann-Kathrin; Ness, Vanessa; Epplen, Jörg T; Arning, Larissa

2012-08-01

The ADORA2A gene encodes the adenosine A(2A) receptor that is highly expressed in the striatum where it plays a role in modulating glutamatergic and dopaminergic transmission. Glutamatergic signaling has been suggested to play a pivotal role in cognitive functions related to the pre-attentive processing of external stimuli. Yet, the precise molecular mechanism of these processes is poorly understood. Therefore, we aimed to investigate whether ADORA2A gene variation has modulating effects on visual pre-attentive sensory memory processing. Studying two polymorphisms, rs5751876 and rs2298383, in 199 healthy control subjects who performed a partial-report paradigm, we find that ADORA2A variation is associated with differences in the efficiency of pre-attentive sensory memory sub-processes. We show that especially the initial visual availability of stimulus information is rendered more efficiently in the homozygous rare genotype groups. Processes related to the transfer of information into working memory and the duration of visual sensory (iconic) memory are compromised in the homozygous rare genotype groups. Our results show a differential genotype-dependent modulation of pre-attentive sensory memory sub-processes. Hence, we assume that this modulation may be due to differential effects of increased adenosine A(2A) receptor signaling on glutamatergic transmission and striatal medium spiny neuron (MSN) interaction. Copyright © 2011 Elsevier B.V. and ECNP. All rights reserved.

Optical tomographic memories: algorithms for the efficient information readout

NASA Astrophysics Data System (ADS)

Pantelic, Dejan V.

1990-07-01

Tomographic alogithms are modified in order to reconstruct the inf ormation previously stored by focusing laser radiation in a volume of photosensitive media. Apriori information about the position of bits of inf ormation is used. 1. THE PRINCIPLES OF TOMOGRAPHIC MEMORIES Tomographic principles can be used to store and reconstruct the inf ormation artificially stored in a bulk of a photosensitive media 1 The information is stored by changing some characteristics of a memory material (e. g. refractive index). Radiation from the two independent light sources (e. g. lasers) is f ocused inside the memory material. In this way the intensity of the light is above the threshold only in the localized point where the light rays intersect. By scanning the material the information can be stored in binary or nary format. When the information is stored it can be read by tomographic methods. However the situation is quite different from the classical tomographic problem. Here a lot of apriori information is present regarding the p0- sitions of the bits of information profile representing single bit and a mode of operation (binary or n-ary). 2. ALGORITHMS FOR THE READOUT OF THE TOMOGRAPHIC MEMORIES Apriori information enables efficient reconstruction of the memory contents. In this paper a few methods for the information readout together with the simulation results will be presented. Special attention will be given to the noise considerations. Two different

Working memory and the strategic control of attention in older and younger adults.

PubMed

Hayes, Melissa G; Kelly, Andrew J; Smith, Anderson D

2013-03-01

The objective of this study was to investigate the effects of aging on the strategic control of attention and the extent to which this relationship is mediated by working memory capacity (WMC). This study also sought to investigate boundary conditions wherein age differences in selectivity may occur. Across 2 studies, the value-directed remembering task used by Castel and colleagues (Castel, A. D., Balota, D. A., & McCabe, D. P. (2009). Memory efficiency and the strategic control of attention at encoding: Impairments of value-directed remembering in Alzheimer's Disease. Neuropsychology, 23, 297-306) was modified to include value-directed forgetting. Study 2 incorporated valence as an additional task demand, and age differences were predicted in both studies due to increased demands of controlled processing. Automated operation span and Stroop span were included as working memory measures, and working memory was predicted to mediate performance. Results confirmed these predictions, as older adults were less efficient in maximizing selectivity scores when high demands were placed on selectivity processes, and working memory was found to mediate performance on this task. When list length was increased from previous studies and participants were required to actively forget negative-value words, older adults were not able to selectively encode high-value information to the same degree as younger adults. Furthermore, WMC appears to support the ability to selectively encode information.

Efficient frequent pattern mining algorithm based on node sets in cloud computing environment

NASA Astrophysics Data System (ADS)

Billa, V. N. Vinay Kumar; Lakshmanna, K.; Rajesh, K.; Reddy, M. Praveen Kumar; Nagaraja, G.; Sudheer, K.

2017-11-01

The ultimate goal of Data Mining is to determine the hidden information which is useful in making decisions using the large databases collected by an organization. This Data Mining involves many tasks that are to be performed during the process. Mining frequent itemsets is the one of the most important tasks in case of transactional databases. These transactional databases contain the data in very large scale where the mining of these databases involves the consumption of physical memory and time in proportion to the size of the database. A frequent pattern mining algorithm is said to be efficient only if it consumes less memory and time to mine the frequent itemsets from the given large database. Having these points in mind in this thesis we proposed a system which mines frequent itemsets in an optimized way in terms of memory and time by using cloud computing as an important factor to make the process parallel and the application is provided as a service. A complete framework which uses a proven efficient algorithm called FIN algorithm. FIN algorithm works on Nodesets and POC (pre-order coding) tree. In order to evaluate the performance of the system we conduct the experiments to compare the efficiency of the same algorithm applied in a standalone manner and in cloud computing environment on a real time data set which is traffic accidents data set. The results show that the memory consumption and execution time taken for the process in the proposed system is much lesser than those of standalone system.

Spin-transfer-torque efficiency enhanced by edge-damage of perpendicular magnetic random access memories

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Kyungmi; Lee, Kyung-Jin, E-mail: kj-lee@korea.ac.kr; Department of Materials Science and Engineering, Korea University, Seoul 136-713

2015-08-07

We numerically investigate the effect of magnetic and electrical damages at the edge of a perpendicular magnetic random access memory (MRAM) cell on the spin-transfer-torque (STT) efficiency that is defined by the ratio of thermal stability factor to switching current. We find that the switching mode of an edge-damaged cell is different from that of an undamaged cell, which results in a sizable reduction in the switching current. Together with a marginal reduction of the thermal stability factor of an edge-damaged cell, this feature makes the STT efficiency large. Our results suggest that a precise edge control is viable formore » the optimization of STT-MRAM.« less

SLIC superpixels compared to state-of-the-art superpixel methods.

PubMed

Achanta, Radhakrishna; Shaji, Appu; Smith, Kevin; Lucchi, Aurelien; Fua, Pascal; Süsstrunk, Sabine

2012-11-01

Computer vision applications have come to rely increasingly on superpixels in recent years, but it is not always clear what constitutes a good superpixel algorithm. In an effort to understand the benefits and drawbacks of existing methods, we empirically compare five state-of-the-art superpixel algorithms for their ability to adhere to image boundaries, speed, memory efficiency, and their impact on segmentation performance. We then introduce a new superpixel algorithm, simple linear iterative clustering (SLIC), which adapts a k-means clustering approach to efficiently generate superpixels. Despite its simplicity, SLIC adheres to boundaries as well as or better than previous methods. At the same time, it is faster and more memory efficient, improves segmentation performance, and is straightforward to extend to supervoxel generation.

An FMM-FFT Accelerated SIE Simulator for Analyzing EM Wave Propagation in Mine Environments Loaded With Conductors

PubMed Central

Sheng, Weitian; Zhou, Chenming; Liu, Yang; Bagci, Hakan; Michielssen, Eric

2018-01-01

A fast and memory efficient three-dimensional full-wave simulator for analyzing electromagnetic (EM) wave propagation in electrically large and realistic mine tunnels/galleries loaded with conductors is proposed. The simulator relies on Muller and combined field surface integral equations (SIEs) to account for scattering from mine walls and conductors, respectively. During the iterative solution of the system of SIEs, the simulator uses a fast multipole method-fast Fourier transform (FMM-FFT) scheme to reduce CPU and memory requirements. The memory requirement is further reduced by compressing large data structures via singular value and Tucker decompositions. The efficiency, accuracy, and real-world applicability of the simulator are demonstrated through characterization of EM wave propagation in electrically large mine tunnels/galleries loaded with conducting cables and mine carts. PMID:29726545

Wide-Range Motion Estimation Architecture with Dual Search Windows for High Resolution Video Coding

NASA Astrophysics Data System (ADS)

Dung, Lan-Rong; Lin, Meng-Chun

This paper presents a memory-efficient motion estimation (ME) technique for high-resolution video compression. The main objective is to reduce the external memory access, especially for limited local memory resource. The reduction of memory access can successfully save the notorious power consumption. The key to reduce the memory accesses is based on center-biased algorithm in that the center-biased algorithm performs the motion vector (MV) searching with the minimum search data. While considering the data reusability, the proposed dual-search-windowing (DSW) approaches use the secondary windowing as an option per searching necessity. By doing so, the loading of search windows can be alleviated and hence reduce the required external memory bandwidth. The proposed techniques can save up to 81% of external memory bandwidth and require only 135 MBytes/sec, while the quality degradation is less than 0.2dB for 720p HDTV clips coded at 8Mbits/sec.

Fast, noise-free memory for photon synchronization at room temperature.

PubMed

Finkelstein, Ran; Poem, Eilon; Michel, Ohad; Lahad, Ohr; Firstenberg, Ofer

2018-01-01

Future quantum photonic networks require coherent optical memories for synchronizing quantum sources and gates of probabilistic nature. We demonstrate a fast ladder memory (FLAME) mapping the optical field onto the superposition between electronic orbitals of rubidium vapor. Using a ladder-level system of orbital transitions with nearly degenerate frequencies simultaneously enables high bandwidth, low noise, and long memory lifetime. We store and retrieve 1.7-ns-long pulses, containing 0.5 photons on average, and observe short-time external efficiency of 25%, memory lifetime (1/ e ) of 86 ns, and below 10 -4 added noise photons. Consequently, coupling this memory to a probabilistic source would enhance the on-demand photon generation probability by a factor of 12, the highest number yet reported for a noise-free, room temperature memory. This paves the way toward the controlled production of large quantum states of light from probabilistic photon sources.

Cognitive Control Network Contributions to Memory-Guided Visual Attention

PubMed Central

Rosen, Maya L.; Stern, Chantal E.; Michalka, Samantha W.; Devaney, Kathryn J.; Somers, David C.

2016-01-01

Visual attentional capacity is severely limited, but humans excel in familiar visual contexts, in part because long-term memories guide efficient deployment of attention. To investigate the neural substrates that support memory-guided visual attention, we performed a set of functional MRI experiments that contrast long-term, memory-guided visuospatial attention with stimulus-guided visuospatial attention in a change detection task. Whereas the dorsal attention network was activated for both forms of attention, the cognitive control network (CCN) was preferentially activated during memory-guided attention. Three posterior nodes in the CCN, posterior precuneus, posterior callosal sulcus/mid-cingulate, and lateral intraparietal sulcus exhibited the greatest specificity for memory-guided attention. These 3 regions exhibit functional connectivity at rest, and we propose that they form a subnetwork within the broader CCN. Based on the task activation patterns, we conclude that the nodes of this subnetwork are preferentially recruited for long-term memory guidance of visuospatial attention. PMID:25750253

Neuroanatomic organization of sound memory in humans.

PubMed

Kraut, Michael A; Pitcock, Jeffery A; Calhoun, Vince; Li, Juan; Freeman, Thomas; Hart, John

2006-11-01

The neural interface between sensory perception and memory is a central issue in neuroscience, particularly initial memory organization following perceptual analyses. We used functional magnetic resonance imaging to identify anatomic regions extracting initial auditory semantic memory information related to environmental sounds. Two distinct anatomic foci were detected in the right superior temporal gyrus when subjects identified sounds representing either animals or threatening items. Threatening animal stimuli elicited signal changes in both foci, suggesting a distributed neural representation. Our results demonstrate both category- and feature-specific responses to nonverbal sounds in early stages of extracting semantic memory information from these sounds. This organization allows for these category-feature detection nodes to extract early, semantic memory information for efficient processing of transient sound stimuli. Neural regions selective for threatening sounds are similar to those of nonhuman primates, demonstrating semantic memory organization for basic biological/survival primitives are present across species.

Impaired quality and efficiency of sleep impairs cognitive functioning in Addison's disease.

PubMed

Henry, Michelle; Ross, Ian Louis; Wolf, Pedro Sofio Abril; Thomas, Kevin Garth Flusk

2017-04-01

Standard replacement therapy for Addison's disease (AD) does not restore a normal circadian rhythm. Periods of sub- and supra- physiological cortisol levels experienced by patients with AD likely induce disrupted sleep. Given that healthy sleep plays an important role in memory consolidation, the novelty of the current study was to characterise, using objective measures, the relationship between sleep and memory in patients with AD, and to examine the hypothesis that poor sleep is a biological mechanism underlying memory impairment in those patients. We used a within-subjects design. Ten patients with AD and 10 matched healthy controls completed standardised neuropsychological tests assessing declarative memory (Rey Auditory Verbal Learning Test) and procedural memory (Finger Tapping Task) before and after a period of actigraphy-measured sleep, and before and after a period of waking. Relative to healthy controls, patients with AD experienced disrupted sleep characterised by poorer sleep efficiency and more time spent awake. Patients also showed impaired verbal learning and memory relative to healthy controls (p=0.007). Furthermore, whereas healthy controls' declarative memory performance benefited from a period of sleep compared to waking (p=0.032), patients with AD derived no such benefit from sleep (p=0.448). Regarding the procedural memory task, analyses detected no significant between-group differences (all p's<0.065), and neither group showed significant sleep-enhanced performance. We demonstrated, using actigraphy and standardized measures of memory performance, an association between sleep disturbances and cognitive deficits in patients with AD. These results suggest that, in patients with AD, the source of memory deficits is, at least to some extent, disrupted sleep patterns that interfere with optimal consolidation of previously-learned declarative information. Hence, treating the sleep disturbances that are frequently experienced by patients with AD may improve their cognitive functioning. Copyright © 2017 Elsevier Ltd. All rights reserved.

APINetworks Java. A Java approach to the efficient treatment of large-scale complex networks

NASA Astrophysics Data System (ADS)

Muñoz-Caro, Camelia; Niño, Alfonso; Reyes, Sebastián; Castillo, Miriam

2016-10-01

We present a new version of the core structural package of our Application Programming Interface, APINetworks, for the treatment of complex networks in arbitrary computational environments. The new version is written in Java and presents several advantages over the previous C++ version: the portability of the Java code, the easiness of object-oriented design implementations, and the simplicity of memory management. In addition, some additional data structures are introduced for storing the sets of nodes and edges. Also, by resorting to the different garbage collectors currently available in the JVM the Java version is much more efficient than the C++ one with respect to memory management. In particular, the G1 collector is the most efficient one because of the parallel execution of G1 and the Java application. Using G1, APINetworks Java outperforms the C++ version and the well-known NetworkX and JGraphT packages in the building and BFS traversal of linear and complete networks. The better memory management of the present version allows for the modeling of much larger networks.

A Component-Based FPGA Design Framework for Neuronal Ion Channel Dynamics Simulations

PubMed Central

Mak, Terrence S. T.; Rachmuth, Guy; Lam, Kai-Pui; Poon, Chi-Sang

2008-01-01

Neuron-machine interfaces such as dynamic clamp and brain-implantable neuroprosthetic devices require real-time simulations of neuronal ion channel dynamics. Field Programmable Gate Array (FPGA) has emerged as a high-speed digital platform ideal for such application-specific computations. We propose an efficient and flexible component-based FPGA design framework for neuronal ion channel dynamics simulations, which overcomes certain limitations of the recently proposed memory-based approach. A parallel processing strategy is used to minimize computational delay, and a hardware-efficient factoring approach for calculating exponential and division functions in neuronal ion channel models is used to conserve resource consumption. Performances of the various FPGA design approaches are compared theoretically and experimentally in corresponding implementations of the AMPA and NMDA synaptic ion channel models. Our results suggest that the component-based design framework provides a more memory economic solution as well as more efficient logic utilization for large word lengths, whereas the memory-based approach may be suitable for time-critical applications where a higher throughput rate is desired. PMID:17190033

Pushing typists back on the learning curve: Memory chunking in the hierarchical control of skilled typewriting.

PubMed

Yamaguchi, Motonori; Logan, Gordon D

2016-12-01

Hierarchical control of skilled performance depends on the ability of higher level control to process several lower level units as a single chunk. The present study investigated the development of hierarchical control of skilled typewriting, focusing on the process of memory chunking. In the first 3 experiments, skilled typists typed words or nonwords under concurrent memory load. Memory chunks developed and consolidated into long-term memory when the same typing materials were repeated in 6 consecutive trials, but chunks did not develop when repetitions were spaced. However, when concurrent memory load was removed during training, memory chunks developed more efficiently with longer lags between repetitions than shorter lags. From these results, it is proposed that memory chunking requires 2 representations of the same letter string to be maintained simultaneously in short-term memory: 1 representation from the current trial, and the other from an earlier trial that is either retained from the immediately preceding trial or retrieved from long-term memory (i.e., study state retrieval). (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Undermining belief in false memories leads to less efficient problem-solving behaviour.

PubMed

Wang, Jianqin; Otgaar, Henry; Howe, Mark L; Smeets, Tom; Merckelbach, Harald; Nahouli, Zacharia

2017-08-01

Memories of events for which the belief in the occurrence of those events is undermined, but recollection is retained, are called nonbelieved memories (NBMs). The present experiments examined the effects of NBMs on subsequent problem-solving behaviour. In Experiment 1, we challenged participants' beliefs in their memories and examined whether NBMs affected subsequent solution rates on insight-based problems. True and false memories were elicited using the Deese/Roediger-McDermott (DRM) paradigm. Then participants' belief in true and false memories was challenged by telling them the item had not been presented. We found that when the challenge led to undermining belief in false memories, fewer problems were solved than when belief was not challenged. In Experiment 2, a similar procedure was used except that some participants solved the problems one week rather than immediately after the feedback. Again, our results showed that undermining belief in false memories resulted in lower problem solution rates. These findings suggest that for false memories, belief is an important agent in whether memories serve as effective primes for immediate and delayed problem-solving.

Combined Cognitive Training vs. Memory Strategy Training in Healthy Older Adults

PubMed Central

Li, Bing; Zhu, Xinyi; Hou, Jianhua; Chen, Tingji; Wang, Pengyun; Li, Juan

2016-01-01

As mnemonic utilization deficit in older adults associates with age-related decline in executive function, we hypothesized that memory strategy training combined with executive function training might induce larger training effect in memory and broader training effects in non-memory outcomes than pure memory training. The present study compared the effects of combined cognitive training (executive function training plus memory strategy training) to pure memory strategy training. Forty healthy older adults were randomly assigned to a combined cognitive training group or a memory strategy training group. A control group receiving no training was also included. Combined cognitive training group received 16 sessions of training (eight sessions of executive function training followed by eight sessions of memory strategy training). Memory training group received 16 sessions of memory strategy training. The results partly supported our hypothesis in that indeed improved performance on executive function was only found in combined training group, whereas memory performance increased less in combined training compared to memory strategy group. Results suggest that combined cognitive training may be less efficient than pure memory training in memory outcomes, though the influences from insufficient training time and less closeness between trained executive function and working memory could not be excluded; however it has broader training effects in non-memory outcomes. Clinical Trial Registration: www.chictr.org.cn, identifier ChiCTR-OON-16007793. PMID:27375521

Functional cross‐hemispheric shift between object‐place paired associate memory and spatial memory in the human hippocampus

PubMed Central

Lee, Choong‐Hee; Ryu, Jungwon; Lee, Sang‐Hun; Kim, Hakjin

2016-01-01

ABSTRACT The hippocampus plays critical roles in both object‐based event memory and spatial navigation, but it is largely unknown whether the left and right hippocampi play functionally equivalent roles in these cognitive domains. To examine the hemispheric symmetry of human hippocampal functions, we used an fMRI scanner to measure BOLD activity while subjects performed tasks requiring both object‐based event memory and spatial navigation in a virtual environment. Specifically, the subjects were required to form object‐place paired associate memory after visiting four buildings containing discrete objects in a virtual plus maze. The four buildings were visually identical, and the subjects used distal visual cues (i.e., scenes) to differentiate the buildings. During testing, the subjects were required to identify one of the buildings when cued with a previously associated object, and when shifted to a random place, the subject was expected to navigate to the previously chosen building. We observed that the BOLD activity foci changed from the left hippocampus to the right hippocampus as task demand changed from identifying a previously seen object (object‐cueing period) to searching for its paired‐associate place (object‐cued place recognition period). Furthermore, the efficient retrieval of object‐place paired associate memory (object‐cued place recognition period) was correlated with the BOLD response of the left hippocampus, whereas the efficient retrieval of relatively pure spatial memory (spatial memory period) was correlated with the right hippocampal BOLD response. These findings suggest that the left and right hippocampi in humans might process qualitatively different information for remembering episodic events in space. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc. PMID:27009679

Reduced prefrontal efficiency for visuospatial working memory in attention-deficit/hyperactivity disorder.

PubMed

Bédard, Anne-Claude V; Newcorn, Jeffrey H; Clerkin, Suzanne M; Krone, Beth; Fan, Jin; Halperin, Jeffrey M; Schulz, Kurt P

2014-09-01

Visuospatial working memory impairments have been implicated in the pathophysiology of attention-deficit/hyperactivity disorder (ADHD). However, most ADHD research has focused on the neural correlates of nonspatial mnemonic processes. This study examined brain activation and functional connectivity for visuospatial working memory in youth with and without ADHD. Twenty-four youth with ADHD and 21 age- and sex-matched healthy controls were scanned with functional magnetic resonance imaging while performing an N-back test of working memory for spatial position. Block-design analyses contrasted activation and functional connectivity separately for high (2-back) and low (1-back) working memory load conditions versus the control condition (0-back). The effect of working memory load was modeled with linear contrasts. The 2 groups performed comparably on the task and demonstrated similar patterns of frontoparietal activation, with no differences in linear gains in activation as working memory load increased. However, youth with ADHD showed greater activation in the left dorsolateral prefrontal cortex (DLPFC) and left posterior cingulate cortex (PCC), greater functional connectivity between the left DLPFC and left intraparietal sulcus, and reduced left DLPFC connectivity with left midcingulate cortex and PCC for the high load contrast compared to controls (p < .01; k > 100 voxels). Reanalysis using a more conservative statistical approach (p < .001; k > 100 voxels) yielded group differences in PCC activation and DLPFC-midcingulate connectivity. Youth with ADHD show decreased efficiency of DLPFC for high-load visuospatial working memory and greater reliance on posterior spatial attention circuits to store and update spatial position than healthy control youth. Findings should be replicated in larger samples. Copyright © 2014 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Memory is Not Enough: The Neurobiological Substrates of Dynamic Cognitive Reserve.

PubMed

Serra, Laura; Bruschini, Michela; Di Domenico, Carlotta; Gabrielli, Giulia Bechi; Marra, Camillo; Caltagirone, Carlo; Cercignani, Mara; Bozzali, Marco

2017-01-01

Changes in the residual memory variance are considered as a dynamic aspect of cognitive reserve (d-CR). We aimed to investigate for the first time the neural substrate associated with changes in the residual memory variance overtime in patients with amnestic mild cognitive impairment (aMCI). Thirty-four aMCI patients followed-up for 36 months and 48 healthy elderly individuals (HE) were recruited. All participants underwent 3T MRI, collecting T1-weighted images for voxel-based morphometry (VBM). They underwent an extensive neuropsychological battery, including six episodic memory tests. In patients and controls, factor analyses were used on the episodic memory scores to obtain a composite memory score (C-MS). Partial Least Square analyses were used to decompose the variance of C-MS in latent variables (LT scores), accounting for demographic variables and for the general cognitive efficiency level; linear regressions were applied on LT scores, striping off any contribution of general cognitive abilities, to obtain the residual value of memory variance, considered as an index of d-CR. LT scores and d-CR were used in discriminant analysis, in patients only. Finally, LT scores and d-CR were used as variable of interest in VBM analysis. The d-CR score was not able to correctly classify patients. In both aMCI patients and HE, LT1st and d-CR scores showed correlations with grey matter volumes in common and in specific brain areas. Using CR measures limited to assess memory function is likely less sensitive to detect the cognitive decline and predict the evolution of Alzheimer's disease. In conclusion, d-CR needs a measure of general cognition to identify conversion to Alzheimer's disease efficiently.

Memory-Efficient Analysis of Dense Functional Connectomes.

PubMed

Loewe, Kristian; Donohue, Sarah E; Schoenfeld, Mircea A; Kruse, Rudolf; Borgelt, Christian

2016-01-01

The functioning of the human brain relies on the interplay and integration of numerous individual units within a complex network. To identify network configurations characteristic of specific cognitive tasks or mental illnesses, functional connectomes can be constructed based on the assessment of synchronous fMRI activity at separate brain sites, and then analyzed using graph-theoretical concepts. In most previous studies, relatively coarse parcellations of the brain were used to define regions as graphical nodes. Such parcellated connectomes are highly dependent on parcellation quality because regional and functional boundaries need to be relatively consistent for the results to be interpretable. In contrast, dense connectomes are not subject to this limitation, since the parcellation inherent to the data is used to define graphical nodes, also allowing for a more detailed spatial mapping of connectivity patterns. However, dense connectomes are associated with considerable computational demands in terms of both time and memory requirements. The memory required to explicitly store dense connectomes in main memory can render their analysis infeasible, especially when considering high-resolution data or analyses across multiple subjects or conditions. Here, we present an object-based matrix representation that achieves a very low memory footprint by computing matrix elements on demand instead of explicitly storing them. In doing so, memory required for a dense connectome is reduced to the amount needed to store the underlying time series data. Based on theoretical considerations and benchmarks, different matrix object implementations and additional programs (based on available Matlab functions and Matlab-based third-party software) are compared with regard to their computational efficiency. The matrix implementation based on on-demand computations has very low memory requirements, thus enabling analyses that would be otherwise infeasible to conduct due to insufficient memory. An open source software package containing the created programs is available for download.

Memory-Efficient Analysis of Dense Functional Connectomes

PubMed Central

Loewe, Kristian; Donohue, Sarah E.; Schoenfeld, Mircea A.; Kruse, Rudolf; Borgelt, Christian

2016-01-01

The functioning of the human brain relies on the interplay and integration of numerous individual units within a complex network. To identify network configurations characteristic of specific cognitive tasks or mental illnesses, functional connectomes can be constructed based on the assessment of synchronous fMRI activity at separate brain sites, and then analyzed using graph-theoretical concepts. In most previous studies, relatively coarse parcellations of the brain were used to define regions as graphical nodes. Such parcellated connectomes are highly dependent on parcellation quality because regional and functional boundaries need to be relatively consistent for the results to be interpretable. In contrast, dense connectomes are not subject to this limitation, since the parcellation inherent to the data is used to define graphical nodes, also allowing for a more detailed spatial mapping of connectivity patterns. However, dense connectomes are associated with considerable computational demands in terms of both time and memory requirements. The memory required to explicitly store dense connectomes in main memory can render their analysis infeasible, especially when considering high-resolution data or analyses across multiple subjects or conditions. Here, we present an object-based matrix representation that achieves a very low memory footprint by computing matrix elements on demand instead of explicitly storing them. In doing so, memory required for a dense connectome is reduced to the amount needed to store the underlying time series data. Based on theoretical considerations and benchmarks, different matrix object implementations and additional programs (based on available Matlab functions and Matlab-based third-party software) are compared with regard to their computational efficiency. The matrix implementation based on on-demand computations has very low memory requirements, thus enabling analyses that would be otherwise infeasible to conduct due to insufficient memory. An open source software package containing the created programs is available for download. PMID:27965565

Impairments in Component Processes of Executive Function and Episodic Memory in Alcoholism, HIV Infection, and HIV Infection with Alcoholism Comorbidity.

PubMed

Fama, Rosemary; Sullivan, Edith V; Sassoon, Stephanie A; Pfefferbaum, Adolf; Zahr, Natalie M

2016-12-01

Executive functioning and episodic memory impairment occur in HIV infection (HIV) and chronic alcoholism (ALC). Comorbidity of these conditions (HIV + ALC) is prevalent and heightens risk of vulnerability to separate and compounded deficits. Age and disease-related variables can also serve as mediators of cognitive impairment and should be considered, given the extended longevity of HIV-infected individuals in this era of improved pharmacological therapy. HIV, ALC, HIV + ALC, and normal controls (NC) were administered traditional and computerized tests of executive function and episodic memory. Test scores were expressed as age- and education-corrected Z-scores; selective tests were averaged to compute Executive Function and Episodic Memory Composite scores. Efficiency scores were calculated for tests with accuracy and response times. HIV, ALC, and HIV + ALC had lower scores than NC on Executive Function and Episodic Memory Composites, with HIV + ALC even lower than ALC and HIV on the Episodic Memory Composite. Impairments in planning and free recall of visuospatial material were observed in ALC, whereas impairments in psychomotor speed, sequencing, narrative free recall, and pattern recognition were observed in HIV. Lower decision-making efficiency scores than NC occurred in all 3 clinical groups. In ALC, age and lifetime alcohol consumption were each unique predictors of Executive Function and Episodic Memory Composite scores. In HIV + ALC, age was a unique predictor of Episodic Memory Composite score. Disease-specific and disease-overlapping patterns of impairment in HIV, ALC, and HIV + ALC have implications regarding brain systems disrupted by each disease and clinical ramifications regarding the complexities and compounded damping of cognitive functioning associated with dual diagnosis that may be exacerbated with aging. Copyright © 2016 by the Research Society on Alcoholism.

Bundle block adjustment of large-scale remote sensing data with Block-based Sparse Matrix Compression combined with Preconditioned Conjugate Gradient

NASA Astrophysics Data System (ADS)

Zheng, Maoteng; Zhang, Yongjun; Zhou, Shunping; Zhu, Junfeng; Xiong, Xiaodong

2016-07-01

In recent years, new platforms and sensors in photogrammetry, remote sensing and computer vision areas have become available, such as Unmanned Aircraft Vehicles (UAV), oblique camera systems, common digital cameras and even mobile phone cameras. Images collected by all these kinds of sensors could be used as remote sensing data sources. These sensors can obtain large-scale remote sensing data which consist of a great number of images. Bundle block adjustment of large-scale data with conventional algorithm is very time and space (memory) consuming due to the super large normal matrix arising from large-scale data. In this paper, an efficient Block-based Sparse Matrix Compression (BSMC) method combined with the Preconditioned Conjugate Gradient (PCG) algorithm is chosen to develop a stable and efficient bundle block adjustment system in order to deal with the large-scale remote sensing data. The main contribution of this work is the BSMC-based PCG algorithm which is more efficient in time and memory than the traditional algorithm without compromising the accuracy. Totally 8 datasets of real data are used to test our proposed method. Preliminary results have shown that the BSMC method can efficiently decrease the time and memory requirement of large-scale data.

Working memory capacity predicts listwise directed forgetting in adults and children.

PubMed

Aslan, Alp; Zellner, Martina; Bäuml, Karl-Heinz T

2010-05-01

In listwise directed forgetting, participants are cued to forget previously studied material and to learn new material instead. Such cueing typically leads to forgetting of the first set of material and to memory enhancement of the second. The present study examined the role of working memory capacity in adults' and children's listwise directed forgetting. Working memory capacity was assessed with complex span tasks. In Experiment 1 working memory capacity predicted young adults' directed-forgetting performance, demonstrating a positive relationship between working memory capacity and each of the two directed-forgetting effects. In Experiment 2 we replicated the finding with a sample of first and a sample of fourth-grade children, and additionally showed that working memory capacity can account for age-related increases in directed-forgetting efficiency between the two age groups. Following the view that directed forgetting is mediated by inhibition of the first encoded list, the results support the proposal of a close link between working memory capacity and inhibitory function.

Holographic implementation of a binary associative memory for improved recognition

NASA Astrophysics Data System (ADS)

Bandyopadhyay, Somnath; Ghosh, Ajay; Datta, Asit K.

1998-03-01

Neural network associate memory has found wide application sin pattern recognition techniques. We propose an associative memory model for binary character recognition. The interconnection strengths of the memory are binary valued. The concept of sparse coding is sued to enhance the storage efficiency of the model. The question of imposed preconditioning of pattern vectors, which is inherent in a sparsely coded conventional memory, is eliminated by using a multistep correlation technique an the ability of correct association is enhanced in a real-time application. A potential optoelectronic implementation of the proposed associative memory is also described. The learning and recall is possible by using digital optical matrix-vector multiplication, where full use of parallelism and connectivity of optics is made. A hologram is used in the experiment as a longer memory (LTM) for storing all input information. The short-term memory or the interconnection weight matrix required during the recall process is configured by retrieving the necessary information from the holographic LTM.

The role of memory for visual search in scenes

PubMed Central

Võ, Melissa Le-Hoa; Wolfe, Jeremy M.

2014-01-01

Many daily activities involve looking for something. The ease with which these searches are performed often allows one to forget that searching represents complex interactions between visual attention and memory. While a clear understanding exists of how search efficiency will be influenced by visual features of targets and their surrounding distractors or by the number of items in the display, the role of memory in search is less well understood. Contextual cueing studies have shown that implicit memory for repeated item configurations can facilitate search in artificial displays. When searching more naturalistic environments, other forms of memory come into play. For instance, semantic memory provides useful information about which objects are typically found where within a scene, and episodic scene memory provides information about where a particular object was seen the last time a particular scene was viewed. In this paper, we will review work on these topics, with special emphasis on the role of memory in guiding search in organized, real-world scenes. PMID:25684693

High-speed noise-free optical quantum memory

NASA Astrophysics Data System (ADS)

Kaczmarek, K. T.; Ledingham, P. M.; Brecht, B.; Thomas, S. E.; Thekkadath, G. S.; Lazo-Arjona, O.; Munns, J. H. D.; Poem, E.; Feizpour, A.; Saunders, D. J.; Nunn, J.; Walmsley, I. A.

