Distributed shared memory for roaming large volumes.
Castanié, Laurent; Mion, Christophe; Cavin, Xavier; Lévy, Bruno
2006-01-01
We present a cluster-based volume rendering system for roaming very large volumes. This system allows to move a gigabyte-sized probe inside a total volume of several tens or hundreds of gigabytes in real-time. While the size of the probe is limited by the total amount of texture memory on the cluster, the size of the total data set has no theoretical limit. The cluster is used as a distributed graphics processing unit that both aggregates graphics power and graphics memory. A hardware-accelerated volume renderer runs in parallel on the cluster nodes and the final image compositing is implemented using a pipelined sort-last rendering algorithm. Meanwhile, volume bricking and volume paging allow efficient data caching. On each rendering node, a distributed hierarchical cache system implements a global software-based distributed shared memory on the cluster. In case of a cache miss, this system first checks page residency on the other cluster nodes instead of directly accessing local disks. Using two Gigabit Ethernet network interfaces per node, we accelerate data fetching by a factor of 4 compared to directly accessing local disks. The system also implements asynchronous disk access and texture loading, which makes it possible to overlap data loading, volume slicing and rendering for optimal volume roaming.
A general model for memory interference in a multiprocessor system with memory hierarchy
NASA Technical Reports Server (NTRS)
Taha, Badie A.; Standley, Hilda M.
1989-01-01
The problem of memory interference in a multiprocessor system with a hierarchy of shared buses and memories is addressed. The behavior of the processors is represented by a sequence of memory requests with each followed by a determined amount of processing time. A statistical queuing network model for determining the extent of memory interference in multiprocessor systems with clusters of memory hierarchies is presented. The performance of the system is measured by the expected number of busy memory clusters. The results of the analytic model are compared with simulation results, and the correlation between them is found to be very high.
Parallel processing for scientific computations
NASA Technical Reports Server (NTRS)
Alkhatib, Hasan S.
1995-01-01
The scope of this project dealt with the investigation of the requirements to support distributed computing of scientific computations over a cluster of cooperative workstations. Various experiments on computations for the solution of simultaneous linear equations were performed in the early phase of the project to gain experience in the general nature and requirements of scientific applications. A specification of a distributed integrated computing environment, DICE, based on a distributed shared memory communication paradigm has been developed and evaluated. The distributed shared memory model facilitates porting existing parallel algorithms that have been designed for shared memory multiprocessor systems to the new environment. The potential of this new environment is to provide supercomputing capability through the utilization of the aggregate power of workstations cooperating in a cluster interconnected via a local area network. Workstations, generally, do not have the computing power to tackle complex scientific applications, making them primarily useful for visualization, data reduction, and filtering as far as complex scientific applications are concerned. There is a tremendous amount of computing power that is left unused in a network of workstations. Very often a workstation is simply sitting idle on a desk. A set of tools can be developed to take advantage of this potential computing power to create a platform suitable for large scientific computations. The integration of several workstations into a logical cluster of distributed, cooperative, computing stations presents an alternative to shared memory multiprocessor systems. In this project we designed and evaluated such a system.
Shared Memory Parallelization of an Implicit ADI-type CFD Code
NASA Technical Reports Server (NTRS)
Hauser, Th.; Huang, P. G.
1999-01-01
A parallelization study designed for ADI-type algorithms is presented using the OpenMP specification for shared-memory multiprocessor programming. Details of optimizations specifically addressed to cache-based computer architectures are described and performance measurements for the single and multiprocessor implementation are summarized. The paper demonstrates that optimization of memory access on a cache-based computer architecture controls the performance of the computational algorithm. A hybrid MPI/OpenMP approach is proposed for clusters of shared memory machines to further enhance the parallel performance. The method is applied to develop a new LES/DNS code, named LESTool. A preliminary DNS calculation of a fully developed channel flow at a Reynolds number of 180, Re(sub tau) = 180, has shown good agreement with existing data.
Hybrid MPI+OpenMP Programming of an Overset CFD Solver and Performance Investigations
NASA Technical Reports Server (NTRS)
Djomehri, M. Jahed; Jin, Haoqiang H.; Biegel, Bryan (Technical Monitor)
2002-01-01
This report describes a two level parallelization of a Computational Fluid Dynamic (CFD) solver with multi-zone overset structured grids. The approach is based on a hybrid MPI+OpenMP programming model suitable for shared memory and clusters of shared memory machines. The performance investigations of the hybrid application on an SGI Origin2000 (O2K) machine is reported using medium and large scale test problems.
Cooperative Data Sharing: Simple Support for Clusters of SMP Nodes
NASA Technical Reports Server (NTRS)
DiNucci, David C.; Balley, David H. (Technical Monitor)
1997-01-01
Libraries like PVM and MPI send typed messages to allow for heterogeneous cluster computing. Lower-level libraries, such as GAM, provide more efficient access to communication by removing the need to copy messages between the interface and user space in some cases. still lower-level interfaces, such as UNET, get right down to the hardware level to provide maximum performance. However, these are all still interfaces for passing messages from one process to another, and have limited utility in a shared-memory environment, due primarily to the fact that message passing is just another term for copying. This drawback is made more pertinent by today's hybrid architectures (e.g. clusters of SMPs), where it is difficult to know beforehand whether two communicating processes will share memory. As a result, even portable language tools (like HPF compilers) must either map all interprocess communication, into message passing with the accompanying performance degradation in shared memory environments, or they must check each communication at run-time and implement the shared-memory case separately for efficiency. Cooperative Data Sharing (CDS) is a single user-level API which abstracts all communication between processes into the sharing and access coordination of memory regions, in a model which might be described as "distributed shared messages" or "large-grain distributed shared memory". As a result, the user programs to a simple latency-tolerant abstract communication specification which can be mapped efficiently to either a shared-memory or message-passing based run-time system, depending upon the available architecture. Unlike some distributed shared memory interfaces, the user still has complete control over the assignment of data to processors, the forwarding of data to its next likely destination, and the queuing of data until it is needed, so even the relatively high latency present in clusters can be accomodated. CDS does not require special use of an MMU, which can add overhead to some DSM systems, and does not require an SPMD programming model. unlike some message-passing interfaces, CDS allows the user to implement efficient demand-driven applications where processes must "fight" over data, and does not perform copying if processes share memory and do not attempt concurrent writes. CDS also supports heterogeneous computing, dynamic process creation, handlers, and a very simple thread-arbitration mechanism. Additional support for array subsections is currently being considered. The CDS1 API, which forms the kernel of CDS, is built primarily upon only 2 communication primitives, one process initiation primitive, and some data translation (and marshalling) routines, memory allocation routines, and priority control routines. The entire current collection of 28 routines provides enough functionality to implement most (or all) of MPI 1 and 2, which has a much larger interface consisting of hundreds of routines. still, the API is small enough to consider integrating into standard os interfaces for handling inter-process communication in a network-independent way. This approach would also help to solve many of the problems plaguing other higher-level standards such as MPI and PVM which must, in some cases, "play OS" to adequately address progress and process control issues. The CDS2 API, a higher level of interface roughly equivalent in functionality to MPI and to be built entirely upon CDS1, is still being designed. It is intended to add support for the equivalent of communicators, reduction and other collective operations, process topologies, additional support for process creation, and some automatic memory management. CDS2 will not exactly match MPI, because the copy-free semantics of communication from CDS1 will be supported. CDS2 application programs will be free to carefully also use CDS1. CDS1 has been implemented on networks of workstations running unmodified Unix-based operating systems, using UDP/IP and vendor-supplied high- performance locks. Although its inter-node performance is currently unimpressive due to rudimentary implementation technique, it even now outperforms highly-optimized MPI implementation on intra-node communication due to its support for non-copy communication. The similarity of the CDS1 architecture to that of other projects such as UNET and TRAP suggests that the inter-node performance can be increased significantly to surpass MPI or PVM, and it may be possible to migrate some of its functionality to communication controllers.
NASA Technical Reports Server (NTRS)
Fatoohi, Rod; Saini, Subbash; Ciotti, Robert
2006-01-01
We study the performance of inter-process communication on four high-speed multiprocessor systems using a set of communication benchmarks. The goal is to identify certain limiting factors and bottlenecks with the interconnect of these systems as well as to compare these interconnects. We measured network bandwidth using different number of communicating processors and communication patterns, such as point-to-point communication, collective communication, and dense communication patterns. The four platforms are: a 512-processor SGI Altix 3700 BX2 shared-memory machine with 3.2 GB/s links; a 64-processor (single-streaming) Cray XI shared-memory machine with 32 1.6 GB/s links; a 128-processor Cray Opteron cluster using a Myrinet network; and a 1280-node Dell PowerEdge cluster with an InfiniBand network. Our, results show the impact of the network bandwidth and topology on the overall performance of each interconnect.
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.
Parallel Navier-Stokes computations on shared and distributed memory architectures
NASA Technical Reports Server (NTRS)
Hayder, M. Ehtesham; Jayasimha, D. N.; Pillay, Sasi Kumar
1995-01-01
We study a high order finite difference scheme to solve the time accurate flow field of a jet using the compressible Navier-Stokes equations. As part of our ongoing efforts, we have implemented our numerical model on three parallel computing platforms to study the computational, communication, and scalability characteristics. The platforms chosen for this study are a cluster of workstations connected through fast networks (the LACE experimental testbed at NASA Lewis), a shared memory multiprocessor (the Cray YMP), and a distributed memory multiprocessor (the IBM SPI). Our focus in this study is on the LACE testbed. We present some results for the Cray YMP and the IBM SP1 mainly for comparison purposes. On the LACE testbed, we study: (1) the communication characteristics of Ethernet, FDDI, and the ALLNODE networks and (2) the overheads induced by the PVM message passing library used for parallelizing the application. We demonstrate that clustering of workstations is effective and has the potential to be computationally competitive with supercomputers at a fraction of the cost.
A Massively Parallel Code for Polarization Calculations
NASA Astrophysics Data System (ADS)
Akiyama, Shizuka; Höflich, Peter
2001-03-01
We present an implementation of our Monte-Carlo radiation transport method for rapidly expanding, NLTE atmospheres for massively parallel computers which utilizes both the distributed and shared memory models. This allows us to take full advantage of the fast communication and low latency inherent to nodes with multiple CPUs, and to stretch the limits of scalability with the number of nodes compared to a version which is based on the shared memory model. Test calculations on a local 20-node Beowulf cluster with dual CPUs showed an improved scalability by about 40%.
Vascular system modeling in parallel environment - distributed and shared memory approaches
Jurczuk, Krzysztof; Kretowski, Marek; Bezy-Wendling, Johanne
2011-01-01
The paper presents two approaches in parallel modeling of vascular system development in internal organs. In the first approach, new parts of tissue are distributed among processors and each processor is responsible for perfusing its assigned parts of tissue to all vascular trees. Communication between processors is accomplished by passing messages and therefore this algorithm is perfectly suited for distributed memory architectures. The second approach is designed for shared memory machines. It parallelizes the perfusion process during which individual processing units perform calculations concerning different vascular trees. The experimental results, performed on a computing cluster and multi-core machines, show that both algorithms provide a significant speedup. PMID:21550891
Hypercluster - Parallel processing for computational mechanics
NASA Technical Reports Server (NTRS)
Blech, Richard A.
1988-01-01
An account is given of the development status, performance capabilities and implications for further development of NASA-Lewis' testbed 'hypercluster' parallel computer network, in which multiple processors communicate through a shared memory. Processors have local as well as shared memory; the hypercluster is expanded in the same manner as the hypercube, with processor clusters replacing the normal single processor node. The NASA-Lewis machine has three nodes with a vector personality and one node with a scalar personality. Each of the vector nodes uses four board-level vector processors, while the scalar node uses four general-purpose microcomputer boards.
Implementation of Parallel Dynamic Simulation on Shared-Memory vs. Distributed-Memory Environments
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jin, Shuangshuang; Chen, Yousu; Wu, Di
2015-12-09
Power system dynamic simulation computes the system response to a sequence of large disturbance, such as sudden changes in generation or load, or a network short circuit followed by protective branch switching operation. It consists of a large set of differential and algebraic equations, which is computational intensive and challenging to solve using single-processor based dynamic simulation solution. High-performance computing (HPC) based parallel computing is a very promising technology to speed up the computation and facilitate the simulation process. This paper presents two different parallel implementations of power grid dynamic simulation using Open Multi-processing (OpenMP) on shared-memory platform, and Messagemore » Passing Interface (MPI) on distributed-memory clusters, respectively. The difference of the parallel simulation algorithms and architectures of the two HPC technologies are illustrated, and their performances for running parallel dynamic simulation are compared and demonstrated.« less
Scaling Irregular Applications through Data Aggregation and Software Multithreading
DOE Office of Scientific and Technical Information (OSTI.GOV)
Morari, Alessandro; Tumeo, Antonino; Chavarría-Miranda, Daniel
Bioinformatics, data analytics, semantic databases, knowledge discovery are emerging high performance application areas that exploit dynamic, linked data structures such as graphs, unbalanced trees or unstructured grids. These data structures usually are very large, requiring significantly more memory than available on single shared memory systems. Additionally, these data structures are difficult to partition on distributed memory systems. They also present poor spatial and temporal locality, thus generating unpredictable memory and network accesses. The Partitioned Global Address Space (PGAS) programming model seems suitable for these applications, because it allows using a shared memory abstraction across distributed-memory clusters. However, current PGAS languagesmore » and libraries are built to target regular remote data accesses and block transfers. Furthermore, they usually rely on the Single Program Multiple Data (SPMD) parallel control model, which is not well suited to the fine grained, dynamic and unbalanced parallelism of irregular applications. In this paper we present {\\bf GMT} (Global Memory and Threading library), a custom runtime library that enables efficient execution of irregular applications on commodity clusters. GMT integrates a PGAS data substrate with simple fork/join parallelism and provides automatic load balancing on a per node basis. It implements multi-level aggregation and lightweight multithreading to maximize memory and network bandwidth with fine-grained data accesses and tolerate long data access latencies. A key innovation in the GMT runtime is its thread specialization (workers, helpers and communication threads) that realize the overall functionality. We compare our approach with other PGAS models, such as UPC running using GASNet, and hand-optimized MPI code on a set of typical large-scale irregular applications, demonstrating speedups of an order of magnitude.« less
Parallel k-means++ for Multiple Shared-Memory Architectures
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mackey, Patrick S.; Lewis, Robert R.
2016-09-22
In recent years k-means++ has become a popular initialization technique for improved k-means clustering. To date, most of the work done to improve its performance has involved parallelizing algorithms that are only approximations of k-means++. In this paper we present a parallelization of the exact k-means++ algorithm, with a proof of its correctness. We develop implementations for three distinct shared-memory architectures: multicore CPU, high performance GPU, and the massively multithreaded Cray XMT platform. We demonstrate the scalability of the algorithm on each platform. In addition we present a visual approach for showing which platform performed k-means++ the fastest for varyingmore » data sizes.« less
Importance of balanced architectures in the design of high-performance imaging systems
NASA Astrophysics Data System (ADS)
Sgro, Joseph A.; Stanton, Paul C.
1999-03-01
Imaging systems employed in demanding military and industrial applications, such as automatic target recognition and computer vision, typically require real-time high-performance computing resources. While high- performances computing systems have traditionally relied on proprietary architectures and custom components, recent advances in high performance general-purpose microprocessor technology have produced an abundance of low cost components suitable for use in high-performance computing systems. A common pitfall in the design of high performance imaging system, particularly systems employing scalable multiprocessor architectures, is the failure to balance computational and memory bandwidth. The performance of standard cluster designs, for example, in which several processors share a common memory bus, is typically constrained by memory bandwidth. The symptom characteristic of this problem is failure to the performance of the system to scale as more processors are added. The problem becomes exacerbated if I/O and memory functions share the same bus. The recent introduction of microprocessors with large internal caches and high performance external memory interfaces makes it practical to design high performance imaging system with balanced computational and memory bandwidth. Real word examples of such designs will be presented, along with a discussion of adapting algorithm design to best utilize available memory bandwidth.
Parallel Clustering Algorithm for Large-Scale Biological Data Sets
Wang, Minchao; Zhang, Wu; Ding, Wang; Dai, Dongbo; Zhang, Huiran; Xie, Hao; Chen, Luonan; Guo, Yike; Xie, Jiang
2014-01-01
Backgrounds Recent explosion of biological data brings a great challenge for the traditional clustering algorithms. With increasing scale of data sets, much larger memory and longer runtime are required for the cluster identification problems. The affinity propagation algorithm outperforms many other classical clustering algorithms and is widely applied into the biological researches. However, the time and space complexity become a great bottleneck when handling the large-scale data sets. Moreover, the similarity matrix, whose constructing procedure takes long runtime, is required before running the affinity propagation algorithm, since the algorithm clusters data sets based on the similarities between data pairs. Methods Two types of parallel architectures are proposed in this paper to accelerate the similarity matrix constructing procedure and the affinity propagation algorithm. The memory-shared architecture is used to construct the similarity matrix, and the distributed system is taken for the affinity propagation algorithm, because of its large memory size and great computing capacity. An appropriate way of data partition and reduction is designed in our method, in order to minimize the global communication cost among processes. Result A speedup of 100 is gained with 128 cores. The runtime is reduced from serval hours to a few seconds, which indicates that parallel algorithm is capable of handling large-scale data sets effectively. The parallel affinity propagation also achieves a good performance when clustering large-scale gene data (microarray) and detecting families in large protein superfamilies. PMID:24705246
Experiences using OpenMP based on Computer Directed Software DSM on a PC Cluster
NASA Technical Reports Server (NTRS)
Hess, Matthias; Jost, Gabriele; Mueller, Matthias; Ruehle, Roland
2003-01-01
In this work we report on our experiences running OpenMP programs on a commodity cluster of PCs running a software distributed shared memory (DSM) system. We describe our test environment and report on the performance of a subset of the NAS Parallel Benchmarks that have been automaticaly parallelized for OpenMP. We compare the performance of the OpenMP implementations with that of their message passing counterparts and discuss performance differences.