2018-04-01

Optical quantum memories are devices that store and recall quantum light and are vital to the realization of future photonic quantum networks. To date, much effort has been put into improving storage times and efficiencies of such devices to enable long-distance communications. However, less attention has been devoted to building quantum memories which add zero noise to the output. Even small additional noise can render the memory classical by destroying the fragile quantum signatures of the stored light. Therefore, noise performance is a critical parameter for all quantum memories. Here we introduce an intrinsically noise-free quantum memory protocol based on two-photon off-resonant cascaded absorption (ORCA). We demonstrate successful storage of GHz-bandwidth heralded single photons in a warm atomic vapor with no added noise, confirmed by the unaltered photon-number statistics upon recall. Our ORCA memory meets the stringent noise requirements for quantum memories while combining high-speed and room-temperature operation with technical simplicity, and therefore is immediately applicable to low-latency quantum networks.

The role of memory for visual search in scenes.

PubMed

Le-Hoa Võ, Melissa; Wolfe, Jeremy M

2015-03-01

Many daily activities involve looking for something. The ease with which these searches are performed often allows one to forget that searching represents complex interactions between visual attention and memory. Although a clear understanding exists of how search efficiency will be influenced by visual features of targets and their surrounding distractors or by the number of items in the display, the role of memory in search is less well understood. Contextual cueing studies have shown that implicit memory for repeated item configurations can facilitate search in artificial displays. When searching more naturalistic environments, other forms of memory come into play. For instance, semantic memory provides useful information about which objects are typically found where within a scene, and episodic scene memory provides information about where a particular object was seen the last time a particular scene was viewed. In this paper, we will review work on these topics, with special emphasis on the role of memory in guiding search in organized, real-world scenes. © 2015 New York Academy of Sciences.

Image detection and compression for memory efficient system analysis

NASA Astrophysics Data System (ADS)

Bayraktar, Mustafa

2015-02-01

The advances in digital signal processing have been progressing towards efficient use of memory and processing. Both of these factors can be utilized efficiently by using feasible techniques of image storage by computing the minimum information of image which will enhance computation in later processes. Scale Invariant Feature Transform (SIFT) can be utilized to estimate and retrieve of an image. In computer vision, SIFT can be implemented to recognize the image by comparing its key features from SIFT saved key point descriptors. The main advantage of SIFT is that it doesn't only remove the redundant information from an image but also reduces the key points by matching their orientation and adding them together in different windows of image [1]. Another key property of this approach is that it works on highly contrasted images more efficiently because it`s design is based on collecting key points from the contrast shades of image.

Learning Efficiency: Identifying Individual Differences in Learning Rate and Retention in Healthy Adults.

PubMed

Zerr, Christopher L; Berg, Jeffrey J; Nelson, Steven M; Fishell, Andrew K; Savalia, Neil K; McDermott, Kathleen B

2018-06-01

People differ in how quickly they learn information and how long they remember it, yet individual differences in learning abilities within healthy adults have been relatively neglected. In two studies, we examined the relation between learning rate and subsequent retention using a new foreign-language paired-associates task (the learning-efficiency task), which was designed to eliminate ceiling effects that often accompany standardized tests of learning and memory in healthy adults. A key finding was that quicker learners were also more durable learners (i.e., exhibited better retention across a delay), despite studying the material for less time. Additionally, measures of learning and memory from this task were reliable in Study 1 ( N = 281) across 30 hr and Study 2 ( N = 92; follow-up n = 46) across 3 years. We conclude that people vary in how efficiently they learn, and we describe a reliable and valid method for assessing learning efficiency within healthy adults.

Efficient computation of the Grünwald-Letnikov fractional diffusion derivative using adaptive time step memory

NASA Astrophysics Data System (ADS)

MacDonald, Christopher L.; Bhattacharya, Nirupama; Sprouse, Brian P.; Silva, Gabriel A.

2015-09-01

Computing numerical solutions to fractional differential equations can be computationally intensive due to the effect of non-local derivatives in which all previous time points contribute to the current iteration. In general, numerical approaches that depend on truncating part of the system history while efficient, can suffer from high degrees of error and inaccuracy. Here we present an adaptive time step memory method for smooth functions applied to the Grünwald-Letnikov fractional diffusion derivative. This method is computationally efficient and results in smaller errors during numerical simulations. Sampled points along the system's history at progressively longer intervals are assumed to reflect the values of neighboring time points. By including progressively fewer points backward in time, a temporally 'weighted' history is computed that includes contributions from the entire past of the system, maintaining accuracy, but with fewer points actually calculated, greatly improving computational efficiency.

Intraday return inefficiency and long memory in the volatilities of forex markets and the role of trading volume

NASA Astrophysics Data System (ADS)

Shahzad, Syed Jawad Hussain; Hernandez, Jose Areola; Hanif, Waqas; Kayani, Ghulam Mujtaba

2018-09-01

We investigate the dynamics of efficiency and long memory, and the impact of trading volume on the efficiency of returns and volatilities of four major traded currencies, namely, the EUR, GBP, CHF and JPY. We do so by implementing full sample and rolling window multifractal detrended fluctuation analysis (MF-DFA) and a quantile-on-quantile (QQ) approach. This paper sheds new light by employing high frequency (5-min interval) data spanning from Jan 1, 2007 to Dec 31, 2016. Realized volatilities are estimated using Andersen et al.'s (2001) measure, while the QQ method employed is drawn from Sim and Zhou (2015). We find evidence of higher efficiency levels in the JPY and CHF currency markets. The impact of trading volume on efficiency is only significant for the JPY and CHF currencies. The GBP currency appears to be the least efficient, followed by the EUR. Implications of the results are discussed.

Healthcare knowledge management through building and operationalising healthcare enterprise memory.

PubMed

Cheah, Y N; Abidi, S S

1999-01-01

In this paper we suggest that the healthcare enterprise needs to be more conscious of its vast knowledge resources vis-à-vis the exploitation of knowledge management techniques to efficiently manage its knowledge. The development of healthcare enterprise memory is suggested as a solution, together with a novel approach advocating the operationalisation of healthcare enterprise memories leading to the modelling of healthcare processes for strategic planning. As an example, we present a simulation of Service Delivery Time in a hospital's OPD.

Memory CD4+ T cells: beyond “helper” functions

PubMed Central

Boonnak, Kobporn; Subbarao, Kanta

2012-01-01

In influenza virus infection, antibodies, memory CD8+ T cells, and CD4+ T cells have all been shown to mediate immune protection, but how they operate and interact with one another to mediate efficient immune responses against virus infection is not well understood. In this issue of the JCI, McKinstry et al. have identified unique functions of memory CD4+ T cells beyond providing “help” for B cell and CD8+ T cell responses during influenza virus infection. PMID:22820285

Development and Evaluation of a Casualty Evacuation Model for a European Conflict.

DTIC Science & Technology

1985-12-01

EVAC, the computer code which implements our technique, has been used to solve a series of test problems in less time and requiring less memory than...the order of 1/K the amount of main memory for a K-commodity problem, so it can solve significantly larger problems than MCNF. I . 10 CHAPTER II A...technique may require only half the memory of the general L.P. package [6]. These advances are due to the efficient data structures which have been

Processing Efficiency in Preschoolers' Memory Span: Individual Differences Related to Age and Anxiety

ERIC Educational Resources Information Center

Visu-Petra, Laura; Miclea, Mircea; Cheie, Lavinia; Benga, Oana

2009-01-01

In self-paced auditory memory span tasks, the microanalysis of response timing measures represents a developmentally sensitive measure, providing insights into the development of distinct processing rates during recall performance. The current study first examined the effects of age and trait anxiety on span accuracy (effectiveness) and response…

An Integrated Decision-Making Framework for Sustainability Assessment: A Case Study of Memorial University

ERIC Educational Resources Information Center

Waheed, Bushra; Khan, Faisal; Veitch, Brian; Hawboldt, Kelly

2011-01-01

This article presents an overview of the sustainability initiatives at the St. John's campus of Memorial University in Newfoundland and Labrador (Canada). The key initiatives include setting a realistic goal for energy efficiency, becoming carbon neutral, and conducting various research and outreach projects related to sustainability. As…

Working Memory Deficits, Increased Anxiety-Like Traits, and Seizure Susceptibility in BDNF Overexpressing Mice

ERIC Educational Resources Information Center

Papaleo, Francesco; Silverman, Jill L.; Aney, Jordan; Tian, Qingjun; Barkan, Charlotte L.; Chadman, Kathryn K.; Crawley, Jacqueline N.

2011-01-01

BDNF regulates components of cognitive processes and has been implicated in psychiatric disorders. Here we report that genetic overexpression of the BDNF mature isoform (BDNF-tg) in female mice impaired working memory functions while sparing components of fear conditioning. BDNF-tg mice also displayed reduced breeding efficiency, higher…

A multiresolution halftoning algorithm for progressive display

NASA Astrophysics Data System (ADS)

Mukherjee, Mithun; Sharma, Gaurav

2005-01-01

We describe and implement an algorithmic framework for memory efficient, 'on-the-fly' halftoning in a progressive transmission environment. Instead of a conventional approach which repeatedly recalls the continuous tone image from memory and subsequently halftones it for display, the proposed method achieves significant memory efficiency by storing only the halftoned image and updating it in response to additional information received through progressive transmission. Thus the method requires only a single frame-buffer of bits for storage of the displayed binary image and no additional storage is required for the contone data. The additional image data received through progressive transmission is accommodated through in-place updates of the buffer. The method is thus particularly advantageous for high resolution bi-level displays where it can result in significant savings in memory. The proposed framework is implemented using a suitable multi-resolution, multi-level modification of error diffusion that is motivated by the presence of a single binary frame-buffer. Aggregates of individual display bits constitute the multiple output levels at a given resolution. This creates a natural progression of increasing resolution with decreasing bit-depth.

Visual Search Elicits the Electrophysiological Marker of Visual Working Memory

PubMed Central

Emrich, Stephen M.; Al-Aidroos, Naseem; Pratt, Jay; Ferber, Susanne

2009-01-01

Background Although limited in capacity, visual working memory (VWM) plays an important role in many aspects of visually-guided behavior. Recent experiments have demonstrated an electrophysiological marker of VWM encoding and maintenance, the contralateral delay activity (CDA), which has been shown in multiple tasks that have both explicit and implicit memory demands. Here, we investigate whether the CDA is evident during visual search, a thoroughly-researched task that is a hallmark of visual attention but has no explicit memory requirements. Methodology/Principal Findings The results demonstrate that the CDA is present during a lateralized search task, and that it is similar in amplitude to the CDA observed in a change-detection task, but peaks slightly later. The changes in CDA amplitude during search were strongly correlated with VWM capacity, as well as with search efficiency. These results were paralleled by behavioral findings showing a strong correlation between VWM capacity and search efficiency. Conclusions/Significance We conclude that the activity observed during visual search was generated by the same neural resources that subserve VWM, and that this activity reflects the maintenance of previously searched distractors. PMID:19956663

Age differences in memory control: evidence from updating and retrieval-practice tasks.

PubMed

Lechuga, Maria Teresa; Moreno, Virginia; Pelegrina, Santiago; Gómez-Ariza, Carlos J; Bajo, Maria Teresa

2006-11-01

Some contemporary approaches suggest that inhibitory mechanisms play an important role in cognitive development. In addition, several authors distinguish between intentional and unintentional inhibitory processes in cognition. We report two experiments aimed at exploring possible developmental changes in these two types of inhibitory mechanisms. In Experiment 1, an updating task was used. This task requires that participants intentionally suppress irrelevant information from working memory. In Experiment 2, the retrieval-practice task was used. Retrieval practice of a subset of studied items is thought to involve unintentional inhibitory processes to overcome interference from competing memories. As a result, suppressed items become forgotten in a later memory test. Results of the experiments indicated that younger children (8) were less efficient than older children (12) and adults at intentionally suppressing information (updating task). However, when the task required unintentional inhibition of competing items (retrieval-practice task), this developmental trend was not found and children and adults showed similar levels of retrieval-induced forgetting. The results are discussed in terms of the development of efficient inhibition and the distinction between intentional and unintentional inhibitions.

Distributed-Memory Fast Maximal Independent Set

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kanewala Appuhamilage, Thejaka Amila J.; Zalewski, Marcin J.; Lumsdaine, Andrew

The Maximal Independent Set (MIS) graph problem arises in many applications such as computer vision, information theory, molecular biology, and process scheduling. The growing scale of MIS problems suggests the use of distributed-memory hardware as a cost-effective approach to providing necessary compute and memory resources. Luby proposed four randomized algorithms to solve the MIS problem. All those algorithms are designed focusing on shared-memory machines and are analyzed using the PRAM model. These algorithms do not have direct efficient distributed-memory implementations. In this paper, we extend two of Luby’s seminal MIS algorithms, “Luby(A)” and “Luby(B),” to distributed-memory execution, and we evaluatemore » their performance. We compare our results with the “Filtered MIS” implementation in the Combinatorial BLAS library for two types of synthetic graph inputs.« less

An English Vocabulary Learning System Based on Fuzzy Theory and Memory Cycle

NASA Astrophysics Data System (ADS)

Wang, Tzone I.; Chiu, Ti Kai; Huang, Liang Jun; Fu, Ru Xuan; Hsieh, Tung-Cheng

This paper proposes an English Vocabulary Learning System based on the Fuzzy Theory and the Memory Cycle Theory to help a learner to memorize vocabularies easily. By using fuzzy inferences and personal memory cycles, it is possible to find an article that best suits a learner. After reading an article, a quiz is provided for the learner to improve his/her memory of the vocabulary in the article. Early researches use just explicit response (ex. quiz exam) to update memory cycles of newly learned vocabulary; apart from that approach, this paper proposes a methodology that also modify implicitly the memory cycles of learned word. By intensive reading of articles recommended by our approach, a learner learns new words quickly and reviews learned words implicitly as well, and by which the vocabulary ability of the learner improves efficiently.

Unconditional room-temperature quantum memory

NASA Astrophysics Data System (ADS)

Hosseini, M.; Campbell, G.; Sparkes, B. M.; Lam, P. K.; Buchler, B. C.

2011-10-01

Just as classical information systems require buffers and memory, the same is true for quantum information systems. The potential that optical quantum information processing holds for revolutionizing computation and communication is therefore driving significant research into developing optical quantum memory. A practical optical quantum memory must be able to store and recall quantum states on demand with high efficiency and low noise. Ideally, the platform for the memory would also be simple and inexpensive. Here, we present a complete tomographic reconstruction of quantum states that have been stored in the ground states of rubidium in a vapour cell operating at around 80°C. Without conditional measurements, we show recall fidelity up to 98% for coherent pulses containing around one photon. To unambiguously verify that our memory beats the quantum no-cloning limit we employ state-independent verification using conditional variance and signal-transfer coefficients.

Fast maximum intensity projections of large medical data sets by exploiting hierarchical memory architectures.

PubMed

Kiefer, Gundolf; Lehmann, Helko; Weese, Jürgen

2006-04-01

Maximum intensity projections (MIPs) are an important visualization technique for angiographic data sets. Efficient data inspection requires frame rates of at least five frames per second at preserved image quality. Despite the advances in computer technology, this task remains a challenge. On the one hand, the sizes of computed tomography and magnetic resonance images are increasing rapidly. On the other hand, rendering algorithms do not automatically benefit from the advances in processor technology, especially for large data sets. This is due to the faster evolving processing power and the slower evolving memory access speed, which is bridged by hierarchical cache memory architectures. In this paper, we investigate memory access optimization methods and use them for generating MIPs on general-purpose central processing units (CPUs) and graphics processing units (GPUs), respectively. These methods can work on any level of the memory hierarchy, and we show that properly combined methods can optimize memory access on multiple levels of the hierarchy at the same time. We present performance measurements to compare different algorithm variants and illustrate the influence of the respective techniques. On current hardware, the efficient handling of the memory hierarchy for CPUs improves the rendering performance by a factor of 3 to 4. On GPUs, we observed that the effect is even larger, especially for large data sets. The methods can easily be adjusted to different hardware specifics, although their impact can vary considerably. They can also be used for other rendering techniques than MIPs, and their use for more general image processing task could be investigated in the future.

Age-specific effects of voluntary exercise on memory and the older brain.

PubMed

Siette, Joyce; Westbrook, R Frederick; Cotman, Carl; Sidhu, Kuldip; Zhu, Wanlin; Sachdev, Perminder; Valenzuela, Michael J

2013-03-01

Physical exercise in early adulthood and mid-life improves cognitive function and enhances brain plasticity, but the effects of commencing exercise in late adulthood are not well-understood. We investigated the effects of voluntary exercise in the restoration of place recognition memory in aged rats and examined hippocampal changes of synaptic density and neurogenesis. We found a highly selective age-related deficit in place recognition memory that is stable across retest sessions and correlates strongly with loss of hippocampal synapses. Additionally, 12 weeks of voluntary running at 20 months of age removed the deficit in the hippocampally dependent place recognition memory. Voluntary running restored presynaptic density in the dentate gyrus and CA3 hippocampal subregions in aged rats to levels beyond those observed in younger animals, in which exercise had no functional or synaptic effects. By contrast, hippocampal neurogenesis, a possible memory-related mechanism, increased in both young and aged rats after physical exercise but was not linked with performance in the place recognition task. We used graph-based network analysis based on synaptic covariance patterns to characterize efficient intrahippocampal connectivity. This analysis revealed that voluntary running completely reverses the profound degradation of hippocampal network efficiency that accompanies sedentary aging. Furthermore, at an individual animal level, both overall hippocampal presynaptic density and subregional connectivity independently contribute to prediction of successful place recognition memory performance. Our findings emphasize the unique synaptic effects of exercise on the aged brain and their specific relevance to a hippocampally based memory system for place recognition. Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Extending the BEAGLE library to a multi-FPGA platform

PubMed Central

2013-01-01

Background Maximum Likelihood (ML)-based phylogenetic inference using Felsenstein’s pruning algorithm is a standard method for estimating the evolutionary relationships amongst a set of species based on DNA sequence data, and is used in popular applications such as RAxML, PHYLIP, GARLI, BEAST, and MrBayes. The Phylogenetic Likelihood Function (PLF) and its associated scaling and normalization steps comprise the computational kernel for these tools. These computations are data intensive but contain fine grain parallelism that can be exploited by coprocessor architectures such as FPGAs and GPUs. A general purpose API called BEAGLE has recently been developed that includes optimized implementations of Felsenstein’s pruning algorithm for various data parallel architectures. In this paper, we extend the BEAGLE API to a multiple Field Programmable Gate Array (FPGA)-based platform called the Convey HC-1. Results The core calculation of our implementation, which includes both the phylogenetic likelihood function (PLF) and the tree likelihood calculation, has an arithmetic intensity of 130 floating-point operations per 64 bytes of I/O, or 2.03 ops/byte. Its performance can thus be calculated as a function of the host platform’s peak memory bandwidth and the implementation’s memory efficiency, as 2.03 × peak bandwidth × memory efficiency. Our FPGA-based platform has a peak bandwidth of 76.8 GB/s and our implementation achieves a memory efficiency of approximately 50%, which gives an average throughput of 78 Gflops. This represents a ~40X speedup when compared with BEAGLE’s CPU implementation on a dual Xeon 5520 and 3X speedup versus BEAGLE’s GPU implementation on a Tesla T10 GPU for very large data sizes. The power consumption is 92 W, yielding a power efficiency of 1.7 Gflops per Watt. Conclusions The use of data parallel architectures to achieve high performance for likelihood-based phylogenetic inference requires high memory bandwidth and a design methodology that emphasizes high memory efficiency. To achieve this objective, we integrated 32 pipelined processing elements (PEs) across four FPGAs. For the design of each PE, we developed a specialized synthesis tool to generate a floating-point pipeline with resource and throughput constraints to match the target platform. We have found that using low-latency floating-point operators can significantly reduce FPGA area and still meet timing requirement on the target platform. We found that this design methodology can achieve performance that exceeds that of a GPU-based coprocessor. PMID:23331707

Complementary-encoding holographic associative memory using a photorefractive crystal

NASA Astrophysics Data System (ADS)

Yuan, ShiFu; Wu, Minxian; Yan, Yingbai; Jin, Guofan

1996-06-01

We present a holographic implementation of accurate associative memory with only one holographic memory system. In the implementation, the stored and test images are coded by using complementary-encoding method. The recalled complete image is also a coded image that can be decoded with a decoding mask to get an original image or its complement image. The experiment shows that the complementary encoding can efficiently increase the addressing accuracy in a simple way. Instead of the above complementary-encoding method, a scheme that uses complementary area-encoding method is also proposed for the holographic implementation of gray-level image associative memory with accurate addressing.

Efficient packing of patterns in sparse distributed memory by selective weighting of input bits

NASA Technical Reports Server (NTRS)

Kanerva, Pentti

1991-01-01

When a set of patterns is stored in a distributed memory, any given storage location participates in the storage of many patterns. From the perspective of any one stored pattern, the other patterns act as noise, and such noise limits the memory's storage capacity. The more similar the retrieval cues for two patterns are, the more the patterns interfere with each other in memory, and the harder it is to separate them on retrieval. A method is described of weighting the retrieval cues to reduce such interference and thus to improve the separability of patterns that have similar cues.

Memory and Spin Injection Devices Involving Half Metals

DOE PAGES

Shaughnessy, M.; Snow, Ryan; Damewood, L.; ...

2011-01-01

We suggest memory and spin injection devices fabricated with half-metallic materials and based on the anomalous Hall effect. Schematic diagrams of the memory chips, in thin film and bulk crystal form, are presented. Spin injection devices made in thin film form are also suggested. These devices do not need any external magnetic field but make use of their own magnetization. Only a gate voltage is needed. The carriers are 100% spin polarized. Memory devices may potentially be smaller, faster, and less volatile than existing ones, and the injection devices may be much smaller and more efficient than existing spin injectionmore » devices.« less

Programming distributed memory architectures using Kali

NASA Technical Reports Server (NTRS)

Mehrotra, Piyush; Vanrosendale, John

1990-01-01

Programming nonshared memory systems is more difficult than programming shared memory systems, in part because of the relatively low level of current programming environments for such machines. A new programming environment is presented, Kali, which provides a global name space and allows direct access to remote data values. In order to retain efficiency, Kali provides a system on annotations, allowing the user to control those aspects of the program critical to performance, such as data distribution and load balancing. The primitives and constructs provided by the language is described, and some of the issues raised in translating a Kali program for execution on distributed memory systems are also discussed.

Efficient linear algebra routines for symmetric matrices stored in packed form.

PubMed

Ahlrichs, Reinhart; Tsereteli, Kakha

2002-01-30

Quantum chemistry methods require various linear algebra routines for symmetric matrices, for example, diagonalization or Cholesky decomposition for positive matrices. We present a small set of these basic routines that are efficient and minimize memory requirements.

Attractor neural networks with resource-efficient synaptic connectivity

NASA Astrophysics Data System (ADS)

Pehlevan, Cengiz; Sengupta, Anirvan

Memories are thought to be stored in the attractor states of recurrent neural networks. Here we explore how resource constraints interplay with memory storage function to shape synaptic connectivity of attractor networks. We propose that given a set of memories, in the form of population activity patterns, the neural circuit choses a synaptic connectivity configuration that minimizes a resource usage cost. We argue that the total synaptic weight (l1-norm) in the network measures the resource cost because synaptic weight is correlated with synaptic volume, which is a limited resource, and is proportional to neurotransmitter release and post-synaptic current, both of which cost energy. Using numerical simulations and replica theory, we characterize optimal connectivity profiles in resource-efficient attractor networks. Our theory explains several experimental observations on cortical connectivity profiles, 1) connectivity is sparse, because synapses are costly, 2) bidirectional connections are overrepresented and 3) are stronger, because attractor states need strong recurrence.

Exploring the effect of depressive symptoms and ageing on metamemory in an Italian adult sample.

PubMed

Fastame, Maria Chiara

2014-01-01

The current study aimed to investigate the effect of depression and age-related factors on metamemory measures in an Italian adult sample. Fifty-eight healthy participants were recruited in Northern Italy and were, respectively, assigned to the following groups: Young (20-30 years old), old (60-70 years old), and Very Old (71-84 years old). Participants were administered a battery of tests, including a word recall task, self-referent mnestic efficiency scales, general beliefs about memory, and depression measures. General beliefs about memory, self-efficacy, and beliefs about the control of personal memory were predicted by age, education, depression, and mnestic and cognitive efficiency. Finally, age-related differences were found in metamemory measures: the accuracy of mnestic control processes is thought to be lower by very old adults than by old and young individuals.

Survival Processing Enhances Visual Search Efficiency.

PubMed

Cho, Kit W

2018-05-01

Words rated for their survival relevance are remembered better than when rated using other well-known memory mnemonics. This finding, which is known as the survival advantage effect and has been replicated in many studies, suggests that our memory systems are molded by natural selection pressures. In two experiments, the present study used a visual search task to examine whether there is likewise a survival advantage for our visual systems. Participants rated words for their survival relevance or for their pleasantness before locating that object's picture in a search array with 8 or 16 objects. Although there was no difference in search times among the two rating scenarios when set size was 8, survival processing reduced visual search times when set size was 16. These findings reflect a search efficiency effect and suggest that similar to our memory systems, our visual systems are also tuned toward self-preservation.

Design of a Variational Multiscale Method for Turbulent Compressible Flows

NASA Technical Reports Server (NTRS)

Diosady, Laslo Tibor; Murman, Scott M.

2013-01-01

A spectral-element framework is presented for the simulation of subsonic compressible high-Reynolds-number flows. The focus of the work is maximizing the efficiency of the computational schemes to enable unsteady simulations with a large number of spatial and temporal degrees of freedom. A collocation scheme is combined with optimized computational kernels to provide a residual evaluation with computational cost independent of order of accuracy up to 16th order. The optimized residual routines are used to develop a low-memory implicit scheme based on a matrix-free Newton-Krylov method. A preconditioner based on the finite-difference diagonalized ADI scheme is developed which maintains the low memory of the matrix-free implicit solver, while providing improved convergence properties. Emphasis on low memory usage throughout the solver development is leveraged to implement a coupled space-time DG solver which may offer further efficiency gains through adaptivity in both space and time.

Binary Associative Memories as a Benchmark for Spiking Neuromorphic Hardware

PubMed Central

Stöckel, Andreas; Jenzen, Christoph; Thies, Michael; Rückert, Ulrich

2017-01-01

Large-scale neuromorphic hardware platforms, specialized computer systems for energy efficient simulation of spiking neural networks, are being developed around the world, for example as part of the European Human Brain Project (HBP). Due to conceptual differences, a universal performance analysis of these systems in terms of runtime, accuracy and energy efficiency is non-trivial, yet indispensable for further hard- and software development. In this paper we describe a scalable benchmark based on a spiking neural network implementation of the binary neural associative memory. We treat neuromorphic hardware and software simulators as black-boxes and execute exactly the same network description across all devices. Experiments on the HBP platforms under varying configurations of the associative memory show that the presented method allows to test the quality of the neuron model implementation, and to explain significant deviations from the expected reference output. PMID:28878642

Entanglement distillation for quantum communication network with atomic-ensemble memories.

PubMed

Li, Tao; Yang, Guo-Jian; Deng, Fu-Guo

2014-10-06

Atomic ensembles are effective memory nodes for quantum communication network due to the long coherence time and the collective enhancement effect for the nonlinear interaction between an ensemble and a photon. Here we investigate the possibility of achieving the entanglement distillation for nonlocal atomic ensembles by the input-output process of a single photon as a result of cavity quantum electrodynamics. We give an optimal entanglement concentration protocol (ECP) for two-atomic-ensemble systems in a partially entangled pure state with known parameters and an efficient ECP for the systems in an unknown partially entangled pure state with a nondestructive parity-check detector (PCD). For the systems in a mixed entangled state, we introduce an entanglement purification protocol with PCDs. These entanglement distillation protocols have high fidelity and efficiency with current experimental techniques, and they are useful for quantum communication network with atomic-ensemble memories.

Electro-Optic Quantum Memory for Light Using Two-Level Atoms

NASA Astrophysics Data System (ADS)

Hétet, G.; Longdell, J. J.; Alexander, A. L.; Lam, P. K.; Sellars, M. J.

2008-01-01

We present a simple quantum memory scheme that allows for the storage of a light field in an ensemble of two-level atoms. The technique is analogous to the NMR gradient echo for which the imprinting and recalling of the input field are performed by controlling a linearly varying broadening. Our protocol is perfectly efficient in the limit of high optical depths and the output pulse is emitted in the forward direction. We provide a numerical analysis of the protocol together with an experiment performed in a solid state system. In close agreement with our model, the experiment shows a total efficiency of up to 15%, and a recall efficiency of 26%. We suggest simple realizable improvements for the experiment to surpass the no-cloning limit.

Electro-optic quantum memory for light using two-level atoms.

PubMed

Hétet, G; Longdell, J J; Alexander, A L; Lam, P K; Sellars, M J

2008-01-18

We present a simple quantum memory scheme that allows for the storage of a light field in an ensemble of two-level atoms. The technique is analogous to the NMR gradient echo for which the imprinting and recalling of the input field are performed by controlling a linearly varying broadening. Our protocol is perfectly efficient in the limit of high optical depths and the output pulse is emitted in the forward direction. We provide a numerical analysis of the protocol together with an experiment performed in a solid state system. In close agreement with our model, the experiment shows a total efficiency of up to 15%, and a recall efficiency of 26%. We suggest simple realizable improvements for the experiment to surpass the no-cloning limit.

Synthesis of energy-efficient FSMs implemented in PLD circuits

NASA Astrophysics Data System (ADS)

Nawrot, Radosław; Kulisz, Józef; Kania, Dariusz

2017-11-01

The paper presents an outline of a simple synthesis method of energy-efficient FSMs. The idea consists in using local clock gating to selectively block the clock signal, if no transition of a state of a memory element is required. The research was dedicated to logic circuits using Programmable Logic Devices as the implementation platform, but the conclusions can be applied to any synchronous circuit. The experimental section reports a comparison of three methods of implementing sequential circuits in PLDs with respect to clock distribution: the classical fully synchronous structure, the structure exploiting the Enable Clock inputs of memory elements, and the structure using clock gating. The results show that the approach based on clock gating is the most efficient one, and it leads to significant reduction of dynamic power consumed by the FSM.

An implicit scheme with memory reduction technique for steady state solutions of DVBE in all flow regimes

NASA Astrophysics Data System (ADS)

Yang, L. M.; Shu, C.; Yang, W. M.; Wu, J.

2018-04-01

High consumption of memory and computational effort is the major barrier to prevent the widespread use of the discrete velocity method (DVM) in the simulation of flows in all flow regimes. To overcome this drawback, an implicit DVM with a memory reduction technique for solving a steady discrete velocity Boltzmann equation (DVBE) is presented in this work. In the method, the distribution functions in the whole discrete velocity space do not need to be stored, and they are calculated from the macroscopic flow variables. As a result, its memory requirement is in the same order as the conventional Euler/Navier-Stokes solver. In the meantime, it is more efficient than the explicit DVM for the simulation of various flows. To make the method efficient for solving flow problems in all flow regimes, a prediction step is introduced to estimate the local equilibrium state of the DVBE. In the prediction step, the distribution function at the cell interface is calculated by the local solution of DVBE. For the flow simulation, when the cell size is less than the mean free path, the prediction step has almost no effect on the solution. However, when the cell size is much larger than the mean free path, the prediction step dominates the solution so as to provide reasonable results in such a flow regime. In addition, to further improve the computational efficiency of the developed scheme in the continuum flow regime, the implicit technique is also introduced into the prediction step. Numerical results showed that the proposed implicit scheme can provide reasonable results in all flow regimes and increase significantly the computational efficiency in the continuum flow regime as compared with the existing DVM solvers.

LightAssembler: fast and memory-efficient assembly algorithm for high-throughput sequencing reads.

PubMed

El-Metwally, Sara; Zakaria, Magdi; Hamza, Taher

2016-11-01

The deluge of current sequenced data has exceeded Moore's Law, more than doubling every 2 years since the next-generation sequencing (NGS) technologies were invented. Accordingly, we will able to generate more and more data with high speed at fixed cost, but lack the computational resources to store, process and analyze it. With error prone high throughput NGS reads and genomic repeats, the assembly graph contains massive amount of redundant nodes and branching edges. Most assembly pipelines require this large graph to reside in memory to start their workflows, which is intractable for mammalian genomes. Resource-efficient genome assemblers combine both the power of advanced computing techniques and innovative data structures to encode the assembly graph efficiently in a computer memory. LightAssembler is a lightweight assembly algorithm designed to be executed on a desktop machine. It uses a pair of cache oblivious Bloom filters, one holding a uniform sample of [Formula: see text]-spaced sequenced [Formula: see text]-mers and the other holding [Formula: see text]-mers classified as likely correct, using a simple statistical test. LightAssembler contains a light implementation of the graph traversal and simplification modules that achieves comparable assembly accuracy and contiguity to other competing tools. Our method reduces the memory usage by [Formula: see text] compared to the resource-efficient assemblers using benchmark datasets from GAGE and Assemblathon projects. While LightAssembler can be considered as a gap-based sequence assembler, different gap sizes result in an almost constant assembly size and genome coverage. https://github.com/SaraEl-Metwally/LightAssembler CONTACT: sarah_almetwally4@mans.edu.egSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Multiprocessor architecture: Synthesis and evaluation

NASA Technical Reports Server (NTRS)

Standley, Hilda M.