An Evaluation of Architectural Platforms for Parallel Navier-Stokes Computations
NASA Technical Reports Server (NTRS)
Jayasimha, D. N.; Hayder, M. E.; Pillay, S. K.
1996-01-01
We study the computational, communication, and scalability characteristics of a computational fluid dynamics application, which solves the time accurate flow field of a jet using the compressible Navier-Stokes equations, on a variety of parallel architecture platforms. The platforms chosen for this study are a cluster of workstations (the LACE experimental testbed at NASA Lewis), a shared memory multiprocessor (the Cray YMP), and distributed memory multiprocessors with different topologies - the IBM SP and the Cray T3D. We investigate the impact of various networks connecting the cluster of workstations on the performance of the application and the overheads induced by popular message passing libraries used for parallelization. The work also highlights the importance of matching the memory bandwidth to the processor speed for good single processor performance. By studying the performance of an application on a variety of architectures, we are able to point out the strengths and weaknesses of each of the example computing platforms.
Parallelizing Navier-Stokes Computations on a Variety of Architectural Platforms
NASA Technical Reports Server (NTRS)
Jayasimha, D. N.; Hayder, M. E.; Pillay, S. K.
1997-01-01
We study the computational, communication, and scalability characteristics of a Computational Fluid Dynamics application, which solves the time accurate flow field of a jet using the compressible Navier-Stokes equations, on a variety of parallel architectural platforms. The platforms chosen for this study are a cluster of workstations (the LACE experimental testbed at NASA Lewis), a shared memory multiprocessor (the Cray YMP), distributed memory multiprocessors with different topologies-the IBM SP and the Cray T3D. We investigate the impact of various networks, connecting the cluster of workstations, on the performance of the application and the overheads induced by popular message passing libraries used for parallelization. The work also highlights the importance of matching the memory bandwidth to the processor speed for good single processor performance. By studying the performance of an application on a variety of architectures, we are able to point out the strengths and weaknesses of each of the example computing platforms.
Message Passing vs. Shared Address Space on a Cluster of SMPs
NASA Technical Reports Server (NTRS)
Shan, Hongzhang; Singh, Jaswinder Pal; Oliker, Leonid; Biswas, Rupak
2000-01-01
The convergence of scalable computer architectures using clusters of PCs (or PC-SMPs) with commodity networking has become an attractive platform for high end scientific computing. Currently, message-passing and shared address space (SAS) are the two leading programming paradigms for these systems. Message-passing has been standardized with MPI, and is the most common and mature programming approach. However message-passing code development can be extremely difficult, especially for irregular structured computations. SAS offers substantial ease of programming, but may suffer from performance limitations due to poor spatial locality, and high protocol overhead. In this paper, we compare the performance of and programming effort, required for six applications under both programming models on a 32 CPU PC-SMP cluster. Our application suite consists of codes that typically do not exhibit high efficiency under shared memory programming. due to their high communication to computation ratios and complex communication patterns. Results indicate that SAS can achieve about half the parallel efficiency of MPI for most of our applications: however, on certain classes of problems SAS performance is competitive with MPI. We also present new algorithms for improving the PC cluster performance of MPI collective operations.
Experiences Using OpenMP Based on Compiler Directed Software DSM on a PC Cluster
NASA Technical Reports Server (NTRS)
Hess, Matthias; Jost, Gabriele; Mueller, Matthias; Ruehle, Roland; Biegel, Bryan (Technical Monitor)
2002-01-01
In this work we report on our experiences running OpenMP (message passing) programs on a commodity cluster of PCs (personal computers) running a software distributed shared memory (DSM) system. We describe our test environment and report on the performance of a subset of the NAS (NASA Advanced Supercomputing) Parallel Benchmarks that have been automatically parallelized for OpenMP. We compare the performance of the OpenMP implementations with that of their message passing counterparts and discuss performance differences.
Scalable Parallel Density-based Clustering and Applications
NASA Astrophysics Data System (ADS)
Patwary, Mostofa Ali
2014-04-01
Recently, density-based clustering algorithms (DBSCAN and OPTICS) have gotten significant attention of the scientific community due to their unique capability of discovering arbitrary shaped clusters and eliminating noise data. These algorithms have several applications, which require high performance computing, including finding halos and subhalos (clusters) from massive cosmology data in astrophysics, analyzing satellite images, X-ray crystallography, and anomaly detection. However, parallelization of these algorithms are extremely challenging as they exhibit inherent sequential data access order, unbalanced workload resulting in low parallel efficiency. To break the data access sequentiality and to achieve high parallelism, we develop new parallel algorithms, both for DBSCAN and OPTICS, designed using graph algorithmic techniques. For example, our parallel DBSCAN algorithm exploits the similarities between DBSCAN and computing connected components. Using datasets containing up to a billion floating point numbers, we show that our parallel density-based clustering algorithms significantly outperform the existing algorithms, achieving speedups up to 27.5 on 40 cores on shared memory architecture and speedups up to 5,765 using 8,192 cores on distributed memory architecture. In our experiments, we found that while achieving the scalability, our algorithms produce clustering results with comparable quality to the classical algorithms.
ERIC Educational Resources Information Center
Long, Nicole M.; Kahana, Michael J.
2017-01-01
Although episodic and semantic memory share overlapping neural mechanisms, it remains unclear how our pre-existing semantic associations modulate the formation of new, episodic associations. When freely recalling recently studied words, people rely on both episodic and semantic associations, shown through temporal and semantic clustering of…
Message Passing and Shared Address Space Parallelism on an SMP Cluster
NASA Technical Reports Server (NTRS)
Shan, Hongzhang; Singh, Jaswinder P.; Oliker, Leonid; Biswas, Rupak; Biegel, Bryan (Technical Monitor)
2002-01-01
Currently, message passing (MP) and shared address space (SAS) are the two leading parallel programming paradigms. MP has been standardized with MPI, and is the more common and mature approach; however, code development can be extremely difficult, especially for irregularly structured computations. SAS offers substantial ease of programming, but may suffer from performance limitations due to poor spatial locality and high protocol overhead. In this paper, we compare the performance of and the programming effort required for six applications under both programming models on a 32-processor PC-SMP cluster, a platform that is becoming increasingly attractive for high-end scientific computing. Our application suite consists of codes that typically do not exhibit scalable performance under shared-memory programming due to their high communication-to-computation ratios and/or complex communication patterns. Results indicate that SAS can achieve about half the parallel efficiency of MPI for most of our applications, while being competitive for the others. A hybrid MPI+SAS strategy shows only a small performance advantage over pure MPI in some cases. Finally, improved implementations of two MPI collective operations on PC-SMP clusters are presented.
NASA Technical Reports Server (NTRS)
Jost, Gabriele; Labarta, Jesus; Gimenez, Judit
2004-01-01
With the current trend in parallel computer architectures towards clusters of shared memory symmetric multi-processors, parallel programming techniques have evolved that support parallelism beyond a single level. When comparing the performance of applications based on different programming paradigms, it is important to differentiate between the influence of the programming model itself and other factors, such as implementation specific behavior of the operating system (OS) or architectural issues. Rewriting-a large scientific application in order to employ a new programming paradigms is usually a time consuming and error prone task. Before embarking on such an endeavor it is important to determine that there is really a gain that would not be possible with the current implementation. A detailed performance analysis is crucial to clarify these issues. The multilevel programming paradigms considered in this study are hybrid MPI/OpenMP, MLP, and nested OpenMP. The hybrid MPI/OpenMP approach is based on using MPI [7] for the coarse grained parallelization and OpenMP [9] for fine grained loop level parallelism. The MPI programming paradigm assumes a private address space for each process. Data is transferred by explicitly exchanging messages via calls to the MPI library. This model was originally designed for distributed memory architectures but is also suitable for shared memory systems. The second paradigm under consideration is MLP which was developed by Taft. The approach is similar to MPi/OpenMP, using a mix of coarse grain process level parallelization and loop level OpenMP parallelization. As it is the case with MPI, a private address space is assumed for each process. The MLP approach was developed for ccNUMA architectures and explicitly takes advantage of the availability of shared memory. A shared memory arena which is accessible by all processes is required. Communication is done by reading from and writing to the shared memory.
Ensuring correct rollback recovery in distributed shared memory systems
NASA Technical Reports Server (NTRS)
Janssens, Bob; Fuchs, W. Kent
1995-01-01
Distributed shared memory (DSM) implemented on a cluster of workstations is an increasingly attractive platform for executing parallel scientific applications. Checkpointing and rollback techniques can be used in such a system to allow the computation to progress in spite of the temporary failure of one or more processing nodes. This paper presents the design of an independent checkpointing method for DSM that takes advantage of DSM's specific properties to reduce error-free and rollback overhead. The scheme reduces the dependencies that need to be considered for correct rollback to those resulting from transfers of pages. Furthermore, in-transit messages can be recovered without the use of logging. We extend the scheme to a DSM implementation using lazy release consistency, where the frequency of dependencies is further reduced.
Aho-Corasick String Matching on Shared and Distributed Memory Parallel Architectures
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tumeo, Antonino; Villa, Oreste; Chavarría-Miranda, Daniel
String matching is at the core of many critical applications, including network intrusion detection systems, search engines, virus scanners, spam filters, DNA and protein sequencing, and data mining. For all of these applications string matching requires a combination of (sometimes all) the following characteristics: high and/or predictable performance, support for large data sets and flexibility of integration and customization. Many software based implementations targeting conventional cache-based microprocessors fail to achieve high and predictable performance requirements, while Field-Programmable Gate Array (FPGA) implementations and dedicated hardware solutions fail to support large data sets (dictionary sizes) and are difficult to integrate and customize.more » The advent of multicore, multithreaded, and GPU-based systems is opening the possibility for software based solutions to reach very high performance at a sustained rate. This paper compares several software-based implementations of the Aho-Corasick string searching algorithm for high performance systems. We discuss the implementation of the algorithm on several types of shared-memory high-performance architectures (Niagara 2, large x86 SMPs and Cray XMT), distributed memory with homogeneous processing elements (InfiniBand cluster of x86 multicores) and heterogeneous processing elements (InfiniBand cluster of x86 multicores with NVIDIA Tesla C10 GPUs). We describe in detail how each solution achieves the objectives of supporting large dictionaries, sustaining high performance, and enabling customization and flexibility using various data sets.« less
Oelerich, Jan Oliver; Duschek, Lennart; Belz, Jürgen; Beyer, Andreas; Baranovskii, Sergei D; Volz, Kerstin
2017-06-01
We present a new multislice code for the computer simulation of scanning transmission electron microscope (STEM) images based on the frozen lattice approximation. Unlike existing software packages, the code is optimized to perform well on highly parallelized computing clusters, combining distributed and shared memory architectures. This enables efficient calculation of large lateral scanning areas of the specimen within the frozen lattice approximation and fine-grained sweeps of parameter space. Copyright © 2017 Elsevier B.V. All rights reserved.
Explaining prompts children to privilege inductively rich properties.
Walker, Caren M; Lombrozo, Tania; Legare, Cristine H; Gopnik, Alison
2014-11-01
Four experiments with preschool-aged children test the hypothesis that engaging in explanation promotes inductive reasoning on the basis of shared causal properties as opposed to salient (but superficial) perceptual properties. In Experiments 1a and 1b, 3- to 5-year-old children prompted to explain during a causal learning task were more likely to override a tendency to generalize according to perceptual similarity and instead extend an internal feature to an object that shared a causal property. Experiment 2 replicated this effect of explanation in a case of label extension (i.e., categorization). Experiment 3 demonstrated that explanation improves memory for clusters of causally relevant (non-perceptual) features, but impairs memory for superficial (perceptual) features, providing evidence that effects of explanation are selective in scope and apply to memory as well as inference. In sum, our data support the proposal that engaging in explanation influences children's reasoning by privileging inductively rich, causal properties. Copyright © 2014 Elsevier B.V. All rights reserved.
Slobounov, Semyon M.; Zhang, K.; Pennell, D.; Ray, W.; Johnson, B.; Sebastianelli, W.
2010-01-01
Memory problems are one of the most common symptoms of sport-related mild traumatic brain injury (MTBI), known as concussion. Surprisingly, little research has examined spatial memory in concussed athletes given its importance in athletic environments. Here, we combine functional magnetic resonance imaging (fMRI) with a virtual reality (VR) paradigm designed to investigate the possibility of residual functional deficits in recently concussed but asymptomatic individuals. Specifically, we report performance of spatial memory navigation tasks in a VR environment and fMRI data in 15 athletes suffering from MTBI and 15 neurologically normal, athletically active age matched controls. No differences in performance were observed between these two groups of subjects in terms of success rate (94 and 92%) and time to complete the spatial memory navigation tasks (mean = 19.5 and 19.7 s). Whole brain analysis revealed that similar brain activation patterns were observed during both encoding and retrieval among the groups. However, concussed athletes showed larger cortical networks with additional increases in activity outside of the shared region of interest (ROI) during encoding. Quantitative analysis of blood oxygen level dependent (BOLD) signal revealed that concussed individuals had a significantly larger cluster size during encoding at parietal cortex, right dorsolateral prefrontal cortex, and right hippocampus. In addition, there was a significantly larger BOLD signal percent change at the right hippocampus. Neither cluster size nor BOLD signal percent change at shared ROIs was different between groups during retrieval. These major findings are discussed with respect to current hypotheses regarding the neural mechanism responsible for alteration of brain functions in a clinical setting. PMID:20039023
A scalable approach to solving dense linear algebra problems on hybrid CPU-GPU systems
Song, Fengguang; Dongarra, Jack
2014-10-01
Aiming to fully exploit the computing power of all CPUs and all graphics processing units (GPUs) on hybrid CPU-GPU systems to solve dense linear algebra problems, in this paper we design a class of heterogeneous tile algorithms to maximize the degree of parallelism, to minimize the communication volume, and to accommodate the heterogeneity between CPUs and GPUs. The new heterogeneous tile algorithms are executed upon our decentralized dynamic scheduling runtime system, which schedules a task graph dynamically and transfers data between compute nodes automatically. The runtime system uses a new distributed task assignment protocol to solve data dependencies between tasksmore » without any coordination between processing units. By overlapping computation and communication through dynamic scheduling, we are able to attain scalable performance for the double-precision Cholesky factorization and QR factorization. Finally, our approach demonstrates a performance comparable to Intel MKL on shared-memory multicore systems and better performance than both vendor (e.g., Intel MKL) and open source libraries (e.g., StarPU) in the following three environments: heterogeneous clusters with GPUs, conventional clusters without GPUs, and shared-memory systems with multiple GPUs.« less
A scalable approach to solving dense linear algebra problems on hybrid CPU-GPU systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Song, Fengguang; Dongarra, Jack
Aiming to fully exploit the computing power of all CPUs and all graphics processing units (GPUs) on hybrid CPU-GPU systems to solve dense linear algebra problems, in this paper we design a class of heterogeneous tile algorithms to maximize the degree of parallelism, to minimize the communication volume, and to accommodate the heterogeneity between CPUs and GPUs. The new heterogeneous tile algorithms are executed upon our decentralized dynamic scheduling runtime system, which schedules a task graph dynamically and transfers data between compute nodes automatically. The runtime system uses a new distributed task assignment protocol to solve data dependencies between tasksmore » without any coordination between processing units. By overlapping computation and communication through dynamic scheduling, we are able to attain scalable performance for the double-precision Cholesky factorization and QR factorization. Finally, our approach demonstrates a performance comparable to Intel MKL on shared-memory multicore systems and better performance than both vendor (e.g., Intel MKL) and open source libraries (e.g., StarPU) in the following three environments: heterogeneous clusters with GPUs, conventional clusters without GPUs, and shared-memory systems with multiple GPUs.« less
Parallel ALLSPD-3D: Speeding Up Combustor Analysis Via Parallel Processing
NASA Technical Reports Server (NTRS)
Fricker, David M.
1997-01-01
The ALLSPD-3D Computational Fluid Dynamics code for reacting flow simulation was run on a set of benchmark test cases to determine its parallel efficiency. These test cases included non-reacting and reacting flow simulations with varying numbers of processors. Also, the tests explored the effects of scaling the simulation with the number of processors in addition to distributing a constant size problem over an increasing number of processors. The test cases were run on a cluster of IBM RS/6000 Model 590 workstations with ethernet and ATM networking plus a shared memory SGI Power Challenge L workstation. The results indicate that the network capabilities significantly influence the parallel efficiency, i.e., a shared memory machine is fastest and ATM networking provides acceptable performance. The limitations of ethernet greatly hamper the rapid calculation of flows using ALLSPD-3D.