1990-01-01

Multiprocessor computed architecture evaluation for structural computations is the focus of the research effort described. Results obtained are expected to lead to more efficient use of existing architectures and to suggest designs for new, application specific, architectures. The brief descriptions given outline a number of related efforts directed toward this purpose. The difficulty is analyzing an existing architecture or in designing a new computer architecture lies in the fact that the performance of a particular architecture, within the context of a given application, is determined by a number of factors. These include, but are not limited to, the efficiency of the computation algorithm, the programming language and support environment, the quality of the program written in the programming language, the multiplicity of the processing elements, the characteristics of the individual processing elements, the interconnection network connecting processors and non-local memories, and the shared memory organization covering the spectrum from no shared memory (all local memory) to one global access memory. These performance determiners may be loosely classified as being software or hardware related. This distinction is not clear or even appropriate in many cases. The effect of the choice of algorithm is ignored by assuming that the algorithm is specified as given. Effort directed toward the removal of the effect of the programming language and program resulted in the design of a high-level parallel programming language. Two characteristics of the fundamental structure of the architecture (memory organization and interconnection network) are examined.

Efficient Bayesian inference for natural time series using ARFIMA processes

NASA Astrophysics Data System (ADS)

Graves, Timothy; Gramacy, Robert; Franzke, Christian; Watkins, Nicholas

2016-04-01

Many geophysical quantities, such as atmospheric temperature, water levels in rivers, and wind speeds, have shown evidence of long memory (LM). LM implies that these quantities experience non-trivial temporal memory, which potentially not only enhances their predictability, but also hampers the detection of externally forced trends. Thus, it is important to reliably identify whether or not a system exhibits LM. We present a modern and systematic approach to the inference of LM. We use the flexible autoregressive fractional integrated moving average (ARFIMA) model, which is widely used in time series analysis, and of increasing interest in climate science. Unlike most previous work on the inference of LM, which is frequentist in nature, we provide a systematic treatment of Bayesian inference. In particular, we provide a new approximate likelihood for efficient parameter inference, and show how nuisance parameters (e.g., short-memory effects) can be integrated over in order to focus on long-memory parameters and hypothesis testing more directly. We illustrate our new methodology on the Nile water level data and the central England temperature (CET) time series, with favorable comparison to the standard estimators [1]. In addition we show how the method can be used to perform joint inference of the stability exponent and the memory parameter when ARFIMA is extended to allow for alpha-stable innovations. Such models can be used to study systems where heavy tails and long range memory coexist. [1] Graves et al, Nonlin. Processes Geophys., 22, 679-700, 2015; doi:10.5194/npg-22-679-2015.

System level mechanisms of adaptation, learning, memory formation and evolvability: the role of chaperone and other networks.

PubMed

Gyurko, David M; Soti, Csaba; Stetak, Attila; Csermely, Peter

2014-05-01

During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here, we describe first the protein structure networks of molecular chaperones, then characterize chaperone containing sub-networks of interactomes called as chaperone-networks or chaperomes. We review the role of molecular chaperones in short-term adaptation of cellular networks in response to stress, and in long-term adaptation discussing their putative functions in the regulation of evolvability. We provide a general overview of possible network mechanisms of adaptation, learning and memory formation. We propose that changes of network rigidity play a key role in learning and memory formation processes. Flexible network topology provides ' learning-competent' state. Here, networks may have much less modular boundaries than locally rigid, highly modular networks, where the learnt information has already been consolidated in a memory formation process. Since modular boundaries are efficient filters of information, in the 'learning-competent' state information filtering may be much smaller, than after memory formation. This mechanism restricts high information transfer to the 'learning competent' state. After memory formation, modular boundary-induced segregation and information filtering protect the stored information. The flexible networks of young organisms are generally in a 'learning competent' state. On the contrary, locally rigid networks of old organisms have lost their 'learning competent' state, but store and protect their learnt information efficiently. We anticipate that the above mechanism may operate at the level of both protein-protein interaction and neuronal networks.

Scientific developments of liquid crystal-based optical memory: a review

NASA Astrophysics Data System (ADS)

Prakash, Jai; Chandran, Achu; Biradar, Ashok M.

2017-01-01

The memory behavior in liquid crystals (LCs), although rarely observed, has made very significant headway over the past three decades since their discovery in nematic type LCs. It has gone from a mere scientific curiosity to application in variety of commodities. The memory element formed by numerous LCs have been protected by patents, and some commercialized, and used as compensation to non-volatile memory devices, and as memory in personal computers and digital cameras. They also have the low cost, large area, high speed, and high density memory needed for advanced computers and digital electronics. Short and long duration memory behavior for industrial applications have been obtained from several LC materials, and an LC memory with interesting features and applications has been demonstrated using numerous LCs. However, considerable challenges still exist in searching for highly efficient, stable, and long-lifespan materials and methods so that the development of useful memory devices is possible. This review focuses on the scientific and technological approach of fascinating applications of LC-based memory. We address the introduction, development status, novel design and engineering principles, and parameters of LC memory. We also address how the amalgamation of LCs could bring significant change/improvement in memory effects in the emerging field of nanotechnology, and the application of LC memory as the active component for futuristic and interesting memory devices.

Scientific developments of liquid crystal-based optical memory: a review.

PubMed

Prakash, Jai; Chandran, Achu; Biradar, Ashok M

2017-01-01

The memory behavior in liquid crystals (LCs), although rarely observed, has made very significant headway over the past three decades since their discovery in nematic type LCs. It has gone from a mere scientific curiosity to application in variety of commodities. The memory element formed by numerous LCs have been protected by patents, and some commercialized, and used as compensation to non-volatile memory devices, and as memory in personal computers and digital cameras. They also have the low cost, large area, high speed, and high density memory needed for advanced computers and digital electronics. Short and long duration memory behavior for industrial applications have been obtained from several LC materials, and an LC memory with interesting features and applications has been demonstrated using numerous LCs. However, considerable challenges still exist in searching for highly efficient, stable, and long-lifespan materials and methods so that the development of useful memory devices is possible. This review focuses on the scientific and technological approach of fascinating applications of LC-based memory. We address the introduction, development status, novel design and engineering principles, and parameters of LC memory. We also address how the amalgamation of LCs could bring significant change/improvement in memory effects in the emerging field of nanotechnology, and the application of LC memory as the active component for futuristic and interesting memory devices.

Selecting Learning Tasks: Effects of Adaptation and Shared Control on Learning Efficiency and Task Involvement

ERIC Educational Resources Information Center

Corbalan, Gemma; Kester, Liesbeth; van Merrienboer, Jeroen J. G.

2008-01-01

Complex skill acquisition by performing authentic learning tasks is constrained by limited working memory capacity [Baddeley, A. D. (1992). Working memory. "Science, 255", 556-559]. To prevent cognitive overload, task difficulty and support of each newly selected learning task can be adapted to the learner's competence level and perceived task…

Inhibition of Different Histone Acetyltransferases (HATs) Uncovers Transcription-Dependent and -Independent Acetylation-Mediated Mechanisms in Memory Formation

ERIC Educational Resources Information Center

Merschbaecher, Katja; Hatko, Lucyna; Folz, Jennifer; Mueller, Uli

2016-01-01

Acetylation of histones changes the efficiency of the transcription processes and thus contributes to the formation of long-term memory (LTM). In our comparative study, we used two inhibitors to characterize the contribution of different histone acetyl transferases (HATs) to appetitive associative learning in the honeybee. For one we applied…

What Makes a Skilled Writer? Working Memory and Audience Awareness during Text Composition

ERIC Educational Resources Information Center

Alamargot, Denis; Caporossi, Gilles; Chesnet, David; Ros, Christine

2011-01-01

This study investigated the role of working memory capacity as a factor for individual differences in the ability to compose a text with communicative efficiency based on audience awareness. We analyzed its differential effects on the dynamics of the writing processes, as well as on the content of the finished product. Twenty-five graduate…

Verbal Rehearsal and Short-Term Memory in Reading-disabled Children

ERIC Educational Resources Information Center

Torgesen, Joseph; Goldman, Tina

1977-01-01

To determine whether the frequently found short-term memory deficits in poor readers reflect a lack of ability or inclination to use efficient task strategies, the performances of second-grade good and poor readers were compared on a task which allowed direct observation of the use of verbal rehearsal as a mnemonic strategy. (Author/JMB)

Low Working Memory Capacity Impedes both Efficiency and Learning of Number Transcoding in Children

ERIC Educational Resources Information Center

Camos, Valerie

2008-01-01

This study aimed to evaluate the impact of individual differences in working memory capacity on number transcoding. A recently proposed model, ADAPT (a developmental asemantic procedural transcoding model), accounts for the development of number transcoding from verbal form to Arabic form by two mechanisms: the learning of new production rules…

Investigating Sentence Processing and Language Segmentation in Explaining Children's Performance on a Sentence-Span Task

ERIC Educational Resources Information Center

Mainela-Arnold, Elina; Misra, Maya; Miller, Carol; Poll, Gerard H.; Park, Ji Sook

2012-01-01

Background: Children with poor language abilities tend to perform poorly on verbal working memory tasks. This result has been interpreted as evidence that limitations in working memory capacity may interfere with the development of a mature linguistic system. However, it is possible that language abilities, such as the efficiency of sentence…

A manual for PARTI runtime primitives

NASA Technical Reports Server (NTRS)

Berryman, Harry; Saltz, Joel

1990-01-01

Primitives are presented that are designed to help users efficiently program irregular problems (e.g., unstructured mesh sweeps, sparse matrix codes, adaptive mesh partial differential equations solvers) on distributed memory machines. These primitives are also designed for use in compilers for distributed memory multiprocessors. Communications patterns are captured at runtime, and the appropriate send and receive messages are automatically generated.

Age-Related Differences in the Temporal Dynamics of Prospective Memory Retrieval: A Lifespan Approach

ERIC Educational Resources Information Center

Mattli, Florentina; Zollig, Jacqueline; West, Robert

2011-01-01

The efficiency of prospective memory (PM) typically increases from childhood to young adulthood and then decreases in later adulthood. The current study used event-related brain potentials (ERPs) to examine the development of the neural correlates of processes associated with the detection of a PM cue, switching from the ongoing activity to the…

Searching while loaded: Visual working memory does not interfere with hybrid search efficiency but hybrid search uses working memory capacity.

PubMed

Drew, Trafton; Boettcher, Sage E P; Wolfe, Jeremy M

2016-02-01

In "hybrid search" tasks, such as finding items on a grocery list, one must search the scene for targets while also searching the list in memory. How is the representation of a visual item compared with the representations of items in the memory set? Predominant theories would propose a role for visual working memory (VWM) either as the site of the comparison or as a conduit between visual and memory systems. In seven experiments, we loaded VWM in different ways and found little or no effect on hybrid search performance. However, the presence of a hybrid search task did reduce the measured capacity of VWM by a constant amount regardless of the size of the memory or visual sets. These data are broadly consistent with an account in which VWM must dedicate a fixed amount of its capacity to passing visual representations to long-term memory for comparison to the items in the memory set. The data cast doubt on models in which the search template resides in VWM or where memory set item representations are moved from LTM through VWM to earlier areas for comparison to visual items.

In-memory interconnect protocol configuration registers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cheng, Kevin Y.; Roberts, David A.

Systems, apparatuses, and methods for moving the interconnect protocol configuration registers into the main memory space of a node. The region of memory used for storing the interconnect protocol configuration registers may also be made cacheable to reduce the latency of accesses to the interconnect protocol configuration registers. Interconnect protocol configuration registers which are used during a startup routine may be prefetched into the host's cache to make the startup routine more efficient. The interconnect protocol configuration registers for various interconnect protocols may include one or more of device capability tables, memory-side statistics (e.g., to support two-level memory data mappingmore » decisions), advanced memory and interconnect features such as repair resources and routing tables, prefetching hints, error correcting code (ECC) bits, lists of device capabilities, set and store base address, capability, device ID, status, configuration, capabilities, and other settings.« less

Facing the future: Memory as an evolved system for planning future acts

PubMed Central

Klein, Stanley B.; Robertson, Theresa E.; Delton, Andrew W.

2013-01-01

All organisms capable of long-term memory are necessarily oriented toward the future. We propose that one of the most important adaptive functions of long-term episodic memory is to store information about the past in the service of planning for the personal future. Because a system should have especially efficient performance when engaged in a task that makes maximal use of its evolved machinery, we predicted that future-oriented planning would result in especially good memory relative to other memory tasks. We tested recall performance of a word list, using encoding tasks with different temporal perspectives (e.g., past, future) but a similar context. Consistent with our hypothesis, future-oriented encoding produced superior recall. We discuss these findings in light of their implications for the thesis that memory evolved to enable its possessor to anticipate and respond to future contingencies that cannot be known with certainty. PMID:19966234

Memory Detection 2.0: The First Web-Based Memory Detection Test

PubMed Central

Kleinberg, Bennett; Verschuere, Bruno

2015-01-01

There is accumulating evidence that reaction times (RTs) can be used to detect recognition of critical (e.g., crime) information. A limitation of this research base is its reliance upon small samples (average n = 24), and indications of publication bias. To advance RT-based memory detection, we report upon the development of the first web-based memory detection test. Participants in this research (Study1: n = 255; Study2: n = 262) tried to hide 2 high salient (birthday, country of origin) and 2 low salient (favourite colour, favourite animal) autobiographical details. RTs allowed to detect concealed autobiographical information, and this, as predicted, more successfully so than error rates, and for high salient than for low salient items. While much remains to be learned, memory detection 2.0 seems to offer an interesting new platform to efficiently and validly conduct RT-based memory detection research. PMID:25874966

Nonlinear analysis of an improved continuum model considering headway change with memory

NASA Astrophysics Data System (ADS)

Cheng, Rongjun; Wang, Jufeng; Ge, Hongxia; Li, Zhipeng

2018-01-01

Considering the effect of headway changes with memory, an improved continuum model of traffic flow is proposed in this paper. By means of linear stability theory, the new model’s linear stability with the effect of headway changes with memory is obtained. Through nonlinear analysis, the KdV-Burgers equation is derived to describe the propagating behavior of traffic density wave near the neutral stability line. Numerical simulation is carried out to study the improved traffic flow model, which explores how the headway changes with memory affected each car’s velocity, density and energy consumption. Numerical results show that when considering the effects of headway changes with memory, the traffic jams can be suppressed efficiently. Furthermore, research results demonstrate that the effect of headway changes with memory can avoid the disadvantage of historical information, which will improve the stability of traffic flow and minimize car energy consumption.

Combating Memory Corruption Attacks On Scada Devices

NASA Astrophysics Data System (ADS)

Bellettini, Carlo; Rrushi, Julian

Memory corruption attacks on SCADA devices can cause significant disruptions to control systems and the industrial processes they operate. However, despite the presence of numerous memory corruption vulnerabilities, few, if any, techniques have been proposed for addressing the vulnerabilities or for combating memory corruption attacks. This paper describes a technique for defending against memory corruption attacks by enforcing logical boundaries between potentially hostile data and safe data in protected processes. The technique encrypts all input data using random keys; the encrypted data is stored in main memory and is decrypted according to the principle of least privilege just before it is processed by the CPU. The defensive technique affects the precision with which attackers can corrupt control data and pure data, protecting against code injection and arc injection attacks, and alleviating problems posed by the incomparability of mitigation techniques. An experimental evaluation involving the popular Modbus protocol demonstrates the feasibility and efficiency of the defensive technique.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Janjusic, Tommy; Kartsaklis, Christos

Memory scalability is an enduring problem and bottleneck that plagues many parallel codes. Parallel codes designed for High Performance Systems are typically designed over the span of several, and in some instances 10+, years. As a result, optimization practices which were appropriate for earlier systems may no longer be valid and thus require careful optimization consideration. Specifically, parallel codes whose memory footprint is a function of their scalability must be carefully considered for future exa-scale systems. In this paper we present a methodology and tool to study the memory scalability of parallel codes. Using our methodology we evaluate an applicationmore » s memory footprint as a function of scalability, which we coined memory efficiency, and describe our results. In particular, using our in-house tools we can pinpoint the specific application components which contribute to the application s overall memory foot-print (application data- structures, libraries, etc.).« less

Parallel computing for probabilistic fatigue analysis

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Lua, Yuan J.; Smith, Mark D.

1993-01-01

This paper presents the results of Phase I research to investigate the most effective parallel processing software strategies and hardware configurations for probabilistic structural analysis. We investigate the efficiency of both shared and distributed-memory architectures via a probabilistic fatigue life analysis problem. We also present a parallel programming approach, the virtual shared-memory paradigm, that is applicable across both types of hardware. Using this approach, problems can be solved on a variety of parallel configurations, including networks of single or multiprocessor workstations. We conclude that it is possible to effectively parallelize probabilistic fatigue analysis codes; however, special strategies will be needed to achieve large-scale parallelism to keep large number of processors busy and to treat problems with the large memory requirements encountered in practice. We also conclude that distributed-memory architecture is preferable to shared-memory for achieving large scale parallelism; however, in the future, the currently emerging hybrid-memory architectures will likely be optimal.

Optical interconnection network for parallel access to multi-rank memory in future computing systems.

PubMed

Wang, Kang; Gu, Huaxi; Yang, Yintang; Wang, Kun

2015-08-10

With the number of cores increasing, there is an emerging need for a high-bandwidth low-latency interconnection network, serving core-to-memory communication. In this paper, aiming at the goal of simultaneous access to multi-rank memory, we propose an optical interconnection network for core-to-memory communication. In the proposed network, the wavelength usage is delicately arranged so that cores can communicate with different ranks at the same time and broadcast for flow control can be achieved. A distributed memory controller architecture that works in a pipeline mode is also designed for efficient optical communication and transaction address processes. The scaling method and wavelength assignment for the proposed network are investigated. Compared with traditional electronic bus-based core-to-memory communication, the simulation results based on the PARSEC benchmark show that the bandwidth enhancement and latency reduction are apparent.

Temporal context memory in high-functioning autism.

PubMed

Gras-Vincendon, Agnès; Mottron, Laurent; Salamé, Pierre; Bursztejn, Claude; Danion, Jean-Marie

2007-11-01

Episodic memory, i.e. memory for specific episodes situated in space and time, seems impaired in individuals with autism. According to weak central coherence theory, individuals with autism have general difficulty connecting contextual and item information which then impairs their capacity to memorize information in context. This study investigated temporal context memory for visual information in individuals with autism. Eighteen adolescents and adults with high-functioning autism (HFA) or Asperger syndrome (AS) and age- and IQ-matched typically developing participants were tested using a recency judgement task. The performance of the autistic group did not differ from that of the control group, nor did the performance between the AS and HFA groups. We conclude that autism in high-functioning individuals does not impair temporal context memory as assessed on this task. We suggest that individuals with autism are as efficient on this task as typically developing subjects because contextual memory performance here involves more automatic than organizational processing.

The effect of strategic memory training in older adults: who benefits most?

PubMed

Rosi, Alessia; Del Signore, Federica; Canelli, Elisa; Allegri, Nicola; Bottiroli, Sara; Vecchi, Tomaso; Cavallini, Elena

2017-12-07

Previous research has suggested that there is a degree of variability among older adults' response to memory training, such that some individuals benefit more than others. The aim of the present study was to identify the profile of older adults who were likely to benefit most from a strategic memory training program that has previously proved to be effective in improving memory in healthy older adults. In total, 44 older adults (60-83 years) participated in a strategic memory training. We examined memory training benefits by measuring changes in memory practiced (word list learning) and non-practiced tasks (grocery list and associative learning). In addition, a battery of cognitive measures was administered in order to assess crystallized and fluid abilities, short-term memory, working memory, and processing speed. Results confirmed the efficacy of the training in improving performance in both practiced and non-practiced memory tasks. For the practiced memory tasks, results showed that memory baseline performance and crystallized ability predicted training gains. For the non-practiced memory tasks, analyses showed that memory baseline performance was a significant predictor of gain in the grocery list learning task. For the associative learning task, the significant predictors were memory baseline performance, processing speed, and marginally the age. Our results indicate that older adults with a higher baseline memory capacity and with more efficient cognitive resources were those who tended to benefit most from the training. The present study provides new avenues in designing personalized intervention according to the older adults' cognitive profile.

More Efficient e-Learning through Design: Color of Text and Background

ERIC Educational Resources Information Center

Zufic, Janko; Kalpic, Damir

2009-01-01

Background: The area of research aimed for a more efficient e-learning is slowly widening from purely technical to the areas of psychology, didactics and methodology. The question is whether the text or background color influence the efficiency of memory, i.e. learning. If the answer to that question is positive, then another question arises which…

Hippocampal gamma-band Synchrony and pupillary responses index memory during visual search.

PubMed

Montefusco-Siegmund, Rodrigo; Leonard, Timothy K; Hoffman, Kari L

2017-04-01

Memory for scenes is supported by the hippocampus, among other interconnected structures, but the neural mechanisms related to this process are not well understood. To assess the role of the hippocampus in memory-guided scene search, we recorded local field potentials and multiunit activity from the hippocampus of macaques as they performed goal-directed search tasks using natural scenes. We additionally measured pupil size during scene presentation, which in humans is modulated by recognition memory. We found that both pupil dilation and search efficiency accompanied scene repetition, thereby indicating memory for scenes. Neural correlates included a brief increase in hippocampal multiunit activity and a sustained synchronization of unit activity to gamma band oscillations (50-70 Hz). The repetition effects on hippocampal gamma synchronization occurred when pupils were most dilated, suggesting an interaction between aroused, attentive processing and hippocampal correlates of recognition memory. These results suggest that the hippocampus may support memory-guided visual search through enhanced local gamma synchrony. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

In search of memory tests equivalent for experiments on animals and humans.

PubMed

Brodziak, Andrzej; Kołat, Estera; Różyk-Myrta, Alicja

2014-12-19

Older people often exhibit memory impairments. Contemporary demographic trends cause aging of the society. In this situation, it is important to conduct clinical trials of drugs and use training methods to improve memory capacity. Development of new memory tests requires experiments on animals and then clinical trials in humans. Therefore, we decided to review the assessment methods and search for tests that evaluate analogous cognitive processes in animals and humans. This review has enabled us to propose 2 pairs of tests of the efficiency of working memory capacity in animals and humans. We propose a basic set of methods for complex clinical trials of drugs and training methods to improve memory, consisting of 2 pairs of tests: 1) the Novel Object Recognition Test - Sternberg Item Recognition Test and 2) the Object-Location Test - Visuospatial Memory Test. We postulate that further investigations of methods that are equivalent in animals experiments and observations performed on humans are necessary.

Efficient implementation of a 3-dimensional ADI method on the iPSC/860

DOE Office of Scientific and Technical Information (OSTI.GOV)

Van der Wijngaart, R.F.

1993-12-31

A comparison is made between several domain decomposition strategies for the solution of three-dimensional partial differential equations on a MIMD distributed memory parallel computer. The grids used are structured, and the numerical algorithm is ADI. Important implementation issues regarding load balancing, storage requirements, network latency, and overlap of computations and communications are discussed. Results of the solution of the three-dimensional heat equation on the Intel iPSC/860 are presented for the three most viable methods. It is found that the Bruno-Cappello decomposition delivers optimal computational speed through an almost complete elimination of processor idle time, while providing good memory efficiency.

The role of cue detection for prospective memory development across the lifespan.

PubMed

Hering, Alexandra; Wild-Wall, Nele; Gajewski, Patrick D; Falkenstein, Michael; Kliegel, Matthias; Zinke, Katharina

2016-12-01

Behavioral findings suggest an inverted U-shaped pattern of prospective memory development across the lifespan. A key mechanism underlying this development is the ability to detect cues. We examined the influence of cue detection on prospective memory, combining behavioral and electrophysiological measures, in three age groups: adolescents (12-14 years), young (19-28 years), and old adults (66-77 years). Cue detection was manipulated by varying the distinctiveness (i.e., how easy it was to detect the cue based on color) of the prospective memory cue in a semantic judgment ongoing task. Behavioral results supported the pattern of an inverted U-shape with a pronounced prospective memory decrease in old adults. Adolescents and young adults showed a prospective memory specific modulation (larger amplitudes for the cues compared to other trials) already for the N1 component. No such specific modulation was evident in old adults for the early N1 component but only at the later P3b component. Adolescents showed differential modulations of the amplitude also for irrelevant information at the P3b, suggesting less efficient processing. In terms of conceptual implications, present findings underline the importance of cue detection for prospective remembering and reveal different developmental trajectories for cue detection. Our findings suggest that cue detection is not a unitary process but consists of multiple stages corresponding to several ERP components that differentially contribute to prospective memory performance across the lifespan. In adolescents resource allocation for detecting cues seemed successful initially but less efficient at later stages; whereas we found the opposite pattern for old adults. Copyright © 2016 Elsevier Ltd. All rights reserved.

Stability of whole brain and regional network topology within and between resting and cognitive states.

PubMed

Rzucidlo, Justyna K; Roseman, Paige L; Laurienti, Paul J; Dagenbach, Dale

2013-01-01

Graph-theory based analyses of resting state functional Magnetic Resonance Imaging (fMRI) data have been used to map the network organization of the brain. While numerous analyses of resting state brain organization exist, many questions remain unexplored. The present study examines the stability of findings based on this approach over repeated resting state and working memory state sessions within the same individuals. This allows assessment of stability of network topology within the same state for both rest and working memory, and between rest and working memory as well. fMRI scans were performed on five participants while at rest and while performing the 2-back working memory task five times each, with task state alternating while they were in the scanner. Voxel-based whole brain network analyses were performed on the resulting data along with analyses of functional connectivity in regions associated with resting state and working memory. Network topology was fairly stable across repeated sessions of the same task, but varied significantly between rest and working memory. In the whole brain analysis, local efficiency, Eloc, differed significantly between rest and working memory. Analyses of network statistics for the precuneus and dorsolateral prefrontal cortex revealed significant differences in degree as a function of task state for both regions and in local efficiency for the precuneus. Conversely, no significant differences were observed across repeated sessions of the same state. These findings suggest that network topology is fairly stable within individuals across time for the same state, but also fluid between states. Whole brain voxel-based network analyses may prove to be a valuable tool for exploring how functional connectivity changes in response to task demands.

LSG: An External-Memory Tool to Compute String Graphs for Next-Generation Sequencing Data Assembly.

PubMed

Bonizzoni, Paola; Vedova, Gianluca Della; Pirola, Yuri; Previtali, Marco; Rizzi, Raffaella

2016-03-01

The large amount of short read data that has to be assembled in future applications, such as in metagenomics or cancer genomics, strongly motivates the investigation of disk-based approaches to index next-generation sequencing (NGS) data. Positive results in this direction stimulate the investigation of efficient external memory algorithms for de novo assembly from NGS data. Our article is also motivated by the open problem of designing a space-efficient algorithm to compute a string graph using an indexing procedure based on the Burrows-Wheeler transform (BWT). We have developed a disk-based algorithm for computing string graphs in external memory: the light string graph (LSG). LSG relies on a new representation of the FM-index that is exploited to use an amount of main memory requirement that is independent from the size of the data set. Moreover, we have developed a pipeline for genome assembly from NGS data that integrates LSG with the assembly step of SGA (Simpson and Durbin, 2012 ), a state-of-the-art string graph-based assembler, and uses BEETL for indexing the input data. LSG is open source software and is available online. We have analyzed our implementation on a 875-million read whole-genome dataset, on which LSG has built the string graph using only 1GB of main memory (reducing the memory occupation by a factor of 50 with respect to SGA), while requiring slightly more than twice the time than SGA. The analysis of the entire pipeline shows an important decrease in memory usage, while managing to have only a moderate increase in the running time.

Memory Applications Using Resonant Tunneling Diodes

NASA Astrophysics Data System (ADS)

Shieh, Ming-Huei

Resonant tunneling diodes (RTDs) producing unique folding current-voltage (I-V) characteristics have attracted considerable research attention due to their promising application in signal processing and multi-valued logic. The negative differential resistance of RTDs renders the operating points self-latching and stable. We have proposed a multiple -dimensional multiple-state RTD-based static random-access memory (SRAM) cell in which the number of stable states can significantly be increased to (N + 1)^ m or more for m number of N-peak RTDs connected in series. The proposed cells take advantage of the hysteresis and folding I-V characteristics of RTD. Several cell designs are presented and evaluated. A two-dimensional nine-state memory cell has been implemented and demonstrated by a breadboard circuit using two 2-peak RTDs. The hysteresis phenomenon in a series of RTDs is also further analyzed. The switch model provided in SPICE 3 can be utilized to simulate the hysteretic I-V characteristics of RTDs. A simple macro-circuit is described to model the hysteretic I-V characteristic of RTD for circuit simulation. A new scheme for storing word-wide multiple-bit information very efficiently in a single memory cell using RTDs is proposed. An efficient and inexpensive periphery circuit to read from and write into the cell is also described. Simulation results on the design of a 3-bit memory cell scheme using one-peak RTDs are also presented. Finally, a binary transistor-less memory cell which is only composed of a pair of RTDs and an ordinary rectifier diode is presented and investigated. A simple means for reading and writing information from or into the memory cell is also discussed.

A learnable parallel processing architecture towards unity of memory and computing

NASA Astrophysics Data System (ADS)

Li, H.; Gao, B.; Chen, Z.; Zhao, Y.; Huang, P.; Ye, H.; Liu, L.; Liu, X.; Kang, J.

2015-08-01

Developing energy-efficient parallel information processing systems beyond von Neumann architecture is a long-standing goal of modern information technologies. The widely used von Neumann computer architecture separates memory and computing units, which leads to energy-hungry data movement when computers work. In order to meet the need of efficient information processing for the data-driven applications such as big data and Internet of Things, an energy-efficient processing architecture beyond von Neumann is critical for the information society. Here we show a non-von Neumann architecture built of resistive switching (RS) devices named “iMemComp”, where memory and logic are unified with single-type devices. Leveraging nonvolatile nature and structural parallelism of crossbar RS arrays, we have equipped “iMemComp” with capabilities of computing in parallel and learning user-defined logic functions for large-scale information processing tasks. Such architecture eliminates the energy-hungry data movement in von Neumann computers. Compared with contemporary silicon technology, adder circuits based on “iMemComp” can improve the speed by 76.8% and the power dissipation by 60.3%, together with a 700 times aggressive reduction in the circuit area.

A learnable parallel processing architecture towards unity of memory and computing.

PubMed

Li, H; Gao, B; Chen, Z; Zhao, Y; Huang, P; Ye, H; Liu, L; Liu, X; Kang, J

2015-08-14

Developing energy-efficient parallel information processing systems beyond von Neumann architecture is a long-standing goal of modern information technologies. The widely used von Neumann computer architecture separates memory and computing units, which leads to energy-hungry data movement when computers work. In order to meet the need of efficient information processing for the data-driven applications such as big data and Internet of Things, an energy-efficient processing architecture beyond von Neumann is critical for the information society. Here we show a non-von Neumann architecture built of resistive switching (RS) devices named "iMemComp", where memory and logic are unified with single-type devices. Leveraging nonvolatile nature and structural parallelism of crossbar RS arrays, we have equipped "iMemComp" with capabilities of computing in parallel and learning user-defined logic functions for large-scale information processing tasks. Such architecture eliminates the energy-hungry data movement in von Neumann computers. Compared with contemporary silicon technology, adder circuits based on "iMemComp" can improve the speed by 76.8% and the power dissipation by 60.3%, together with a 700 times aggressive reduction in the circuit area.

Computational performance of a smoothed particle hydrodynamics simulation for shared-memory parallel computing

NASA Astrophysics Data System (ADS)

Nishiura, Daisuke; Furuichi, Mikito; Sakaguchi, Hide

2015-09-01

The computational performance of a smoothed particle hydrodynamics (SPH) simulation is investigated for three types of current shared-memory parallel computer devices: many integrated core (MIC) processors, graphics processing units (GPUs), and multi-core CPUs. We are especially interested in efficient shared-memory allocation methods for each chipset, because the efficient data access patterns differ between compute unified device architecture (CUDA) programming for GPUs and OpenMP programming for MIC processors and multi-core CPUs. We first introduce several parallel implementation techniques for the SPH code, and then examine these on our target computer architectures to determine the most effective algorithms for each processor unit. In addition, we evaluate the effective computing performance and power efficiency of the SPH simulation on each architecture, as these are critical metrics for overall performance in a multi-device environment. In our benchmark test, the GPU is found to produce the best arithmetic performance as a standalone device unit, and gives the most efficient power consumption. The multi-core CPU obtains the most effective computing performance. The computational speed of the MIC processor on Xeon Phi approached that of two Xeon CPUs. This indicates that using MICs is an attractive choice for existing SPH codes on multi-core CPUs parallelized by OpenMP, as it gains computational acceleration without the need for significant changes to the source code.

The Efficiency and the Scalability of an Explicit Operator on an IBM POWER4 System

NASA Technical Reports Server (NTRS)

Frumkin, Michael; Biegel, Bryan A. (Technical Monitor)

2002-01-01

We present an evaluation of the efficiency and the scalability of an explicit CFD operator on an IBM POWER4 system. The POWER4 architecture exhibits a common trend in HPC architectures: boosting CPU processing power by increasing the number of functional units, while hiding the latency of memory access by increasing the depth of the memory hierarchy. The overall machine performance depends on the ability of the caches-buses-fabric-memory to feed the functional units with the data to be processed. In this study we evaluate the efficiency and scalability of one explicit CFD operator on an IBM POWER4. This operator performs computations at the points of a Cartesian grid and involves a few dozen floating point numbers and on the order of 100 floating point operations per grid point. The computations in all grid points are independent. Specifically, we estimate the efficiency of the RHS operator (SP of NPB) on a single processor as the observed/peak performance ratio. Then we estimate the scalability of the operator on a single chip (2 CPUs), a single MCM (8 CPUs), 16 CPUs, and the whole machine (32 CPUs). Then we perform the same measurements for a chache-optimized version of the RHS operator. For our measurements we use the HPM (Hardware Performance Monitor) counters available on the POWER4. These counters allow us to analyze the obtained performance results.

HTMT-class Latency Tolerant Parallel Architecture for Petaflops Scale Computation

NASA Technical Reports Server (NTRS)

Sterling, Thomas; Bergman, Larry

2000-01-01

Computational Aero Sciences and other numeric intensive computation disciplines demand computing throughputs substantially greater than the Teraflops scale systems only now becoming available. The related fields of fluids, structures, thermal, combustion, and dynamic controls are among the interdisciplinary areas that in combination with sufficient resolution and advanced adaptive techniques may force performance requirements towards Petaflops. This will be especially true for compute intensive models such as Navier-Stokes are or when such system models are only part of a larger design optimization computation involving many design points. Yet recent experience with conventional MPP configurations comprising commodity processing and memory components has shown that larger scale frequently results in higher programming difficulty and lower system efficiency. While important advances in system software and algorithms techniques have had some impact on efficiency and programmability for certain classes of problems, in general it is unlikely that software alone will resolve the challenges to higher scalability. As in the past, future generations of high-end computers may require a combination of hardware architecture and system software advances to enable efficient operation at a Petaflops level. The NASA led HTMT project has engaged the talents of a broad interdisciplinary team to develop a new strategy in high-end system architecture to deliver petaflops scale computing in the 2004/5 timeframe. The Hybrid-Technology, MultiThreaded parallel computer architecture incorporates several advanced technologies in combination with an innovative dynamic adaptive scheduling mechanism to provide unprecedented performance and efficiency within practical constraints of cost, complexity, and power consumption. The emerging superconductor Rapid Single Flux Quantum electronics can operate at 100 GHz (the record is 770 GHz) and one percent of the power required by convention semiconductor logic. Wave Division Multiplexing optical communications can approach a peak per fiber bandwidth of 1 Tbps and the new Data Vortex network topology employing this technology can connect tens of thousands of ports providing a bi-section bandwidth on the order of a Petabyte per second with latencies well below 100 nanoseconds, even under heavy loads. Processor-in-Memory (PIM) technology combines logic and memory on the same chip exposing the internal bandwidth of the memory row buffers at low latency. And holographic storage photorefractive storage technologies provide high-density memory with access a thousand times faster than conventional disk technologies. Together these technologies enable a new class of shared memory system architecture with a peak performance in the range of a Petaflops but size and power requirements comparable to today's largest Teraflops scale systems. To achieve high-sustained performance, HTMT combines an advanced multithreading processor architecture with a memory-driven coarse-grained latency management strategy called "percolation", yielding high efficiency while reducing the much of the parallel programming burden. This paper will present the basic system architecture characteristics made possible through this series of advanced technologies and then give a detailed description of the new percolation approach to runtime latency management.

Low Latency Messages on Distributed Memory Multiprocessors

DOE PAGES

Rosing, Matt; Saltz, Joel

1995-01-01

This article describes many of the issues in developing an efficient interface for communication on distributed memory machines. Although the hardware component of message latency is less than 1 ws on many distributed memory machines, the software latency associated with sending and receiving typed messages is on the order of 50 μs. The reason for this imbalance is that the software interface does not match the hardware. By changing the interface to match the hardware more closely, applications with fine grained communication can be put on these machines. This article describes several tests performed and many of the issues involvedmore » in supporting low latency messages on distributed memory machines.« less

False memory in aging: effects of emotional valence on word recognition accuracy.

PubMed

Piguet, Olivier; Connally, Emily; Krendl, Anne C; Huot, Jessica R; Corkin, Suzanne

2008-06-01

Memory is susceptible to distortions. Valence and increasing age are variables known to affect memory accuracy and may increase false alarm production. Interaction between these variables and their impact on false memory was investigated in 36 young (18-28 years) and 36 older (61-83 years) healthy adults. At study, participants viewed lists of neutral words orthographically related to negative, neutral, or positive critical lures (not presented). Memory for these words was subsequently tested with a remember-know procedure. At test, items included the words seen at study and their associated critical lures, as well as sets of orthographically related neutral words not seen at study and their associated unstudied lures. Positive valence was shown to have two opposite effects on older adults' discrimination of the lures: It improved correct rejection of unstudied lures but increased false memory for critical lures (i.e., lures associated with words studied previously). Thus, increased salience triggered by positive valence may disrupt memory accuracy in older adults when discriminating among similar events. These findings likely reflect a source memory deficit due to decreased efficiency in cognitive control processes with aging.

When is working memory important for arithmetic? The impact of strategy and age.

PubMed

Cragg, Lucy; Richardson, Sophie; Hubber, Paula J; Keeble, Sarah; Gilmore, Camilla

2017-01-01

Our ability to perform arithmetic relies heavily on working memory, the manipulation and maintenance of information in mind. Previous research has found that in adults, procedural strategies, particularly counting, rely on working memory to a greater extent than retrieval strategies. During childhood there are changes in the types of strategies employed, as well as an increase in the accuracy and efficiency of strategy execution. As such it seems likely that the role of working memory in arithmetic may also change, however children and adults have never been directly compared. This study used traditional dual-task methodology, with the addition of a control load condition, to investigate the extent to which working memory requirements for different arithmetic strategies change with age between 9-11 years, 12-14 years and young adulthood. We showed that both children and adults employ working memory when solving arithmetic problems, no matter what strategy they choose. This study highlights the importance of considering working memory in understanding the difficulties that some children and adults have with mathematics, as well as the need to include working memory in theoretical models of mathematical cognition.

Protective Capacity of Memory CD8+ T Cells is Dictated by Antigen Exposure History and Nature of the Infection

PubMed Central

Nolz, Jeffrey C.; Harty, John T.

2011-01-01

SUMMARY Infection or vaccination confers heightened resistance to pathogen re-challenge due to quantitative and qualitative differences between naïve and primary memory T cells. Herein, we show that secondary (boosted) memory CD8+ T cells were better than primary memory CD8+ T cells in controlling some, but not all acute infections with diverse pathogens. However, secondary memory CD8+ T cells were less efficient than an equal number of primary memory cells at preventing chronic LCMV infection and are more susceptible to functional exhaustion. Importantly, localization of memory CD8+ T cells within lymph nodes, which is reduced by antigen re-stimulation, was critical for both viral control in lymph nodes and for the sustained CD8+ T cell response required to prevent chronic LCMV infection. Thus, repeated antigen-stimulation shapes memory CD8+ T cell populations to either enhance or decrease per cell protective immunity in a pathogen-specific manner, a concept of importance in vaccine design against specific diseases. PMID:21549619

The Role of Ephs and Ephrins in Memory Formation

PubMed Central

Dines, Monica

2016-01-01

The ability to efficiently store memories in the brain is a fundamental process and its impairment is associated with multiple human mental disorders. Evidence indicates that long-term memory formation involves alterations of synaptic efficacy produced by modifications in neural transmission and morphology. The Eph receptors and their cognate ephrin ligands have been shown to be involved in these key neuronal processes by regulating events such as presynaptic transmitter release, postsynaptic glutamate receptor conductance and trafficking, synaptic glutamate reuptake, and dendritic spine morphogenesis. Recent findings show that Ephs and ephrins are needed for memory formation in different organisms. These proteins participate in the formation of various types of memories that are subserved by different neurons and brain regions. Ephs and ephrins are involved in brain disorders and diseases with memory impairment symptoms, including Alzheimer’s disease and anxiety. Drugs that agonize or antagonize Ephs/ephrins signaling have been developed and could serve as therapeutic agents to treat such diseases. Ephs and ephrins may therefore induce cellular alterations mandatory for memory formation and serve as a target for pharmacological intervention for treatment of memory-related brain diseases. PMID:26371183

Components of working memory and visual selective attention.

PubMed

Burnham, Bryan R; Sabia, Matthew; Langan, Catherine

2014-02-01

Load theory (Lavie, N., Hirst, A., De Fockert, J. W., & Viding, E. [2004]. Load theory of selective attention and cognitive control. Journal of Experimental Psychology: General, 133, 339-354.) proposes that control of attention depends on the amount and type of load that is imposed by current processing. Specifically, perceptual load should lead to efficient distractor rejection, whereas working memory load (dual-task coordination) should hinder distractor rejection. Studies support load theory's prediction that working memory load will lead to larger distractor effects; however, these studies used secondary tasks that required only verbal working memory and the central executive. The present study examined which other working memory components (visual, spatial, and phonological) influence visual selective attention. Subjects completed an attentional capture task alone (single-task) or while engaged in a working memory task (dual-task). Results showed that along with the central executive, visual and spatial working memory influenced selective attention, but phonological working memory did not. Specifically, attentional capture was larger when visual or spatial working memory was loaded, but phonological working memory load did not affect attentional capture. The results are consistent with load theory and suggest specific components of working memory influence visual selective attention. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Soft error rate simulation and initial design considerations of neutron intercepting silicon chip (NISC)

NASA Astrophysics Data System (ADS)

Celik, Cihangir

Advances in microelectronics result in sub-micrometer electronic technologies as predicted by Moore's Law, 1965, which states the number of transistors in a given space would double every two years. The most available memory architectures today have submicrometer transistor dimensions. The International Technology Roadmap for Semiconductors (ITRS), a continuation of Moore's Law, predicts that Dynamic Random Access Memory (DRAM) will have an average half pitch size of 50 nm and Microprocessor Units (MPU) will have an average gate length of 30 nm over the period of 2008-2012. Decreases in the dimensions satisfy the producer and consumer requirements of low power consumption, more data storage for a given space, faster clock speed, and portability of integrated circuits (IC), particularly memories. On the other hand, these properties also lead to a higher susceptibility of IC designs to temperature, magnetic interference, power supply, and environmental noise, and radiation. Radiation can directly or indirectly affect device operation. When a single energetic particle strikes a sensitive node in the micro-electronic device, it can cause a permanent or transient malfunction in the device. This behavior is called a Single Event Effect (SEE). SEEs are mostly transient errors that generate an electric pulse which alters the state of a logic node in the memory device without having a permanent effect on the functionality of the device. This is called a Single Event Upset (SEU) or Soft Error . Contrary to SEU, Single Event Latchup (SEL), Single Event Gate Rapture (SEGR), or Single Event Burnout (SEB) they have permanent effects on the device operation and a system reset or recovery is needed to return to proper operations. The rate at which a device or system encounters soft errors is defined as Soft Error Rate (SER). The semiconductor industry has been struggling with SEEs and is taking necessary measures in order to continue to improve system designs in nano-scale technologies. Prevention of SEEs has been studied and applied in the semiconductor industry by including radiation protection precautions in the system architecture or by using corrective algorithms in the system operation. Decreasing 10B content (20%of natural boron) in the natural boron of Borophosphosilicate glass (BPSG) layers that are conventionally used in the fabrication of semiconductor devices was one of the major radiation protection approaches for the system architecture. Neutron interaction in the BPSG layer was the origin of the SEEs because of the 10B (n,alpha) 7Li reaction products. Both of the particles produced have the capability of ionization in the silicon substrate region, whose thickness is comparable to the ranges of these particles. Using the soft error phenomenon in exactly the opposite manner of the semiconductor industry can provide a new neutron detection system based on the SERs in the semiconductor memories. By investigating the soft error mechanisms in the available semiconductor memories and enhancing the soft error occurrences in these devices, one can convert all memory using intelligent systems into portable, power efficient, directiondependent neutron detectors. The Neutron Intercepting Silicon Chip (NISC) project aims to achieve this goal by introducing 10B-enriched BPSG layers to the semiconductor memory architectures. This research addresses the development of a simulation tool, the NISC Soft Error Analysis Tool (NISCSAT), for soft error modeling and analysis in the semiconductor memories to provide basic design considerations for the NISC. NISCSAT performs particle transport and calculates the soft error probabilities, or SER, depending on energy depositions of the particles in a given memory node model of the NISC. Soft error measurements were performed with commercially available, off-the-shelf semiconductor memories and microprocessors to observe soft error variations with the neutron flux and memory supply voltage. Measurement results show that soft errors in the memories increase proportionally with the neutron flux, whereas they decrease with increasing the supply voltages. NISC design considerations include the effects of device scaling, 10B content in the BPSG layer, incoming neutron energy, and critical charge of the node for this dissertation. NISCSAT simulations were performed with various memory node models to account these effects. Device scaling simulations showed that any further increase in the thickness of the BPSG layer beyond 2 mum causes self-shielding of the incoming neutrons due to the BPSG layer and results in lower detection efficiencies. Moreover, if the BPSG layer is located more than 4 mum apart from the depletion region in the node, there are no soft errors in the node due to the fact that both of the reaction products have lower ranges in the silicon or any possible node layers. Calculation results regarding the critical charge indicated that the mean charge deposition of the reaction products in the sensitive volume of the node is about 15 fC. It is evident that the NISC design should have a memory architecture with a critical charge of 15 fC or less to obtain higher detection efficiencies. Moreover, the sensitive volume should be placed in close proximity to the BPSG layers so that its location would be within the range of alpha and 7Li particles. Results showed that the distance between the BPSG layer and the sensitive volume should be less than 2 mum to increase the detection efficiency of the NISC. Incoming neutron energy was also investigated by simulations and the results obtained from these simulations showed that NISC neutron detection efficiency is related with the neutron cross-sections of 10B (n,alpha) 7Li reaction, e.g., ratio of the thermal (0.0253 eV) to fast (2 MeV) neutron detection efficiencies is approximately equal to 8000:1. Environmental conditions and their effects on the NISC performance were also studied in this research. Cosmic rays were modeled and simulated via NISCSAT to investigate detection reliability of the NISC. Simulation results show that cosmic rays account for less than 2 % of the soft errors for the thermal neutron detection. On the other hand, fast neutron detection by the NISC, which already has a poor efficiency due to the low neutron cross-sections, becomes almost impossible at higher altitudes where the cosmic ray fluxes and their energies are higher. NISCSAT simulations regarding soft error dependency of the NISC for temperature and electromagnetic fields show that there are no significant effects in the NISC detection efficiency. Furthermore, the detection efficiency of the NISC decreases with both air humidity and use of moderators since the incoming neutrons scatter away before reaching the memory surface.

Face recognition by applying wavelet subband representation and kernel associative memory.

PubMed

Zhang, Bai-Ling; Zhang, Haihong; Ge, Shuzhi Sam

2004-01-01

In this paper, we propose an efficient face recognition scheme which has two features: 1) representation of face images by two-dimensional (2-D) wavelet subband coefficients and 2) recognition by a modular, personalised classification method based on kernel associative memory models. Compared to PCA projections and low resolution "thumb-nail" image representations, wavelet subband coefficients can efficiently capture substantial facial features while keeping computational complexity low. As there are usually very limited samples, we constructed an associative memory (AM) model for each person and proposed to improve the performance of AM models by kernel methods. Specifically, we first applied kernel transforms to each possible training pair of faces sample and then mapped the high-dimensional feature space back to input space. Our scheme using modular autoassociative memory for face recognition is inspired by the same motivation as using autoencoders for optical character recognition (OCR), for which the advantages has been proven. By associative memory, all the prototypical faces of one particular person are used to reconstruct themselves and the reconstruction error for a probe face image is used to decide if the probe face is from the corresponding person. We carried out extensive experiments on three standard face recognition datasets, the FERET data, the XM2VTS data, and the ORL data. Detailed comparisons with earlier published results are provided and our proposed scheme offers better recognition accuracy on all of the face datasets.

Efficient Learning for the Poor: New Insights into Literacy Acquisition for Children

ERIC Educational Resources Information Center

Abadzi, Helen

2008-01-01

Reading depends on the speed of visual recognition and capacity of short-term memory. To understand a sentence, the mind must read it fast enough to capture it within the limits of the short-term memory. This means that children must attain a minimum speed of fairly accurate reading to understand a passage. Learning to read involves "tricking" the…

DOE Office of Scientific and Technical Information (OSTI.GOV)

Donofrio, David

A method and apparatus for performing stencil computations efficiently are disclosed. In one embodiment, a processor receives an offset, and in response, retrieves a value from a memory via a single instruction, where the retrieving comprises: identifying, based on the offset, one of a plurality of registers of the processor; loading an address stored in the identified register; and retrieving from the memory the value at the address.

Rapid Dynamic Assessment of Expertise to Improve the Efficiency of Adaptive Elearning

ERIC Educational Resources Information Center

Kalyuga, Slava; Sweller, John

2005-01-01

In this article we suggest a method of evaluating learner expertise based on assessment of the content of working memory and the extent to which cognitive load has been reduced by knowledge retrieved from long-term memory. The method was tested in an experiment with an elementary algebra tutor using a yoked control design. In the learner-adapted…

The Development of Automaticity in Short-Term Memory Search: Item-Response Learning and Category Learning

ERIC Educational Resources Information Center

Cao, Rui; Nosofsky, Robert M.; Shiffrin, Richard M.

2017-01-01

In short-term-memory (STM)-search tasks, observers judge whether a test probe was present in a short list of study items. Here we investigated the long-term learning mechanisms that lead to the highly efficient STM-search performance observed under conditions of consistent-mapping (CM) training, in which targets and foils never switch roles across…

A manual for PARTI runtime primitives, revision 1

NASA Technical Reports Server (NTRS)

Das, Raja; Saltz, Joel; Berryman, Harry

1991-01-01

Primitives are presented that are designed to help users efficiently program irregular problems (e.g., unstructured mesh sweeps, sparse matrix codes, adaptive mesh partial differential equations solvers) on distributed memory machines. These primitives are also designed for use in compilers for distributed memory multiprocessors. Communications patterns are captured at runtime, and the appropriate send and receive messages are automatically generated.

The Influence of Working Memory and Phonological Processing on English Language Learner Children's Bilingual Reading and Language Acquisition

ERIC Educational Resources Information Center

Swanson, H. Lee; Orosco, Michael J.; Lussier, Cathy M.; Gerber, Michael M.; Guzman-Orth, Danielle A.

2011-01-01

In this study, we explored whether the contribution of working memory (WM) to children's (N = 471) 2nd language (L2) reading and language acquisition was best accounted for by processing efficiency at a phonological level and/or by executive processes independent of phonological processing. Elementary school children (Grades 1, 2, & 3) whose…

Thermomechanical Modeling of Shape Memory Alloys and Applications

NASA Astrophysics Data System (ADS)

Lexcellent, C.; Leclercq, S.

The aim of the present paper is a general macroscopic description of the thermomechanical behavior of shape memory alloys (SMA). We use for framework the thermodynamics of irreversible processes. This model is efficient for describing the behavior of "smart" structures as a bronchial, a tentacle element and an prosthesis hybrid structure made of Ti Ni SMA wires embedded in a resin epoxy matrix.

Posttraining Increases in REM Sleep Intensity Implicate REM Sleep in Memory Processing and Provide a Biological Marker of Learning Potential

ERIC Educational Resources Information Center

Nader, Rebecca S.; Smith, Carlyle T.; Nixon, Margaret R.

2004-01-01

Posttraining rapid eye movement (REM) sleep has been reported to be important for efficient memory consolidation. The present results demonstrate increases in the intensity of REM sleep during the night of sleep following cognitive procedural/implicit task acquisition. These REM increases manifest as increases in total number of rapid eye…

Attention and memory benefits for physical attractiveness may mediate prosocial biases.

PubMed

Becker, David Vaughn

2017-01-01

Mating motivations can explain attractiveness benefits, but what proximate mechanisms might serve as efficient causes of these biases? There is growing evidence that visual cues of physical attractiveness capture attention and facilitate memory, enhancing salience in ways that could underlie, for example, preferring one job applicant over another. All of these effects beg deeper questions about the meaning of attractiveness.

Information processing efficiency in patients with multiple sclerosis.

PubMed

Archibald, C J; Fisk, J D

2000-10-01

Reduced information processing efficiency, consequent to impaired neural transmission, has been proposed as underlying various cognitive problems in patients with Multiple Sclerosis (MS). This study employed two measures developed from experimental psychology that control for the potential confound of perceptual-motor abnormalities (Salthouse, Babcock, & Shaw, 1991; Sternberg, 1966, 1969) to assess the speed of information processing and working memory capacity in patients with mild to moderate MS. Although patients had significantly more cognitive complaints than neurologically intact matched controls, their performance on standard tests of immediate memory span did not differ from control participants and their word list learning was within normal limits. On the experimental measures, both relapsing-remitting and secondary-progressive patients exhibited significantly slowed information processing speed relative to controls. However, only the secondary-progressive patients had an additional decrement in working memory capacity. Depression, fatigue, or neurologic disability did not account for performance differences on these measures. While speed of information processing may be slowed early in the disease process, deficits in working memory capacity may appear only as there is progression of MS. It is these latter deficits, however, that may underlie the impairment of new learning that patients with MS demonstrate.

Binary mesh partitioning for cache-efficient visualization.

PubMed

Tchiboukdjian, Marc; Danjean, Vincent; Raffin, Bruno

2010-01-01

One important bottleneck when visualizing large data sets is the data transfer between processor and memory. Cache-aware (CA) and cache-oblivious (CO) algorithms take into consideration the memory hierarchy to design cache efficient algorithms. CO approaches have the advantage to adapt to unknown and varying memory hierarchies. Recent CA and CO algorithms developed for 3D mesh layouts significantly improve performance of previous approaches, but they lack of theoretical performance guarantees. We present in this paper a {\\schmi O}(N\\log N) algorithm to compute a CO layout for unstructured but well shaped meshes. We prove that a coherent traversal of a N-size mesh in dimension d induces less than N/B+{\\schmi O}(N/M;{1/d}) cache-misses where B and M are the block size and the cache size, respectively. Experiments show that our layout computation is faster and significantly less memory consuming than the best known CO algorithm. Performance is comparable to this algorithm for classical visualization algorithm access patterns, or better when the BSP tree produced while computing the layout is used as an acceleration data structure adjusted to the layout. We also show that cache oblivious approaches lead to significant performance increases on recent GPU architectures.

Static Memory Deduplication for Performance Optimization in Cloud Computing.

PubMed

Jia, Gangyong; Han, Guangjie; Wang, Hao; Yang, Xuan

2017-04-27

In a cloud computing environment, the number of virtual machines (VMs) on a single physical server and the number of applications running on each VM are continuously growing. This has led to an enormous increase in the demand of memory capacity and subsequent increase in the energy consumption in the cloud. Lack of enough memory has become a major bottleneck for scalability and performance of virtualization interfaces in cloud computing. To address this problem, memory deduplication techniques which reduce memory demand through page sharing are being adopted. However, such techniques suffer from overheads in terms of number of online comparisons required for the memory deduplication. In this paper, we propose a static memory deduplication (SMD) technique which can reduce memory capacity requirement and provide performance optimization in cloud computing. The main innovation of SMD is that the process of page detection is performed offline, thus potentially reducing the performance cost, especially in terms of response time. In SMD, page comparisons are restricted to the code segment, which has the highest shared content. Our experimental results show that SMD efficiently reduces memory capacity requirement and improves performance. We demonstrate that, compared to other approaches, the cost in terms of the response time is negligible.

Control of Working Memory in Rhesus Monkeys (Macaca mulatta)

PubMed Central

Tu, Hsiao-Wei; Hampton, Robert R.

2014-01-01

Cognitive control is critical for efficiently using the limited resources in working memory. It is well established that humans use rehearsal to increase the probability of remembering needed information, but little is known in nonhumans, with some studies reporting the absence of active control and others subject to alternative explanations. We trained monkeys in a visual matching-to-sample paradigm with a post-sample memory cue. Monkeys either saw a remember cue that predicted the occurrence of a matching test that required memory for the sample, or a forget cue that predicted a discrimination test that did not require memory of the sample. Infrequent probe trials on which monkeys were given tests of the type not cued on that trial were used to assess whether memory was under cognitive control. Our procedures controlled for reward expectation and for the surprising nature of the probes. Monkeys matched less accurately after forget cues, while discrimination accuracy was equivalent in the two cue conditions. We also tested monkeys with lists of two consecutive sample images that shared the same cue. Again, memory for expected memory tests was superior to that on unexpected tests. Together these results show that monkeys cognitively control their working memory. PMID:25436219

Bigger is better and worse: on the intricate relationship between hippocampal size and memory.

PubMed

Molnár, Katalin; Kéri, Szabolcs

2014-04-01

The structure-function relationship between the hippocampal region and memory is a debated topic in the literature. It has been suggested that larger hippocampi are associated with less effective memory performance in healthy young adults because of a partial synaptic pruning. Here, we tested this hypothesis in individuals with Fragile X Syndrome (FXS) with known abnormal pruning and IQ- and age-matched individuals with hypoxic brain injury, preterm birth, and obstetric complications. Results revealed larger normalized hippocampal volume in FXS compared with neurotypical controls, whereas individuals with hypoxic injury had smaller hippocampi. In neurotypical controls and individuals with hypoxic injury, better general memory, as indexed by the Wechsler Memory Scale-Revised, was associated with larger hippocampus. In contrast, in FXS we observed the opposite relationship: larger hippocampus was associated with worse general memory. Caudate volume did not correlate with memory in either group. These results suggest that incomplete pruning in young healthy adults may not contribute to less efficient memory capacity, and hippocampal size is positively associated with memory performance. However, abnormally large and poorly pruned hippocampus may indeed be less effective in FXS. Copyright © 2014 Elsevier Ltd. All rights reserved.

Static Memory Deduplication for Performance Optimization in Cloud Computing

PubMed Central

Jia, Gangyong; Han, Guangjie; Wang, Hao; Yang, Xuan

2017-01-01

In a cloud computing environment, the number of virtual machines (VMs) on a single physical server and the number of applications running on each VM are continuously growing. This has led to an enormous increase in the demand of memory capacity and subsequent increase in the energy consumption in the cloud. Lack of enough memory has become a major bottleneck for scalability and performance of virtualization interfaces in cloud computing. To address this problem, memory deduplication techniques which reduce memory demand through page sharing are being adopted. However, such techniques suffer from overheads in terms of number of online comparisons required for the memory deduplication. In this paper, we propose a static memory deduplication (SMD) technique which can reduce memory capacity requirement and provide performance optimization in cloud computing. The main innovation of SMD is that the process of page detection is performed offline, thus potentially reducing the performance cost, especially in terms of response time. In SMD, page comparisons are restricted to the code segment, which has the highest shared content. Our experimental results show that SMD efficiently reduces memory capacity requirement and improves performance. We demonstrate that, compared to other approaches, the cost in terms of the response time is negligible. PMID:28448434

A shared neural ensemble links distinct contextual memories encoded close in time

NASA Astrophysics Data System (ADS)

Cai, Denise J.; Aharoni, Daniel; Shuman, Tristan; Shobe, Justin; Biane, Jeremy; Song, Weilin; Wei, Brandon; Veshkini, Michael; La-Vu, Mimi; Lou, Jerry; Flores, Sergio E.; Kim, Isaac; Sano, Yoshitake; Zhou, Miou; Baumgaertel, Karsten; Lavi, Ayal; Kamata, Masakazu; Tuszynski, Mark; Mayford, Mark; Golshani, Peyman; Silva, Alcino J.

2016-06-01

Recent studies suggest that a shared neural ensemble may link distinct memories encoded close in time. According to the memory allocation hypothesis, learning triggers a temporary increase in neuronal excitability that biases the representation of a subsequent memory to the neuronal ensemble encoding the first memory, such that recall of one memory increases the likelihood of recalling the other memory. Here we show in mice that the overlap between the hippocampal CA1 ensembles activated by two distinct contexts acquired within a day is higher than when they are separated by a week. Several findings indicate that this overlap of neuronal ensembles links two contextual memories. First, fear paired with one context is transferred to a neutral context when the two contexts are acquired within a day but not across a week. Second, the first memory strengthens the second memory within a day but not across a week. Older mice, known to have lower CA1 excitability, do not show the overlap between ensembles, the transfer of fear between contexts, or the strengthening of the second memory. Finally, in aged mice, increasing cellular excitability and activating a common ensemble of CA1 neurons during two distinct context exposures rescued the deficit in linking memories. Taken together, these findings demonstrate that contextual memories encoded close in time are linked by directing storage into overlapping ensembles. Alteration of these processes by ageing could affect the temporal structure of memories, thus impairing efficient recall of related information.

Spatial memory enhances the evacuation efficiency of virtual pedestrians under poor visibility condition

NASA Astrophysics Data System (ADS)

Ma, Yi; Lee, Eric Wai Ming; Shi, Meng; Kwok Kit Yuen, Richard

2018-03-01

Spatial memory is a critical navigation support tool for disoriented evacuees during evacuation under adverse environmental conditions such as dark or smoky conditions. Owing to the complexity of memory, it is challenging to understand the effect of spatial memory on pedestrian evacuation quantitatively. In this study, we propose a simple method to quantitatively represent the evacueeʼs spatial memory about the emergency exit, model the evacuation of pedestrians under the guidance of the spatial memory, and investigate the effect of the evacueeʼs spatial memory on the evacuation from theoretical and physical perspectives. The result shows that (i) a good memory can significantly assist the evacuation of pedestrians under poor visibility conditions, and the evacuation can always succeed when the degree of the memory exceeds a threshold (\\varphi > 0.5); (ii) the effect of memory is superior to that of “follow-the-crowd” under the same environmental conditions; (iii) in the case of multiple exits, the difference in the degree of the memory between evacuees has a significant effect (the greater the difference, the faster the evacuation) for the evacuation under poor visibility conditions. Our study provides a new quantitative insight into the effect of spatial memory on crowd evacuation under poor visibility conditions. Project supported by the Research Grants Council of the Hong Kong Special Administrative Region, China (Grant No. 11203615).

An analytical study of physical models with inherited temporal and spatial memory

NASA Astrophysics Data System (ADS)

Jaradat, Imad; Alquran, Marwan; Al-Khaled, Kamel

2018-04-01

Du et al. (Sci. Reb. 3, 3431 (2013)) demonstrated that the fractional derivative order can be physically interpreted as a memory index by fitting the test data of memory phenomena. The aim of this work is to study analytically the joint effect of the memory index on time and space coordinates simultaneously. For this purpose, we introduce a novel bivariate fractional power series expansion that is accompanied by twofold fractional derivatives ordering α, β\\in(0,1]. Further, some convergence criteria concerning our expansion are presented and an analog of the well-known bivariate Taylor's formula in the sense of mixed fractional derivatives is obtained. Finally, in order to show the functionality and efficiency of this expansion, we employ the corresponding Taylor's series method to obtain closed-form solutions of various physical models with inherited time and space memory.

Memory-guided attention in the anterior thalamus.

PubMed

Leszczyński, Marcin; Staudigl, Tobias

2016-07-01

The anterior thalamus is densely connected with both the hippocampus and the prefrontal cortex. It is known to play a role in learning and episodic memory. Given its connectivity profile with the prefrontal cortex, it may also be expected to contribute to executive functions. Recent studies in both rodents and humans add to our understanding of anterior thalamic function, suggesting that it is a key region for allocating attention. We discuss the convergence between studies in rodents and humans, both of which imply that the anterior thalamus may play a key role in memory-guided attention. We suggest that efficient allocation of attention to memory representations requires interaction between the memory-related hippocampal and the attention related fronto-parietal networks. We further propose that the anterior thalamus is a hub that connects and modulates both systems. Copyright © 2016 Elsevier Ltd. All rights reserved.

Nanophotonic rare-earth quantum memory with optically controlled retrieval.

PubMed

Zhong, Tian; Kindem, Jonathan M; Bartholomew, John G; Rochman, Jake; Craiciu, Ioana; Miyazono, Evan; Bettinelli, Marco; Cavalli, Enrico; Verma, Varun; Nam, Sae Woo; Marsili, Francesco; Shaw, Matthew D; Beyer, Andrew D; Faraon, Andrei

2017-09-29

Optical quantum memories are essential elements in quantum networks for long-distance distribution of quantum entanglement. Scalable development of quantum network nodes requires on-chip qubit storage functionality with control of the readout time. We demonstrate a high-fidelity nanophotonic quantum memory based on a mesoscopic neodymium ensemble coupled to a photonic crystal cavity. The nanocavity enables >95% spin polarization for efficient initialization of the atomic frequency comb memory and time bin-selective readout through an enhanced optical Stark shift of the comb frequencies. Our solid-state memory is integrable with other chip-scale photon source and detector devices for multiplexed quantum and classical information processing at the network nodes. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

From Contextual Fear to a Dynamic View of Memory Systems

PubMed Central

Fanselow, Michael S

2009-01-01

The brain does not learn and remember in a unitary fashion. Rather, different circuits specialize in certain classes of problems and encode different types of information. Damage to one of these systems typically results in amnesia only for the form of memory that is the affected region's specialty. How does the brain allocate a specific category of memory to a particular circuit? This question has received little attention. The currently dominant view, Multiple Memory Systems Theory, assumes that such abilities are hard-wired. Using fear conditioning as a paradigmatic case, I propose an alternative model in which mnemonic processing is allocated to specific circuits through a dynamic process. Potential circuits compete to form memories with the most efficient circuits emerging as winners. However, alternate circuits compensate when these “primary” circuits are compromised. PMID:19939724

Max-plus and min-plus projection autoassociative morphological memories and their compositions for pattern classification.