Implementations of BLAST for parallel computers.
Jülich, A
1995-02-01
The BLAST sequence comparison programs have been ported to a variety of parallel computers-the shared memory machine Cray Y-MP 8/864 and the distributed memory architectures Intel iPSC/860 and nCUBE. Additionally, the programs were ported to run on workstation clusters. We explain the parallelization techniques and consider the pros and cons of these methods. The BLAST programs are very well suited for parallelization for a moderate number of processors. We illustrate our results using the program blastp as an example. As input data for blastp, a 799 residue protein query sequence and the protein database PIR were used.
Costa, Patrício Soares; Santos, Nadine Correia; Cunha, Pedro; Cotter, Jorge; Sousa, Nuno
2013-01-01
The main focus of this study was to illustrate the applicability of multiple correspondence analysis (MCA) in detecting and representing underlying structures in large datasets used to investigate cognitive ageing. Principal component analysis (PCA) was used to obtain main cognitive dimensions, and MCA was used to detect and explore relationships between cognitive, clinical, physical, and lifestyle variables. Two PCA dimensions were identified (general cognition/executive function and memory), and two MCA dimensions were retained. Poorer cognitive performance was associated with older age, less school years, unhealthier lifestyle indicators, and presence of pathology. The first MCA dimension indicated the clustering of general/executive function and lifestyle indicators and education, while the second association was between memory and clinical parameters and age. The clustering analysis with object scores method was used to identify groups sharing similar characteristics. The weaker cognitive clusters in terms of memory and executive function comprised individuals with characteristics contributing to a higher MCA dimensional mean score (age, less education, and presence of indicators of unhealthier lifestyle habits and/or clinical pathologies). MCA provided a powerful tool to explore complex ageing data, covering multiple and diverse variables, showing if a relationship exists and how variables are related, and offering statistical results that can be seen both analytically and visually.
Zhu, Hao; Sun, Yan; Rajagopal, Gunaretnam; Mondry, Adrian; Dhar, Pawan
2004-01-01
Background Many arrhythmias are triggered by abnormal electrical activity at the ionic channel and cell level, and then evolve spatio-temporally within the heart. To understand arrhythmias better and to diagnose them more precisely by their ECG waveforms, a whole-heart model is required to explore the association between the massively parallel activities at the channel/cell level and the integrative electrophysiological phenomena at organ level. Methods We have developed a method to build large-scale electrophysiological models by using extended cellular automata, and to run such models on a cluster of shared memory machines. We describe here the method, including the extension of a language-based cellular automaton to implement quantitative computing, the building of a whole-heart model with Visible Human Project data, the parallelization of the model on a cluster of shared memory computers with OpenMP and MPI hybrid programming, and a simulation algorithm that links cellular activity with the ECG. Results We demonstrate that electrical activities at channel, cell, and organ levels can be traced and captured conveniently in our extended cellular automaton system. Examples of some ECG waveforms simulated with a 2-D slice are given to support the ECG simulation algorithm. A performance evaluation of the 3-D model on a four-node cluster is also given. Conclusions Quantitative multicellular modeling with extended cellular automata is a highly efficient and widely applicable method to weave experimental data at different levels into computational models. This process can be used to investigate complex and collective biological activities that can be described neither by their governing differentiation equations nor by discrete parallel computation. Transparent cluster computing is a convenient and effective method to make time-consuming simulation feasible. Arrhythmias, as a typical case, can be effectively simulated with the methods described. PMID:15339335
A highly efficient multi-core algorithm for clustering extremely large datasets
2010-01-01
Background In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput technologies. This demand is likely to increase. Standard algorithms for analyzing data, such as cluster algorithms, need to be parallelized for fast processing. Unfortunately, most approaches for parallelizing algorithms largely rely on network communication protocols connecting and requiring multiple computers. One answer to this problem is to utilize the intrinsic capabilities in current multi-core hardware to distribute the tasks among the different cores of one computer. Results We introduce a multi-core parallelization of the k-means and k-modes cluster algorithms based on the design principles of transactional memory for clustering gene expression microarray type data and categorial SNP data. Our new shared memory parallel algorithms show to be highly efficient. We demonstrate their computational power and show their utility in cluster stability and sensitivity analysis employing repeated runs with slightly changed parameters. Computation speed of our Java based algorithm was increased by a factor of 10 for large data sets while preserving computational accuracy compared to single-core implementations and a recently published network based parallelization. Conclusions Most desktop computers and even notebooks provide at least dual-core processors. Our multi-core algorithms show that using modern algorithmic concepts, parallelization makes it possible to perform even such laborious tasks as cluster sensitivity and cluster number estimation on the laboratory computer. PMID:20370922
NASA Technical Reports Server (NTRS)
Kikuchi, Hideaki; Kalia, Rajiv K.; Nakano, Aiichiro; Vashishta, Priya; Shimojo, Fuyuki; Saini, Subhash
2003-01-01
Scalability of a low-cost, Intel Xeon-based, multi-Teraflop Linux cluster is tested for two high-end scientific applications: Classical atomistic simulation based on the molecular dynamics method and quantum mechanical calculation based on the density functional theory. These scalable parallel applications use space-time multiresolution algorithms and feature computational-space decomposition, wavelet-based adaptive load balancing, and spacefilling-curve-based data compression for scalable I/O. Comparative performance tests are performed on a 1,024-processor Linux cluster and a conventional higher-end parallel supercomputer, 1,184-processor IBM SP4. The results show that the performance of the Linux cluster is comparable to that of the SP4. We also study various effects, such as the sharing of memory and L2 cache among processors, on the performance.
High-performance computing — an overview
NASA Astrophysics Data System (ADS)
Marksteiner, Peter
1996-08-01
An overview of high-performance computing (HPC) is given. Different types of computer architectures used in HPC are discussed: vector supercomputers, high-performance RISC processors, various parallel computers like symmetric multiprocessors, workstation clusters, massively parallel processors. Software tools and programming techniques used in HPC are reviewed: vectorizing compilers, optimization and vector tuning, optimization for RISC processors; parallel programming techniques like shared-memory parallelism, message passing and data parallelism; and numerical libraries.
Thaler, Nicholas S; Terranova, Jennifer; Turner, Alisa; Mayfield, Joan; Allen, Daniel N
2015-01-01
Recent studies have examined heterogeneous neuropsychological outcomes in childhood traumatic brain injury (TBI) using cluster analysis. These studies have identified homogeneous subgroups based on tests of IQ, memory, and other cognitive abilities that show some degree of association with specific cognitive, emotional, and behavioral outcomes, and have demonstrated that the clusters derived for children with TBI are different from those observed in normal populations. However, the extent to which these subgroups are stable across abilities has not been examined, and this has significant implications for the generalizability and clinical utility of TBI clusters. The current study addressed this by comparing IQ and memory profiles of 137 children who sustained moderate-to-severe TBI. Cluster analysis of IQ and memory scores indicated that a four-cluster solution was optimal for the IQ scores and a five-cluster solution was optimal for the memory scores. Three clusters on each battery differed primarily by level of performance, while the others had pattern variations. Cross-plotting the clusters across respective IQ and memory test scores indicated that clusters defined by level were generally stable, while clusters defined by pattern differed. Notably, children with slower processing speed exhibited low-average to below-average performance on memory indexes. These results provide some support for the stability of previously identified memory and IQ clusters and provide information about the relationship between IQ and memory in children with TBI.
Fast distributed large-pixel-count hologram computation using a GPU cluster.
Pan, Yuechao; Xu, Xuewu; Liang, Xinan
2013-09-10
Large-pixel-count holograms are one essential part for big size holographic three-dimensional (3D) display, but the generation of such holograms is computationally demanding. In order to address this issue, we have built a graphics processing unit (GPU) cluster with 32.5 Tflop/s computing power and implemented distributed hologram computation on it with speed improvement techniques, such as shared memory on GPU, GPU level adaptive load balancing, and node level load distribution. Using these speed improvement techniques on the GPU cluster, we have achieved 71.4 times computation speed increase for 186M-pixel holograms. Furthermore, we have used the approaches of diffraction limits and subdivision of holograms to overcome the GPU memory limit in computing large-pixel-count holograms. 745M-pixel and 1.80G-pixel holograms were computed in 343 and 3326 s, respectively, for more than 2 million object points with RGB colors. Color 3D objects with 1.02M points were successfully reconstructed from 186M-pixel hologram computed in 8.82 s with all the above three speed improvement techniques. It is shown that distributed hologram computation using a GPU cluster is a promising approach to increase the computation speed of large-pixel-count holograms for large size holographic display.
Temporal Clustering and Sequencing in Short-Term Memory and Episodic Memory
ERIC Educational Resources Information Center
Farrell, Simon
2012-01-01
A model of short-term memory and episodic memory is presented, with the core assumptions that (a) people parse their continuous experience into episodic clusters and (b) items are clustered together in memory as episodes by binding information within an episode to a common temporal context. Along with the additional assumption that information…
Performing an allreduce operation using shared memory
Archer, Charles J [Rochester, MN; Dozsa, Gabor [Ardsley, NY; Ratterman, Joseph D [Rochester, MN; Smith, Brian E [Rochester, MN
2012-04-17
Methods, apparatus, and products are disclosed for performing an allreduce operation using shared memory that include: receiving, by at least one of a plurality of processing cores on a compute node, an instruction to perform an allreduce operation; establishing, by the core that received the instruction, a job status object for specifying a plurality of shared memory allreduce work units, the plurality of shared memory allreduce work units together performing the allreduce operation on the compute node; determining, by an available core on the compute node, a next shared memory allreduce work unit in the job status object; and performing, by that available core on the compute node, that next shared memory allreduce work unit.
Performing an allreduce operation using shared memory
Archer, Charles J; Dozsa, Gabor; Ratterman, Joseph D; Smith, Brian E
2014-06-10
Methods, apparatus, and products are disclosed for performing an allreduce operation using shared memory that include: receiving, by at least one of a plurality of processing cores on a compute node, an instruction to perform an allreduce operation; establishing, by the core that received the instruction, a job status object for specifying a plurality of shared memory allreduce work units, the plurality of shared memory allreduce work units together performing the allreduce operation on the compute node; determining, by an available core on the compute node, a next shared memory allreduce work unit in the job status object; and performing, by that available core on the compute node, that next shared memory allreduce work unit.
Performance and Application of Parallel OVERFLOW Codes on Distributed and Shared Memory Platforms
NASA Technical Reports Server (NTRS)
Djomehri, M. Jahed; Rizk, Yehia M.
1999-01-01
The presentation discusses recent studies on the performance of the two parallel versions of the aerodynamics CFD code, OVERFLOW_MPI and _MLP. Developed at NASA Ames, the serial version, OVERFLOW, is a multidimensional Navier-Stokes flow solver based on overset (Chimera) grid technology. The code has recently been parallelized in two ways. One is based on the explicit message-passing interface (MPI) across processors and uses the _MPI communication package. This approach is primarily suited for distributed memory systems and workstation clusters. The second, termed the multi-level parallel (MLP) method, is simple and uses shared memory for all communications. The _MLP code is suitable on distributed-shared memory systems. For both methods, the message passing takes place across the processors or processes at the advancement of each time step. This procedure is, in effect, the Chimera boundary conditions update, which is done in an explicit "Jacobi" style. In contrast, the update in the serial code is done in more of the "Gauss-Sidel" fashion. The programming efforts for the _MPI code is more complicated than for the _MLP code; the former requires modification of the outer and some inner shells of the serial code, whereas the latter focuses only on the outer shell of the code. The _MPI version offers a great deal of flexibility in distributing grid zones across a specified number of processors in order to achieve load balancing. The approach is capable of partitioning zones across multiple processors or sending each zone and/or cluster of several zones into a single processor. The message passing across the processors consists of Chimera boundary and/or an overlap of "halo" boundary points for each partitioned zone. The MLP version is a new coarse-grain parallel concept at the zonal and intra-zonal levels. A grouping strategy is used to distribute zones into several groups forming sub-processes which will run in parallel. The total volume of grid points in each group are approximately balanced. A proper number of threads are initially allocated to each group, and in subsequent iterations during the run-time, the number of threads are adjusted to achieve load balancing across the processes. Each process exploits the multitasking directives already established in Overflow.
Efficient Numeric and Geometric Computations using Heterogeneous Shared Memory Architectures
2017-10-04
Report: Efficient Numeric and Geometric Computations using Heterogeneous Shared Memory Architectures The views, opinions and/or findings contained in this...Chapel Hill Title: Efficient Numeric and Geometric Computations using Heterogeneous Shared Memory Architectures Report Term: 0-Other Email: dm...algorithms for scientific and geometric computing by exploiting the power and performance efficiency of heterogeneous shared memory architectures . These
Brandon, Nicole R; Beike, Denise R; Cole, Holly E
2017-07-01
Autobiographical memories (AMs) can be used to create and maintain closeness with others [Alea, N., & Bluck, S. (2003). Why are you telling me that? A conceptual model of the social function of autobiographical memory. Memory, 11(2), 165-178]. However, the differential effects of memory specificity are not well established. Two studies with 148 participants tested whether the order in which autobiographical knowledge (AK) and specific episodic AM (EAM) are shared affects feelings of closeness. Participants read two memories hypothetically shared by each of four strangers. The strangers first shared either AK or an EAM, and then shared either AK or an EAM. Participants were randomly assigned to read either positive or negative AMs from the strangers. Findings suggest that people feel closer to those who share positive AMs in the same way they construct memories: starting with general and moving to specific.
Francis, Wendy S; Taylor, Randolph S; Gutiérrez, Marisela; Liaño, Mary K; Manzanera, Diana G; Penalver, Renee M
2018-05-19
Two experiments investigated how well bilinguals utilise long-standing semantic associations to encode and retrieve semantic clusters in verbal episodic memory. In Experiment 1, Spanish-English bilinguals (N = 128) studied and recalled word and picture sets. Word recall was equivalent in L1 and L2, picture recall was better in L1 than in L2, and the picture superiority effect was stronger in L1 than in L2. Semantic clustering in word and picture recall was equivalent in L1 and L2. In Experiment 2, Spanish-English bilinguals (N = 128) and English-speaking monolinguals (N = 128) studied and recalled word sequences that contained semantically related pairs. Data were analyzed using a multinomial processing tree approach, the pair-clustering model. Cluster formation was more likely for semantically organised than for randomly ordered word sequences. Probabilities of cluster formation, cluster retrieval, and retrieval of unclustered items did not differ across languages or language groups. Language proficiency has little if any impact on the utilisation of long-standing semantic associations, which are language-general.
Distributed computing for membrane-based modeling of action potential propagation.
Porras, D; Rogers, J M; Smith, W M; Pollard, A E
2000-08-01
Action potential propagation simulations with physiologic membrane currents and macroscopic tissue dimensions are computationally expensive. We, therefore, analyzed distributed computing schemes to reduce execution time in workstation clusters by parallelizing solutions with message passing. Four schemes were considered in two-dimensional monodomain simulations with the Beeler-Reuter membrane equations. Parallel speedups measured with each scheme were compared to theoretical speedups, recognizing the relationship between speedup and code portions that executed serially. A data decomposition scheme based on total ionic current provided the best performance. Analysis of communication latencies in that scheme led to a load-balancing algorithm in which measured speedups at 89 +/- 2% and 75 +/- 8% of theoretical speedups were achieved in homogeneous and heterogeneous clusters of workstations. Speedups in this scheme with the Luo-Rudy dynamic membrane equations exceeded 3.0 with eight distributed workstations. Cluster speedups were comparable to those measured during parallel execution on a shared memory machine.
Accelerating Smith-Waterman Algorithm for Biological Database Search on CUDA-Compatible GPUs
NASA Astrophysics Data System (ADS)
Munekawa, Yuma; Ino, Fumihiko; Hagihara, Kenichi
This paper presents a fast method capable of accelerating the Smith-Waterman algorithm for biological database search on a cluster of graphics processing units (GPUs). Our method is implemented using compute unified device architecture (CUDA), which is available on the nVIDIA GPU. As compared with previous methods, our method has four major contributions. (1) The method efficiently uses on-chip shared memory to reduce the data amount being transferred between off-chip video memory and processing elements in the GPU. (2) It also reduces the number of data fetches by applying a data reuse technique to query and database sequences. (3) A pipelined method is also implemented to overlap GPU execution with database access. (4) Finally, a master/worker paradigm is employed to accelerate hundreds of database searches on a cluster system. In experiments, the peak performance on a GeForce GTX 280 card reaches 8.32 giga cell updates per second (GCUPS). We also find that our method reduces the amount of data fetches to 1/140, achieving approximately three times higher performance than a previous CUDA-based method. Our 32-node cluster version is approximately 28 times faster than a single GPU version. Furthermore, the effective performance reaches 75.6 giga instructions per second (GIPS) using 32 GeForce 8800 GTX cards.
Lew, Timothy F; Vul, Edward
2015-01-01
People seem to compute the ensemble statistics of objects and use this information to support the recall of individual objects in visual working memory. However, there are many different ways that hierarchical structure might be encoded. We examined the format of structured memories by asking subjects to recall the locations of objects arranged in different spatial clustering structures. Consistent with previous investigations of structured visual memory, subjects recalled objects biased toward the center of their clusters. Subjects also recalled locations more accurately when they were arranged in fewer clusters containing more objects, suggesting that subjects used the clustering structure of objects to aid recall. Furthermore, subjects had more difficulty recalling larger relative distances, consistent with subjects encoding the positions of objects relative to clusters and recalling them with magnitude-proportional (Weber) noise. Our results suggest that clustering improved the fidelity of recall by biasing the recall of locations toward cluster centers to compensate for uncertainty and by reducing the magnitude of encoded relative distances.
Expressing Parallelism with ROOT
NASA Astrophysics Data System (ADS)
Piparo, D.; Tejedor, E.; Guiraud, E.; Ganis, G.; Mato, P.; Moneta, L.; Valls Pla, X.; Canal, P.
2017-10-01
The need for processing the ever-increasing amount of data generated by the LHC experiments in a more efficient way has motivated ROOT to further develop its support for parallelism. Such support is being tackled both for shared-memory and distributed-memory environments. The incarnations of the aforementioned parallelism are multi-threading, multi-processing and cluster-wide executions. In the area of multi-threading, we discuss the new implicit parallelism and related interfaces, as well as the new building blocks to safely operate with ROOT objects in a multi-threaded environment. Regarding multi-processing, we review the new MultiProc framework, comparing it with similar tools (e.g. multiprocessing module in Python). Finally, as an alternative to PROOF for cluster-wide executions, we introduce the efforts on integrating ROOT with state-of-the-art distributed data processing technologies like Spark, both in terms of programming model and runtime design (with EOS as one of the main components). For all the levels of parallelism, we discuss, based on real-life examples and measurements, how our proposals can increase the productivity of scientists.
Expressing Parallelism with ROOT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Piparo, D.; Tejedor, E.; Guiraud, E.
The need for processing the ever-increasing amount of data generated by the LHC experiments in a more efficient way has motivated ROOT to further develop its support for parallelism. Such support is being tackled both for shared-memory and distributed-memory environments. The incarnations of the aforementioned parallelism are multi-threading, multi-processing and cluster-wide executions. In the area of multi-threading, we discuss the new implicit parallelism and related interfaces, as well as the new building blocks to safely operate with ROOT objects in a multi-threaded environment. Regarding multi-processing, we review the new MultiProc framework, comparing it with similar tools (e.g. multiprocessing module inmore » Python). Finally, as an alternative to PROOF for cluster-wide executions, we introduce the efforts on integrating ROOT with state-of-the-art distributed data processing technologies like Spark, both in terms of programming model and runtime design (with EOS as one of the main components). For all the levels of parallelism, we discuss, based on real-life examples and measurements, how our proposals can increase the productivity of scientists.« less
NASA Technical Reports Server (NTRS)
Soltis, Steven R.; Ruwart, Thomas M.; OKeefe, Matthew T.
1996-01-01
The global file system (GFS) is a prototype design for a distributed file system in which cluster nodes physically share storage devices connected via a network-like fiber channel. Networks and network-attached storage devices have advanced to a level of performance and extensibility so that the previous disadvantages of shared disk architectures are no longer valid. This shared storage architecture attempts to exploit the sophistication of storage device technologies whereas a server architecture diminishes a device's role to that of a simple component. GFS distributes the file system responsibilities across processing nodes, storage across the devices, and file system resources across the entire storage pool. GFS caches data on the storage devices instead of the main memories of the machines. Consistency is established by using a locking mechanism maintained by the storage devices to facilitate atomic read-modify-write operations. The locking mechanism is being prototyped in the Silicon Graphics IRIX operating system and is accessed using standard Unix commands and modules.
NASA Astrophysics Data System (ADS)
Georgiev, K.; Zlatev, Z.
2010-11-01
The Danish Eulerian Model (DEM) is an Eulerian model for studying the transport of air pollutants on large scale. Originally, the model was developed at the National Environmental Research Institute of Denmark. The model computational domain covers Europe and some neighbour parts belong to the Atlantic Ocean, Asia and Africa. If DEM model is to be applied by using fine grids, then its discretization leads to a huge computational problem. This implies that such a model as DEM must be run only on high-performance computer architectures. The implementation and tuning of such a complex large-scale model on each different computer is a non-trivial task. Here, some comparison results of running of this model on different kind of vector (CRAY C92A, Fujitsu, etc.), parallel computers with distributed memory (IBM SP, CRAY T3E, Beowulf clusters, Macintosh G4 clusters, etc.), parallel computers with shared memory (SGI Origin, SUN, etc.) and parallel computers with two levels of parallelism (IBM SMP, IBM BlueGene/P, clusters of multiprocessor nodes, etc.) will be presented. The main idea in the parallel version of DEM is domain partitioning approach. Discussions according to the effective use of the cache and hierarchical memories of the modern computers as well as the performance, speed-ups and efficiency achieved will be done. The parallel code of DEM, created by using MPI standard library, appears to be highly portable and shows good efficiency and scalability on different kind of vector and parallel computers. Some important applications of the computer model output are presented in short.
Shared Semantics and the Use of Organizational Memories for E-Mail Communications.
ERIC Educational Resources Information Center
Schwartz, David G.
1998-01-01
Examines the use of shared semantics information to link concepts in an organizational memory to e-mail communications. Presents a framework for determining shared semantics based on organizational and personal user profiles. Illustrates how shared semantics are used by the HyperMail system to help link organizational memories (OM) content to…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Clark, M. A.; Strelchenko, Alexei; Vaquero, Alejandro
Lattice quantum chromodynamics simulations in nuclear physics have benefited from a tremendous number of algorithmic advances such as multigrid and eigenvector deflation. These improve the time to solution but do not alleviate the intrinsic memory-bandwidth constraints of the matrix-vector operation dominating iterative solvers. Batching this operation for multiple vectors and exploiting cache and register blocking can yield a super-linear speed up. Block-Krylov solvers can naturally take advantage of such batched matrix-vector operations, further reducing the iterations to solution by sharing the Krylov space between solves. However, practical implementations typically suffer from the quadratic scaling in the number of vector-vector operations.more » Using the QUDA library, we present an implementation of a block-CG solver on NVIDIA GPUs which reduces the memory-bandwidth complexity of vector-vector operations from quadratic to linear. We present results for the HISQ discretization, showing a 5x speedup compared to highly-optimized independent Krylov solves on NVIDIA's SaturnV cluster.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ibrahim, Khaled Z.; Epifanovsky, Evgeny; Williams, Samuel
Coupled-cluster methods provide highly accurate models of molecular structure through explicit numerical calculation of tensors representing the correlation between electrons. These calculations are dominated by a sequence of tensor contractions, motivating the development of numerical libraries for such operations. While based on matrix–matrix multiplication, these libraries are specialized to exploit symmetries in the molecular structure and in electronic interactions, and thus reduce the size of the tensor representation and the complexity of contractions. The resulting algorithms are irregular and their parallelization has been previously achieved via the use of dynamic scheduling or specialized data decompositions. We introduce our efforts tomore » extend the Libtensor framework to work in the distributed memory environment in a scalable and energy-efficient manner. We achieve up to 240× speedup compared with the optimized shared memory implementation of Libtensor. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures (Cray XC30 and XC40, and IBM Blue Gene/Q), and on a heterogeneous GPU-CPU system (Cray XK7). As the bottlenecks shift from being compute-bound DGEMM's to communication-bound collectives as the size of the molecular system scales, we adopt two radically different parallelization approaches for handling load-imbalance, tasking and bulk synchronous models. Nevertheless, we preserve a unified interface to both programming models to maintain the productivity of computational quantum chemists.« less
Ibrahim, Khaled Z.; Epifanovsky, Evgeny; Williams, Samuel; ...
2017-03-08
Coupled-cluster methods provide highly accurate models of molecular structure through explicit numerical calculation of tensors representing the correlation between electrons. These calculations are dominated by a sequence of tensor contractions, motivating the development of numerical libraries for such operations. While based on matrix–matrix multiplication, these libraries are specialized to exploit symmetries in the molecular structure and in electronic interactions, and thus reduce the size of the tensor representation and the complexity of contractions. The resulting algorithms are irregular and their parallelization has been previously achieved via the use of dynamic scheduling or specialized data decompositions. We introduce our efforts tomore » extend the Libtensor framework to work in the distributed memory environment in a scalable and energy-efficient manner. We achieve up to 240× speedup compared with the optimized shared memory implementation of Libtensor. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures (Cray XC30 and XC40, and IBM Blue Gene/Q), and on a heterogeneous GPU-CPU system (Cray XK7). As the bottlenecks shift from being compute-bound DGEMM's to communication-bound collectives as the size of the molecular system scales, we adopt two radically different parallelization approaches for handling load-imbalance, tasking and bulk synchronous models. Nevertheless, we preserve a unified interface to both programming models to maintain the productivity of computational quantum chemists.« less
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.
Secondary immunization generates clonally related antigen-specific plasma cells and memory B cells.
Frölich, Daniela; Giesecke, Claudia; Mei, Henrik E; Reiter, Karin; Daridon, Capucine; Lipsky, Peter E; Dörner, Thomas
2010-09-01
Rechallenge with T cell-dependent Ags induces memory B cells to re-enter germinal centers (GCs) and undergo further expansion and differentiation into plasma cells (PCs) and secondary memory B cells. It is currently not known whether the expanded population of memory B cells and PCs generated in secondary GCs are clonally related, nor has the extent of proliferation and somatic hypermutation of their precursors been delineated. In this study, after secondary tetanus toxoid (TT) immunization, TT-specific PCs increased 17- to 80-fold on days 6-7, whereas TT-specific memory B cells peaked (delayed) on day 14 with a 2- to 22-fold increase. Molecular analyses of V(H)DJ(H) rearrangements of individual cells revealed no major differences of gene usage and CDR3 length between TT-specific PCs and memory B cells, and both contained extensive evidence of somatic hypermutation with a pattern consistent with GC reactions. This analysis identified clonally related TT-specific memory B cells and PCs. Within clusters of clonally related cells, sequences shared a number of mutations but also could contain additional base pair changes. The data indicate that although following secondary immunization PCs can derive from memory B cells without further somatic hypermutation, in some circumstances, likely within GC reactions, asymmetric mutation can occur. These results suggest that after the fate decision to differentiate into secondary memory B cells or PCs, some committed precursors continue to proliferate and mutate their V(H) genes.
NASA Astrophysics Data System (ADS)
Rastogi, Richa; Londhe, Ashutosh; Srivastava, Abhishek; Sirasala, Kirannmayi M.; Khonde, Kiran
2017-03-01
In this article, a new scalable 3D Kirchhoff depth migration algorithm is presented on state of the art multicore CPU based cluster. Parallelization of 3D Kirchhoff depth migration is challenging due to its high demand of compute time, memory, storage and I/O along with the need of their effective management. The most resource intensive modules of the algorithm are traveltime calculations and migration summation which exhibit an inherent trade off between compute time and other resources. The parallelization strategy of the algorithm largely depends on the storage of calculated traveltimes and its feeding mechanism to the migration process. The presented work is an extension of our previous work, wherein a 3D Kirchhoff depth migration application for multicore CPU based parallel system had been developed. Recently, we have worked on improving parallel performance of this application by re-designing the parallelization approach. The new algorithm is capable to efficiently migrate both prestack and poststack 3D data. It exhibits flexibility for migrating large number of traces within the available node memory and with minimal requirement of storage, I/O and inter-node communication. The resultant application is tested using 3D Overthrust data on PARAM Yuva II, which is a Xeon E5-2670 based multicore CPU cluster with 16 cores/node and 64 GB shared memory. Parallel performance of the algorithm is studied using different numerical experiments and the scalability results show striking improvement over its previous version. An impressive 49.05X speedup with 76.64% efficiency is achieved for 3D prestack data and 32.00X speedup with 50.00% efficiency for 3D poststack data, using 64 nodes. The results also demonstrate the effectiveness and robustness of the improved algorithm with high scalability and efficiency on a multicore CPU cluster.
Comparing the OpenMP, MPI, and Hybrid Programming Paradigm on an SMP Cluster
NASA Technical Reports Server (NTRS)
Jost, Gabriele; Jin, Haoqiang; anMey, Dieter; Hatay, Ferhat F.
2003-01-01
With the advent of parallel hardware and software technologies users are faced with the challenge to choose a programming paradigm best suited for the underlying computer architecture. With the current trend in parallel computer architectures towards clusters of shared memory symmetric multi-processors (SMP), parallel programming techniques have evolved to support parallelism beyond a single level. Which programming paradigm is the best will depend on the nature of the given problem, the hardware architecture, and the available software. In this study we will compare different programming paradigms for the parallelization of a selected benchmark application on a cluster of SMP nodes. We compare the timings of different implementations of the same CFD benchmark application employing the same numerical algorithm on a cluster of Sun Fire SMP nodes. The rest of the paper is structured as follows: In section 2 we briefly discuss the programming models under consideration. We describe our compute platform in section 3. The different implementations of our benchmark code are described in section 4 and the performance results are presented in section 5. We conclude our study in section 6.
Long-term memory and volatility clustering in high-frequency price changes
NASA Astrophysics Data System (ADS)
oh, Gabjin; Kim, Seunghwan; Eom, Cheoljun
2008-02-01
We studied the long-term memory in diverse stock market indices and foreign exchange rates using Detrended Fluctuation Analysis (DFA). For all high-frequency market data studied, no significant long-term memory property was detected in the return series, while a strong long-term memory property was found in the volatility time series. The possible causes of the long-term memory property were investigated using the return data filtered by the AR(1) model, reflecting the short-term memory property, the GARCH(1,1) model, reflecting the volatility clustering property, and the FIGARCH model, reflecting the long-term memory property of the volatility time series. The memory effect in the AR(1) filtered return and volatility time series remained unchanged, while the long-term memory property diminished significantly in the volatility series of the GARCH(1,1) filtered data. Notably, there is no long-term memory property, when we eliminate the long-term memory property of volatility by the FIGARCH model. For all data used, although the Hurst exponents of the volatility time series changed considerably over time, those of the time series with the volatility clustering effect removed diminish significantly. Our results imply that the long-term memory property of the volatility time series can be attributed to the volatility clustering observed in the financial time series.
Shared Memory Parallelism for 3D Cartesian Discrete Ordinates Solver
NASA Astrophysics Data System (ADS)
Moustafa, Salli; Dutka-Malen, Ivan; Plagne, Laurent; Ponçot, Angélique; Ramet, Pierre
2014-06-01
This paper describes the design and the performance of DOMINO, a 3D Cartesian SN solver that implements two nested levels of parallelism (multicore+SIMD) on shared memory computation nodes. DOMINO is written in C++, a multi-paradigm programming language that enables the use of powerful and generic parallel programming tools such as Intel TBB and Eigen. These two libraries allow us to combine multi-thread parallelism with vector operations in an efficient and yet portable way. As a result, DOMINO can exploit the full power of modern multi-core processors and is able to tackle very large simulations, that usually require large HPC clusters, using a single computing node. For example, DOMINO solves a 3D full core PWR eigenvalue problem involving 26 energy groups, 288 angular directions (S16), 46 × 106 spatial cells and 1 × 1012 DoFs within 11 hours on a single 32-core SMP node. This represents a sustained performance of 235 GFlops and 40:74% of the SMP node peak performance for the DOMINO sweep implementation. The very high Flops/Watt ratio of DOMINO makes it a very interesting building block for a future many-nodes nuclear simulation tool.
NASA Astrophysics Data System (ADS)
Leamy, Michael J.; Springer, Adam C.
In this research we report parallel implementation of a Cellular Automata-based simulation tool for computing elastodynamic response on complex, two-dimensional domains. Elastodynamic simulation using Cellular Automata (CA) has recently been presented as an alternative, inherently object-oriented technique for accurately and efficiently computing linear and nonlinear wave propagation in arbitrarily-shaped geometries. The local, autonomous nature of the method should lead to straight-forward and efficient parallelization. We address this notion on symmetric multiprocessor (SMP) hardware using a Java-based object-oriented CA code implementing triangular state machines (i.e., automata) and the MPI bindings written in Java (MPJ Express). We use MPJ Express to reconfigure our existing CA code to distribute a domain's automata to cores present on a dual quad-core shared-memory system (eight total processors). We note that this message passing parallelization strategy is directly applicable to computer clustered computing, which will be the focus of follow-on research. Results on the shared memory platform indicate nearly-ideal, linear speed-up. We conclude that the CA-based elastodynamic simulator is easily configured to run in parallel, and yields excellent speed-up on SMP hardware.