PubMed

Dos Santos, Alex Santana; Valle, Marcos Eduardo

2018-04-01

Autoassociative morphological memories (AMMs) are robust and computationally efficient memory models with unlimited storage capacity. In this paper, we present the max-plus and min-plus projection autoassociative morphological memories (PAMMs) as well as their compositions. Briefly, the max-plus PAMM yields the largest max-plus combination of the stored vectors which is less than or equal to the input. Dually, the vector recalled by the min-plus PAMM corresponds to the smallest min-plus combination which is larger than or equal to the input. Apart from unlimited absolute storage capacity and one step retrieval, PAMMs and their compositions exhibit an excellent noise tolerance. Furthermore, the new memories yielded quite promising results in classification problems with a large number of features and classes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Effects of Age and Acute Moderate Alcohol Administration on Electrophysiological Correlates of Working Memory Maintenance

PubMed Central

Boissoneault, Jeff; Frazier, Ian; Lewis, Ben; Nixon, Sara Jo

2016-01-01

Background Previous studies suggest older adults may be differentially susceptible to the acute neurobehavioral effects of moderate alcohol intake. To our knowledge, no studies have addressed acute moderate alcohol effects on the electrophysiological correlates of working memory in younger and older social drinkers. This study characterized alcohol-related effects on frontal theta (FTP) and posterior alpha power (PAP) associated with maintenance of visual information during a working memory task. Methods Older (55–70 years of age; n = 51, 29 women) and younger (25–35 years of age; n = 70, 39 women) community-dwelling moderate drinkers were recruited for this study. Participants were given either placebo or an active dose targeting breath alcohol concentrations (BrACs) of 0.04 or 0.065 g/dL. Following absorption, participants completed a visual working memory task assessing cue recognition following a 9s delay. FTP and PAP were determined via Fourier transformation and subjected to 2 (age group) X 3 (dose) X 2 (repeated: working memory task condition) mixed models analysis. Results In addition to expected age-related reductions in PAP, a significant age group X dose interaction was detected for PAP such that 0.04 g/dL dose level was associated with greater PAP in younger adults but lower PAP in their older counterparts. PAP was lower in older vs younger adults at both active doses. Further mixed models revealed a significant negative association between PAP and working memory efficiency for older adults. No effects of age, dose, or their interaction were noted for FTP. Conclusions Results bolster the small but growing body of evidence that older adults exhibit differential sensitivity to the neurobehavioral effects of moderate alcohol use. Given the theoretical role of PAP in attentional and working memory function, these findings shed light on the attentional mechanisms underlying effects of acute moderate alcohol on working memory efficiency in older adults. PMID:27419803

The efficiency of multimedia learning into old age.

PubMed

Van Gerven, Pascal W M; Paas, Fred; Van Merriënboer, Jeroen J G; Hendriks, Maaike; Schmidt, Henk G

2003-12-01

On the basis of a multimodal model of working memory, cognitive load theory predicts that a multimedia-based instructional format leads to a better acquisition of complex subject matter than a purely visual instructional format. This study investigated the extent to which age and instructional format had an impact on training efficiency among both young and old adults. It was hypothesised that studying worked examples that are presented as a narrated animation (multimedia condition) is a more efficient means of complex skill training than studying visually presented worked examples (unimodal condition) and solving conventional problems. Furthermore, it was hypothesised that multimedia-based worked examples are especially helpful for elderly learners, who have to deal with a general decline of working-memory resources, because they address both mode-specific working-memory stores. The sample consisted of 60 young (mean age = 15.98 years) and 60 old adults (mean age = 64.48 years). Participants of both age groups were trained in either a conventional, a unimodal, or a multimedia condition. Subsequently, they had to solve a series of test problems. Dependent variables were perceived cognitive load during the training, performance on the test, and efficiency in terms of the ratio between these two variables. Results showed that for both age groups multimedia-based worked examples were more efficient than the other training formats in that less cognitive load led to at least an equal performance level. Although no difference in the beneficial effect of multimedia learning was found between the age groups, multimedia-based instructions seem promising for the elderly.

Paradoxical sleep as a tool for understanding the hippocampal mechanisms of contextual memory.

PubMed

Sil'kis, I G

2010-01-01

Existing data on the involvement of the hippocampus in contextual memory and the fact that contextual memory is impaired in dreams occurring during paradoxical sleep allowed us to suggest that one of the causes of this impairment consists of changes in the efficiency of synaptic transmission in the hippocampus due to increases (as compared with waking) in the concentrations of acetylcholine, dopamine, and cortisol, as well as the absence of serotonin and noradrenaline. Our previous analysis showed that in paradoxical sleep, long-term depression can be induced all components of the polysynaptic pathway through the hippocampal formation, while potentiation can occur at the inputs from the entorhinal cortex to hippocampal fields CA1 and CA3 and in the associative connections in field CA3. It is hypothesized that the correct functioning of episodic memory requires efficient transmission of signals in each component of the polysynaptic pathway through the hippocampus, allowing a neuronal representation of the context to be created within it. In the state of waking, reproduction of the context of an episode simultaneously activates the neuronal representation of the context remembered in the hippocampus and neuronal representations of the details of the episode remembered in those areas of the cortex in which they were processed. It follows from the proposed mechanism that any neurotransmitter or neuropeptide able to promote longterm potentiation in all components of the polysynaptic pathway through the hippocampus can improve episodic memory. As the consequences of the mechanism are consistent with experimental data, it can be used to seek agents improving episodic memory.

An extract of Salvia (sage) with anticholinesterase properties improves memory and attention in healthy older volunteers.

PubMed

Scholey, Andrew B; Tildesley, Nicola T J; Ballard, Clive G; Wesnes, Keith A; Tasker, Andrea; Perry, Elaine K; Kennedy, David O

2008-05-01

Species of Salvia (sage) have a long-standing reputation in European medical herbalism, including for memory enhancement. In recent controlled trials, administration of sage extracts with established cholinergic properties improved cognitive function in young adults. This randomised, placebo-controlled, double-blind, balanced, five-period crossover study investigated the acute effects on cognitive performance of a standardised extract of Salvia officinalis in older adults. Twenty volunteers (>65 years of age, mean = 72.95) received four active doses of extract (167, 333, 666 and 1332 mg) and a placebo with a 7-day wash-out period between visits. Assessment involved completion of the Cognitive Drug Research computerised assessment battery. On study days, treatments were administered immediately following a baseline assessment with further assessment at 1, 2.5, 4 and 6 h post treatment. Compared with the placebo condition (which exhibited the characteristic performance decline over the day), the 333-mg dose was associated with significant enhancement of secondary memory performance at all testing times. The same measure benefited to a lesser extent from other doses. There also were significant improvements to accuracy of attention following the 333-mg dose. In vitro analysis confirmed cholinesterase inhibiting properties for the extract. The overall pattern of results is consistent with a dose-related benefit to processes involved in efficient stimulus processing and/or memory consolidation rather than retrieval or working memory efficiency. These findings extend those of the memory-enhancing effects of Salvia extracts in younger populations and warrant further investigation in larger series, in other populations and with different dosing regimes.

Obstructive sleep apnea exaggerates cognitive dysfunction in stroke patients.

PubMed

Zhang, Yan; Wang, Wanhua; Cai, Sijie; Sheng, Qi; Pan, Shenggui; Shen, Fang; Tang, Qing; Liu, Yang

2017-05-01

Obstructive sleep apnea (OSA) is very common in stroke survivors. It potentially worsens the cognitive dysfunction and inhibits their functional recovery. However, whether OSA independently damages the cognitive function in stroke patients is unclear. A simple method for evaluating OSA-induced cognitive impairment is also missing. Forty-four stroke patients six weeks after onset and 24 non-stroke patients with snoring were recruited for the polysomnographic study of OSA and sleep architecture. Their cognitive status was evaluated with a validated Chinese version of Cambridge Prospective Memory Test. The relationship between memory deficits and respiratory, sleeping, and dementia-related clinical variables were analyzed with correlation and multiple linear regression tests. OSA significantly and independently damaged time- and event-based prospective memory in stroke patients, although it had less power than the stroke itself. The impairment of prospective memory was correlated with increased apnea-hypopnea index, decreased minimal and mean levels of peripheral oxygen saturation, and disrupted sleeping continuity (reduced sleep efficiency and increased microarousal index). The further regression analysis identified minimal levels of peripheral oxygen saturation and sleep efficiency to be the two most important predictors for the decreased time-based prospective memory in stroke patients. OSA independently contributes to the cognitive dysfunction in stroke patients, potentially through OSA-caused hypoxemia and sleeping discontinuity. The prospective memory test is a simple but sensitive method to detect OSA-induced cognitive impairment in stroke patients. Proper therapies of OSA might improve the cognitive function and increase the life quality of stroke patients. Copyright © 2017 Elsevier B.V. All rights reserved.

Visuospatial working memory in very preterm and term born children--impact of age and performance.

PubMed

Mürner-Lavanchy, I; Ritter, B C; Spencer-Smith, M M; Perrig, W J; Schroth, G; Steinlin, M; Everts, R

2014-07-01

Working memory is crucial for meeting the challenges of daily life and performing academic tasks, such as reading or arithmetic. Very preterm born children are at risk of low working memory capacity. The aim of this study was to examine the visuospatial working memory network of school-aged preterm children and to determine the effect of age and performance on the neural working memory network. Working memory was assessed in 41 very preterm born children and 36 term born controls (aged 7-12 years) using functional magnetic resonance imaging (fMRI) and neuropsychological assessment. While preterm children and controls showed equal working memory performance, preterm children showed less involvement of the right middle frontal gyrus, but higher fMRI activation in superior frontal regions than controls. The younger and low-performing preterm children presented an atypical working memory network whereas the older high-performing preterm children recruited a working memory network similar to the controls. Results suggest that younger and low-performing preterm children show signs of less neural efficiency in frontal brain areas. With increasing age and performance, compensational mechanisms seem to occur, so that in preterm children, the typical visuospatial working memory network is established by the age of 12 years. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

A case of persistent retrograde amnesia following a dissociative fugue: neuropsychological and neurofunctional underpinnings of loss of autobiographical memory and self-awareness.

PubMed

Hennig-Fast, Kristina; Meister, Franziska; Frodl, Thomas; Beraldi, Anna; Padberg, Frank; Engel, Rolf R; Reiser, Maximilian; Möller, Hans-Jürgen; Meindl, Thomas

2008-10-01

Autobiographical memory relies on complex interactions between episodic memory contents, associated emotions and a sense of self-continuity over the course of one's life. This paper reports a study based upon the case of the patient NN who suffered from a complete loss of autobiographical memory and awareness of identity subsequent to a dissociative fugue. Neuropsychological, behavioral, and functional neuroimaging tests converged on the conclusion that NN suffered from a selective retrograde amnesia following an episode of dissociative fugue, during which he had lost explicit knowledge and vivid memory of his personal past. NN's loss of self-related memories was mirrored in neurobiological changes after the fugue whereas his semantic memory remained intact. Although NN still claimed to suffer from a stable loss of autobiographical, self-relevant memories 1 year after the fugue state, a proportionate improvement in underlying fronto-temporal neuronal networks was evident at this point in time. In spite of this improvement in neuronal activation, his anterograde visual memory had been decreased. It is posited that our data provide evidence for the important role of visual processing in autobiographical memory as well as for the efficiency of protective control mechanisms that constitute functional retrograde amnesia.

Expectancy effects in source memory: how moving to a bad neighborhood can change your memory.

PubMed

Kroneisen, Meike; Woehe, Larissa; Rausch, Leonie Sophie

2015-02-01

Enhanced memory for cheaters could be suited to avoid social exchange situations in which we run the risk of getting exploited by others. Several experiments demonstrated that we have better source memory for faces combined with negative rather than positive behavior (Bell & Buchner, Memory & Cognition, 38, 29-41, 2010) or for cheaters and cooperators showing unexpected behavior (Bell, Buchner, Kroneisen, Giang, Journal of Experimental Psychology: Learning, Memory, and Cognition, 38, 1512-1529, 2012). In the present study, we compared two groups: Group 1 just saw faces combined with aggressive, prosocial or neutral behavior descriptions, but got no further information, whereas group 2 was explicitly told that they would now see the behavior descriptions of very aggressive and unsocial persons. To measure old-new discrimination, source memory, and guessing biases separately, we used a multinomial model. When having no expectancies about the behavior of the presented people, enhanced source memory for aggressive persons was found. In comparison, source memory for faces combined with prosocial behavior descriptions was significantly higher in the group expecting only aggressive persons. These findings can be attributed to a mechanism that focuses on expectancy-incongruent information, representing a more flexible and therefore efficient memory strategy for remembering exchange-relevant information.

High performance nonvolatile memory devices based on Cu2-xSe nanowires

NASA Astrophysics Data System (ADS)

Wu, Chun-Yan; Wu, Yi-Liang; Wang, Wen-Jian; Mao, Dun; Yu, Yong-Qiang; Wang, Li; Xu, Jun; Hu, Ji-Gang; Luo, Lin-Bao

2013-11-01

We report on the rational synthesis of one-dimensional Cu2-xSe nanowires (NWs) via a solution method. Electrical analysis of Cu2-xSe NWs based memory device exhibits a stable and reproducible bipolar resistive switching behavior with a low set voltage (0.3-0.6 V), which can enable the device to write and erase data efficiently. Remarkably, the memory device has a record conductance switching ratio of 108, much higher than other devices ever reported. At last, a conducting filaments model is introduced to account for the resistive switching behavior. The totality of this study suggests that the Cu2-xSe NWs are promising building blocks for fabricating high-performance and low-consumption nonvolatile memory devices.

Rapid solution of large-scale systems of equations

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.

1994-01-01

The analysis and design of complex aerospace structures requires the rapid solution of large systems of linear and nonlinear equations, eigenvalue extraction for buckling, vibration and flutter modes, structural optimization and design sensitivity calculation. Computers with multiple processors and vector capabilities can offer substantial computational advantages over traditional scalar computer for these analyses. These computers fall into two categories: shared memory computers and distributed memory computers. This presentation covers general-purpose, highly efficient algorithms for generation/assembly or element matrices, solution of systems of linear and nonlinear equations, eigenvalue and design sensitivity analysis and optimization. All algorithms are coded in FORTRAN for shared memory computers and many are adapted to distributed memory computers. The capability and numerical performance of these algorithms will be addressed.

Only "efficient" emotional stimuli affect the content of working memory during free-recollection from natural scenes.

PubMed

Buttafuoco, Arianna; Pedale, Tiziana; Buchanan, Tony W; Santangelo, Valerio

2018-02-01

Emotional events are thought to have privileged access to attention and memory, consuming resources needed to encode competing emotionally neutral stimuli. However, it is not clear whether this detrimental effect is automatic or depends on the successful maintenance of the specific emotional object within working memory. Here, participants viewed everyday scenes including an emotional object among other neutral objects followed by a free-recollection task. Results showed that emotional objects-irrespective of their perceptual saliency-were recollected more often than neutral objects. The probability of being recollected increased as a function of the arousal of the emotional objects, specifically for negative objects. Successful recollection of emotional objects (positive or negative) from a scene reduced the overall number of recollected neutral objects from the same scene. This indicates that only emotional stimuli that are efficient in grabbing (and then consuming) available attentional resources play a crucial role during the encoding of competing information, with a subsequent bias in the recollection of neutral representations.

Ultra Low Density Shape Memory Polymer Foams With Tunable Physicochemical Properties for Treatment of intracranial Aneurysms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Singhal, Pooja

Shape memory polymers (SMPs) are a rapidly emerging class of smart materials that can be stored in a deformed temporary shape, and can actively return to their original shape upon application of an external stimulus such as heat, pH or light. This behavior is particularly advantageous for minimally invasive biomedical applications comprising embolic/regenerative scaffolds, as it enables a transcatheter delivery of the device to the target site. The focus of this work was to exploit this shape memory behavior of polyurethanes, and develop an efficient embolic SMP foam device for the treatment of intracranial aneurysms.In summary, this work reports amore » novel family of ultra low density polymer foams which can be delivered via a minimally invasive surgery to the aneurysm site, actuated in a controlled manner to efficiently embolize the aneurysm while promoting physiological fluid/blood flow through the reticulated/open porous structure, and eventually biodegrade leading to complete healing of the vasculature.« less

Manipulating motor performance and memory through real-time fMRI neurofeedback.

PubMed

Scharnowski, Frank; Veit, Ralf; Zopf, Regine; Studer, Petra; Bock, Simon; Diedrichsen, Jörn; Goebel, Rainer; Mathiak, Klaus; Birbaumer, Niels; Weiskopf, Nikolaus

2015-05-01

Task performance depends on ongoing brain activity which can be influenced by attention, arousal, or motivation. However, such modulating factors of cognitive efficiency are unspecific, can be difficult to control, and are not suitable to facilitate neural processing in a regionally specific manner. Here, we non-pharmacologically manipulated regionally specific brain activity using technically sophisticated real-time fMRI neurofeedback. This was accomplished by training participants to simultaneously control ongoing brain activity in circumscribed motor and memory-related brain areas, namely the supplementary motor area and the parahippocampal cortex. We found that learned voluntary control over these functionally distinct brain areas caused functionally specific behavioral effects, i.e. shortening of motor reaction times and specific interference with memory encoding. The neurofeedback approach goes beyond improving cognitive efficiency by unspecific psychological factors such as attention, arousal, or motivation. It allows for directly manipulating sustained activity of task-relevant brain regions in order to yield specific behavioral or cognitive effects. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Non-Markovian quantum processes: Complete framework and efficient characterization

NASA Astrophysics Data System (ADS)

Pollock, Felix A.; Rodríguez-Rosario, César; Frauenheim, Thomas; Paternostro, Mauro; Modi, Kavan

2018-01-01

Currently, there is no systematic way to describe a quantum process with memory solely in terms of experimentally accessible quantities. However, recent technological advances mean we have control over systems at scales where memory effects are non-negligible. The lack of such an operational description has hindered advances in understanding physical, chemical, and biological processes, where often unjustified theoretical assumptions are made to render a dynamical description tractable. This has led to theories plagued with unphysical results and no consensus on what a quantum Markov (memoryless) process is. Here, we develop a universal framework to characterize arbitrary non-Markovian quantum processes. We show how a multitime non-Markovian process can be reconstructed experimentally, and that it has a natural representation as a many-body quantum state, where temporal correlations are mapped to spatial ones. Moreover, this state is expected to have an efficient matrix-product-operator form in many cases. Our framework constitutes a systematic tool for the effective description of memory-bearing open-system evolutions.

Manipulating motor performance and memory through real-time fMRI neurofeedback

PubMed Central

Scharnowski, Frank; Veit, Ralf; Zopf, Regine; Studer, Petra; Bock, Simon; Diedrichsen, Jörn; Goebel, Rainer; Mathiak, Klaus; Birbaumer, Niels; Weiskopf, Nikolaus

2015-01-01

Task performance depends on ongoing brain activity which can be influenced by attention, arousal, or motivation. However, such modulating factors of cognitive efficiency are unspecific, can be difficult to control, and are not suitable to facilitate neural processing in a regionally specific manner. Here, we non-pharmacologically manipulated regionally specific brain activity using technically sophisticated real-time fMRI neurofeedback. This was accomplished by training participants to simultaneously control ongoing brain activity in circumscribed motor and memory-related brain areas, namely the supplementary motor area and the parahippocampal cortex. We found that learned voluntary control over these functionally distinct brain areas caused functionally specific behavioral effects, i.e. shortening of motor reaction times and specific interference with memory encoding. The neurofeedback approach goes beyond improving cognitive efficiency by unspecific psychological factors such as attention, arousal, or motivation. It allows for directly manipulating sustained activity of task-relevant brain regions in order to yield specific behavioral or cognitive effects. PMID:25796342

Efficient L1 regularization-based reconstruction for fluorescent molecular tomography using restarted nonlinear conjugate gradient.

PubMed

Shi, Junwei; Zhang, Bin; Liu, Fei; Luo, Jianwen; Bai, Jing

2013-09-15

For the ill-posed fluorescent molecular tomography (FMT) inverse problem, the L1 regularization can protect the high-frequency information like edges while effectively reduce the image noise. However, the state-of-the-art L1 regularization-based algorithms for FMT reconstruction are expensive in memory, especially for large-scale problems. An efficient L1 regularization-based reconstruction algorithm based on nonlinear conjugate gradient with restarted strategy is proposed to increase the computational speed with low memory consumption. The reconstruction results from phantom experiments demonstrate that the proposed algorithm can obtain high spatial resolution and high signal-to-noise ratio, as well as high localization accuracy for fluorescence targets.

Multi-petascale highly efficient parallel supercomputer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Asaad, Sameh; Bellofatto, Ralph E.; Blocksome, Michael A.

A Multi-Petascale Highly Efficient Parallel Supercomputer of 100 petaflop-scale includes node architectures based upon System-On-a-Chip technology, where each processing node comprises a single Application Specific Integrated Circuit (ASIC). The ASIC nodes are interconnected by a five dimensional torus network that optimally maximize the throughput of packet communications between nodes and minimize latency. The network implements collective network and a global asynchronous network that provides global barrier and notification functions. Integrated in the node design include a list-based prefetcher. The memory system implements transaction memory, thread level speculation, and multiversioning cache that improves soft error rate at the same time andmore » supports DMA functionality allowing for parallel processing message-passing.« less

Generic Entity Resolution in Relational Databases

NASA Astrophysics Data System (ADS)

Sidló, Csaba István

Entity Resolution (ER) covers the problem of identifying distinct representations of real-world entities in heterogeneous databases. We consider the generic formulation of ER problems (GER) with exact outcome. In practice, input data usually resides in relational databases and can grow to huge volumes. Yet, typical solutions described in the literature employ standalone memory resident algorithms. In this paper we utilize facilities of standard, unmodified relational database management systems (RDBMS) to enhance the efficiency of GER algorithms. We study and revise the problem formulation, and propose practical and efficient algorithms optimized for RDBMS external memory processing. We outline a real-world scenario and demonstrate the advantage of algorithms by performing experiments on insurance customer data.

GraphReduce: Processing Large-Scale Graphs on Accelerator-Based Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sengupta, Dipanjan; Song, Shuaiwen; Agarwal, Kapil

2015-11-15

Recent work on real-world graph analytics has sought to leverage the massive amount of parallelism offered by GPU devices, but challenges remain due to the inherent irregularity of graph algorithms and limitations in GPU-resident memory for storing large graphs. We present GraphReduce, a highly efficient and scalable GPU-based framework that operates on graphs that exceed the device’s internal memory capacity. GraphReduce adopts a combination of edge- and vertex-centric implementations of the Gather-Apply-Scatter programming model and operates on multiple asynchronous GPU streams to fully exploit the high degrees of parallelism in GPUs with efficient graph data movement between the host andmore » device.« less

Shared virtual memory and generalized speedup

NASA Technical Reports Server (NTRS)

Sun, Xian-He; Zhu, Jianping

1994-01-01

Generalized speedup is defined as parallel speed over sequential speed. The generalized speedup and its relation with other existing performance metrics, such as traditional speedup, efficiency, scalability, etc., are carefully studied. In terms of the introduced asymptotic speed, it was shown that the difference between the generalized speedup and the traditional speedup lies in the definition of the efficiency of uniprocessor processing, which is a very important issue in shared virtual memory machines. A scientific application was implemented on a KSR-1 parallel computer. Experimental and theoretical results show that the generalized speedup is distinct from the traditional speedup and provides a more reasonable measurement. In the study of different speedups, various causes of superlinear speedup are also presented.

A Mutant Mouse with a Highly Specific Contextual Fear-Conditioning Deficit Found in an N-Ethyl-N-Nitrosourea (ENU) Mutagenesis Screen

ERIC Educational Resources Information Center

Pletcher, Mathew T.; Wiltshire, Tim; Tarantino, Lisa M.; Mayford, Mark; Reijmers, Leon G.; Coats, Jennifer K.

2006-01-01

Targeted mutagenesis in mice has shown that genes from a wide variety of gene families are involved in memory formation. The efficient identification of genes involved in learning and memory could be achieved by random mutagenesis combined with high-throughput phenotyping. Here, we provide the first report of a mutagenesis screen that has…

Guidance of visual search by memory and knowledge.

PubMed

Hollingworth, Andrew

2012-01-01

To behave intelligently in the world, humans must be able to find objects efficiently within the complex environments they inhabit. A growing proportion of the literature on visual search is devoted to understanding this type of natural search. In the present chapter, I review the literature on visual search through natural scenes, focusing on the role of memory and knowledge in guiding attention to task-relevant objects.

Interference control in working memory: comparing groups of children with atypical development.

PubMed

Palladino, Paola; Ferrari, Marcella

2013-01-01

The study aimed to test whether working memory deficits in children at risk of Learning Disabilities (LD) and/or attention deficit/hyperactivity disorder (ADHD) can be attributed to deficits in interference control, thereby implicating prefrontal systems. Two groups of children known for showing poor working memory (i.e., children with poor comprehension and children with ADHD) were compared to a group of children with specific reading decoding problems (i.e., having severe problems in phonological rather than working memory) and to a control group. All children were tested with a verbal working memory task. Interference control of irrelevant items was examined by a lexical decision task presented immediately after the final recall in about half the trials, selected at random. The interference control measure was therefore directly related to working memory performance. Results confirmed deficient working memory performance in poor comprehenders and children at risk of ADHD + LD. More interestingly, this working memory deficit was associated with greater activation of irrelevant information than in the control group. Poor decoders showed more efficient interference control, in contrast to poor comprehenders and ADHD + LD children. These results indicated that interfering items were still highly accessible to working memory in children who fail the working memory task. In turn, these findings strengthen and clarify the role of interference control, one of the most critical prefrontal functions, in working memory.

Self-organization and solution of shortest-path optimization problems with memristive networks

NASA Astrophysics Data System (ADS)

Pershin, Yuriy V.; Di Ventra, Massimiliano

2013-07-01

We show that memristive networks, namely networks of resistors with memory, can efficiently solve shortest-path optimization problems. Indeed, the presence of memory (time nonlocality) promotes self organization of the network into the shortest possible path(s). We introduce a network entropy function to characterize the self-organized evolution, show the solution of the shortest-path problem and demonstrate the healing property of the solution path. Finally, we provide an algorithm to solve the traveling salesman problem. Similar considerations apply to networks of memcapacitors and meminductors, and networks with memory in various dimensions.

Molecular implementation of molecular shift register memories

NASA Technical Reports Server (NTRS)

Beratan, David N. (Inventor); Onuchic, Jose N. (Inventor)

1991-01-01

An electronic shift register memory (20) at the molecular level is described. The memory elements are based on a chain of electron transfer molecules (22) and the information is shifted by photoinduced (26) electron transfer reactions. Thus, multi-step sequences of charge transfer reactions are used to move charge with high efficiency down a molecular chain. The device integrates compositions of the invention onto a VLSI substrate (36), providing an example of a molecular electronic device which may be fabricated. Three energy level schemes, molecular implementation of these schemes, optical excitation strategies, charge amplification strategies, and error correction strategies are described.

Epigenetic and chromatin-based mechanisms in environmental stress adaptation and stress memory in plants.

PubMed

Lämke, Jörn; Bäurle, Isabel

2017-06-27

Plants frequently have to weather both biotic and abiotic stressors, and have evolved sophisticated adaptation and defense mechanisms. In recent years, chromatin modifications, nucleosome positioning, and DNA methylation have been recognized as important components in these adaptations. Given their potential epigenetic nature, such modifications may provide a mechanistic basis for a stress memory, enabling plants to respond more efficiently to recurring stress or even to prepare their offspring for potential future assaults. In this review, we discuss both the involvement of chromatin in stress responses and the current evidence on somatic, intergenerational, and transgenerational stress memory.

The hard fall effect: high working memory capacity leads to a higher, but less robust short-term memory performance.

PubMed

Thomassin, Noémylle; Gonthier, Corentin; Guerraz, Michel; Roulin, Jean-Luc

2015-01-01

Participants with a high working memory span tend to perform better than low spans in a variety of tasks. However, their performance is paradoxically more impaired when they have to perform two tasks at once, a phenomenon that could be labeled the "hard fall effect." The present study tested whether this effect exists in a short-term memory task, and investigated the proposal that the effect is due to high spans using efficient facilitative strategies under simple task conditions. Ninety-eight participants performed a spatial short-term memory task under simple and dual task conditions; stimuli presentation times either allowed for the use of complex facilitative strategies or not. High spans outperformed low spans only under simple task conditions when presentation times allowed for the use of facilitative strategies. These results indicate that the hard fall effect exists on a short-term memory task and may be caused by individual differences in strategy use.

Makalu: fast recoverable allocation of non-volatile memory

DOE PAGES

Bhandari, Kumud; Chakrabarti, Dhruva R.; Boehm, Hans-J.

2016-10-19

Byte addressable non-volatile memory (NVRAM) is likely to supplement, and perhaps eventually replace, DRAM. Applications can then persist data structures directly in memory instead of serializing them and storing them onto a durable block device. However, failures during execution can leave data structures in NVRAM unreachable or corrupt. In this paper, we present Makalu, a system that addresses non-volatile memory management. Makalu offers an integrated allocator and recovery-time garbage collector that maintains internal consistency, avoids NVRAM memory leaks, and is efficient, all in the face of failures. We show that a careful allocator design can support a less restrictive andmore » a much more familiar programming model than existing persistent memory allocators. Our allocator significantly reduces the per allocation persistence overhead by lazily persisting non-essential metadata and by employing a post-failure recovery-time garbage collector. Experimental results show that the resulting online speed and scalability of our allocator are comparable to well-known transient allocators, and significantly better than state-of-the-art persistent allocators.« less

A case of hyperthymesia: Rethinking the role of the amygdala in autobiographical memory

PubMed Central

Ally, Brandon A.; Hussey, Erin P.; Donahue, Manus J.

2012-01-01

Much controversy has been focused on the extent to which the amygdala belongs to the autobiographical memory core network. Early evidence suggested the amygdala played a vital role in emotional processing, likely helping to encode emotionally charged stimuli. However, recent work has highlighted the amygdala’s role in social and self-referential processing, leading to speculation that the amygdala likely supports the encoding and retrieval of autobiographical memory. Here, cognitive as well as structural and functional magnetic resonance imaging data was collected from an extremely rare individual with near-perfect autobiographical memory, or hyperthymesia. Right amygdala hypertrophy (approximately 20%) and enhanced amygdala-to-hippocampus connectivity (> 10 standard deviations) was observed in this volunteer relative to controls. Based on these findings and previous literature, we speculate that the amygdala likely charges autobiographical memories with emotional, social, and self-relevance. In heightened memory, this system may be hyperactive, allowing for many types of autobiographical information, including emotionally benign, to be more efficiently processed as self-relevant for encoding and storage. PMID:22519463

Syntactic Recursion Facilitates and Working Memory Predicts Recursive Theory of Mind

PubMed Central

Arslan, Burcu; Hohenberger, Annette; Verbrugge, Rineke

2017-01-01

In this study, we focus on the possible roles of second-order syntactic recursion and working memory in terms of simple and complex span tasks in the development of second-order false belief reasoning. We tested 89 Turkish children in two age groups, one younger (4;6–6;5 years) and one older (6;7–8;10 years). Although second-order syntactic recursion is significantly correlated with the second-order false belief task, results of ordinal logistic regressions revealed that the main predictor of second-order false belief reasoning is complex working memory span. Unlike simple working memory and second-order syntactic recursion tasks, the complex working memory task required processing information serially with additional reasoning demands that require complex working memory strategies. Based on our results, we propose that children’s second-order theory of mind develops when they have efficient reasoning rules to process embedded beliefs serially, thus overcoming a possible serial processing bottleneck. PMID:28072823

A simple spatial working memory and attention test on paired symbols shows developmental deficits in schizophrenia patients.

PubMed

Song, Wei; Zhang, Kai; Sun, Jinhua; Ma, Lina; Jesse, Forrest Fabian; Teng, Xiaochun; Zhou, Ying; Bao, Hechen; Chen, Shiqing; Wang, Shuai; Yang, Beimeng; Chu, Xixia; Ding, Wenhua; Du, Yasong; Cheng, Zaohuo; Wu, Bin; Chen, Shanguang; He, Guang; He, Lin; Chen, Xiaoping; Li, Weidong

2013-01-01

People with neuropsychiatric disorders such as schizophrenia often display deficits in spatial working memory and attention. Evaluating working memory and attention in schizophrenia patients is usually based on traditional tasks and the interviewer's judgment. We developed a simple Spatial Working Memory and Attention Test on Paired Symbols (SWAPS). It takes only several minutes to complete, comprising 101 trials for each subject. In this study, we tested 72 schizophrenia patients and 188 healthy volunteers in China. In a healthy control group with ages ranging from 12 to 60, the efficiency score (accuracy divided by reaction time) reached a peak in the 20-27 age range and then declined with increasing age. Importantly, schizophrenia patients failed to display this developmental trend in the same age range and adults had significant deficits compared to the control group. Our data suggests that this simple Spatial Working Memory and Attention Test on Paired Symbols can be a useful tool for studies of spatial working memory and attention in neuropsychiatric disorders.

Better Organic Ternary Memory Performance through Self-Assembled Alkyltrichlorosilane Monolayers on Indium Tin Oxide (ITO) Surfaces.

PubMed

Hou, Xiang; Cheng, Xue-Feng; Zhou, Jin; He, Jing-Hui; Xu, Qing-Feng; Li, Hua; Li, Na-Jun; Chen, Dong-Yun; Lu, Jian-Mei

2017-11-16

Recently, surface engineering of the indium tin oxide (ITO) electrode of sandwich-like organic electric memory devices was found to effectively improve their memory performances. However, there are few methods to modify the ITO substrates. In this paper, we have successfully prepared alkyltrichlorosilane self-assembled monolayers (SAMs) on ITO substrates, and resistive random access memory devices are fabricated on these surfaces. Compared to the unmodified ITO substrates, organic molecules (i.e., 2-((4-butylphenyl)amino)-4-((4-butylphenyl)iminio)-3-oxocyclobut-1-en-1-olate, SA-Bu) grown on these SAM-modified ITO substrates have rougher surface morphologies but a smaller mosaicity. The organic layer on the SAM-modified ITO further aged to eliminate the crystalline phase diversity. In consequence, the ternary memory yields are effectively improved to approximately 40-47 %. Our results suggest that the insertion of alkyltrichlorosilane self-assembled monolayers could be an efficient method to improve the performance of organic memory devices. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Makalu: fast recoverable allocation of non-volatile memory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhandari, Kumud; Chakrabarti, Dhruva R.; Boehm, Hans-J.