Job Management Requirements for NAS Parallel Systems and Clusters
NASA Technical Reports Server (NTRS)
Saphir, William; Tanner, Leigh Ann; Traversat, Bernard
1995-01-01
A job management system is a critical component of a production supercomputing environment, permitting oversubscribed resources to be shared fairly and efficiently. Job management systems that were originally designed for traditional vector supercomputers are not appropriate for the distributed-memory parallel supercomputers that are becoming increasingly important in the high performance computing industry. Newer job management systems offer new functionality but do not solve fundamental problems. We address some of the main issues in resource allocation and job scheduling we have encountered on two parallel computers - a 160-node IBM SP2 and a cluster of 20 high performance workstations located at the Numerical Aerodynamic Simulation facility. We describe the requirements for resource allocation and job management that are necessary to provide a production supercomputing environment on these machines, prioritizing according to difficulty and importance, and advocating a return to fundamental issues.
NASA Astrophysics Data System (ADS)
Lai, Siyan; Xu, Ying; Shao, Bo; Guo, Menghan; Lin, Xiaola
2017-04-01
In this paper we study on Monte Carlo method for solving systems of linear algebraic equations (SLAE) based on shared memory. Former research demostrated that GPU can effectively speed up the computations of this issue. Our purpose is to optimize Monte Carlo method simulation on GPUmemoryachritecture specifically. Random numbers are organized to storein shared memory, which aims to accelerate the parallel algorithm. Bank conflicts can be avoided by our Collaborative Thread Arrays(CTA)scheme. The results of experiments show that the shared memory based strategy can speed up the computaions over than 3X at most.
A Reassessment of IgM Memory Subsets in Humans.
Bagnara, Davide; Squillario, Margherita; Kipling, David; Mora, Thierry; Walczak, Aleksandra M; Da Silva, Lucie; Weller, Sandra; Dunn-Walters, Deborah K; Weill, Jean-Claude; Reynaud, Claude-Agnès
2015-10-15
From paired blood and spleen samples from three adult donors, we performed high-throughput VH sequencing of human B cell subsets defined by IgD and CD27 expression: IgD(+)CD27(+) ("marginal zone [MZ]"), IgD(-)CD27(+) ("memory," including IgM ["IgM-only"], IgG and IgA) and IgD(-)CD27(-) cells ("double-negative," including IgM, IgG, and IgA). A total of 91,294 unique sequences clustered in 42,670 clones, revealing major clonal expansions in each of these subsets. Among these clones, we further analyzed those shared sequences from different subsets or tissues for VH gene mutation, H-CDR3-length, and VH/JH usage, comparing these different characteristics with all sequences from their subset of origin for which these parameters constitute a distinct signature. The IgM-only repertoire profile differed notably from that of MZ B cells by a higher mutation frequency and lower VH4 and higher JH6 gene usage. Strikingly, IgM sequences from clones shared between the MZ and the memory IgG/IgA compartments showed a mutation and repertoire profile of IgM-only and not of MZ B cells. Similarly, all IgM clonal relationships (among MZ, IgM-only, and double-negative compartments) involved sequences with the characteristics of IgM-only B cells. Finally, clonal relationships between tissues suggested distinct recirculation characteristics between MZ and switched B cells. The "IgM-only" subset (including cells with its repertoire signature but higher IgD or lower CD27 expression levels) thus appear as the only subset showing precursor-product relationships with CD27(+) switched memory B cells, indicating that they represent germinal center-derived IgM memory B cells and that IgM memory and MZ B cells constitute two distinct entities. Copyright © 2015 by The American Association of Immunologists, Inc.
CaLRS: A Critical-Aware Shared LLC Request Scheduling Algorithm on GPGPU
Ma, Jianliang; Meng, Jinglei; Chen, Tianzhou; Wu, Minghui
2015-01-01
Ultra high thread-level parallelism in modern GPUs usually introduces numerous memory requests simultaneously. So there are always plenty of memory requests waiting at each bank of the shared LLC (L2 in this paper) and global memory. For global memory, various schedulers have already been developed to adjust the request sequence. But we find few work has ever focused on the service sequence on the shared LLC. We measured that a big number of GPU applications always queue at LLC bank for services, which provide opportunity to optimize the service order on LLC. Through adjusting the GPU memory request service order, we can improve the schedulability of SM. So we proposed a critical-aware shared LLC request scheduling algorithm (CaLRS) in this paper. The priority representative of memory request is critical for CaLRS. We use the number of memory requests that originate from the same warp but have not been serviced when they arrive at the shared LLC bank to represent the criticality of each warp. Experiments show that the proposed scheme can boost the SM schedulability effectively by promoting the scheduling priority of the memory requests with high criticality and improves the performance of GPU indirectly. PMID:25729772
Time Constraints and Resource Sharing in Adults' Working Memory Spans
ERIC Educational Resources Information Center
Barrouillet, Pierre; Bernardin, Sophie; Camos, Valerie
2004-01-01
This article presents a new model that accounts for working memory spans in adults, the time-based resource-sharing model. The model assumes that both components (i.e., processing and maintenance) of the main working memory tasks require attention and that memory traces decay as soon as attention is switched away. Because memory retrievals are…
Wang, Qi; Lee, Dasom; Hou, Yubo
2017-07-01
Internet technology provides a new means of recalling and sharing personal memories in the digital age. What is the mnemonic consequence of posting personal memories online? Theories of transactive memory and autobiographical memory would make contrasting predictions. In the present study, college students completed a daily diary for a week, listing at the end of each day all the events that happened to them on that day. They also reported whether they posted any of the events online. Participants received a surprise memory test after the completion of the diary recording and then another test a week later. At both tests, events posted online were significantly more likely than those not posted online to be recalled. It appears that sharing memories online may provide unique opportunities for rehearsal and meaning-making that facilitate memory retention.
Differential patterns of contextual organization of memory in first-episode psychosis.
Murty, Vishnu P; McKinney, Rachel A; DuBrow, Sarah; Jalbrzikowski, Maria; Haas, Gretchen L; Luna, Beatriz
2018-02-15
Contextual information is used to support and organize episodic memory. Prior research has reliably shown memory deficits in psychosis; however, little research has characterized how this population uses contextual information during memory recall. We employed an approach founded in a computational framework of free recall to quantify how individuals with first episode of psychosis (FEP, N = 97) and controls (CON, N = 55) use temporal and semantic context to organize memory recall. Free recall was characterized using the Hopkins Verbal Learning Test-Revised (HVLT-R). We compared FEP and CON on three measures of free recall: proportion recalled, temporal clustering, and semantic clustering. Measures of temporal/semantic clustering quantified how individuals use contextual information to organize memory recall. We also assessed to what extent these measures relate to antipsychotic use and differentiated between different types of psychosis. We also explored the relationship between these measures and intelligence. In comparison to CON, FEP had reduced recall and less temporal clustering during free recall (p < 0.05, Bonferroni-corrected), and showed a trend towards greater semantic clustering (p = 0.10, Bonferroni-corrected). Within FEP, antipsychotic use and diagnoses did not differentiate between free recall accuracy or contextual organization of memory. IQ was related to free recall accuracy, but not the use of contextual information during recall in either group (p < 0.05, Bonferroni-corrected). These results show that in addition to deficits in memory recall, FEP differed in how they organize memories compared to CON.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sayan Ghosh, Jeff Hammond
OpenSHMEM is a community effort to unifyt and standardize the SHMEM programming model. MPI (Message Passing Interface) is a well-known community standard for parallel programming using distributed memory. The most recen t release of MPI, version 3.0, was designed in part to support programming models like SHMEM.OSHMPI is an implementation of the OpenSHMEM standard using MPI-3 for the Linux operating system. It is the first implementation of SHMEM over MPI one-sided communication and has the potential to be widely adopted due to the portability and widely availability of Linux and MPI-3. OSHMPI has been tested on a variety of systemsmore » and implementations of MPI-3, includingInfiniBand clusters using MVAPICH2 and SGI shared-memory supercomputers using MPICH. Current support is limited to Linux but may be extended to Apple OSX if there is sufficient interest. The code is opensource via https://github.com/jeffhammond/oshmpi« less
Mick, Eran; Stern, Adi; Sorek, Rotem
2013-01-01
The CRISPR (clustered regularly interspaced short palindromic repeats)/Cas (CRISPR-associated) system of bacteria and archaea constitutes a mechanism of acquired adaptive immunity against phages, which is based on genome-encoded markers of previously infecting phage sequences (“spacers”). As a repository of phage sequences, these spacers make the system particularly suitable for elucidating phage-bacteria interactions in metagenomic studies. Recent metagenomic analyses of CRISPRs associated with the human microbiome intriguingly revealed conserved “memory spacers” shared by bacteria in multiple unrelated, geographically separated individuals. Here, we discuss possible avenues for explaining this phenomenon by integrating insights from CRISPR biology and phage-bacteria ecology, with a special focus on the human gut. We further explore the growing body of evidence for the role of CRISPR/Cas in regulating the interplay between bacteria and lysogenic phages, which may be intimately related to the presence of memory spacers and sheds new light on the multifaceted biological and ecological modes of action of CRISPR/Cas. PMID:23439321
Synaptic clustering within dendrites: an emerging theory of memory formation
Kastellakis, George; Cai, Denise J.; Mednick, Sara C.; Silva, Alcino J.; Poirazi, Panayiota
2015-01-01
It is generally accepted that complex memories are stored in distributed representations throughout the brain, however the mechanisms underlying these representations are not understood. Here, we review recent findings regarding the subcellular mechanisms implicated in memory formation, which provide evidence for a dendrite-centered theory of memory. Plasticity-related phenomena which affect synaptic properties, such as synaptic tagging and capture, synaptic clustering, branch strength potentiation and spinogenesis provide the foundation for a model of memory storage that relies heavily on processes operating at the dendrite level. The emerging picture suggests that clusters of functionally related synapses may serve as key computational and memory storage units in the brain. We discuss both experimental evidence and theoretical models that support this hypothesis and explore its advantages for neuronal function. PMID:25576663
Nunes, Ludmila D.; Garcia-Marques, Leonel; Ferreira, Mário B.; Ramos, Tânia
2017-01-01
An extension of the DRM paradigm was used to study the impact of central traits (Asch, 1946) in impression formation. Traits corresponding to the four clusters of the implicit theory of personality—intellectual, positive and negative; and social, positive and negative (Rosenberg et al., 1968)—were used to develop lists containing several traits of one cluster and one central trait prototypical of the opposite cluster. Participants engaging in impression formation relative to participants engaging in memorization not only produced higher levels of false memories corresponding to the same cluster of the list traits but, under response time pressure at retrieval, also produced more false memories of the cluster corresponding to the central trait. We argue that the importance of central traits stems from their ability to activate their corresponding semantic space within a specialized associative memory structure underlying the implicit theory of personality. PMID:28878708
Shared versus distributed memory multiprocessors
NASA Technical Reports Server (NTRS)
Jordan, Harry F.
1991-01-01
The question of whether multiprocessors should have shared or distributed memory has attracted a great deal of attention. Some researchers argue strongly for building distributed memory machines, while others argue just as strongly for programming shared memory multiprocessors. A great deal of research is underway on both types of parallel systems. Special emphasis is placed on systems with a very large number of processors for computation intensive tasks and considers research and implementation trends. It appears that the two types of systems will likely converge to a common form for large scale multiprocessors.
ERIC Educational Resources Information Center
Vergauwe, Evie; Barrouillet, Pierre; Camos, Valerie
2009-01-01
Examinations of interference between visual and spatial materials in working memory have suggested domain- and process-based fractionations of visuo-spatial working memory. The present study examined the role of central time-based resource sharing in visuo-spatial working memory and assessed its role in obtained interference patterns. Visual and…
Long, Nicole M.; Kahana, Michael J.
2016-01-01
Although episodic and semantic memory share overlapping neural mechanisms, it remains unclear how our pre-existing semantic associations modulate the formation of new, episodic associations. When freely recalling recently studied words, people rely on both episodic and semantic associations, shown through temporal and semantic clustering of responses. We asked whether orienting participants toward semantic associations interferes with or facilitates the formation of episodic associations. We compared electroencephalographic (EEG) activity recorded during the encoding of subsequently recalled words that were either temporally or semantically clustered. Participants studied words with or without a concurrent semantic orienting task. We identified a neural signature of successful episodic association formation whereby high frequency EEG activity (HFA, 44 – 100 Hz) overlying left prefrontal regions increased for subsequently temporally clustered words, but only for those words studied without a concurrent semantic orienting task. To confirm that this disruption in the formation of episodic associations was driven by increased semantic processing, we measured the neural correlates of subsequent semantic clustering. We found that HFA increased for subsequently semantically clustered words only for lists with a concurrent semantic orienting task. This dissociation suggests that increased semantic processing of studied items interferes with the neural processes that support the formation of novel episodic associations. PMID:27617775
Long, Nicole M; Kahana, Michael J
2017-02-01
Although episodic and semantic memory share overlapping neural mechanisms, it remains unclear how our pre-existing semantic associations modulate the formation of new, episodic associations. When freely recalling recently studied words, people rely on both episodic and semantic associations, shown through temporal and semantic clustering of responses. We asked whether orienting participants toward semantic associations interferes with or facilitates the formation of episodic associations. We compared electroencephalographic (EEG) activity recorded during the encoding of subsequently recalled words that were either temporally or semantically clustered. Participants studied words with or without a concurrent semantic orienting task. We identified a neural signature of successful episodic association formation whereby high-frequency EEG activity (HFA, 44-100 Hz) overlying left prefrontal regions increased for subsequently temporally clustered words, but only for those words studied without a concurrent semantic orienting task. To confirm that this disruption in the formation of episodic associations was driven by increased semantic processing, we measured the neural correlates of subsequent semantic clustering. We found that HFA increased for subsequently semantically clustered words only for lists with a concurrent semantic orienting task. This dissociation suggests that increased semantic processing of studied items interferes with the neural processes that support the formation of novel episodic associations. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
NASA Technical Reports Server (NTRS)
Harper, Richard E.; Butler, Bryan P.
1990-01-01
The Draper fault-tolerant processor with fault-tolerant shared memory (FTP/FTSM), which is designed to allow application tasks to continue execution during the memory alignment process, is described. Processor performance is not affected by memory alignment. In addition, the FTP/FTSM incorporates a hardware scrubber device to perform the memory alignment quickly during unused memory access cycles. The FTP/FTSM architecture is described, followed by an estimate of the time required for channel reintegration.
Wang, Qi
2006-01-01
The relations of maternal reminiscing style and child self-concept to children's shared and independent autobiographical memories were examined in a sample of 189 three-year-olds and their mothers from Chinese families in China, first-generation Chinese immigrant families in the United States, and European American families. Mothers shared memories with their children and completed questionnaires; children recounted autobiographical events and described themselves with a researcher. Independent of culture, gender, child age, and language skills, maternal elaborations and evaluations were associated with children's shared memory reports, and maternal evaluations and child agentic self-focus were associated with children's independent memory reports. Maternal style and child self-concept further mediated cultural influences on children's memory. The findings provide insight into the social-cultural construction of autobiographical memory.
A reassessment of IgM memory subsets in humans
Bagnara, Davide; Squillario, Margherita; Kipling, David; Mora, Thierry; Walczak, Aleksandra M.; Da Silva, Lucie; Weller, Sandra; Dunn-Walters, Deborah K.; Weill, Jean-Claude; Reynaud, Claude-Agnès
2015-01-01
From paired blood and spleen samples from three adult donors we performed high-throughput V-h sequencing of human B-cell subsets defined by IgD and CD27 expression: IgD+CD27+ (“MZ”), IgD−CD27+(“memory”, including IgM (“IgM-only”), IgG and IgA) and IgD−CD27− cells (“double-negative”, including IgM, IgG and IgA). 91,294 unique sequences clustered in 42,670 clones, revealing major clonal expansions in each of these subsets. Among these clones, we further analyzed those shared sequences from different subsets or tissues for Vh-gene mutation, H-CDR3-length, and Vh/Jh usage, comparing these different characteristics with all sequences from their subset of origin, for which these parameters constitute a distinct signature. The IgM-only repertoire profile differed notably from that of MZ B cells by a higher mutation frequency, and lower Vh4 and higher Jh6 gene usage. Strikingly, IgM sequences from clones shared between the MZ and the memory IgG/IgA compartments showed a mutation and repertoire profile of IgM-only and not of MZ B cells. Similarly, all IgM clonal relationships (between MZ, IgM-only, and double-negative compartments) involved sequences with the characteristics of IgM-only B cells. Finally, clonal relationships between tissues suggested distinct recirculation characteristics between MZ and switched B cells. The “IgM-only” subset (including cells with its repertoire signature but higher IgD or lower CD27 expression levels) thus appear as the only subset showing precursor-product relationships with CD27+ switched memory B cells, indicating that they represent germinal center-derived IgM memory B cells, and that IgM memory and MZ B cells constitute two distinct entities. PMID:26355154
Optimal colour quality of LED clusters based on memory colours.
Smet, Kevin; Ryckaert, Wouter R; Pointer, Michael R; Deconinck, Geert; Hanselaer, Peter
2011-03-28
The spectral power distributions of tri- and tetrachromatic clusters of Light-Emitting-Diodes, composed of simulated and commercially available LEDs, were optimized with a genetic algorithm to maximize the luminous efficacy of radiation and the colour quality as assessed by the memory colour quality metric developed by the authors. The trade-off of the colour quality as assessed by the memory colour metric and the luminous efficacy of radiation was investigated by calculating the Pareto optimal front using the NSGA-II genetic algorithm. Optimal peak wavelengths and spectral widths of the LEDs were derived, and over half of them were found to be close to Thornton's prime colours. The Pareto optimal fronts of real LED clusters were always found to be smaller than those of the simulated clusters. The effect of binning on designing a real LED cluster was investigated and was found to be quite large. Finally, a real LED cluster of commercially available AlGaInP, InGaN and phosphor white LEDs was optimized to obtain a higher score on memory colour quality scale than its corresponding CIE reference illuminant.