Byte addressable non-volatile memory (NVRAM) is likely to supplement, and perhaps eventually replace, DRAM. Applications can then persist data structures directly in memory instead of serializing them and storing them onto a durable block device. However, failures during execution can leave data structures in NVRAM unreachable or corrupt. In this paper, we present Makalu, a system that addresses non-volatile memory management. Makalu offers an integrated allocator and recovery-time garbage collector that maintains internal consistency, avoids NVRAM memory leaks, and is efficient, all in the face of failures. We show that a careful allocator design can support a less restrictive andmore » a much more familiar programming model than existing persistent memory allocators. Our allocator significantly reduces the per allocation persistence overhead by lazily persisting non-essential metadata and by employing a post-failure recovery-time garbage collector. Experimental results show that the resulting online speed and scalability of our allocator are comparable to well-known transient allocators, and significantly better than state-of-the-art persistent allocators.« less

A chiral-based magnetic memory device without a permanent magnet

PubMed Central

Dor, Oren Ben; Yochelis, Shira; Mathew, Shinto P.; Naaman, Ron; Paltiel, Yossi

2013-01-01

Several technologies are currently in use for computer memory devices. However, there is a need for a universal memory device that has high density, high speed and low power requirements. To this end, various types of magnetic-based technologies with a permanent magnet have been proposed. Recent charge-transfer studies indicate that chiral molecules act as an efficient spin filter. Here we utilize this effect to achieve a proof of concept for a new type of chiral-based magnetic-based Si-compatible universal memory device without a permanent magnet. More specifically, we use spin-selective charge transfer through a self-assembled monolayer of polyalanine to magnetize a Ni layer. This magnitude of magnetization corresponds to applying an external magnetic field of 0.4 T to the Ni layer. The readout is achieved using low currents. The presented technology has the potential to overcome the limitations of other magnetic-based memory technologies to allow fabricating inexpensive, high-density universal memory-on-chip devices. PMID:23922081

A chiral-based magnetic memory device without a permanent magnet.

PubMed

Ben Dor, Oren; Yochelis, Shira; Mathew, Shinto P; Naaman, Ron; Paltiel, Yossi

2013-01-01

Several technologies are currently in use for computer memory devices. However, there is a need for a universal memory device that has high density, high speed and low power requirements. To this end, various types of magnetic-based technologies with a permanent magnet have been proposed. Recent charge-transfer studies indicate that chiral molecules act as an efficient spin filter. Here we utilize this effect to achieve a proof of concept for a new type of chiral-based magnetic-based Si-compatible universal memory device without a permanent magnet. More specifically, we use spin-selective charge transfer through a self-assembled monolayer of polyalanine to magnetize a Ni layer. This magnitude of magnetization corresponds to applying an external magnetic field of 0.4 T to the Ni layer. The readout is achieved using low currents. The presented technology has the potential to overcome the limitations of other magnetic-based memory technologies to allow fabricating inexpensive, high-density universal memory-on-chip devices.

Inserting Thienyl Linkers into Conjugated Molecules for Efficient Multilevel Electronic Memory: A New Understanding of Charge-Trapping in Organic Materials.

PubMed

Li, Yang; Li, Hua; He, Jinghui; Xu, Qingfeng; Li, Najun; Chen, Dongyun; Lu, Jianmei

2016-03-18

The practical application of organic memory devices requires low power consumption and reliable device quality. Herein, we report that inserting thienyl units into D-π-A molecules can improve these parameters by tuning the texture of the film. Theoretical calculations revealed that introducing thienyl π bridges increased the planarity of the molecular backbone and extended the D-A conjugation. Thus, molecules with more thienyl spacers showed improved stacking and orientation in the film state relative to the substrates. The corresponding sandwiched memory devices showed enhanced ternary memory behavior, with lower threshold voltages and better repeatability. The conductive switching and variation in the performance of the memory devices were interpreted by using an extended-charge-trapping mechanism. Our study suggests that judicious molecular engineering can facilitate control of the orientation of the crystallite in the solid state to achieve superior multilevel memory performance. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Sports training enhances visuo-spatial cognition regardless of open-closed typology

PubMed Central

Hsieh, Shu-Shih; Chen, Kuan-Fu; Chang, Yu-Kai

2017-01-01

The aim of this study was to investigate the effects of open and closed sport participation on visuo-spatial attention and memory performance among young adults. Forty-eight young adults—16 open-skill athletes, 16 closed-skill athletes, and 16 non-athletes controls—were recruited for the study. Both behavioral performance and event-related potential (ERP) measurement were assessed when participants performed non-delayed and delayed match-to-sample task that tested visuo-spatial attention and memory processing. Results demonstrated that regardless of training typology, the athlete groups exhibited shorter reaction times in both the visuo-spatial attention and memory conditions than the control group with no existence of speed-accuracy trade-off. Similarly, a larger P3 amplitudes were observed in both athlete groups than in the control group for the visuo-spatial memory condition. These findings suggest that sports training, regardless of typology, are associated with superior visuo-spatial attention and memory performance, and more efficient neural resource allocation in memory processing. PMID:28560098

How to Assess Gaming-Induced Benefits on Attention and Working Memory.

PubMed

Mishra, Jyoti; Bavelier, Daphne; Gazzaley, Adam

2012-06-01

Our daily actions are driven by our goals in the moment, constantly forcing us to choose among various options. Attention and working memory are key enablers of that process. Attention allows for selective processing of goal-relevant information and rejecting task-irrelevant information. Working memory functions to maintain goal-relevant information in memory for brief periods of time for subsequent recall and/or manipulation. Efficient attention and working memory thus support the best extraction and retention of environmental information for optimal task performance. Recent studies have evidenced that attention and working memory abilities can be enhanced by cognitive training games as well as entertainment videogames. Here we review key cognitive paradigms that have been used to evaluate the impact of game-based training on various aspects of attention and working memory. Common use of such methodology within the scientific community will enable direct comparison of the efficacy of different games across age groups and clinical populations. The availability of common assessment tools will ultimately facilitate development of the most effective forms of game-based training for cognitive rehabilitation and education.

How to Assess Gaming-Induced Benefits on Attention and Working Memory

PubMed Central

Mishra, Jyoti; Bavelier, Daphne

2012-01-01

Abstract Our daily actions are driven by our goals in the moment, constantly forcing us to choose among various options. Attention and working memory are key enablers of that process. Attention allows for selective processing of goal-relevant information and rejecting task-irrelevant information. Working memory functions to maintain goal-relevant information in memory for brief periods of time for subsequent recall and/or manipulation. Efficient attention and working memory thus support the best extraction and retention of environmental information for optimal task performance. Recent studies have evidenced that attention and working memory abilities can be enhanced by cognitive training games as well as entertainment videogames. Here we review key cognitive paradigms that have been used to evaluate the impact of game-based training on various aspects of attention and working memory. Common use of such methodology within the scientific community will enable direct comparison of the efficacy of different games across age groups and clinical populations. The availability of common assessment tools will ultimately facilitate development of the most effective forms of game-based training for cognitive rehabilitation and education. PMID:24761314

Cognitive Control Network Contributions to Memory-Guided Visual Attention.

PubMed

Rosen, Maya L; Stern, Chantal E; Michalka, Samantha W; Devaney, Kathryn J; Somers, David C

2016-05-01

Visual attentional capacity is severely limited, but humans excel in familiar visual contexts, in part because long-term memories guide efficient deployment of attention. To investigate the neural substrates that support memory-guided visual attention, we performed a set of functional MRI experiments that contrast long-term, memory-guided visuospatial attention with stimulus-guided visuospatial attention in a change detection task. Whereas the dorsal attention network was activated for both forms of attention, the cognitive control network(CCN) was preferentially activated during memory-guided attention. Three posterior nodes in the CCN, posterior precuneus, posterior callosal sulcus/mid-cingulate, and lateral intraparietal sulcus exhibited the greatest specificity for memory-guided attention. These 3 regions exhibit functional connectivity at rest, and we propose that they form a subnetwork within the broader CCN. Based on the task activation patterns, we conclude that the nodes of this subnetwork are preferentially recruited for long-term memory guidance of visuospatial attention. Published by Oxford University Press 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.

A comparison of select image-compression algorithms for an electronic still camera

NASA Technical Reports Server (NTRS)

Nerheim, Rosalee

1989-01-01

This effort is a study of image-compression algorithms for an electronic still camera. An electronic still camera can record and transmit high-quality images without the use of film, because images are stored digitally in computer memory. However, high-resolution images contain an enormous amount of information, and will strain the camera's data-storage system. Image compression will allow more images to be stored in the camera's memory. For the electronic still camera, a compression algorithm that produces a reconstructed image of high fidelity is most important. Efficiency of the algorithm is the second priority. High fidelity and efficiency are more important than a high compression ratio. Several algorithms were chosen for this study and judged on fidelity, efficiency and compression ratio. The transform method appears to be the best choice. At present, the method is compressing images to a ratio of 5.3:1 and producing high-fidelity reconstructed images.

Question structure impacts efficiency and performance in an interactive guessing game: implications for strategy engagement and executive functioning.

PubMed

Longenecker, Julia; Liu, Kristy; Chen, Eric Y H

2012-12-30

In an interactive guessing game, controls had higher performance and efficiency than patients with schizophrenia in correct trials. Patients' difficulties generating efficient questions suggest an increased taxation of working memory and an inability to engage an appropriate strategy, leading to impulsive behavior and reduced success. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Factors that influence the generation of autobiographical memory conjunction errors

PubMed Central

Devitt, Aleea L.; Monk-Fromont, Edwin; Schacter, Daniel L.; Addis, Donna Rose

2015-01-01

The constructive nature of memory is generally adaptive, allowing us to efficiently store, process and learn from life events, and simulate future scenarios to prepare ourselves for what may come. However, the cost of a flexibly constructive memory system is the occasional conjunction error, whereby the components of an event are authentic, but the combination of those components is false. Using a novel recombination paradigm, it was demonstrated that details from one autobiographical memory may be incorrectly incorporated into another, forming autobiographical memory conjunction errors that elude typical reality monitoring checks. The factors that contribute to the creation of these conjunction errors were examined across two experiments. Conjunction errors were more likely to occur when the corresponding details were partially rather than fully recombined, likely due to increased plausibility and ease of simulation of partially recombined scenarios. Brief periods of imagination increased conjunction error rates, in line with the imagination inflation effect. Subjective ratings suggest that this inflation is due to similarity of phenomenological experience between conjunction and authentic memories, consistent with a source monitoring perspective. Moreover, objective scoring of memory content indicates that increased perceptual detail may be particularly important for the formation of autobiographical memory conjunction errors. PMID:25611492

Real-world spatial regularities affect visual working memory for objects.

PubMed

Kaiser, Daniel; Stein, Timo; Peelen, Marius V

2015-12-01

Traditional memory research has focused on measuring and modeling the capacity of visual working memory for simple stimuli such as geometric shapes or colored disks. Although these studies have provided important insights, it is unclear how their findings apply to memory for more naturalistic stimuli. An important aspect of real-world scenes is that they contain a high degree of regularity: For instance, lamps appear above tables, not below them. In the present study, we tested whether such real-world spatial regularities affect working memory capacity for individual objects. Using a delayed change-detection task with concurrent verbal suppression, we found enhanced visual working memory performance for objects positioned according to real-world regularities, as compared to irregularly positioned objects. This effect was specific to upright stimuli, indicating that it did not reflect low-level grouping, because low-level grouping would be expected to equally affect memory for upright and inverted displays. These results suggest that objects can be held in visual working memory more efficiently when they are positioned according to frequently experienced real-world regularities. We interpret this effect as the grouping of single objects into larger representational units.

When is working memory important for arithmetic? The impact of strategy and age

PubMed Central

Richardson, Sophie; Hubber, Paula J.; Keeble, Sarah; Gilmore, Camilla

2017-01-01

Our ability to perform arithmetic relies heavily on working memory, the manipulation and maintenance of information in mind. Previous research has found that in adults, procedural strategies, particularly counting, rely on working memory to a greater extent than retrieval strategies. During childhood there are changes in the types of strategies employed, as well as an increase in the accuracy and efficiency of strategy execution. As such it seems likely that the role of working memory in arithmetic may also change, however children and adults have never been directly compared. This study used traditional dual-task methodology, with the addition of a control load condition, to investigate the extent to which working memory requirements for different arithmetic strategies change with age between 9–11 years, 12–14 years and young adulthood. We showed that both children and adults employ working memory when solving arithmetic problems, no matter what strategy they choose. This study highlights the importance of considering working memory in understanding the difficulties that some children and adults have with mathematics, as well as the need to include working memory in theoretical models of mathematical cognition. PMID:29228008

The Role of Ephs and Ephrins in Memory Formation.

PubMed

Dines, Monica; Lamprecht, Raphael

2016-04-01

The ability to efficiently store memories in the brain is a fundamental process and its impairment is associated with multiple human mental disorders. Evidence indicates that long-term memory formation involves alterations of synaptic efficacy produced by modifications in neural transmission and morphology. The Eph receptors and their cognate ephrin ligands have been shown to be involved in these key neuronal processes by regulating events such as presynaptic transmitter release, postsynaptic glutamate receptor conductance and trafficking, synaptic glutamate reuptake, and dendritic spine morphogenesis. Recent findings show that Ephs and ephrins are needed for memory formation in different organisms. These proteins participate in the formation of various types of memories that are subserved by different neurons and brain regions. Ephs and ephrins are involved in brain disorders and diseases with memory impairment symptoms, including Alzheimer's disease and anxiety. Drugs that agonize or antagonize Ephs/ephrins signaling have been developed and could serve as therapeutic agents to treat such diseases. Ephs and ephrins may therefore induce cellular alterations mandatory for memory formation and serve as a target for pharmacological intervention for treatment of memory-related brain diseases. © The Author 2015. Published by Oxford University Press on behalf of CINP.

A multilevel nonvolatile magnetoelectric memory

NASA Astrophysics Data System (ADS)

Shen, Jianxin; Cong, Junzhuang; Shang, Dashan; Chai, Yisheng; Shen, Shipeng; Zhai, Kun; Sun, Young

2016-09-01

The coexistence and coupling between magnetization and electric polarization in multiferroic materials provide extra degrees of freedom for creating next-generation memory devices. A variety of concepts of multiferroic or magnetoelectric memories have been proposed and explored in the past decade. Here we propose a new principle to realize a multilevel nonvolatile memory based on the multiple states of the magnetoelectric coefficient (α) of multiferroics. Because the states of α depends on the relative orientation between magnetization and polarization, one can reach different levels of α by controlling the ratio of up and down ferroelectric domains with external electric fields. Our experiments in a device made of the PMN-PT/Terfenol-D multiferroic heterostructure confirm that the states of α can be well controlled between positive and negative by applying selective electric fields. Consequently, two-level, four-level, and eight-level nonvolatile memory devices are demonstrated at room temperature. This kind of multilevel magnetoelectric memory retains all the advantages of ferroelectric random access memory but overcomes the drawback of destructive reading of polarization. In contrast, the reading of α is nondestructive and highly efficient in a parallel way, with an independent reading coil shared by all the memory cells.

The effects of age, glucose ingestion and gluco-regulatory control on episodic memory.

PubMed

Riby, Leigh Martin; Meikle, Andrew; Glover, Cheryl

2004-09-01

Previous research has been inconclusive regarding the impact of glucose ingestion and gluco-regulatory control on cognitive performance in healthy older adults. The aim of this research was to determine whether glucose specifically enhanced episodic memory in an older population. In addition, the link between individual differences in glucose regulation and the magnitude of the enhancement effect was examined. A within subjects, counterbalanced, crossover design was used with 20 participants (60-80 year olds), each serving as his/her control. Episodic memory was tested by presenting unrelated paired associates followed by immediate and delayed cued recall, and delayed recognition, under single and dual task conditions. In addition, a battery of cognitive tests was administered, including tests of semantic memory, working memory and speed of processing. Glucose ingestion was found to largely facilitate performance of episodic memory. Furthermore, subsidiary analyses found that gluco-regulatory efficiency predicted episodic memory performance in both control and glucose conditions. A boost in performance after glucose ingestion was particularly seen in the episodic memory domain. Notably, strong evidence was provided for the utility of gluco-regulatory control measures as indicators of cognitive decline in the elderly.

Circadian modulation of short-term memory in Drosophila.

PubMed

Lyons, Lisa C; Roman, Gregg

2009-01-01

Endogenous biological clocks are widespread regulators of behavior and physiology, allowing for a more efficient allocation of efforts and resources over the course of a day. The extent that different processes are regulated by circadian oscillators, however, is not fully understood. We investigated the role of the circadian clock on short-term associative memory formation using a negatively reinforced olfactory-learning paradigm in Drosophila melanogaster. We found that memory formation was regulated in a circadian manner. The peak performance in short-term memory (STM) occurred during the early subjective night with a twofold performance amplitude after a single pairing of conditioned and unconditioned stimuli. This rhythm in memory is eliminated in both timeless and period mutants and is absent during constant light conditions. Circadian gating of sensory perception does not appear to underlie the rhythm in short-term memory as evidenced by the nonrhythmic shock avoidance and olfactory avoidance behaviors. Moreover, central brain oscillators appear to be responsible for the modulation as cryptochrome mutants, in which the antennal circadian oscillators are nonfunctional, demonstrate robust circadian rhythms in short-term memory. Together these data suggest that central, rather than peripheral, circadian oscillators modulate the formation of short-term associative memory and not the perception of the stimuli.

Efficient parallelization for AMR MHD multiphysics calculations; implementation in AstroBEAR

NASA Astrophysics Data System (ADS)

Carroll-Nellenback, Jonathan J.; Shroyer, Brandon; Frank, Adam; Ding, Chen

2013-03-01

Current adaptive mesh refinement (AMR) simulations require algorithms that are highly parallelized and manage memory efficiently. As compute engines grow larger, AMR simulations will require algorithms that achieve new levels of efficient parallelization and memory management. We have attempted to employ new techniques to achieve both of these goals. Patch or grid based AMR often employs ghost cells to decouple the hyperbolic advances of each grid on a given refinement level. This decoupling allows each grid to be advanced independently. In AstroBEAR we utilize this independence by threading the grid advances on each level with preference going to the finer level grids. This allows for global load balancing instead of level by level load balancing and allows for greater parallelization across both physical space and AMR level. Threading of level advances can also improve performance by interleaving communication with computation, especially in deep simulations with many levels of refinement. While we see improvements of up to 30% on deep simulations run on a few cores, the speedup is typically more modest (5-20%) for larger scale simulations. To improve memory management we have employed a distributed tree algorithm that requires processors to only store and communicate local sections of the AMR tree structure with neighboring processors. Using this distributed approach we are able to get reasonable scaling efficiency (>80%) out to 12288 cores and up to 8 levels of AMR - independent of the use of threading.

Interplay between affect and arousal in recognition memory.

PubMed

Greene, Ciara M; Bahri, Pooja; Soto, David

2010-07-23

Emotional states linked to arousal and mood are known to affect the efficiency of cognitive performance. However, the extent to which memory processes may be affected by arousal, mood or their interaction is poorly understood. Following a study phase of abstract shapes, we altered the emotional state of participants by means of exposure to music that varied in both mood and arousal dimensions, leading to four different emotional states: (i) positive mood-high arousal; (ii) positive mood-low arousal; (iii) negative mood-high arousal; (iv) negative mood-low arousal. Following the emotional induction, participants performed a memory recognition test. Critically, there was an interaction between mood and arousal on recognition performance. Memory was enhanced in the positive mood-high arousal and in the negative mood-low arousal states, relative to the other emotional conditions. Neither mood nor arousal alone but their interaction appears most critical to understanding the emotional enhancement of memory.

Improved Functional Properties and Efficiencies of Nitinol Wires Under High-Performance Shape Memory Effect (HP-SME)

NASA Astrophysics Data System (ADS)

Casati, R.; Saghafi, F.; Biffi, C. A.; Vedani, M.; Tuissi, A.

2017-10-01

Martensitic Ti-rich NiTi intermetallics are broadly used in various cyclic applications as actuators, which exploit the shape memory effect (SME). Recently, a new approach for exploiting austenitic Ni-rich NiTi shape memory alloys as actuators was proposed and named high-performance shape memory effect (HP-SME). HP-SME is based on thermal recovery of de-twinned martensite produced by mechanical loading of the parent phase. The aim of the manuscript consists in evaluating and comparing the fatigue and actuation properties of austenitic HP-SME wires and conventional martensitic SME wires. The effect of the thermomechanical cycling on the actuation response and the changes in the electrical resistivity of both shape memory materials were studied by performing the actuation tests at different stages of the fatigue life. Finally, the changes in the transition temperatures before and after cycling were also investigated by differential calorimetric tests.

UPC++ Programmer’s Guide (v1.0 2017.9)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bachan, J.; Baden, S.; Bonachea, D.

UPC++ is a C++11 library that provides Asynchronous Partitioned Global Address Space (APGAS) programming. It is designed for writing parallel programs that run efficiently and scale well on distributed-memory parallel computers. The APGAS model is single program, multiple-data (SPMD), with each separate thread of execution (referred to as a rank, a term borrowed from MPI) having access to local memory as it would in C++. However, APGAS also provides access to a global address space, which is allocated in shared segments that are distributed over the ranks. UPC++ provides numerous methods for accessing and using global memory. In UPC++, allmore » operations that access remote memory are explicit, which encourages programmers to be aware of the cost of communication and data movement. Moreover, all remote-memory access operations are by default asynchronous, to enable programmers to write code that scales well even on hundreds of thousands of cores.« less

UPC++ Programmer’s Guide, v1.0-2018.3.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bachan, J.; Baden, S.; Bonachea, Dan

UPC++ is a C++11 library that provides Partitioned Global Address Space (PGAS) programming. It is designed for writing parallel programs that run efficiently and scale well on distributed-memory parallel computers. The PGAS model is single program, multiple-data (SPMD), with each separate thread of execution (referred to as a rank, a term borrowed from MPI) having access to local memory as it would in C++. However, PGAS also provides access to a global address space, which is allocated in shared segments that are distributed over the ranks. UPC++ provides numerous methods for accessing and using global memory. In UPC++, all operationsmore » that access remote memory are explicit, which encourages programmers to be aware of the cost of communication and data movement. Moreover, all remote-memory access operations are by default asynchronous, to enable programmers to write code that scales well even on hundreds of thousands of cores.« less

A ground-based memory state tracker for satellite on-board computer memory

NASA Technical Reports Server (NTRS)

Quan, Alan; Angelino, Robert; Hill, Michael; Schwuttke, Ursula; Hervias, Felipe

1993-01-01

The TOPEX/POSEIDON satellite, currently in Earth orbit, will use radar altimetry to measure sea surface height over 90 percent of the world's ice-free oceans. In combination with a precise determination of the spacecraft orbit, the altimetry data will provide maps of ocean topography, which will be used to calculate the speed and direction of ocean currents worldwide. NASA's Jet Propulsion Laboratory (JPL) has primary responsibility for mission operations for TOPEX/POSEIDON. Software applications have been developed to automate mission operations tasks. This paper describes one of these applications, the Memory State Tracker, which allows the ground analyst to examine and track the contents of satellite on-board computer memory quickly and efficiently, in a human-readable format, without having to receive the data directly from the spacecraft. This process is accomplished by maintaining a groundbased mirror-image of spacecraft On-board Computer memory.

Intelligence moderates the benefits of strategy instructions on memory performance: an adult-lifespan examination.

PubMed

Frankenmolen, Nikita L; Altgassen, Mareike; Kessels, Renée; de Waal, Marleen M; Hindriksen, Julie-Anne; Verhoeven, Barbara; Fasotti, Luciano; Scheres, Anouk; Kessels, Roy P C; Oosterman, Joukje M

2017-01-01

Whether older adults can compensate for their associative memory deficit by using memory strategies efficiently might depend on their general cognitive abilities. This study examined the moderating role of an IQ estimate on the beneficial effects of strategy instructions. A total of 142 participants (aged 18-85 years) received either intentional learning or strategy ("sentence generation") instructions during encoding of word pairs. Whereas young adults with a lower IQ benefited from strategy instructions, those with a higher IQ did not, presumably because they already use strategies spontaneously. Older adults showed the opposite effect: following strategy instructions, older adults with a higher IQ showed a strong increase in memory performance (approximately achieving the level of younger adults), whereas older adults with a lower IQ did not, suggesting that they have difficulties implementing the provided strategies. These results highlight the importance of the role of IQ in compensating for the aging-related memory decline.

Strategy difficulty effects in young and older adults' episodic memory are modulated by inter-stimulus intervals and executive control processes.

PubMed

Burger, Lucile; Uittenhove, Kim; Lemaire, Patrick; Taconnat, Laurence

2017-04-01

Efficient execution of strategies is crucial to memory performance and to age-related differences in this performance. Relative strategy complexity influences memory performance and aging effects on memory. Here, we aimed to further our understanding of the effects of relative strategy complexity by looking at the role of cognitive control functions and the time-course of the effects of relative strategy complexity. Thus, we manipulated inter-stimulus intervals (ISI) and assessed executive functions. Results showed that (a) performance as a function of the relative strategy difficulty of the current and previous trial was modulated by ISI, (b) these effects were modulated by inhibition capacities, and (c) significant age differences were found in the way ISI modulates relative strategy difficulty. These findings have important implications for understanding the relationships between aging, executive control, and strategy execution in episodic memory. Copyright © 2017 Elsevier B.V. All rights reserved.

Recurrent Network models of sequence generation and memory

PubMed Central

Rajan, Kanaka; Harvey, Christopher D; Tank, David W

2016-01-01

SUMMARY Sequential activation of neurons is a common feature of network activity during a variety of behaviors, including working memory and decision making. Previous network models for sequences and memory emphasized specialized architectures in which a principled mechanism is pre-wired into their connectivity. Here, we demonstrate that starting from random connectivity and modifying a small fraction of connections, a largely disordered recurrent network can produce sequences and implement working memory efficiently. We use this process, called Partial In-Network training (PINning), to model and match cellular-resolution imaging data from the posterior parietal cortex during a virtual memory-guided two-alternative forced choice task [Harvey, Coen and Tank, 2012]. Analysis of the connectivity reveals that sequences propagate by the cooperation between recurrent synaptic interactions and external inputs, rather than through feedforward or asymmetric connections. Together our results suggest that neural sequences may emerge through learning from largely unstructured network architectures. PMID:26971945

Parameter optimization for transitions between memory states in small arrays of Josephson junctions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rezac, Jacob D.; Imam, Neena; Braiman, Yehuda

Coupled arrays of Josephson junctions possess multiple stable zero voltage states. Such states can store information and consequently can be utilized for cryogenic memory applications. Basic memory operations can be implemented by sending a pulse to one of the junctions and studying transitions between the states. In order to be suitable for memory operations, such transitions between the states have to be fast and energy efficient. Here in this article we employed simulated annealing, a stochastic optimization algorithm, to study parameter optimization of array parameters which minimizes times and energies of transitions between specifically chosen states that can be utilizedmore » for memory operations (Read, Write, and Reset). Simulation results show that such transitions occur with access times on the order of 10–100 ps and access energies on the order of 10 -19–5×10 -18 J. Numerical simulations are validated with approximate analytical results.« less

Below-baseline suppression of competitors during interference resolution by younger but not older adults.

PubMed

Healey, M Karl; Ngo, K W Joan; Hasher, Lynn

2014-01-01

Resolving interference from competing memories is a critical factor in efficient memory retrieval, and several accounts of cognitive aging suggest that difficulty resolving interference may underlie memory deficits such as those seen in the elderly. Although many researchers have suggested that the ability to suppress competitors is a key factor in resolving interference, the evidence supporting this claim has been the subject of debate. Here, we present a new paradigm and results demonstrating that for younger adults, a single retrieval attempt is sufficient to suppress competitors to below-baseline levels of accessibility even though the competitors are never explicitly presented. The extent to which individual younger adults suppressed competitors predicted their performance on a memory span task. In a second experiment, older adults showed no evidence of suppression, which supports the theory that older adults' memory deficits are related to impaired suppression.

Performance Analysis of the NAS Y-MP Workload

NASA Technical Reports Server (NTRS)

Bergeron, Robert J.; Kutler, Paul (Technical Monitor)

1997-01-01

This paper describes the performance characteristics of the computational workloads on the NAS Cray Y-MP machines, a Y-MP 832 and later a Y-MP 8128. Hardware measurements indicated that the Y-MP workload performance matured over time, ultimately sustaining an average throughput of 0.8 GFLOPS and a vector operation fraction of 87%. The measurements also revealed an operation rate exceeding 1 per clock period, a well-balanced architecture featuring a strong utilization of vector functional units, and an efficient memory organization. Introduction of the larger memory 8128 increased throughput by allowing a more efficient utilization of CPUs. Throughput also depended on the metering of the batch queues; low-idle Saturday workloads required a buffer of small jobs to prevent memory starvation of the CPU. UNICOS required about 7% of total CPU time to service the 832 workloads; this overhead decreased to 5% for the 8128 workloads. While most of the system time went to service I/O requests, efficient scheduling prevented excessive idle due to I/O wait. System measurements disclosed no obvious bottlenecks in the response of the machine and UNICOS to the workloads. In most cases, Cray-provided software tools were- quite sufficient for measuring the performance of both the machine and operating, system.

Effects of fiber pre-strain on the healing efficiency of thermoset polymers

NASA Astrophysics Data System (ADS)

Ajisafe, Oludayo

One major challenge that has been facing material self healing is how to heal bigger macroscopic or structural scale damage autonomously, repeatedly, efficiently and at molecular length scale. Different approaches have been used to heal materials. However, none of them can heal macroscopic cracks. Our research group has proposed a novel shape-memory polymer (SMP) based, bio-inspired Close-Then-Heal (CTH) scheme to heal macroscopic cracks in SMP matrix. The most recent development in our group is to use SMP fibers to heal conventional thermosetting polymers according to the CTH scheme. The aim of this study is to further investigate the effect of pre-tension of SMP fibers during the cold-drawing programming on the self-healing efficiency of the conventional thermosetting polymer composites. This was done by fabricating a composite with thermoplastic particles (polycaprolactone) dispersed in a thermosetting polymer matrix (Epon 828). Shape memory fiber pre-tensioned into 3 different groups of 0%, 50% and 100% prestrain, was also embedded into the composite in the longitudinal direction. In this composite, the shape memory effect of the shape memory fibers is utilized for sealing (closing) the cracks and the thermoplastic particles are used for molecular-length scale healing. In this study, 7% by volume of thermoplastic particles was used. Beam specimens were prepared and controlled structural length scale damage was created prior to curing by inserting an aluminum foil of designed thickness in a perpendicular direction to the shape memory fibers before the matrix was allowed to cure. The aluminum sheet was removed post cure to leave a controlled damage. The specimen was healed by fixing the two ends of the beam and heating the sample above the Tg of the shape memory fiber. The recovery force of the sample was recorded and then the beam was tested again to fracture. This fracture healing cycle lasted 7 times. The healing efficiency was evaluated per the peak-tensile load. The Ultrasonic C-scan and SEM were used to examine the healed cracks. It was found that the beams with 100% pre-strained fiber were able to recover repeatedly about 50% of its peak tensile strength; the beams with 50% pre-strained fiber, 43%; and the beams with un-stretched fibers were able to recover about 21% of its original peak tensile strength. Also it was found that the higher the pre-tension the higher the recovery stress seen during the healing cycle.

Distinct cellular pathways select germline-encoded and somatically mutated antibodies into immunological memory

PubMed Central

Kaji, Tomohiro; Ishige, Akiko; Hikida, Masaki; Taka, Junko; Hijikata, Atsushi; Kubo, Masato; Nagashima, Takeshi; Takahashi, Yoshimasa; Kurosaki, Tomohiro; Okada, Mariko; Ohara, Osamu

2012-01-01

One component of memory in the antibody system is long-lived memory B cells selected for the expression of somatically mutated, high-affinity antibodies in the T cell–dependent germinal center (GC) reaction. A puzzling observation has been that the memory B cell compartment also contains cells expressing unmutated, low-affinity antibodies. Using conditional Bcl6 ablation, we demonstrate that these cells are generated through proliferative expansion early after immunization in a T cell–dependent but GC-independent manner. They soon become resting and long-lived and display a novel distinct gene expression signature which distinguishes memory B cells from other classes of B cells. GC-independent memory B cells are later joined by somatically mutated GC descendants at roughly equal proportions and these two types of memory cells efficiently generate adoptive secondary antibody responses. Deletion of T follicular helper (Tfh) cells significantly reduces the generation of mutated, but not unmutated, memory cells early on in the response. Thus, B cell memory is generated along two fundamentally distinct cellular differentiation pathways. One pathway is dedicated to the generation of high-affinity somatic antibody mutants, whereas the other preserves germ line antibody specificities and may prepare the organism for rapid responses to antigenic variants of the invading pathogen. PMID:23027924

Cost-effective, transfer-free, flexible resistive random access memory using laser-scribed reduced graphene oxide patterning technology.

PubMed

Tian, He; Chen, Hong-Yu; Ren, Tian-Ling; Li, Cheng; Xue, Qing-Tang; Mohammad, Mohammad Ali; Wu, Can; Yang, Yi; Wong, H-S Philip

2014-06-11

Laser scribing is an attractive reduced graphene oxide (rGO) growth and patterning technology because the process is low-cost, time-efficient, transfer-free, and flexible. Various laser-scribed rGO (LSG) components such as capacitors, gas sensors, and strain sensors have been demonstrated. However, obstacles remain toward practical application of the technology where all the components of a system are fabricated using laser scribing. Memory components, if developed, will substantially broaden the application space of low-cost, flexible electronic systems. For the first time, a low-cost approach to fabricate resistive random access memory (ReRAM) using laser-scribed rGO as the bottom electrode is experimentally demonstrated. The one-step laser scribing technology allows transfer-free rGO synthesis directly on flexible substrates or non-flat substrates. Using this time-efficient laser-scribing technology, the patterning of a memory-array area up to 100 cm(2) can be completed in 25 min. Without requiring the photoresist coating for lithography, the surface of patterned rGO remains as clean as its pristine state. Ag/HfOx/LSG ReRAM using laser-scribing technology is fabricated in this work. Comprehensive electrical characteristics are presented including forming-free behavior, stable switching, reasonable reliability performance and potential for 2-bit storage per memory cell. The results suggest that laser-scribing technology can potentially produce more cost-effective and time-effective rGO-based circuits and systems for practical applications.