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.
Performance Evaluation of Remote Memory Access (RMA) Programming on Shared Memory Parallel Computers
NASA Technical Reports Server (NTRS)
Jin, Hao-Qiang; Jost, Gabriele; Biegel, Bryan A. (Technical Monitor)
2002-01-01
The purpose of this study is to evaluate the feasibility of remote memory access (RMA) programming on shared memory parallel computers. We discuss different RMA based implementations of selected CFD application benchmark kernels and compare them to corresponding message passing based codes. For the message-passing implementation we use MPI point-to-point and global communication routines. For the RMA based approach we consider two different libraries supporting this programming model. One is a shared memory parallelization library (SMPlib) developed at NASA Ames, the other is the MPI-2 extensions to the MPI Standard. We give timing comparisons for the different implementation strategies and discuss the performance.
SAHAYOG: A Testbed for Load Sharing under Failure,
1987-07-01
messages, shared memory and semaphores . To communicate using messages, processes create message queues using system-provided prim- itives. The message...The size of the memory that is to be shared is decided by the process when it makes a request for memory allocation. The semaphore option of IPC can be...used to prevent two or more concurrent processes from executing their critical sections at the same time. Semaphores must be used when the processes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Buntinas, D.; Mercier, G.; Gropp, W.
2007-09-01
This paper presents the implementation of MPICH2 over the Nemesis communication subsystem and the evaluation of its shared-memory performance. We describe design issues as well as some of the optimization techniques we employed. We conducted a performance evaluation over shared memory using microbenchmarks. The evaluation shows that MPICH2 Nemesis has very low communication overhead, making it suitable for smaller-grained applications.
Comparison of two paradigms for distributed shared memory
DOE Office of Scientific and Technical Information (OSTI.GOV)
Levelt, W.G.; Kaashoek, M.F.; Bal, H.E.
1990-08-01
The paper compares two paradigms for Distributed Shared Memory on loosely coupled computing systems: the shared data-object model as used in Orca, a programming language specially designed for loosely coupled computing systems and the Shared Virtual Memory model. For both paradigms the authors have implemented two systems, one using only point-to-point messages, the other using broadcasting as well. They briefly describe these two paradigms and their implementations. Then they compare their performance on four applications: the traveling salesman problem, alpha-beta search, matrix multiplication and the all pairs shortest paths problem. The measurements show that both paradigms can be used efficientlymore » for programming large-grain parallel applications. Significant speedups were obtained on all applications. The unstructured Shared Virtual Memory paradigm achieves the best absolute performance, although this is largely due to the preliminary nature of the Orca compiler used. The structured shared data-object model achieves the highest speedups and is much easier to program and to debug.« less
A compositional reservoir simulator on distributed memory parallel computers
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rame, M.; Delshad, M.
1995-12-31
This paper presents the application of distributed memory parallel computes to field scale reservoir simulations using a parallel version of UTCHEM, The University of Texas Chemical Flooding Simulator. The model is a general purpose highly vectorized chemical compositional simulator that can simulate a wide range of displacement processes at both field and laboratory scales. The original simulator was modified to run on both distributed memory parallel machines (Intel iPSC/960 and Delta, Connection Machine 5, Kendall Square 1 and 2, and CRAY T3D) and a cluster of workstations. A domain decomposition approach has been taken towards parallelization of the code. Amore » portion of the discrete reservoir model is assigned to each processor by a set-up routine that attempts a data layout as even as possible from the load-balance standpoint. Each of these subdomains is extended so that data can be shared between adjacent processors for stencil computation. The added routines that make parallel execution possible are written in a modular fashion that makes the porting to new parallel platforms straight forward. Results of the distributed memory computing performance of Parallel simulator are presented for field scale applications such as tracer flood and polymer flood. A comparison of the wall-clock times for same problems on a vector supercomputer is also presented.« less
Working memory resources are shared across sensory modalities.
Salmela, V R; Moisala, M; Alho, K
2014-10-01
A common assumption in the working memory literature is that the visual and auditory modalities have separate and independent memory stores. Recent evidence on visual working memory has suggested that resources are shared between representations, and that the precision of representations sets the limit for memory performance. We tested whether memory resources are also shared across sensory modalities. Memory precision for two visual (spatial frequency and orientation) and two auditory (pitch and tone duration) features was measured separately for each feature and for all possible feature combinations. Thus, only the memory load was varied, from one to four features, while keeping the stimuli similar. In Experiment 1, two gratings and two tones-both containing two varying features-were presented simultaneously. In Experiment 2, two gratings and two tones-each containing only one varying feature-were presented sequentially. The memory precision (delayed discrimination threshold) for a single feature was close to the perceptual threshold. However, as the number of features to be remembered was increased, the discrimination thresholds increased more than twofold. Importantly, the decrease in memory precision did not depend on the modality of the other feature(s), or on whether the features were in the same or in separate objects. Hence, simultaneously storing one visual and one auditory feature had an effect on memory precision equal to those of simultaneously storing two visual or two auditory features. The results show that working memory is limited by the precision of the stored representations, and that working memory can be described as a resource pool that is shared across modalities.
Endohedral gallide cluster superconductors and superconductivity in ReGa5.
Xie, Weiwei; Luo, Huixia; Phelan, Brendan F; Klimczuk, Tomasz; Cevallos, Francois Alexandre; Cava, Robert Joseph
2015-12-22
We present transition metal-embedded (T@Gan) endohedral Ga-clusters as a favorable structural motif for superconductivity and develop empirical, molecule-based, electron counting rules that govern the hierarchical architectures that the clusters assume in binary phases. Among the binary T@Gan endohedral cluster systems, Mo8Ga41, Mo6Ga31, Rh2Ga9, and Ir2Ga9 are all previously known superconductors. The well-known exotic superconductor PuCoGa5 and related phases are also members of this endohedral gallide cluster family. We show that electron-deficient compounds like Mo8Ga41 prefer architectures with vertex-sharing gallium clusters, whereas electron-rich compounds, like PdGa5, prefer edge-sharing cluster architectures. The superconducting transition temperatures are highest for the electron-poor, corner-sharing architectures. Based on this analysis, the previously unknown endohedral cluster compound ReGa5 is postulated to exist at an intermediate electron count and a mix of corner sharing and edge sharing cluster architectures. The empirical prediction is shown to be correct and leads to the discovery of superconductivity in ReGa5. The Fermi levels for endohedral gallide cluster compounds are located in deep pseudogaps in the electronic densities of states, an important factor in determining their chemical stability, while at the same time limiting their superconducting transition temperatures.
NASA Technical Reports Server (NTRS)
Waheed, Abdul; Yan, Jerry
1998-01-01
This paper presents a model to evaluate the performance and overhead of parallelizing sequential code using compiler directives for multiprocessing on distributed shared memory (DSM) systems. With increasing popularity of shared address space architectures, it is essential to understand their performance impact on programs that benefit from shared memory multiprocessing. We present a simple model to characterize the performance of programs that are parallelized using compiler directives for shared memory multiprocessing. We parallelized the sequential implementation of NAS benchmarks using native Fortran77 compiler directives for an Origin2000, which is a DSM system based on a cache-coherent Non Uniform Memory Access (ccNUMA) architecture. We report measurement based performance of these parallelized benchmarks from four perspectives: efficacy of parallelization process; scalability; parallelization overhead; and comparison with hand-parallelized and -optimized version of the same benchmarks. Our results indicate that sequential programs can conveniently be parallelized for DSM systems using compiler directives but realizing performance gains as predicted by the performance model depends primarily on minimizing architecture-specific data locality overhead.
Distributed simulation using a real-time shared memory network
NASA Technical Reports Server (NTRS)
Simon, Donald L.; Mattern, Duane L.; Wong, Edmond; Musgrave, Jeffrey L.
1993-01-01
The Advanced Control Technology Branch of the NASA Lewis Research Center performs research in the area of advanced digital controls for aeronautic and space propulsion systems. This work requires the real-time implementation of both control software and complex dynamical models of the propulsion system. We are implementing these systems in a distributed, multi-vendor computer environment. Therefore, a need exists for real-time communication and synchronization between the distributed multi-vendor computers. A shared memory network is a potential solution which offers several advantages over other real-time communication approaches. A candidate shared memory network was tested for basic performance. The shared memory network was then used to implement a distributed simulation of a ramjet engine. The accuracy and execution time of the distributed simulation was measured and compared to the performance of the non-partitioned simulation. The ease of partitioning the simulation, the minimal time required to develop for communication between the processors and the resulting execution time all indicate that the shared memory network is a real-time communication technique worthy of serious consideration.
Multiprocessor shared-memory information exchange
DOE Office of Scientific and Technical Information (OSTI.GOV)
Santoline, L.L.; Bowers, M.D.; Crew, A.W.
1989-02-01
In distributed microprocessor-based instrumentation and control systems, the inter-and intra-subsystem communication requirements ultimately form the basis for the overall system architecture. This paper describes a software protocol which addresses the intra-subsystem communications problem. Specifically the protocol allows for multiple processors to exchange information via a shared-memory interface. The authors primary goal is to provide a reliable means for information to be exchanged between central application processor boards (masters) and dedicated function processor boards (slaves) in a single computer chassis. The resultant Multiprocessor Shared-Memory Information Exchange (MSMIE) protocol, a standard master-slave shared-memory interface suitable for use in nuclear safety systems, ismore » designed to pass unidirectional buffers of information between the processors while providing a minimum, deterministic cycle time for this data exchange.« less
Memory access in shared virtual memory
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berrendorf, R.
1992-01-01
Shared virtual memory (SVM) is a virtual memory layer with a single address space on top of a distributed real memory on parallel computers. We examine the behavior and performance of SVM running a parallel program with medium-grained, loop-level parallelism on top of it. A simulator for the underlying parallel architecture can be used to examine the behavior of SVM more deeply. The influence of several parameters, such as the number of processors, page size, cold or warm start, and restricted page replication, is studied.
Memory access in shared virtual memory
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berrendorf, R.
1992-09-01
Shared virtual memory (SVM) is a virtual memory layer with a single address space on top of a distributed real memory on parallel computers. We examine the behavior and performance of SVM running a parallel program with medium-grained, loop-level parallelism on top of it. A simulator for the underlying parallel architecture can be used to examine the behavior of SVM more deeply. The influence of several parameters, such as the number of processors, page size, cold or warm start, and restricted page replication, is studied.
Study of parameters of the nearest neighbour shared algorithm on clustering documents
NASA Astrophysics Data System (ADS)
Mustika Rukmi, Alvida; Budi Utomo, Daryono; Imro’atus Sholikhah, Neni
2018-03-01
Document clustering is one way of automatically managing documents, extracting of document topics and fastly filtering information. Preprocess of clustering documents processed by textmining consists of: keyword extraction using Rapid Automatic Keyphrase Extraction (RAKE) and making the document as concept vector using Latent Semantic Analysis (LSA). Furthermore, the clustering process is done so that the documents with the similarity of the topic are in the same cluster, based on the preprocesing by textmining performed. Shared Nearest Neighbour (SNN) algorithm is a clustering method based on the number of "nearest neighbors" shared. The parameters in the SNN Algorithm consist of: k nearest neighbor documents, ɛ shared nearest neighbor documents and MinT minimum number of similar documents, which can form a cluster. Characteristics The SNN algorithm is based on shared ‘neighbor’ properties. Each cluster is formed by keywords that are shared by the documents. SNN algorithm allows a cluster can be built more than one keyword, if the value of the frequency of appearing keywords in document is also high. Determination of parameter values on SNN algorithm affects document clustering results. The higher parameter value k, will increase the number of neighbor documents from each document, cause similarity of neighboring documents are lower. The accuracy of each cluster is also low. The higher parameter value ε, caused each document catch only neighbor documents that have a high similarity to build a cluster. It also causes more unclassified documents (noise). The higher the MinT parameter value cause the number of clusters will decrease, since the number of similar documents can not form clusters if less than MinT. Parameter in the SNN Algorithm determine performance of clustering result and the amount of noise (unclustered documents ). The Silhouette coeffisient shows almost the same result in many experiments, above 0.9, which means that SNN algorithm works well with different parameter values.
Working Memory Span Development: A Time-Based Resource-Sharing Model Account
ERIC Educational Resources Information Center
Barrouillet, Pierre; Gavens, Nathalie; Vergauwe, Evie; Gaillard, Vinciane; Camos, Valerie
2009-01-01
The time-based resource-sharing model (P. Barrouillet, S. Bernardin, & V. Camos, 2004) assumes that during complex working memory span tasks, attention is frequently and surreptitiously switched from processing to reactivate decaying memory traces before their complete loss. Three experiments involving children from 5 to 14 years of age…
Direct access inter-process shared memory
Brightwell, Ronald B; Pedretti, Kevin; Hudson, Trammell B
2013-10-22
A technique for directly sharing physical memory between processes executing on processor cores is described. The technique includes loading a plurality of processes into the physical memory for execution on a corresponding plurality of processor cores sharing the physical memory. An address space is mapped to each of the processes by populating a first entry in a top level virtual address table for each of the processes. The address space of each of the processes is cross-mapped into each of the processes by populating one or more subsequent entries of the top level virtual address table with the first entry in the top level virtual address table from other processes.
Memory Network For Distributed Data Processors
NASA Technical Reports Server (NTRS)
Bolen, David; Jensen, Dean; Millard, ED; Robinson, Dave; Scanlon, George
1992-01-01
Universal Memory Network (UMN) is modular, digital data-communication system enabling computers with differing bus architectures to share 32-bit-wide data between locations up to 3 km apart with less than one millisecond of latency. Makes it possible to design sophisticated real-time and near-real-time data-processing systems without data-transfer "bottlenecks". This enterprise network permits transmission of volume of data equivalent to an encyclopedia each second. Facilities benefiting from Universal Memory Network include telemetry stations, simulation facilities, power-plants, and large laboratories or any facility sharing very large volumes of data. Main hub of UMN is reflection center including smaller hubs called Shared Memory Interfaces.
Grouping and binding in visual short-term memory.
Quinlan, Philip T; Cohen, Dale J
2012-09-01
Findings of 2 experiments are reported that challenge the current understanding of visual short-term memory (VSTM). In both experiments, a single study display, containing 6 colored shapes, was presented briefly and then probed with a single colored shape. At stake is how VSTM retains a record of different objects that share common features: In the 1st experiment, 2 study items sometimes shared a common feature (either a shape or a color). The data revealed a color sharing effect, in which memory was much better for items that shared a common color than for items that did not. The 2nd experiment showed that the size of the color sharing effect depended on whether a single pair of items shared a common color or whether 2 pairs of items were so defined-memory for all items improved when 2 color groups were presented. In explaining performance, an account is advanced in which items compete for a fixed number of slots, but then memory recall for any given stored item is prone to error. A critical assumption is that items that share a common color are stored together in a slot as a chunk. The evidence provides further support for the idea that principles of perceptual organization may determine the manner in which items are stored in VSTM. PsycINFO Database Record (c) 2012 APA, all rights reserved.
Community detection using Kernel Spectral Clustering with memory
NASA Astrophysics Data System (ADS)
Langone, Rocco; Suykens, Johan A. K.
2013-02-01
This work is related to the problem of community detection in dynamic scenarios, which for instance arises in the segmentation of moving objects, clustering of telephone traffic data, time-series micro-array data etc. A desirable feature of a clustering model which has to capture the evolution of communities over time is the temporal smoothness between clusters in successive time-steps. In this way the model is able to track the long-term trend and in the same time it smooths out short-term variation due to noise. We use the Kernel Spectral Clustering with Memory effect (MKSC) which allows to predict cluster memberships of new nodes via out-of-sample extension and has a proper model selection scheme. It is based on a constrained optimization formulation typical of Least Squares Support Vector Machines (LS-SVM), where the objective function is designed to explicitly incorporate temporal smoothness as a valid prior knowledge. The latter, in fact, allows the model to cluster the current data well and to be consistent with the recent history. Here we propose a generalization of the MKSC model with an arbitrary memory, not only one time-step in the past. The experiments conducted on toy problems confirm our expectations: the more memory we add to the model, the smoother over time are the clustering results. We also compare with the Evolutionary Spectral Clustering (ESC) algorithm which is a state-of-the art method, and we obtain comparable or better results.
Endohedral gallide cluster superconductors and superconductivity in ReGa5
Xie, Weiwei; Luo, Huixia; Phelan, Brendan F.; Klimczuk, Tomasz; Cevallos, Francois Alexandre; Cava, Robert Joseph
2015-01-01
We present transition metal-embedded (T@Gan) endohedral Ga-clusters as a favorable structural motif for superconductivity and develop empirical, molecule-based, electron counting rules that govern the hierarchical architectures that the clusters assume in binary phases. Among the binary T@Gan endohedral cluster systems, Mo8Ga41, Mo6Ga31, Rh2Ga9, and Ir2Ga9 are all previously known superconductors. The well-known exotic superconductor PuCoGa5 and related phases are also members of this endohedral gallide cluster family. We show that electron-deficient compounds like Mo8Ga41 prefer architectures with vertex-sharing gallium clusters, whereas electron-rich compounds, like PdGa5, prefer edge-sharing cluster architectures. The superconducting transition temperatures are highest for the electron-poor, corner-sharing architectures. Based on this analysis, the previously unknown endohedral cluster compound ReGa5 is postulated to exist at an intermediate electron count and a mix of corner sharing and edge sharing cluster architectures. The empirical prediction is shown to be correct and leads to the discovery of superconductivity in ReGa5. The Fermi levels for endohedral gallide cluster compounds are located in deep pseudogaps in the electronic densities of states, an important factor in determining their chemical stability, while at the same time limiting their superconducting transition temperatures. PMID:26644566
Shared memories reveal shared structure in neural activity across individuals
Chen, J.; Leong, Y.C.; Honey, C.J.; Yong, C.H.; Norman, K.A.; Hasson, U.
2016-01-01
Our lives revolve around sharing experiences and memories with others. When different people recount the same events, how similar are their underlying neural representations? Participants viewed a fifty-minute movie, then verbally described the events during functional MRI, producing unguided detailed descriptions lasting up to forty minutes. As each person spoke, event-specific spatial patterns were reinstated in default-network, medial-temporal, and high-level visual areas. Individual event patterns were both highly discriminable from one another and similar between people, suggesting consistent spatial organization. In many high-order areas, patterns were more similar between people recalling the same event than between recall and perception, indicating systematic reshaping of percept into memory. These results reveal the existence of a common spatial organization for memories in high-level cortical areas, where encoded information is largely abstracted beyond sensory constraints; and that neural patterns during perception are altered systematically across people into shared memory representations for real-life events. PMID:27918531
Combining Distributed and Shared Memory Models: Approach and Evolution of the Global Arrays Toolkit
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nieplocha, Jarek; Harrison, Robert J.; Kumar, Mukul
2002-07-29
Both shared memory and distributed memory models have advantages and shortcomings. Shared memory model is much easier to use but it ignores data locality/placement. Given the hierarchical nature of the memory subsystems in the modern computers this characteristic might have a negative impact on performance and scalability. Various techniques, such as code restructuring to increase data reuse and introducing blocking in data accesses, can address the problem and yield performance competitive with message passing[Singh], however at the cost of compromising the ease of use feature. Distributed memory models such as message passing or one-sided communication offer performance and scalability butmore » they compromise the ease-of-use. In this context, the message-passing model is sometimes referred to as?assembly programming for the scientific computing?. The Global Arrays toolkit[GA1, GA2] attempts to offer the best features of both models. It implements a shared-memory programming model in which data locality is managed explicitly by the programmer. This management is achieved by explicit calls to functions that transfer data between a global address space (a distributed array) and local storage. In this respect, the GA model has similarities to the distributed shared-memory models that provide an explicit acquire/release protocol. However, the GA model acknowledges that remote data is slower to access than local data and allows data locality to be explicitly specified and hence managed. The GA model exposes to the programmer the hierarchical memory of modern high-performance computer systems, and by recognizing the communication overhead for remote data transfer, it promotes data reuse and locality of reference. This paper describes the characteristics of the Global Arrays programming model, capabilities of the toolkit, and discusses its evolution.« 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.
Choi, Hae-Yoon; Kensinger, Elizabeth A; Rajaram, Suparna
2017-09-01
Social transmission of memory and its consequence on collective memory have generated enduring interdisciplinary interest because of their widespread significance in interpersonal, sociocultural, and political arenas. We tested the influence of 3 key factors-emotional salience of information, group structure, and information distribution-on mnemonic transmission, social contagion, and collective memory. Participants individually studied emotionally salient (negative or positive) and nonemotional (neutral) picture-word pairs that were completely shared, partially shared, or unshared within participant triads, and then completed 3 consecutive recalls in 1 of 3 conditions: individual-individual-individual (control), collaborative-collaborative (identical group; insular structure)-individual, and collaborative-collaborative (reconfigured group; diverse structure)-individual. Collaboration enhanced negative memories especially in insular group structure and especially for shared information, and promoted collective forgetting of positive memories. Diverse group structure reduced this negativity effect. Unequally distributed information led to social contagion that creates false memories; diverse structure propagated a greater variety of false memories whereas insular structure promoted confidence in false recognition and false collective memory. A simultaneous assessment of network structure, information distribution, and emotional valence breaks new ground to specify how network structure shapes the spread of negative memories and false memories, and the emergence of collective memory. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
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.
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.
MPgrafic: A parallel MPI version of Grafic-1
NASA Astrophysics Data System (ADS)
Prunet, Simon; Pichon, Christophe
2013-04-01
MPgrafic is a parallel MPI version of Grafic-1 which can produce large cosmological initial conditions on a cluster without requiring shared memory. The real Fourier transforms are carried in place using fftw while minimizing the amount of used memory (at the expense of performance) in the spirit of Grafic-1. The writing of the output file is also carried in parallel. In addition to the technical parallelization, it provides three extensions over Grafic-1: it can produce power spectra with baryon wiggles (DJ Eisenstein and W. Hu, Ap. J. 496);it has the optional ability to load a lower resolution noise map corresponding to the low frequency component which will fix the larger scale modes of the simulation (extra flag 0/1 at the end of the input process) in the spirit of Grafic-2;it can be used in conjunction with constrfield, which generates initial conditions phases from a list of local constraints on density, tidal field density gradient and velocity.
Hybrid-optimization strategy for the communication of large-scale Kinetic Monte Carlo simulation
NASA Astrophysics Data System (ADS)
Wu, Baodong; Li, Shigang; Zhang, Yunquan; Nie, Ningming
2017-02-01
The parallel Kinetic Monte Carlo (KMC) algorithm based on domain decomposition has been widely used in large-scale physical simulations. However, the communication overhead of the parallel KMC algorithm is critical, and severely degrades the overall performance and scalability. In this paper, we present a hybrid optimization strategy to reduce the communication overhead for the parallel KMC simulations. We first propose a communication aggregation algorithm to reduce the total number of messages and eliminate the communication redundancy. Then, we utilize the shared memory to reduce the memory copy overhead of the intra-node communication. Finally, we optimize the communication scheduling using the neighborhood collective operations. We demonstrate the scalability and high performance of our hybrid optimization strategy by both theoretical and experimental analysis. Results show that the optimized KMC algorithm exhibits better performance and scalability than the well-known open-source library-SPPARKS. On 32-node Xeon E5-2680 cluster (total 640 cores), the optimized algorithm reduces the communication time by 24.8% compared with SPPARKS.
Staffaroni, Adam M; Melrose, Rebecca J; Leskin, Lorraine P; Riskin-Jones, Hannah; Harwood, Dylan; Mandelkern, Mark; Sultzer, David L
2017-09-01
The objective of this study was to distinguish the functional neuroanatomy of verbal learning and recognition in Alzheimer's disease (AD) using the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) Word Learning task. In 81 Veterans diagnosed with dementia due to AD, we conducted a cluster-based correlation analysis to assess the relationships between recency and recognition memory scores from the CERAD Word Learning Task and cortical metabolic activity measured using [ 18 F]-fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET). AD patients (Mini-Mental State Examination, MMSE mean = 20.2) performed significantly better on the recall of recency items during learning trials than of primacy and middle items. Recency memory was associated with cerebral metabolism in the left middle and inferior temporal gyri and left fusiform gyrus (p < .05 at the corrected cluster level). In contrast, recognition memory was correlated with metabolic activity in two clusters: (a) a large cluster that included the left hippocampus, parahippocampal gyrus, entorhinal cortex, anterior temporal lobe, and inferior and middle temporal gyri; (b) the bilateral orbitofrontal cortices (OFC). The present study further informs our understanding of the disparate functional neuroanatomy of recency memory and recognition memory in AD. We anticipated that the recency effect would be relatively preserved and associated with temporoparietal brain regions implicated in short-term verbal memory, while recognition memory would be associated with the medial temporal lobe and possibly the OFC. Consistent with our a priori hypotheses, list learning in our AD sample was characterized by a reduced primacy effect and a relatively spared recency effect; however, recency memory was associated with cerebral metabolism in inferior and lateral temporal regions associated with the semantic memory network, rather than regions associated with short-term verbal memory. The correlates of recognition memory included the medial temporal lobe and OFC, replicating prior studies.
Schapiro, Anna C; McDevitt, Elizabeth A; Chen, Lang; Norman, Kenneth A; Mednick, Sara C; Rogers, Timothy T
2017-11-01
Semantic memory encompasses knowledge about both the properties that typify concepts (e.g. robins, like all birds, have wings) as well as the properties that individuate conceptually related items (e.g. robins, in particular, have red breasts). We investigate the impact of sleep on new semantic learning using a property inference task in which both kinds of information are initially acquired equally well. Participants learned about three categories of novel objects possessing some properties that were shared among category exemplars and others that were unique to an exemplar, with exposure frequency varying across categories. In Experiment 1, memory for shared properties improved and memory for unique properties was preserved across a night of sleep, while memory for both feature types declined over a day awake. In Experiment 2, memory for shared properties improved across a nap, but only for the lower-frequency category, suggesting a prioritization of weakly learned information early in a sleep period. The increase was significantly correlated with amount of REM, but was also observed in participants who did not enter REM, suggesting involvement of both REM and NREM sleep. The results provide the first evidence that sleep improves memory for the shared structure of object categories, while simultaneously preserving object-unique information.
Parallelization of a Monte Carlo particle transport simulation code
NASA Astrophysics Data System (ADS)
Hadjidoukas, P.; Bousis, C.; Emfietzoglou, D.
2010-05-01
We have developed a high performance version of the Monte Carlo particle transport simulation code MC4. The original application code, developed in Visual Basic for Applications (VBA) for Microsoft Excel, was first rewritten in the C programming language for improving code portability. Several pseudo-random number generators have been also integrated and studied. The new MC4 version was then parallelized for shared and distributed-memory multiprocessor systems using the Message Passing Interface. Two parallel pseudo-random number generator libraries (SPRNG and DCMT) have been seamlessly integrated. The performance speedup of parallel MC4 has been studied on a variety of parallel computing architectures including an Intel Xeon server with 4 dual-core processors, a Sun cluster consisting of 16 nodes of 2 dual-core AMD Opteron processors and a 200 dual-processor HP cluster. For large problem size, which is limited only by the physical memory of the multiprocessor server, the speedup results are almost linear on all systems. We have validated the parallel implementation against the serial VBA and C implementations using the same random number generator. Our experimental results on the transport and energy loss of electrons in a water medium show that the serial and parallel codes are equivalent in accuracy. The present improvements allow for studying of higher particle energies with the use of more accurate physical models, and improve statistics as more particles tracks can be simulated in low response time.
Automatic Generation of Directive-Based Parallel Programs for Shared Memory Parallel Systems
NASA Technical Reports Server (NTRS)
Jin, Hao-Qiang; Yan, Jerry; Frumkin, Michael
2000-01-01
The shared-memory programming model is a very effective way to achieve parallelism on shared memory parallel computers. As great progress was made in hardware and software technologies, performance of parallel programs with compiler directives has demonstrated large improvement. The introduction of OpenMP directives, the industrial standard for shared-memory programming, has minimized the issue of portability. Due to its ease of programming and its good performance, the technique has become very popular. In this study, we have extended CAPTools, a computer-aided parallelization toolkit, to automatically generate directive-based, OpenMP, parallel programs. We outline techniques used in the implementation of the tool and present test results on the NAS parallel benchmarks and ARC3D, a CFD application. This work demonstrates the great potential of using computer-aided tools to quickly port parallel programs and also achieve good performance.
GPU computing with Kaczmarz’s and other iterative algorithms for linear systems
Elble, Joseph M.; Sahinidis, Nikolaos V.; Vouzis, Panagiotis
2009-01-01
The graphics processing unit (GPU) is used to solve large linear systems derived from partial differential equations. The differential equations studied are strongly convection-dominated, of various sizes, and common to many fields, including computational fluid dynamics, heat transfer, and structural mechanics. The paper presents comparisons between GPU and CPU implementations of several well-known iterative methods, including Kaczmarz’s, Cimmino’s, component averaging, conjugate gradient normal residual (CGNR), symmetric successive overrelaxation-preconditioned conjugate gradient, and conjugate-gradient-accelerated component-averaged row projections (CARP-CG). Computations are preformed with dense as well as general banded systems. The results demonstrate that our GPU implementation outperforms CPU implementations of these algorithms, as well as previously studied parallel implementations on Linux clusters and shared memory systems. While the CGNR method had begun to fall out of favor for solving such problems, for the problems studied in this paper, the CGNR method implemented on the GPU performed better than the other methods, including a cluster implementation of the CARP-CG method. PMID:20526446
NASA Astrophysics Data System (ADS)
Gleason, J. L.; Hillyer, T. N.; Wilkins, J.
2012-12-01
The CERES Science Team integrates data from 5 CERES instruments onboard the Terra, Aqua and NPP missions. The processing chain fuses CERES observations with data from 19 other unique sources. The addition of CERES Flight Model 5 (FM5) onboard NPP, coupled with ground processing system upgrades further emphasizes the need for an automated job-submission utility to manage multiple processing streams concurrently. The operator-driven, legacy-processing approach relied on manually staging data from magnetic tape to limited spinning disk attached to a shared memory architecture system. The migration of CERES production code to a distributed, cluster computing environment with approximately one petabyte of spinning disk containing all precursor input data products facilitates the development of a CERES-specific, automated workflow manager. In the cluster environment, I/O is the primary system resource in contention across jobs. Therefore, system load can be maximized with a throttling workload manager. This poster discusses a Java and Perl implementation of an automated job management tool tailored for CERES processing.
Sleep enhances a spatially mediated generalization of learned values
Tolat, Anisha; Spiers, Hugo J.
2015-01-01
Sleep is thought to play an important role in memory consolidation. Here we tested whether sleep alters the subjective value associated with objects located in spatial clusters that were navigated to in a large-scale virtual town. We found that sleep enhances a generalization of the value of high-value objects to the value of locally clustered objects, resulting in an impaired memory for the value of high-valued objects. Our results are consistent with (a) spatial context helping to bind items together in long-term memory and serve as a basis for generalizing across memories and (b) sleep mediating memory effects on salient/reward-related items. PMID:26373834
Continuous-variable quantum computing in optical time-frequency modes using quantum memories.
Humphreys, Peter C; Kolthammer, W Steven; Nunn, Joshua; Barbieri, Marco; Datta, Animesh; Walmsley, Ian A
2014-09-26
We develop a scheme for time-frequency encoded continuous-variable cluster-state quantum computing using quantum memories. In particular, we propose a method to produce, manipulate, and measure two-dimensional cluster states in a single spatial mode by exploiting the intrinsic time-frequency selectivity of Raman quantum memories. Time-frequency encoding enables the scheme to be extremely compact, requiring a number of memories that are a linear function of only the number of different frequencies in which the computational state is encoded, independent of its temporal duration. We therefore show that quantum memories can be a powerful component for scalable photonic quantum information processing architectures.
ERIC Educational Resources Information Center
Hayes-Roth, Barbara
Two kinds of memory organization are distinguished: segregrated versus integrated. In segregated memory organizations, related learned propositions have separate memory representations. In integrated memory organizations, memory representations of related propositions share common subrepresentations. Segregated memory organizations facilitate…
Wiese, Holger; Schweinberger, Stefan R
2015-01-01
The present study examined whether semantic memory for newly learned people is structured by visual co-occurrence, shared semantics, or both. Participants were trained with pairs of simultaneously presented (i.e., co-occurring) preexperimentally unfamiliar faces, which either did or did not share additionally provided semantic information (occupation, place of living, etc.). Semantic information could also be shared between faces that did not co-occur. A subsequent priming experiment revealed faster responses for both co-occurrence/no shared semantics and no co-occurrence/shared semantics conditions, than for an unrelated condition. Strikingly, priming was strongest in the co-occurrence/shared semantics condition, suggesting additive effects of these factors. Additional analysis of event-related brain potentials yielded priming in the N400 component only for combined effects of visual co-occurrence and shared semantics, with more positive amplitudes in this than in the unrelated condition. Overall, these findings suggest that both semantic relatedness and visual co-occurrence are important when novel information is integrated into person-related semantic memory.
Unsworth, Nash; Spillers, Gregory J; Brewer, Gene A
2012-01-01
Remembering previous experiences from one's personal past is a principal component of psychological well-being, personality, sense of self, decision making, and planning for the future. In the current study the ability to search for autobiographical information in memory was examined by having college students recall their Facebook friends. Individual differences in working memory capacity manifested itself in the search of autobiographical memory by way of the total number of friends remembered, the number of clusters of friends, size of clusters, and the speed with which participants could output their friends' names. Although working memory capacity was related to the ability to search autobiographical memory, participants did not differ in the manner in which they approached the search and used contextual cues to help query their memories. These results corroborate recent theorising, which suggests that working memory is a necessary component of self-generating contextual cues to strategically search memory for autobiographical information.