A comparison of several methods of solving nonlinear regression groundwater flow problems

USGS Publications Warehouse

Cooley, Richard L.

1985-01-01

Computational efficiency and computer memory requirements for four methods of minimizing functions were compared for four test nonlinear-regression steady state groundwater flow problems. The fastest methods were the Marquardt and quasi-linearization methods, which required almost identical computer times and numbers of iterations; the next fastest was the quasi-Newton method, and last was the Fletcher-Reeves method, which did not converge in 100 iterations for two of the problems. The fastest method per iteration was the Fletcher-Reeves method, and this was followed closely by the quasi-Newton method. The Marquardt and quasi-linearization methods were slower. For all four methods the speed per iteration was directly related to the number of parameters in the model. However, this effect was much more pronounced for the Marquardt and quasi-linearization methods than for the other two. Hence the quasi-Newton (and perhaps Fletcher-Reeves) method might be more efficient than either the Marquardt or quasi-linearization methods if the number of parameters in a particular model were large, although this remains to be proven. The Marquardt method required somewhat less central memory than the quasi-linearization metilod for three of the four problems. For all four problems the quasi-Newton method required roughly two thirds to three quarters of the memory required by the Marquardt method, and the Fletcher-Reeves method required slightly less memory than the quasi-Newton method. Memory requirements were not excessive for any of the four methods.

I/O efficient algorithms and applications in geographic information systems

NASA Astrophysics Data System (ADS)

Danner, Andrew

Modern remote sensing methods such a laser altimetry (lidar) and Interferometric Synthetic Aperture Radar (IfSAR) produce georeferenced elevation data at unprecedented rates. Many Geographic Information System (GIS) algorithms designed for terrain modelling applications cannot process these massive data sets. The primary problem is that these data sets are too large to fit in the main internal memory of modern computers and must therefore reside on larger, but considerably slower disks. In these applications, the transfer of data between disk and main memory, or I/O, becomes the primary bottleneck. Working in a theoretical model that more accurately represents this two level memory hierarchy, we can develop algorithms that are I/O-efficient and reduce the amount of disk I/O needed to solve a problem. In this thesis we aim to modernize GIS algorithms and develop a number of I/O-efficient algorithms for processing geographic data derived from massive elevation data sets. For each application, we convert a geographic question to an algorithmic question, develop an I/O-efficient algorithm that is theoretically efficient, implement our approach and verify its performance using real-world data. The applications we consider include constructing a gridded digital elevation model (DEM) from an irregularly spaced point cloud, removing topological noise from a DEM, modeling surface water flow over a terrain, extracting river networks and watershed hierarchies from the terrain, and locating polygons containing query points in a planar subdivision. We initially developed solutions to each of these applications individually. However, we also show how to combine individual solutions to form a scalable geo-processing pipeline that seamlessly solves a sequence of sub-problems with little or no manual intervention. We present experimental results that demonstrate orders of magnitude improvement over previously known algorithms.

Exploring performance issues for a clinical database organized using an entity-attribute-value representation.

PubMed

Chen, R S; Nadkarni, P; Marenco, L; Levin, F; Erdos, J; Miller, P L

2000-01-01

The entity-attribute-value representation with classes and relationships (EAV/CR) provides a flexible and simple database schema to store heterogeneous biomedical data. In certain circumstances, however, the EAV/CR model is known to retrieve data less efficiently than conventionally based database schemas. To perform a pilot study that systematically quantifies performance differences for database queries directed at real-world microbiology data modeled with EAV/CR and conventional representations, and to explore the relative merits of different EAV/CR query implementation strategies. Clinical microbiology data obtained over a ten-year period were stored using both database models. Query execution times were compared for four clinically oriented attribute-centered and entity-centered queries operating under varying conditions of database size and system memory. The performance characteristics of three different EAV/CR query strategies were also examined. Performance was similar for entity-centered queries in the two database models. Performance in the EAV/CR model was approximately three to five times less efficient than its conventional counterpart for attribute-centered queries. The differences in query efficiency became slightly greater as database size increased, although they were reduced with the addition of system memory. The authors found that EAV/CR queries formulated using multiple, simple SQL statements executed in batch were more efficient than single, large SQL statements. This paper describes a pilot project to explore issues in and compare query performance for EAV/CR and conventional database representations. Although attribute-centered queries were less efficient in the EAV/CR model, these inefficiencies may be addressable, at least in part, by the use of more powerful hardware or more memory, or both.

Protein-Based Three-Dimensional Memories and Associative Processors

NASA Astrophysics Data System (ADS)

Birge, Robert

2008-03-01

The field of bioelectronics has benefited from the fact that nature has often solved problems of a similar nature to those which must be solved to create molecular electronic or photonic devices that operate with efficiency and reliability. Retinal proteins show great promise in bioelectronic devices because they operate with high efficiency (˜0.65%), high cyclicity (>10^7), operate over an extended wavelength range (360 -- 630 nm) and can convert light into changes in voltage, pH, absorption or refractive index. This talk will focus on a retinal protein called bacteriorhodopsin, the proton pump of the organism Halobacterium salinarum. Two memories based on this protein will be described. The first is an optical three-dimensional memory. This memory stores information using volume elements (voxels), and provides as much as a thousand-fold improvement in effective capacity over current technology. A unique branching reaction of a variant of bacteriorhodopsin is used to turn each protein into an optically addressed latched AND gate. Although three working prototypes have been developed, a number of cost/performance and architectural issues must be resolved prior to commercialization. The major issue is that the native protein provides a very inefficient branching reaction. Genetic engineering has improved performance by nearly 500-fold, but a further order of magnitude improvement is needed. Protein-based holographic associative memories will also be discussed. The human brain stores and retrieves information via association, and human intelligence is intimately connected to the nature and enormous capacity of this associative search and retrieval process. To a first order approximation, creativity can be viewed as the association of two seemingly disparate concepts to form a totally new construct. Thus, artificial intelligence requires large scale associative memories. Current computer hardware does not provide an optimal environment for creating artificial intelligence due to the serial nature of random access memories. Software cannot provide a satisfactory work-around that does not introduce unacceptable latency. Holographic associative memories provide a useful approach to large scale associative recall. Bacteriorhodopsin has long been recognized for its outstanding holographic properties, and when utilized in the Paek and Psaltis design, provides a high-speed real-time associative memory with variable thresholding and feedback. What remains is to make an associative memory capable of high-speed association and long-term data storage. The use of directed evolution to create a protein with the necessary unique properties will be discussed.

Lesser Neural Pattern Similarity across Repeated Tests Is Associated with Better Long-Term Memory Retention.

PubMed

Karlsson Wirebring, Linnea; Wiklund-Hörnqvist, Carola; Eriksson, Johan; Andersson, Micael; Jonsson, Bert; Nyberg, Lars

2015-07-01

Encoding and retrieval processes enhance long-term memory performance. The efficiency of encoding processes has recently been linked to representational consistency: the reactivation of a representation that gets more specific each time an item is further studied. Here we examined the complementary hypothesis of whether the efficiency of retrieval processes also is linked to representational consistency. Alternatively, recurrent retrieval might foster representational variability--the altering or adding of underlying memory representations. Human participants studied 60 Swahili-Swedish word pairs before being scanned with fMRI the same day and 1 week later. On Day 1, participants were tested three times on each word pair, and on Day 7 each pair was tested once. A BOLD signal change in right superior parietal cortex was associated with subsequent memory on Day 1 and with successful long-term retention on Day 7. A representational similarity analysis in this parietal region revealed that beneficial recurrent retrieval was associated with representational variability, such that the pattern similarity on Day 1 was lower for retrieved words subsequently remembered compared with those subsequently forgotten. This was mirrored by a monotonically decreased BOLD signal change in dorsolateral prefrontal cortex on Day 1 as a function of repeated successful retrieval for words subsequently remembered, but not for words subsequently forgotten. This reduction in prefrontal response could reflect reduced demands on cognitive control. Collectively, the results offer novel insights into why memory retention benefits from repeated retrieval, and they suggest fundamental differences between repeated study and repeated testing. Repeated testing is known to produce superior long-term retention of the to-be-learned material compared with repeated encoding and other learning techniques, much because it fosters repeated memory retrieval. This study demonstrates that repeated memory retrieval might strengthen memory by inducing more differentiated or elaborated memory representations in the parietal cortex, and at the same time reducing demands on prefrontal-cortex-mediated cognitive control processes during retrieval. The findings contrast with recent demonstrations that repeated encoding induces less differentiated or elaborated memory representations. Together, this study suggests a potential neurocognitive explanation of why repeated retrieval is more beneficial for long-term retention than repeated encoding, a phenomenon known as the testing effect. Copyright © 2015 the authors 0270-6474/15/359595-08$15.00/0.

Modulation of learning and memory by the genetic disruption of circadian oscillator populations.

PubMed

Snider, Kaitlin H; Obrietan, Karl

2018-06-23

While a rich literature has documented that the efficiency of learning and memory varies across circadian time, a close survey of that literature reveals extensive heterogeneity in the time of day (TOD) when peak cognitive performance occurs. Moreover, most previous experiments in rodents have not focused on the question of discriminating which memory processes (e.g., working memory, memory acquisition, or retrieval) are modulated by the TOD. Here, we use assays of contextual fear conditioning and spontaneous alternation in WT (C57Bl/6 J) mice to survey circadian modulation of hippocampal-dependent memory at multiple timescales - including working memory (seconds to a few minutes), intermediate-term memory (a delay of thirty minutes), and acquisition and retrieval of long-term memory (a delay of two days). Further, in order to test the relative contributions of circadian timing mechanisms to the modulation of memory, a parallel set of studies were performed in mice lacking clock timing mechanisms. These transgenic mice lacked the essential circadian gene Bmal1, either globally (Bmal1 null) or locally (floxed Bmal1 mice which lack Bmal1 in excitatory forebrain neurons, e.g. cortical and hippocampal neurons). Here, we show that in WT mice, retrieval (but not working memory, intermediate-term memory, or acquisition of long-term memory) is modulated by TOD. However, transgenic mouse models lacking Bmal1 - both globally, and only in forebrain excitatory neurons - show deficits regardless of the memory process tested (and lack circadian modulation of retrieval). These results provide new clarity regarding the impact of TOD on hippocampal-dependent memory and support the key role of hippocampal and cortical circadian oscillations in circadian gating of cognition. Copyright © 2018. Published by Elsevier Inc.

What top-down task sets do for us: an ERP study on the benefits of advance preparation in visual search.

PubMed

Eimer, Martin; Kiss, Monika; Nicholas, Susan

2011-12-01

When target-defining features are specified in advance, attentional target selection in visual search is controlled by preparatory top-down task sets. We used ERP measures to study voluntary target selection in the absence of such feature-specific task sets, and to compare it to selection that is guided by advance knowledge about target features. Visual search arrays contained two different color singleton digits, and participants had to select one of these as target and report its parity. Target color was either known in advance (fixed color task) or had to be selected anew on each trial (free color-choice task). ERP correlates of spatially selective attentional target selection (N2pc) and working memory processing (SPCN) demonstrated rapid target selection and efficient exclusion of color singleton distractors from focal attention and working memory in the fixed color task. In the free color-choice task, spatially selective processing also emerged rapidly, but selection efficiency was reduced, with nontarget singleton digits capturing attention and gaining access to working memory. Results demonstrate the benefits of top-down task sets: Feature-specific advance preparation accelerates target selection, rapidly resolves attentional competition, and prevents irrelevant events from attracting attention and entering working memory.

Low latency messages on distributed memory multiprocessors

NASA Technical Reports Server (NTRS)

Rosing, Matthew; Saltz, Joel

1993-01-01

Many of the issues in developing an efficient interface for communication on distributed memory machines are described and a portable interface is proposed. Although the hardware component of message latency is less than one microsecond on many distributed memory machines, the software latency associated with sending and receiving typed messages is on the order of 50 microseconds. The reason for this imbalance is that the software interface does not match the hardware. By changing the interface to match the hardware more closely, applications with fine grained communication can be put on these machines. Based on several tests that were run on the iPSC/860, an interface that will better match current distributed memory machines is proposed. The model used in the proposed interface consists of a computation processor and a communication processor on each node. Communication between these processors and other nodes in the system is done through a buffered network. Information that is transmitted is either data or procedures to be executed on the remote processor. The dual processor system is better suited for efficiently handling asynchronous communications compared to a single processor system. The ability to send data or procedure is very flexible for minimizing message latency, based on the type of communication being performed. The test performed and the proposed interface are described.

Time and Memory Efficient Online Piecewise Linear Approximation of Sensor Signals.

PubMed

Grützmacher, Florian; Beichler, Benjamin; Hein, Albert; Kirste, Thomas; Haubelt, Christian

2018-05-23

Piecewise linear approximation of sensor signals is a well-known technique in the fields of Data Mining and Activity Recognition. In this context, several algorithms have been developed, some of them with the purpose to be performed on resource constrained microcontroller architectures of wireless sensor nodes. While microcontrollers are usually constrained in computational power and memory resources, all state-of-the-art piecewise linear approximation techniques either need to buffer sensor data or have an execution time depending on the segment’s length. In the paper at hand, we propose a novel piecewise linear approximation algorithm, with a constant computational complexity as well as a constant memory complexity. Our proposed algorithm’s worst-case execution time is one to three orders of magnitude smaller and its average execution time is three to seventy times smaller compared to the state-of-the-art Piecewise Linear Approximation (PLA) algorithms in our experiments. In our evaluations, we show that our algorithm is time and memory efficient without sacrificing the approximation quality compared to other state-of-the-art piecewise linear approximation techniques, while providing a maximum error guarantee per segment, a small parameter space of only one parameter, and a maximum latency of one sample period plus its worst-case execution time.

Genotype Imputation with Millions of Reference Samples

PubMed Central

Browning, Brian L.; Browning, Sharon R.

2016-01-01

We present a genotype imputation method that scales to millions of reference samples. The imputation method, based on the Li and Stephens model and implemented in Beagle v.4.1, is parallelized and memory efficient, making it well suited to multi-core computer processors. It achieves fast, accurate, and memory-efficient genotype imputation by restricting the probability model to markers that are genotyped in the target samples and by performing linear interpolation to impute ungenotyped variants. We compare Beagle v.4.1 with Impute2 and Minimac3 by using 1000 Genomes Project data, UK10K Project data, and simulated data. All three methods have similar accuracy but different memory requirements and different computation times. When imputing 10 Mb of sequence data from 50,000 reference samples, Beagle’s throughput was more than 100× greater than Impute2’s throughput on our computer servers. When imputing 10 Mb of sequence data from 200,000 reference samples in VCF format, Minimac3 consumed 26× more memory per computational thread and 15× more CPU time than Beagle. We demonstrate that Beagle v.4.1 scales to much larger reference panels by performing imputation from a simulated reference panel having 5 million samples and a mean marker density of one marker per four base pairs. PMID:26748515

An efficient photogrammetric stereo matching method for high-resolution images

NASA Astrophysics Data System (ADS)

Li, Yingsong; Zheng, Shunyi; Wang, Xiaonan; Ma, Hao

2016-12-01

Stereo matching of high-resolution images is a great challenge in photogrammetry. The main difficulty is the enormous processing workload that involves substantial computing time and memory consumption. In recent years, the semi-global matching (SGM) method has been a promising approach for solving stereo problems in different data sets. However, the time complexity and memory demand of SGM are proportional to the scale of the images involved, which leads to very high consumption when dealing with large images. To solve it, this paper presents an efficient hierarchical matching strategy based on the SGM algorithm using single instruction multiple data instructions and structured parallelism in the central processing unit. The proposed method can significantly reduce the computational time and memory required for large scale stereo matching. The three-dimensional (3D) surface is reconstructed by triangulating and fusing redundant reconstruction information from multi-view matching results. Finally, three high-resolution aerial date sets are used to evaluate our improvement. Furthermore, precise airborne laser scanner data of one data set is used to measure the accuracy of our reconstruction. Experimental results demonstrate that our method remarkably outperforms in terms of time and memory savings while maintaining the density and precision of the 3D cloud points derived.

A Novel Bat-Shaped Dicyanomethylene-4H-pyran-Functionalized Naphthalimide for Highly Efficient Solution-Processed Multilevel Memory Devices.

PubMed

Zhang, Qi-Jian; Miao, Shi-Feng; Li, Hua; He, Jing-Hui; Li, Na-Jun; Xu, Qing-Feng; Chen, Dong-Yun; Lu, Jian-Mei

2017-06-19

Small-molecule-based multilevel memory devices have attracted increasing attention because of their advantages, such as super-high storage density, fast reading speed, light weight, low energy consumption, and shock resistance. However, the fabrication of small-molecule-based devices always requires expensive vacuum-deposition techniques or high temperatures for spin-coating. Herein, through rational tailoring of a previous molecule, DPCNCANA (4,4'-(6,6'-bis(2-octyl-1,3-dioxo-2,3-dihydro-1H-benzo[de]isoquinolin-6-yl)-9H,9'H-[3,3'-bicarbazole]-9,9'-diyl)dibenzonitrile), a novel bat-shaped A-D-A-type (A-D-A=acceptor-donor-acceptor) symmetric framework has been successfully synthesized and can be dissolved in common solvents at room temperature. Additionally, it has a low-energy bandgap and dense intramolecular stacking in the film state. The solution-processed memory devices exhibited high-performance nonvolatile multilevel data-storage properties with low switching threshold voltages of about -1.3 and -2.7 V, which is beneficial for low power consumption. Our result should prompt the study of highly efficient solution-processed multilevel memory devices in the field of organic electronics. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Fractional Steps methods for transient problems on commodity computer architectures

NASA Astrophysics Data System (ADS)

Krotkiewski, M.; Dabrowski, M.; Podladchikov, Y. Y.

2008-12-01

Fractional Steps methods are suitable for modeling transient processes that are central to many geological applications. Low memory requirements and modest computational complexity facilitates calculations on high-resolution three-dimensional models. An efficient implementation of Alternating Direction Implicit/Locally One-Dimensional schemes for an Opteron-based shared memory system is presented. The memory bandwidth usage, the main bottleneck on modern computer architectures, is specially addressed. High efficiency of above 2 GFlops per CPU is sustained for problems of 1 billion degrees of freedom. The optimized sequential implementation of all 1D sweeps is comparable in execution time to copying the used data in the memory. Scalability of the parallel implementation on up to 8 CPUs is close to perfect. Performing one timestep of the Locally One-Dimensional scheme on a system of 1000 3 unknowns on 8 CPUs takes only 11 s. We validate the LOD scheme using a computational model of an isolated inclusion subject to a constant far field flux. Next, we study numerically the evolution of a diffusion front and the effective thermal conductivity of composites consisting of multiple inclusions and compare the results with predictions based on the differential effective medium approach. Finally, application of the developed parabolic solver is suggested for a real-world problem of fluid transport and reactions inside a reservoir.

Memory-optimized shift operator alternating direction implicit finite difference time domain method for plasma

NASA Astrophysics Data System (ADS)

Song, Wanjun; Zhang, Hou

2017-11-01

Through introducing the alternating direction implicit (ADI) technique and the memory-optimized algorithm to the shift operator (SO) finite difference time domain (FDTD) method, the memory-optimized SO-ADI FDTD for nonmagnetized collisional plasma is proposed and the corresponding formulae of the proposed method for programming are deduced. In order to further the computational efficiency, the iteration method rather than Gauss elimination method is employed to solve the equation set in the derivation of the formulae. Complicated transformations and convolutions are avoided in the proposed method compared with the Z transforms (ZT) ADI FDTD method and the piecewise linear JE recursive convolution (PLJERC) ADI FDTD method. The numerical dispersion of the SO-ADI FDTD method with different plasma frequencies and electron collision frequencies is analyzed and the appropriate ratio of grid size to the minimum wavelength is given. The accuracy of the proposed method is validated by the reflection coefficient test on a nonmagnetized collisional plasma sheet. The testing results show that the proposed method is advantageous for improving computational efficiency and saving computer memory. The reflection coefficient of a perfect electric conductor (PEC) sheet covered by multilayer plasma and the RCS of the objects coated by plasma are calculated by the proposed method and the simulation results are analyzed.

The impact of interference on short-term memory for visual orientation.

PubMed

Rademaker, Rosanne L; Bloem, Ilona M; De Weerd, Peter; Sack, Alexander T

2015-12-01

Visual short-term memory serves as an efficient buffer for maintaining no longer directly accessible information. How robust are visual memories against interference? Memory for simple visual features has proven vulnerable to distractors containing conflicting information along the relevant stimulus dimension, leading to the idea that interacting feature-specific channels at an early stage of visual processing support memory for simple visual features. Here we showed that memory for a single randomly orientated grating was susceptible to interference from a to-be-ignored distractor grating presented midway through a 3-s delay period. Memory for the initially presented orientation became noisier when it differed from the distractor orientation, and response distributions were shifted toward the distractor orientation (by ∼3°). Interestingly, when the distractor was rendered task-relevant by making it a second memory target, memory for both retained orientations showed reduced reliability as a function of increased orientation differences between them. However, the degree to which responses to the first grating shifted toward the orientation of the task-relevant second grating was much reduced. Finally, using a dichoptic display, we demonstrated that these systematic biases caused by a consciously perceived distractor disappeared once the distractor was presented outside of participants' awareness. Together, our results show that visual short-term memory for orientation can be systematically biased by interfering information that is consciously perceived. (c) 2015 APA, all rights reserved).

Intrinsic functional connectivity between amygdala and hippocampus during rest predicts enhanced memory under stress.

PubMed

de Voogd, Lycia D; Klumpers, Floris; Fernández, Guillén; Hermans, Erno J

2017-01-01

Declarative memories of stressful events are less prone to forgetting than mundane events. Animal research has demonstrated that such stress effects on consolidation of hippocampal-dependent memories require the amygdala. In humans, it has been shown that during learning, increased amygdala-hippocampal interactions are related to more efficient memory encoding. Animal models predict that following learning, amygdala-hippocampal interactions are instrumental to strengthening the consolidation of such declarative memories. Whether this is the case in humans is unknown and remains to be empirically verified. To test this, we analyzed data from a sample of 120 healthy male participants who performed an incidental encoding task and subsequently underwent resting-state functional MRI in a stressful and a neutral context. Stress was assessed by measures of salivary cortisol, blood pressure, heart rate, and subjective ratings. Memory was tested afterwards outside of the scanner. Our data show that memory was stronger in the stress context compared to the neutral context and that stress-induced cortisol responses were associated with this memory enhancement. Interestingly, amygdala-hippocampal connectivity during post-encoding awake rest regardless of context (stress or neutral) was associated with the enhanced memory performance under stress. Thus, our findings are in line with a role for intrinsic functional connectivity during rest between the amygdala and the hippocampus in the state effects of stress on strengthening memory. Copyright © 2016 Elsevier Ltd. All rights reserved.

Efficient implementation of multidimensional fast fourier transform on a distributed-memory parallel multi-node computer

DOEpatents

Bhanot, Gyan V [Princeton, NJ; Chen, Dong [Croton-On-Hudson, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY

2012-01-10

The present in invention is directed to a method, system and program storage device for efficiently implementing a multidimensional Fast Fourier Transform (FFT) of a multidimensional array comprising a plurality of elements initially distributed in a multi-node computer system comprising a plurality of nodes in communication over a network, comprising: distributing the plurality of elements of the array in a first dimension across the plurality of nodes of the computer system over the network to facilitate a first one-dimensional FFT; performing the first one-dimensional FFT on the elements of the array distributed at each node in the first dimension; re-distributing the one-dimensional FFT-transformed elements at each node in a second dimension via "all-to-all" distribution in random order across other nodes of the computer system over the network; and performing a second one-dimensional FFT on elements of the array re-distributed at each node in the second dimension, wherein the random order facilitates efficient utilization of the network thereby efficiently implementing the multidimensional FFT. The "all-to-all" re-distribution of array elements is further efficiently implemented in applications other than the multidimensional FFT on the distributed-memory parallel supercomputer.

Efficient implementation of a multidimensional fast fourier transform on a distributed-memory parallel multi-node computer

DOEpatents

Bhanot, Gyan V [Princeton, NJ; Chen, Dong [Croton-On-Hudson, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY

2008-01-01

The present in invention is directed to a method, system and program storage device for efficiently implementing a multidimensional Fast Fourier Transform (FFT) of a multidimensional array comprising a plurality of elements initially distributed in a multi-node computer system comprising a plurality of nodes in communication over a network, comprising: distributing the plurality of elements of the array in a first dimension across the plurality of nodes of the computer system over the network to facilitate a first one-dimensional FFT; performing the first one-dimensional FFT on the elements of the array distributed at each node in the first dimension; re-distributing the one-dimensional FFT-transformed elements at each node in a second dimension via "all-to-all" distribution in random order across other nodes of the computer system over the network; and performing a second one-dimensional FFT on elements of the array re-distributed at each node in the second dimension, wherein the random order facilitates efficient utilization of the network thereby efficiently implementing the multidimensional FFT. The "all-to-all" re-distribution of array elements is further efficiently implemented in applications other than the multidimensional FFT on the distributed-memory parallel supercomputer.

Effects of Transcranial Direct Current Stimulation (tDCS) on Human Memory.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matzen, Laura E.; Trumbo, Michael Christopher Stefan

Training a person in a new knowledge base or skill set is extremely time consuming and costly, particularly in highly specialized domains such as the military and the intelligence community. Recent research in cognitive neuroscience has suggested that a technique called transcranial direct current stimulation (tDCS) has the potential to revolutionize training by enabling learners to acquire new skills faster, more efficiently, and more robustly (Bullard et al., 2011). In this project, we tested the effects of tDCS on two types of memory performance that are critical for learning new skills: associative memory and working memory. Associative memory is memorymore » for the relationship between two items or events. It forms the foundation of all episodic memories, so enhancing associative memory could provide substantial benefits to the speed and robustness of learning new information. We tested the effects of tDCS on associative memory, using a real-world associative memory task: remembering the links between faces and names. Working memory refers to the amount of information that can be held in mind and processed at one time, and it forms the basis for all higher-level cognitive processing. We investigated the degree of transfer between various working memory tasks (the N-back task as a measure of verbal working memory, the rotation-span task as a measure of visuospatial working memory, and Raven's progressive matrices as a measure of fluid intelligence) in order to determine if tDCS-induced facilitation of performance is task-specific or general.« less

Effects of Interfacial Fluorination on Performance Enhancement of High-k-Based Charge Trap Flash Memory

NASA Astrophysics Data System (ADS)

Wang, Chenjie; Huo, Zongliang; Liu, Ziyu; Liu, Yu; Cui, Yanxiang; Wang, Yumei; Li, Fanghua; Liu, Ming

2013-07-01

The effects of interfacial fluorination on the metal/Al2O3/HfO2/SiO2/Si (MAHOS) memory structure have been investigated. By comparing MAHOS memories with and without interfacial fluorination, it was identified that the deterioration of the performance and reliability of MAHOS memories is mainly due to the formation of an interfacial layer that generates excess oxygen vacancies at the interface. Interfacial fluorination suppresses the growth of the interfacial layer, which is confirmed by X-ray photoelectron spectroscopy depth profile analysis, increases enhanced program/erase efficiency, and improves data retention characteristics. Moreover, it was observed that fluorination at the SiO-HfO interface achieves a more effective performance enhancement than that at the HfO-AlO interface.

The memory effect of magnetoelectric coupling in FeGaB/NiTi/PMN-PT multiferroic heterostructure

PubMed Central

Zhou, Ziyao; Zhao, Shishun; Gao, Yuan; Wang, Xinjun; Nan, Tianxiang; Sun, Nian X.; Yang, Xi; Liu, Ming

2016-01-01

Magnetoelectric coupling effect has provided a power efficient approach in controlling the magnetic properties of ferromagnetic materials. However, one remaining issue of ferromagnetic/ferroelectric magnetoelectric bilayer composite is that the induced effective anisotropy disappears with the removal of the electric field. The introducing of the shape memory alloys may prevent such problem by taking the advantage of its shape memory effect. Additionally, the shape memory alloy can also “store” the magnetoelectric coupling before heat release, which introduces more functionality to the system. In this paper, we study a FeGaB/NiTi/PMN-PT multiferroic heterostructure, which can be operating in different states with electric field and temperature manipulation. Such phenomenon is promising for tunable multiferroic devices with multi-functionalities. PMID:26847469

ILC2 memory: Recollection of previous activation.

PubMed

Martinez-Gonzalez, Itziar; Ghaedi, Maryam; Steer, Catherine A; Mathä, Laura; Vivier, Eric; Takei, Fumio

2018-05-01

Immunological memory, traditionally thought to belong to T and B cells, has now been extended to innate lymphocytes, including NK cells and ILC2s, myeloid cells such as macrophages, also termed "trained immunity" and more recently to epithelial stem cells. In this review, we discuss the mechanisms underlying memory generation on ILC2s and speculate about their potential role in human allergic diseases, such as asthma. Moreover, we examine the relevance of the spontaneous ILC2 activation in the lung during the neonatal period in order to efficiently respond to stimuli later in life. These "training" of neonatal ILC2s may have an impact on the generation of memory ILC2s in the adulthood. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

[The contribution of patient H.M. to modern neuroscience].

PubMed

Kawachi, Juro

2013-08-01

In 1953, 27-year-old H.M. underwent bilateral medial temporal lobes resection to control his seizures; however, he suffered from severe amnesia as a result. For the next five decades until his death in December 2008 at the age 82, he was the subject of numerous studies performed by over 100 investigators. The reason why research on H.M. continued for so long is mostly attributed to the efficient organization of excellent researchers. The principal findings of H.M. study encouraged the concept of medial temporal lobe memory system and multiple memory systems, and suggested the slow acquisition of semantic knowledge without medial temporal lobe memory system through repeated experience. By the grace of H.M.'s lifelong contribution, the neuroscience of memory is in full flourish.

Bessel function expansion to reduce the calculation time and memory usage for cylindrical computer-generated holograms.

PubMed

Sando, Yusuke; Barada, Daisuke; Jackin, Boaz Jessie; Yatagai, Toyohiko

2017-07-10

This study proposes a method to reduce the calculation time and memory usage required for calculating cylindrical computer-generated holograms. The wavefront on the cylindrical observation surface is represented as a convolution integral in the 3D Fourier domain. The Fourier transformation of the kernel function involving this convolution integral is analytically performed using a Bessel function expansion. The analytical solution can drastically reduce the calculation time and the memory usage without any cost, compared with the numerical method using fast Fourier transform to Fourier transform the kernel function. In this study, we present the analytical derivation, the efficient calculation of Bessel function series, and a numerical simulation. Furthermore, we demonstrate the effectiveness of the analytical solution through comparisons of calculation time and memory usage.

[Effect of concreteness of target words on verbal working memory: an evaluation using Japanese version of reading span test].

PubMed

Kondo, H; Osaka, N

2000-04-01

Effects of concreteness and representation mode (kanji/hiragana) of target words on working memory during reading was tested using Japanese version of reading span test (RST), developed by Osaka and Osaka (1994). Concreteness and familiarity of target words and difficulty of sentences were carefully controlled. The words with high concreteness resulted in significantly higher RST scores, which suggests the high efficiency of working memory in processing these words. The results suggest that high concrete noun-words associated with visual clues consume less working memory capacity during reading. The effect of representation mode is different between subjects with high-RST and low-RST scores. Characteristic of the high concrete words that may be responsible for the effectiveness of processing are discussed.

Data Movement Dominates: Advanced Memory Technology to Address the Real Exascale Power Problem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bergman, Keren

Energy is the fundamental barrier to Exascale supercomputing and is dominated by the cost of moving data from one point to another, not computation. Similarly, performance is dominated by data movement, not computation. The solution to this problem requires three critical technologies: 3D integration, optical chip-to-chip communication, and a new communication model. The central goal of the Sandia led "Data Movement Dominates" project aimed to develop memory systems and new architectures based on these technologies that have the potential to lower the cost of local memory accesses by orders of magnitude and provide substantially more bandwidth. Only through these transformationalmore » advances can future systems reach the goals of Exascale computing with a manageable power budgets. The Sandia led team included co-PIs from Columbia University, Lawrence Berkeley Lab, and the University of Maryland. The Columbia effort of Data Movement Dominates focused on developing a physically accurate simulation environment and experimental verification for optically-connected memory (OCM) systems that can enable continued performance scaling through high-bandwidth capacity, energy-efficient bit-rate transparency, and time-of-flight latency. With OCM, memory device parallelism and total capacity can scale to match future high-performance computing requirements without sacrificing data-movement efficiency. When we consider systems with integrated photonics, links to memory can be seamlessly integrated with the interconnection network-in a sense, memory becomes a primary aspect of the interconnection network. At the core of the Columbia effort, toward expanding our understanding of OCM enabled computing we have created an integrated modeling and simulation environment that uniquely integrates the physical behavior of the optical layer. The PhoenxSim suite of design and software tools developed under this effort has enabled the co-design of and performance evaluation photonics-enabled OCM architectures on Exascale computing systems.« less

A Study on the Learning Efficiency of Multimedia-Presented, Computer-Based Science Information

ERIC Educational Resources Information Center

Guan, Ying-Hua

2009-01-01

This study investigated the effects of multimedia presentations on the efficiency of learning scientific information (i.e. information on basic anatomy of human brains and their functions, the definition of cognitive psychology, and the structure of human memory). Experiment 1 investigated whether the modality effect could be observed when the…

GraphReduce: Large-Scale Graph Analytics on Accelerator-Based HPC Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sengupta, Dipanjan; Agarwal, Kapil; Song, Shuaiwen

2015-09-30

Recent work on real-world graph analytics has sought to leverage the massive amount of parallelism offered by GPU devices, but challenges remain due to the inherent irregularity of graph algorithms and limitations in GPU-resident memory for storing large graphs. We present GraphReduce, a highly efficient and scalable GPU-based framework that operates on graphs that exceed the device’s internal memory capacity. GraphReduce adopts a combination of both edge- and vertex-centric implementations of the Gather-Apply-Scatter programming model and operates on multiple asynchronous GPU streams to fully exploit the high degrees of parallelism in GPUs with efficient graph data movement between the hostmore » and the device.« less

The long memory and the transaction cost in financial markets

NASA Astrophysics Data System (ADS)

Li, Daye; Nishimura, Yusaku; Men, Ming

2016-01-01

In the present work, we investigate the fractal dimensions of 30 important stock markets from 2006 to 2013; the analysis indicates that the Hurst exponent of emerging markets shifts significantly away from the standard Brownian motion. We propose a model based on the Hurst exponent to explore the considerable profits from the predictable long-term memory. We take the transaction cost into account to justify why the market inefficiency has not been arbitraged away in the majority of cases. The empirical evidence indicates that the majority of the markets are efficient with a certain transaction cost under the no-arbitrage assumption. Furthermore, we use the Monte Carlo simulation to display "the efficient frontier" of the Hurst exponent with different transaction costs.

Holographic recording materials development. [development of cis-trans isomerization for holographic memory

NASA Technical Reports Server (NTRS)

1974-01-01

Developments in the area of organic cis-trans isomerization systems for holographic memory applications are reported. The chemical research effort consisted of photochemical studies leading to the selection of a stilbene derivative and a polymer matrix system which have greatly improved refractive index differences between the cis and trans isomers as well as demonstrated efficiency of the photoisomerization process. In work on lithium niobate effects of sample stoichiometry and of read and write beam polarizations on recording efficiency were investigated. LiNbO3 was used for a study of angular sensitivity and of capability for simultaneous recording of extended objects without interference. The current status of LiNbO3 as a holographic recording material is summarized.

A Prolog Emulator

NASA Technical Reports Server (NTRS)

Tick, Evan

1987-01-01

This note describes an efficient software emulator for the Warren Abstract Machine (WAM) Prolog architecture. The version of the WAM implemented is called Lcode. The Lcode emulator, written in C, executes the 'naive reverse' benchmark at 3900 LIPS. The emulator is one of a set of tools used to measure the memory-referencing characteristics and performance of Prolog programs. These tools include a compiler, assembler, and memory simulators. An overview of the Lcode architecture is given here, followed by a description and listing of the emulator code implementing each Lcode instruction. This note will be of special interest to those studying the WAM and its performance characteristics. In general, this note will be of interest to those creating efficient software emulators for abstract machine architectures.

3D gate-all-around bandgap-engineered SONOS flash memory in vertical silicon pillar with metal gate

NASA Astrophysics Data System (ADS)

Oh, Jae-Sub; Yang, Seong-Dong; Lee, Sang-Youl; Kim, Young-Su; Kang, Min-Ho; Lim, Sung-Kyu; Lee, Hi-Deok; Lee, Ga-Won

2013-08-01

In this paper, a gate-all-around bandgap-engineered silicon-oxide-nitride-oxide-silicon device with a vertical silicon pillar structure and a Ti metal gate are demonstrated for a potential solution to overcome the scaling-down of flash memory device. The devices were fabricated using CMOS-compatible technology and exhibited well-behaved memory characteristics in terms of the program/erase window, retention, and endurance properties. Moreover, the integration of the Ti metal gate demonstrated a significant improvement in the erase characteristics due to the efficient suppression of the electron back tunneling through the blocking oxide.

Realization of the revival of silenced echo (ROSE) quantum memory scheme in orthogonal geometry

NASA Astrophysics Data System (ADS)

Minnegaliev, M. M.; Gerasimov, K. I.; Urmancheev, R. V.; Moiseev, S. A.; Chanelière, T.; Louchet-Chauvet, A.

2018-02-01

We demonstrated quantum memory scheme on revival of silenced echo in orthogonal geometry in Tm3+: Y3Al5O12 crystal. The retrieval efficiency of ˜14% was demonstrated with the 36 µs storage time. In this scheme for the first time we also implemented a suppression of the revived echo signal by applying an external electric field and the echo signal has been recovered on demand if we then applied a second electric pulse with opposite polarity. This technique opens the possibilities for realizing addressing in multi-qubit quantum memory in Tm3+: Y3Al5O12 crystal.

Parallel performance investigations of an unstructured mesh Navier-Stokes solver

NASA Technical Reports Server (NTRS)

Mavriplis, Dimitri J.

2000-01-01

A Reynolds-averaged Navier-Stokes solver based on unstructured mesh techniques for analysis of high-lift configurations is described. The method makes use of an agglomeration multigrid solver for convergence acceleration. Implicit line-smoothing is employed to relieve the stiffness associated with highly stretched meshes. A GMRES technique is also implemented to speed convergence at the expense of additional memory usage. The solver is cache efficient and fully vectorizable, and is parallelized using a two-level hybrid MPI-OpenMP implementation suitable for shared and/or distributed memory architectures, as well as clusters of shared memory machines. Convergence and scalability results are illustrated for various high-lift cases.

The computation of dynamic fractional difference parameter for S&P500 index

NASA Astrophysics Data System (ADS)

Pei, Tan Pei; Cheong, Chin Wen; Galagedera, Don U. A.

2015-10-01

This study evaluates the time-varying long memory behaviors of the S&P500 volatility index using dynamic fractional difference parameters. Time-varying fractional difference parameter shows the dynamic of long memory in volatility series for the pre and post subprime mortgage crisis triggered by U.S. The results find an increasing trend in the S&P500 long memory volatility for the pre-crisis period. However, the onset of Lehman Brothers event reduces the predictability of volatility series following by a slight fluctuation of the factional differencing parameters. After that, the U.S. financial market becomes more informationally efficient and follows a non-stationary random process.

Precision spectral manipulation of optical pulses using a coherent photon echo memory.

PubMed

Buchler, B C; Hosseini, M; Hétet, G; Sparkes, B M; Lam, P K

2010-04-01

Photon echo schemes are excellent candidates for high efficiency coherent optical memory. They are capable of high-bandwidth multipulse storage, pulse resequencing and have been shown theoretically to be compatible with quantum information applications. One particular photon echo scheme is the gradient echo memory (GEM). In this system, an atomic frequency gradient is induced in the direction of light propagation leading to a Fourier decomposition of the optical spectrum along the length of the storage medium. This Fourier encoding allows precision spectral manipulation of the stored light. In this Letter, we show frequency shifting, spectral compression, spectral splitting, and fine dispersion control of optical pulses using GEM.

Memory efficient solution of the primitive equations for numerical weather prediction on the CYBER 205

NASA Technical Reports Server (NTRS)

Tuccillo, J. J.

1984-01-01

Numerical Weather Prediction (NWP), for both operational and research purposes, requires only fast computational speed but also large memory. A technique for solving the Primitive Equations for atmospheric motion on the CYBER 205, as implemented in the Mesoscale Atmospheric Simulation System, which is fully vectorized and requires substantially less memory than other techniques such as the Leapfrog or Adams-Bashforth Schemes is discussed. The technique presented uses the Euler-Backard time marching scheme. Also discussed are several techniques for reducing computational time of the model by replacing slow intrinsic routines by faster algorithms which use only hardware vector instructions.

Likelihood ratio decisions in memory: three implied regularities.

PubMed

Glanzer, Murray; Hilford, Andrew; Maloney, Laurence T

2009-06-01

We analyze four general signal detection models for recognition memory that differ in their distributional assumptions. Our analyses show that a basic assumption of signal detection theory, the likelihood ratio decision axis, implies three regularities in recognition memory: (1) the mirror effect, (2) the variance effect, and (3) the z-ROC length effect. For each model, we present the equations that produce the three regularities and show, in computed examples, how they do so. We then show that the regularities appear in data from a range of recognition studies. The analyses and data in our study support the following generalization: Individuals make efficient recognition decisions on the basis of likelihood ratios.

Working memory network plasticity after anterior temporal lobe resection: a longitudinal functional magnetic resonance imaging study

PubMed Central

Stretton, Jason; Sidhu, Meneka K.; Winston, Gavin P.; Bartlett, Philippa; McEvoy, Andrew W.; Symms, Mark R.; Koepp, Matthias J.; Thompson, Pamela J.

2014-01-01

Working memory is a crucial cognitive function that is disrupted in temporal lobe epilepsy. It is unclear whether this impairment is a consequence of temporal lobe involvement in working memory processes or due to seizure spread to extratemporal eloquent cortex. Anterior temporal lobe resection controls seizures in 50–80% of patients with drug-resistant temporal lobe epilepsy and the effect of surgery on working memory are poorly understood both at a behavioural and neural level. We investigated the impact of temporal lobe resection on the efficiency and functional anatomy of working memory networks. We studied 33 patients with unilateral medial temporal lobe epilepsy (16 left) before, 3 and 12 months after anterior temporal lobe resection. Fifteen healthy control subjects were also assessed in parallel. All subjects had neuropsychological testing and performed a visuospatial working memory functional magnetic resonance imaging paradigm on these three separate occasions. Changes in activation and deactivation patterns were modelled individually and compared between groups. Changes in task performance were included as regressors of interest to assess the efficiency of changes in the networks. Left and right temporal lobe epilepsy patients were impaired on preoperative measures of working memory compared to controls. Working memory performance did not decline following left or right temporal lobe resection, but improved at 3 and 12 months following left and, to a lesser extent, following right anterior temporal lobe resection. After left anterior temporal lobe resection, improved performance correlated with greater deactivation of the left hippocampal remnant and the contralateral right hippocampus. There was a failure of increased deactivation of the left hippocampal remnant at 3 months after left temporal lobe resection compared to control subjects, which had normalized 12 months after surgery. Following right anterior temporal lobe resection there was a progressive increase of activation in the right superior parietal lobe at 3 and 12 months after surgery. There was greater deactivation of the right hippocampal remnant compared to controls between 3 and 12 months after right anterior temporal lobe resection that was associated with lesser improvement in task performance. Working memory improved after anterior temporal lobe resection, particularly following left-sided resections. Postoperative working memory was reliant on the functional capacity of the hippocampal remnant and, following left resections, the functional reserve of the right hippocampus. These data suggest that working memory following temporal lobe resection is dependent on the engagement of the posterior medial temporal lobes and eloquent cortex. PMID:24691395

Stochastic quasi-Newton molecular simulations

NASA Astrophysics Data System (ADS)

Chau, C. D.; Sevink, G. J. A.; Fraaije, J. G. E. M.

2010-08-01

We report a new and efficient factorized algorithm for the determination of the adaptive compound mobility matrix B in a stochastic quasi-Newton method (S-QN) that does not require additional potential evaluations. For one-dimensional and two-dimensional test systems, we previously showed that S-QN gives rise to efficient configurational space sampling with good thermodynamic consistency [C. D. Chau, G. J. A. Sevink, and J. G. E. M. Fraaije, J. Chem. Phys. 128, 244110 (2008)10.1063/1.2943313]. Potential applications of S-QN are quite ambitious, and include structure optimization, analysis of correlations and automated extraction of cooperative modes. However, the potential can only be fully exploited if the computational and memory requirements of the original algorithm are significantly reduced. In this paper, we consider a factorized mobility matrix B=JJT and focus on the nontrivial fundamentals of an efficient algorithm for updating the noise multiplier J . The new algorithm requires O(n2) multiplications per time step instead of the O(n3) multiplications in the original scheme due to Choleski decomposition. In a recursive form, the update scheme circumvents matrix storage and enables limited-memory implementation, in the spirit of the well-known limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method, allowing for a further reduction of the computational effort to O(n) . We analyze in detail the performance of the factorized (FSU) and limited-memory (L-FSU) algorithms in terms of convergence and (multiscale) sampling, for an elementary but relevant system that involves multiple time and length scales. Finally, we use this analysis to formulate conditions for the simulation of the complex high-dimensional potential energy landscapes of interest.

Reducing the computational footprint for real-time BCPNN learning

PubMed Central

Vogginger, Bernhard; Schüffny, René; Lansner, Anders; Cederström, Love; Partzsch, Johannes; Höppner, Sebastian

2015-01-01

The implementation of synaptic plasticity in neural simulation or neuromorphic hardware is usually very resource-intensive, often requiring a compromise between efficiency and flexibility. A versatile, but computationally-expensive plasticity mechanism is provided by the Bayesian Confidence Propagation Neural Network (BCPNN) paradigm. Building upon Bayesian statistics, and having clear links to biological plasticity processes, the BCPNN learning rule has been applied in many fields, ranging from data classification, associative memory, reward-based learning, probabilistic inference to cortical attractor memory networks. In the spike-based version of this learning rule the pre-, postsynaptic and coincident activity is traced in three low-pass-filtering stages, requiring a total of eight state variables, whose dynamics are typically simulated with the fixed step size Euler method. We derive analytic solutions allowing an efficient event-driven implementation of this learning rule. Further speedup is achieved by first rewriting the model which reduces the number of basic arithmetic operations per update to one half, and second by using look-up tables for the frequently calculated exponential decay. Ultimately, in a typical use case, the simulation using our approach is more than one order of magnitude faster than with the fixed step size Euler method. Aiming for a small memory footprint per BCPNN synapse, we also evaluate the use of fixed-point numbers for the state variables, and assess the number of bits required to achieve same or better accuracy than with the conventional explicit Euler method. All of this will allow a real-time simulation of a reduced cortex model based on BCPNN in high performance computing. More important, with the analytic solution at hand and due to the reduced memory bandwidth, the learning rule can be efficiently implemented in dedicated or existing digital neuromorphic hardware. PMID:25657618

Reducing the computational footprint for real-time BCPNN learning.

PubMed

Vogginger, Bernhard; Schüffny, René; Lansner, Anders; Cederström, Love; Partzsch, Johannes; Höppner, Sebastian

2015-01-01

The implementation of synaptic plasticity in neural simulation or neuromorphic hardware is usually very resource-intensive, often requiring a compromise between efficiency and flexibility. A versatile, but computationally-expensive plasticity mechanism is provided by the Bayesian Confidence Propagation Neural Network (BCPNN) paradigm. Building upon Bayesian statistics, and having clear links to biological plasticity processes, the BCPNN learning rule has been applied in many fields, ranging from data classification, associative memory, reward-based learning, probabilistic inference to cortical attractor memory networks. In the spike-based version of this learning rule the pre-, postsynaptic and coincident activity is traced in three low-pass-filtering stages, requiring a total of eight state variables, whose dynamics are typically simulated with the fixed step size Euler method. We derive analytic solutions allowing an efficient event-driven implementation of this learning rule. Further speedup is achieved by first rewriting the model which reduces the number of basic arithmetic operations per update to one half, and second by using look-up tables for the frequently calculated exponential decay. Ultimately, in a typical use case, the simulation using our approach is more than one order of magnitude faster than with the fixed step size Euler method. Aiming for a small memory footprint per BCPNN synapse, we also evaluate the use of fixed-point numbers for the state variables, and assess the number of bits required to achieve same or better accuracy than with the conventional explicit Euler method. All of this will allow a real-time simulation of a reduced cortex model based on BCPNN in high performance computing. More important, with the analytic solution at hand and due to the reduced memory bandwidth, the learning rule can be efficiently implemented in dedicated or existing digital neuromorphic hardware.

Neural correlates of recognition memory of social information in people with schizophrenia

PubMed Central

Harvey, Philippe-Olivier; Lepage, Martin

2014-01-01

Background Social dysfunction is a hallmark characteristic of schizophrenia. Part of it may stem from an inability to efficiently encode social information into memory and retrieve it later. This study focused on whether patients with schizophrenia show a memory boost for socially relevant information and engage the same neural network as controls when processing social stimuli that were previously encoded into memory. Methods Patients with schizophrenia and healthy controls performed a social and nonsocial picture recognition memory task while being scanned. We calculated memory performance using d′. Our main analysis focused on brain activity associated with recognition memory of social and nonsocial pictures. Results Our study included 28 patients with schizophrenia and 26 controls. Healthy controls demonstrated a memory boost for socially relevant information. In contrast, patients with schizophrenia failed to show enhanced recognition sensitivity for social pictures. At the neural level, patients did not engage the dorsomedial prefrontal cortex (DMPFC) as much as controls while recognizing social pictures. Limitations Our study did not include direct measures of self-referential processing. All but 3 patients were taking antipsychotic medications, which may have altered both the behavioural performance during the picture recognition memory task and brain activity. Conclusion Impaired social memory in patients with schizophrenia may be associated with altered DMPFC activity. A reduction of DMPFC activity may reflect less involvement of self-referential processes during memory retrieval. Our functional MRI results contribute to a better mapping of the neural disturbances associated with social memory impairment in patients with schizophrenia and may facilitate the development of innovative treatments, such as transcranial magnetic stimulation. PMID:24119792

Technical support for digital systems technology development. Task order 1: ISP contention analysis and control

NASA Technical Reports Server (NTRS)

Stehle, Roy H.; Ogier, Richard G.

1993-01-01

Alternatives for realizing a packet-based network switch for use on a frequency division multiple access/time division multiplexed (FDMA/TDM) geostationary communication satellite were investigated. Each of the eight downlink beams supports eight directed dwells. The design needed to accommodate multicast packets with very low probability of loss due to contention. Three switch architectures were designed and analyzed. An output-queued, shared bus system yielded a functionally simple system, utilizing a first-in, first-out (FIFO) memory per downlink dwell, but at the expense of a large total memory requirement. A shared memory architecture offered the most efficiency in memory requirements, requiring about half the memory of the shared bus design. The processing requirement for the shared-memory system adds system complexity that may offset the benefits of the smaller memory. An alternative design using a shared memory buffer per downlink beam decreases circuit complexity through a distributed design, and requires at most 1000 packets of memory more than the completely shared memory design. Modifications to the basic packet switch designs were proposed to accommodate circuit-switched traffic, which must be served on a periodic basis with minimal delay. Methods for dynamically controlling the downlink dwell lengths were developed and analyzed. These methods adapt quickly to changing traffic demands, and do not add significant complexity or cost to the satellite and ground station designs. Methods for reducing the memory requirement by not requiring the satellite to store full packets were also proposed and analyzed. In addition, optimal packet and dwell lengths were computed as functions of memory size for the three switch architectures.

Neural correlates of recognition memory of social information in people with schizophrenia.

PubMed

Harvey, Philippe-Olivier; Lepage, Martin

2014-03-01

Social dysfunction is a hallmark characteristic of schizophrenia. Part of it may stem from an inability to efficiently encode social information into memory and retrieve it later. This study focused on whether patients with schizophrenia show a memory boost for socially relevant information and engage the same neural network as controls when processing social stimuli that were previously encoded into memory. Patients with schizophrenia and healthy controls performed a social and nonsocial picture recognition memory task while being scanned. We calculated memory performance using d'. Our main analysis focused on brain activity associated with recognition memory of social and nonsocial pictures. Our study included 28 patients with schizophrenia and 26 controls. Healthy controls demonstrated a memory boost for socially relevant information. In contrast, patients with schizophrenia failed to show enhanced recognition sensitivity for social pictures. At the neural level, patients did not engage the dorsomedial prefrontal cortex (DMPFC) as much as controls while recognizing social pictures. Our study did not include direct measures of self-referential processing. All but 3 patients were taking antipsychotic medications, which may have altered both the behavioural performance during the picture recognition memory task and brain activity. Impaired social memory in patients with schizophrenia may be associated with altered DMPFC activity. A reduction of DMPFC activity may reflect less involvement of self-referential processes during memory retrieval. Our functional MRI results contribute to a better mapping of the neural disturbances associated with social memory impairment in patients with schizophrenia and may facilitate the development of innovative treatments, such as transcranial magnetic stimulation.

Effects of Age and Acute Moderate Alcohol Administration on Electrophysiological Correlates of Working Memory Maintenance.

PubMed

Boissoneault, Jeff; Frazier, Ian; Lewis, Ben; Nixon, Sara Jo

2016-09-01

Previous studies suggest older adults may be differentially susceptible to the acute neurobehavioral effects of moderate alcohol intake. To our knowledge, no studies have addressed acute moderate alcohol effects on the electrophysiological correlates of working memory in younger and older social drinkers. This study characterized alcohol-related effects on frontal theta (FTP) and posterior alpha power (PAP) associated with maintenance of visual information during a working memory task. Older (55 to 70 years of age; n = 51, 29 women) and younger (25 to 35 years of age; n = 70, 39 women) community-dwelling moderate drinkers were recruited for this study. Participants were given either placebo or an active dose targeting breath alcohol concentrations (BrACs) of 0.04 or 0.065 g/dl. Following absorption, participants completed a visual working memory task assessing cue recognition following a 9-s delay. FTP and PAP were determined via Fourier transformation and subjected to 2 (age group) × 3 (dose) × 2 (repeated: working memory task condition) mixed models analysis. In addition to expected age-related reductions in PAP, a significant age group × dose interaction was detected for PAP such that 0.04 g/dl dose level was associated with greater PAP in younger adults but lower PAP in their older counterparts. PAP was lower in older versus younger adults at both active doses. Further mixed models revealed a significant negative association between PAP and working memory efficiency for older adults. No effects of age, dose, or their interaction were noted for FTP. Results bolster the small but growing body of evidence that older adults exhibit differential sensitivity to the neurobehavioral effects of moderate alcohol use. Given the theoretical role of PAP in attentional and working memory function, these findings shed light on the attentional mechanisms underlying effects of acute moderate alcohol on working memory efficiency in older adults. Copyright © 2016 by the Research Society on Alcoholism.

Exascale Hardware Architectures Working Group

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hemmert, S; Ang, J; Chiang, P

2011-03-15

The ASC Exascale Hardware Architecture working group is challenged to provide input on the following areas impacting the future use and usability of potential exascale computer systems: processor, memory, and interconnect architectures, as well as the power and resilience of these systems. Going forward, there are many challenging issues that will need to be addressed. First, power constraints in processor technologies will lead to steady increases in parallelism within a socket. Additionally, all cores may not be fully independent nor fully general purpose. Second, there is a clear trend toward less balanced machines, in terms of compute capability compared tomore » memory and interconnect performance. In order to mitigate the memory issues, memory technologies will introduce 3D stacking, eventually moving on-socket and likely on-die, providing greatly increased bandwidth but unfortunately also likely providing smaller memory capacity per core. Off-socket memory, possibly in the form of non-volatile memory, will create a complex memory hierarchy. Third, communication energy will dominate the energy required to compute, such that interconnect power and bandwidth will have a significant impact. All of the above changes are driven by the need for greatly increased energy efficiency, as current technology will prove unsuitable for exascale, due to unsustainable power requirements of such a system. These changes will have the most significant impact on programming models and algorithms, but they will be felt across all layers of the machine. There is clear need to engage all ASC working groups in planning for how to deal with technological changes of this magnitude. The primary function of the Hardware Architecture Working Group is to facilitate codesign with hardware vendors to ensure future exascale platforms are capable of efficiently supporting the ASC applications, which in turn need to meet the mission needs of the NNSA Stockpile Stewardship Program. This issue is relatively immediate, as there is only a small window of opportunity to influence hardware design for 2018 machines. Given the short timeline a firm co-design methodology with vendors is of prime importance.« less

Effects and mechanisms of working memory training: a review.

PubMed

von Bastian, Claudia C; Oberauer, Klaus

2014-11-01

Can cognitive abilities such as reasoning be improved through working memory training? This question is still highly controversial, with prior studies providing contradictory findings. The lack of theory-driven, systematic approaches and (occasionally serious) methodological shortcomings complicates this debate even more. This review suggests two general mechanisms mediating transfer effects that are (or are not) observed after working memory training: enhanced working memory capacity, enabling people to hold more items in working memory than before training, or enhanced efficiency using the working memory capacity available (e.g., using chunking strategies to remember more items correctly). We then highlight multiple factors that could influence these mechanisms of transfer and thus the success of training interventions. These factors include (1) the nature of the training regime (i.e., intensity, duration, and adaptivity of the training tasks) and, with it, the magnitude of improvements during training, and (2) individual differences in age, cognitive abilities, biological factors, and motivational and personality factors. Finally, we summarize the findings revealed by existing training studies for each of these factors, and thereby present a roadmap for accumulating further empirical evidence regarding the efficacy of working memory training in a systematic way.

Working memory capacity in social anxiety disorder: Revisiting prior conclusions.

PubMed

Waechter, Stephanie; Moscovitch, David A; Vidovic, Vanja; Bielak, Tatiana; Rowa, Karen; McCabe, Randi E

2018-04-01

In one of the few studies examining working memory processes in social anxiety disorder (SAD), Amir and Bomyea (2011) recruited participants with and without SAD to complete a working memory span task with neutral and social threat words. Those with SAD showed better working memory performance for social threat words compared to neutral words, suggesting an enhancement in processing efficiency for socially threatening information in SAD. The current study sought to replicate and extend these findings. In this study, 25 participants with a principal diagnosis of SAD, 24 anxious control (AC) participants with anxiety disorders other than SAD, and 27 healthy control (HC) participants with no anxiety disorder completed a working memory task with social threat, general threat, and neutral stimuli. The groups in the current study demonstrated similar working memory performance within each of the word type conditions, thus failing to replicate the principal findings of Amir and Bomyea (2011). Post hoc analyses revealed a significant association between higher levels of anxiety symptomatology and poorer overall WM performance. These results inform our understanding of working memory in the anxiety disorders and support the importance of replication in psychological research. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Effect of visual and tactile feedback on kinematic synergies in the grasping hand.

PubMed

Patel, Vrajeshri; Burns, Martin; Vinjamuri, Ramana

2016-08-01

The human hand uses a combination of feedforward and feedback mechanisms to accomplish high degree of freedom in grasp control efficiently. In this study, we used a synergy-based control model to determine the effect of sensory feedback on kinematic synergies in the grasping hand. Ten subjects performed two types of grasps: one that included feedback (real) and one without feedback (memory-guided), at two different speeds (rapid and natural). Kinematic synergies were extracted from rapid real and rapid memory-guided grasps using principal component analysis. Synergies extracted from memory-guided grasps revealed greater preservation of natural inter-finger relationships than those found in corresponding synergies extracted from real grasps. Reconstruction of natural real and natural memory-guided grasps was used to test performance and generalizability of synergies. A temporal analysis of reconstruction patterns revealed the differing contribution of individual synergies in real grasps versus memory-guided grasps. Finally, the results showed that memory-guided synergies could not reconstruct real grasps as accurately as real synergies could reconstruct memory-guided grasps. These results demonstrate how visual and tactile feedback affects a closed-loop synergy-based motor control system.

AGEs induce Alzheimer-like tau pathology and memory deficit via RAGE-mediated GSK-3 activation.

PubMed

Li, Xiao-Hong; Lv, Bing-Ling; Xie, Jia-Zhao; Liu, Jing; Zhou, Xin-Wen; Wang, Jian-Zhi

2012-07-01

Accumulation of β-amyloid and hyperphosphorylated tau with synapse damage and memory deterioration are hallmark lesions of Alzheimer disease (AD), but the upstream causative factors are elusive. The advanced glycation endproducts (AGEs) are elevated in AD brains and the AGEs can stimulate β-amyloid production. Whether and how AGEs may cause AD-like tau hyperphosphorylation and memory-related deficits is not known. Here we report that AGEs induce tau hyperphosphorylation, memory deterioration, decline of synaptic proteins, and impairment of long-term potentiation (LTP) in rats. In SK-NS-H cells, upregulation of AGEs receptor (RAGE), inhibition of Akt, and activation of glycogen synthase kinase-3 (GSK-3), Erk1/2, and p38 were observed after treatment with AGEs. In rats, blockage of RAGE attenuated the AGE-induced GSK-3 activation, tau hyperphosphorylation, and memory deficit with restoration of synaptic functions, and simultaneous inhibition of GSK-3 also antagonized the AGE-induced impairments. Our data reveal that AGEs can induce tau hyperphosphorylation and impair synapse and memory through RAGE-mediated GSK-3 activation and targeting RAGE/GSK-3 pathway can efficiently improve the AD-like histopathological changes and memory deterioration. Copyright © 2012 Elsevier Inc. All rights reserved.

Unconditional polarization qubit quantum memory at room temperature

NASA Astrophysics Data System (ADS)

Namazi, Mehdi; Kupchak, Connor; Jordaan, Bertus; Shahrokhshahi, Reihaneh; Figueroa, Eden

2016-05-01

The creation of global quantum key distribution and quantum communication networks requires multiple operational quantum memories. Achieving a considerable reduction in experimental and cost overhead in these implementations is thus a major challenge. Here we present a polarization qubit quantum memory fully-operational at 330K, an unheard frontier in the development of useful qubit quantum technology. This result is achieved through extensive study of how optical response of cold atomic medium is transformed by the motion of atoms at room temperature leading to an optimal characterization of room temperature quantum light-matter interfaces. Our quantum memory shows an average fidelity of 86.6 +/- 0.6% for optical pulses containing on average 1 photon per pulse, thereby defeating any classical strategy exploiting the non-unitary character of the memory efficiency. Our system significantly decreases the technological overhead required to achieve quantum memory operation and will serve as a building block for scalable and technologically simpler many-memory quantum machines. The work was supported by the US-Navy Office of Naval Research, Grant Number N00141410801 and the Simons Foundation, Grant Number SBF241180. B. J. acknowledges financial assistance of the National Research Foundation (NRF) of South Africa.

Enhancing long-term memory with stimulation tunes visual attention in one trial.

PubMed

Reinhart, Robert M G; Woodman, Geoffrey F

2015-01-13

Scientists have long proposed that memory representations control the mechanisms of attention that focus processing on the task-relevant objects in our visual field. Modern theories specifically propose that we rely on working memory to store the object representations that provide top-down control over attentional selection. Here, we show that the tuning of perceptual attention can be sharply accelerated after 20 min of noninvasive brain stimulation over medial-frontal cortex. Contrary to prevailing theories of attention, these improvements did not appear to be caused by changes in the nature of the working memory representations of the search targets. Instead, improvements in attentional tuning were accompanied by changes in an electrophysiological signal hypothesized to index long-term memory. We found that this pattern of effects was reliably observed when we stimulated medial-frontal cortex, but when we stimulated posterior parietal cortex, we found that stimulation directly affected the perceptual processing of the search array elements, not the memory representations providing top-down control. Our findings appear to challenge dominant theories of attention by demonstrating that changes in the storage of target representations in long-term memory may underlie rapid changes in the efficiency with which humans can find targets in arrays of objects.

Effects of the BDNF Val66Met polymorphism and met allele load on declarative memory related neural networks.

PubMed

Dodds, Chris M; Henson, Richard N; Suckling, John; Miskowiak, Kamilla W; Ooi, Cinly; Tait, Roger; Soltesz, Fruzsina; Lawrence, Phil; Bentley, Graham; Maltby, Kay; Skeggs, Andrew; Miller, Sam R; McHugh, Simon; Bullmore, Edward T; Nathan, Pradeep J

2013-01-01

It has been suggested that the BDNF Val66Met polymorphism modulates episodic memory performance via effects on hippocampal neural circuitry. However, fMRI studies have yielded inconsistent results in this respect. Moreover, very few studies have examined the effect of met allele load on activation of memory circuitry. In the present study, we carried out a comprehensive analysis of the effects of the BDNF polymorphism on brain responses during episodic memory encoding and retrieval, including an investigation of the effect of met allele load on memory related activation in the medial temporal lobe. In contrast to previous studies, we found no evidence for an effect of BDNF genotype or met load during episodic memory encoding. Met allele carriers showed increased activation during successful retrieval in right hippocampus but this was contrast-specific and unaffected by met allele load. These results suggest that the BDNF Val66Met polymorphism does not, as previously claimed, exert an observable effect on neural systems underlying encoding of new information into episodic memory but may exert a subtle effect on the efficiency with which such information can be retrieved.

ACCESS: A Communicating and Cooperating Expert Systems System.

DTIC Science & Technology

1988-01-31

therefore more quickly accepted by programmers. This is in part due to the already familiar concepts of multi-processing environments (e.g. semaphores ...Di68] and monitors [Br75]) which can be viewed as a special case of synchronized shared memory models [Di6S]. Heterogeneous systems however, are by...locality of nodes is not possible and frequent access of memory is required. Synchronization of processes also suffers from a loss of efficiency in

A discrete Fourier transform for virtual memory machines

NASA Technical Reports Server (NTRS)

Galant, David C.

1992-01-01

An algebraic theory of the Discrete Fourier Transform is developed in great detail. Examination of the details of the theory leads to a computationally efficient fast Fourier transform for the use on computers with virtual memory. Such an algorithm is of great use on modern desktop machines. A FORTRAN coded version of the algorithm is given for the case when the sequence of numbers to be transformed is a power of two.

A Cache Design to Exploit Structural Locality

DTIC Science & Technology

1991-12-01

memory and secondary storage. Main memory was used to store the instructions and data of an executing pro- gram, while secondary storage held programs ...efficiency of the CPU and faster turnaround of executing programs . In addition to the well known spatial and temporal aspects of locality, Hobart has...identified a third aspect, which he has called structural locality (9). This type of locality is defined as the tendency of an executing program to