Luckey, Chance John; Bhattacharya, Deepta; Goldrath, Ananda W.; Weissman, Irving L.; Benoist, Christophe; Mathis, Diane
2006-01-01
The only cells of the hematopoietic system that undergo self-renewal for the lifetime of the organism are long-term hematopoietic stem cells and memory T and B cells. To determine whether there is a shared transcriptional program among these self-renewing populations, we first compared the gene-expression profiles of naïve, effector and memory CD8+ T cells with those of long-term hematopoietic stem cells, short-term hematopoietic stem cells, and lineage-committed progenitors. Transcripts augmented in memory CD8+ T cells relative to naïve and effector T cells were selectively enriched in long-term hematopoietic stem cells and were progressively lost in their short-term and lineage-committed counterparts. Furthermore, transcripts selectively decreased in memory CD8+ T cells were selectively down-regulated in long-term hematopoietic stem cells and progressively increased with differentiation. To confirm that this pattern was a general property of immunologic memory, we turned to independently generated gene expression profiles of memory, naïve, germinal center, and plasma B cells. Once again, memory-enriched and -depleted transcripts were also appropriately augmented and diminished in long-term hematopoietic stem cells, and their expression correlated with progressive loss of self-renewal function. Thus, there appears to be a common signature of both up- and down-regulated transcripts shared between memory T cells, memory B cells, and long-term hematopoietic stem cells. This signature was not consistently enriched in neural or embryonic stem cell populations and, therefore, appears to be restricted to the hematopoeitic system. These observations provide evidence that the shared phenotype of self-renewal in the hematopoietic system is linked at the molecular level. PMID:16492737
Coane, Jennifer H; McBride, Dawn M; Termonen, Miia-Liisa; Cutting, J Cooper
2016-01-01
The goal of the present study was to examine the contributions of associative strength and similarity in terms of shared features to the production of false memories in the Deese/Roediger-McDermott list-learning paradigm. Whereas the activation/monitoring account suggests that false memories are driven by automatic associative activation from list items to nonpresented lures, combined with errors in source monitoring, other accounts (e.g., fuzzy trace theory, global-matching models) emphasize the importance of semantic-level similarity, and thus predict that shared features between list and lure items will increase false memory. Participants studied lists of nine items related to a nonpresented lure. Half of the lists consisted of items that were associated but did not share features with the lure, and the other half included items that were equally associated but also shared features with the lure (in many cases, these were taxonomically related items). The two types of lists were carefully matched in terms of a variety of lexical and semantic factors, and the same lures were used across list types. In two experiments, false recognition of the critical lures was greater following the study of lists that shared features with the critical lure, suggesting that similarity at a categorical or taxonomic level contributes to false memory above and beyond associative strength. We refer to this phenomenon as a "feature boost" that reflects additive effects of shared meaning and association strength and is generally consistent with accounts of false memory that have emphasized thematic or feature-level similarity among studied and nonstudied representations.
Practical Formal Verification of MPI and Thread Programs
NASA Astrophysics Data System (ADS)
Gopalakrishnan, Ganesh; Kirby, Robert M.
Large-scale simulation codes in science and engineering are written using the Message Passing Interface (MPI). Shared memory threads are widely used directly, or to implement higher level programming abstractions. Traditional debugging methods for MPI or thread programs are incapable of providing useful formal guarantees about coverage. They get bogged down in the sheer number of interleavings (schedules), often missing shallow bugs. In this tutorial we will introduce two practical formal verification tools: ISP (for MPI C programs) and Inspect (for Pthread C programs). Unlike other formal verification tools, ISP and Inspect run directly on user source codes (much like a debugger). They pursue only the relevant set of process interleavings, using our own customized Dynamic Partial Order Reduction algorithms. For a given test harness, DPOR allows these tools to guarantee the absence of deadlocks, instrumented MPI object leaks and communication races (using ISP), and shared memory races (using Inspect). ISP and Inspect have been used to verify large pieces of code: in excess of 10,000 lines of MPI/C for ISP in under 5 seconds, and about 5,000 lines of Pthread/C code in a few hours (and much faster with the use of a cluster or by exploiting special cases such as symmetry) for Inspect. We will also demonstrate the Microsoft Visual Studio and Eclipse Parallel Tools Platform integrations of ISP (these will be available on the LiveCD).
System and method for programmable bank selection for banked memory subsystems
Blumrich, Matthias A.; Chen, Dong; Gara, Alan G.; Giampapa, Mark E.; Hoenicke, Dirk; Ohmacht, Martin; Salapura, Valentina; Sugavanam, Krishnan
2010-09-07
A programmable memory system and method for enabling one or more processor devices access to shared memory in a computing environment, the shared memory including one or more memory storage structures having addressable locations for storing data. The system comprises: one or more first logic devices associated with a respective one or more processor devices, each first logic device for receiving physical memory address signals and programmable for generating a respective memory storage structure select signal upon receipt of pre-determined address bit values at selected physical memory address bit locations; and, a second logic device responsive to each of the respective select signal for generating an address signal used for selecting a memory storage structure for processor access. The system thus enables each processor device of a computing environment memory storage access distributed across the one or more memory storage structures.
High Performance Programming Using Explicit Shared Memory Model on Cray T3D1
NASA Technical Reports Server (NTRS)
Simon, Horst D.; Saini, Subhash; Grassi, Charles
1994-01-01
The Cray T3D system is the first-phase system in Cray Research, Inc.'s (CRI) three-phase massively parallel processing (MPP) program. This system features a heterogeneous architecture that closely couples DEC's Alpha microprocessors and CRI's parallel-vector technology, i.e., the Cray Y-MP and Cray C90. An overview of the Cray T3D hardware and available programming models is presented. Under Cray Research adaptive Fortran (CRAFT) model four programming methods (data parallel, work sharing, message-passing using PVM, and explicit shared memory model) are available to the users. However, at this time data parallel and work sharing programming models are not available to the user community. The differences between standard PVM and CRI's PVM are highlighted with performance measurements such as latencies and communication bandwidths. We have found that the performance of neither standard PVM nor CRI s PVM exploits the hardware capabilities of the T3D. The reasons for the bad performance of PVM as a native message-passing library are presented. This is illustrated by the performance of NAS Parallel Benchmarks (NPB) programmed in explicit shared memory model on Cray T3D. In general, the performance of standard PVM is about 4 to 5 times less than obtained by using explicit shared memory model. This degradation in performance is also seen on CM-5 where the performance of applications using native message-passing library CMMD on CM-5 is also about 4 to 5 times less than using data parallel methods. The issues involved (such as barriers, synchronization, invalidating data cache, aligning data cache etc.) while programming in explicit shared memory model are discussed. Comparative performance of NPB using explicit shared memory programming model on the Cray T3D and other highly parallel systems such as the TMC CM-5, Intel Paragon, Cray C90, IBM-SP1, etc. is presented.
Improving Memory for Optimization and Learning in Dynamic Environments
2011-07-01
algorithm uses simple, in- cremental clustering to separate solutions into memory entries. The cluster centers are used as the models in the memory. This is...entire days of traffic with realistic traffic de - mands and turning ratios on a 32 intersection network modeled on downtown Pittsburgh, Pennsyl- vania...early/tardy problem. Management Science, 35(2):177–191, 1989. [78] Daniel Parrott and Xiaodong Li. A particle swarm model for tracking multiple peaks in
The Role of Semantic Clustering in Optimal Memory Foraging.
Montez, Priscilla; Thompson, Graham; Kello, Christopher T
2015-11-01
Recent studies of semantic memory have investigated two theories of optimal search adopted from the animal foraging literature: Lévy flights and marginal value theorem. Each theory makes different simplifying assumptions and addresses different findings in search behaviors. In this study, an experiment is conducted to test whether clustering in semantic memory may play a role in evidence for both theories. Labeled magnets and a whiteboard were used to elicit spatial representations of semantic knowledge about animals. Category recall sequences from a separate experiment were used to trace search paths over the spatial representations of animal knowledge. Results showed that spatial distances between animal names arranged on the whiteboard were correlated with inter-response intervals (IRIs) during category recall, and distributions of both dependent measures approximated inverse power laws associated with Lévy flights. In addition, IRIs were relatively shorter when paths first entered animal clusters, and longer when they exited clusters, which is consistent with marginal value theorem. In conclusion, area-restricted searches over clustered semantic spaces may account for two different patterns of results interpreted as supporting two different theories of optimal memory foraging. Copyright © 2015 Cognitive Science Society, Inc.
Address tracing for parallel machines
NASA Technical Reports Server (NTRS)
Stunkel, Craig B.; Janssens, Bob; Fuchs, W. Kent
1991-01-01
Recently implemented parallel system address-tracing methods based on several metrics are surveyed. The issues specific to collection of traces for both shared and distributed memory parallel computers are highlighted. Five general categories of address-trace collection methods are examined: hardware-captured, interrupt-based, simulation-based, altered microcode-based, and instrumented program-based traces. The problems unique to shared memory and distributed memory multiprocessors are examined separately.
Howe, Piers D. L.
2017-01-01
To understand how the visual system represents multiple moving objects and how those representations contribute to tracking, it is essential that we understand how the processes of attention and working memory interact. In the work described here we present an investigation of that interaction via a series of tracking and working memory dual-task experiments. Previously, it has been argued that tracking is resistant to disruption by a concurrent working memory task and that any apparent disruption is in fact due to observers making a response to the working memory task, rather than due to competition for shared resources. Contrary to this, in our experiments we find that when task order and response order confounds are avoided, all participants show a similar decrease in both tracking and working memory performance. However, if task and response order confounds are not adequately controlled for we find substantial individual differences, which could explain the previous conflicting reports on this topic. Our results provide clear evidence that tracking and working memory tasks share processing resources. PMID:28410383
Lapierre, Mark D; Cropper, Simon J; Howe, Piers D L
2017-01-01
To understand how the visual system represents multiple moving objects and how those representations contribute to tracking, it is essential that we understand how the processes of attention and working memory interact. In the work described here we present an investigation of that interaction via a series of tracking and working memory dual-task experiments. Previously, it has been argued that tracking is resistant to disruption by a concurrent working memory task and that any apparent disruption is in fact due to observers making a response to the working memory task, rather than due to competition for shared resources. Contrary to this, in our experiments we find that when task order and response order confounds are avoided, all participants show a similar decrease in both tracking and working memory performance. However, if task and response order confounds are not adequately controlled for we find substantial individual differences, which could explain the previous conflicting reports on this topic. Our results provide clear evidence that tracking and working memory tasks share processing resources.
Vergauwe, Evie; Barrouillet, Pierre; Camos, Valérie
2009-07-01
Examinations of interference between visual and spatial materials in working memory have suggested domain- and process-based fractionations of visuo-spatial working memory. The present study examined the role of central time-based resource sharing in visuo-spatial working memory and assessed its role in obtained interference patterns. Visual and spatial storage were combined with both visual and spatial on-line processing components in computer-paced working memory span tasks (Experiment 1) and in a selective interference paradigm (Experiment 2). The cognitive load of the processing components was manipulated to investigate its impact on concurrent maintenance for both within-domain and between-domain combinations of processing and storage components. In contrast to both domain- and process-based fractionations of visuo-spatial working memory, the results revealed that recall performance was determined by the cognitive load induced by the processing of items, rather than by the domain to which those items pertained. These findings are interpreted as evidence for a time-based resource-sharing mechanism in visuo-spatial working memory.
The Role of Semantic Clustering in Optimal Memory Foraging
ERIC Educational Resources Information Center
Montez, Priscilla; Thompson, Graham; Kello, Christopher T.
2015-01-01
Recent studies of semantic memory have investigated two theories of optimal search adopted from the animal foraging literature: Lévy flights and marginal value theorem. Each theory makes different simplifying assumptions and addresses different findings in search behaviors. In this study, an experiment is conducted to test whether clustering in…
Why are you telling me that? A conceptual model of the social function of autobiographical memory.
Alea, Nicole; Bluck, Susan
2003-03-01
In an effort to stimulate and guide empirical work within a functional framework, this paper provides a conceptual model of the social functions of autobiographical memory (AM) across the lifespan. The model delineates the processes and variables involved when AMs are shared to serve social functions. Components of the model include: lifespan contextual influences, the qualitative characteristics of memory (emotionality and level of detail recalled), the speaker's characteristics (age, gender, and personality), the familiarity and similarity of the listener to the speaker, the level of responsiveness during the memory-sharing process, and the nature of the social relationship in which the memory sharing occurs (valence and length of the relationship). These components are shown to influence the type of social function served and/or, the extent to which social functions are served. Directions for future empirical work to substantiate the model and hypotheses derived from the model are provided.
Expectations about Memory Change Across the Life Span Are Impacted By Aging Stereotypes
Lineweaver, Tara T.; Berger, Andrea K.; Hertzog, Christopher
2008-01-01
This study examined whether expectations about memory change with age vary for different personality types. Four adjectives from each of Hummert’s age-stereotype trait sets were selected to create 11 adjective clusters varying in both valence (positive versus negative) and relevance to memory functioning. Three hundred and seventy three participants in three age groups rated the memory abilities of target adults, defined by the adjective clusters, across the adult life span. Consistent with past studies, participants believed in age-related memory decline. However, participants rated target adults with positive personality traits as having better memory ability and less age-related memory decline than target adults with negative personality traits. This effect was larger when the traits were relevant to memory than when they were not. Finally, older participants were more strongly influenced by both the valence and the relevance of the personality descriptions than younger participants. PMID:19290748
Nowicki, Dimitri; Siegelmann, Hava
2010-01-01
This paper introduces a new model of associative memory, capable of both binary and continuous-valued inputs. Based on kernel theory, the memory model is on one hand a generalization of Radial Basis Function networks and, on the other, is in feature space, analogous to a Hopfield network. Attractors can be added, deleted, and updated on-line simply, without harming existing memories, and the number of attractors is independent of input dimension. Input vectors do not have to adhere to a fixed or bounded dimensionality; they can increase and decrease it without relearning previous memories. A memory consolidation process enables the network to generalize concepts and form clusters of input data, which outperforms many unsupervised clustering techniques; this process is demonstrated on handwritten digits from MNIST. Another process, reminiscent of memory reconsolidation is introduced, in which existing memories are refreshed and tuned with new inputs; this process is demonstrated on series of morphed faces. PMID:20552013
Destination memory impairment in older people.
Gopie, Nigel; Craik, Fergus I M; Hasher, Lynn
2010-12-01
Older adults are assumed to have poor destination memory-knowing to whom they tell particular information-and anecdotes about them repeating stories to the same people are cited as informal evidence for this claim. Experiment 1 assessed young and older adults' destination memory by having participants tell facts (e.g., "A dime has 118 ridges around its edge") to pictures of famous people (e.g., Oprah Winfrey). Surprise recognition memory tests, which also assessed confidence, revealed that older adults, compared to young adults, were disproportionately impaired on destination memory relative to spared memory for the individual components (i.e., facts, faces) of the episode. Older adults also were more confident that they had not told a fact to a particular person when they actually had (i.e., a miss); this presumably causes them to repeat information more often than young adults. When the direction of information transfer was reversed in Experiment 2, such that the famous people shared information with the participants (i.e., a source memory experiment), age-related memory differences disappeared. In contrast to the destination memory experiment, older adults in the source memory experiment were more confident than young adults that someone had shared a fact with them when a different person actually had shared the fact (i.e., a false alarm). Overall, accuracy and confidence jointly influence age-related changes to destination memory, a fundamental component of successful communication. (c) 2010 APA, all rights reserved).
Short-term memory and critical clusterization in brain neurons spike series
NASA Astrophysics Data System (ADS)
Bershadskii, A.; Dremencov, E.; Yadid, G.
2003-06-01
A new phenomenon: critical clusterization, is observed in the neuron firing of a genetically defined rat model of depression. The critical clusterization is studied using a multiscaling analysis of the data obtained from the neurons belonging to the Red Nucleus area of the depressive brains. It is suggested that this critical phenomenon can be partially responsible for the observed ill behavior of the depressive brains: loss of short-term motor memory and slow motor reaction.
Azad, Ariful; Ouzounis, Christos A; Kyrpides, Nikos C; Buluç, Aydin
2018-01-01
Abstract Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times and memory demands. Here, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ∼70 million nodes with ∼68 billion edges in ∼2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license. PMID:29315405
Azad, Ariful; Pavlopoulos, Georgios A.; Ouzounis, Christos A.; ...
2018-01-05
Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times andmore » memory demands. In this paper, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ~70 million nodes with ~68 billion edges in ~2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. Finally, HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Azad, Ariful; Pavlopoulos, Georgios A.; Ouzounis, Christos A.
Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times andmore » memory demands. In this paper, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ~70 million nodes with ~68 billion edges in ~2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. Finally, HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license.« less
Interference due to shared features between action plans is influenced by working memory span.
Fournier, Lisa R; Behmer, Lawrence P; Stubblefield, Alexandra M
2014-12-01
In this study, we examined the interactions between the action plans that we hold in memory and the actions that we carry out, asking whether the interference due to shared features between action plans is due to selection demands imposed on working memory. Individuals with low and high working memory spans learned arbitrary motor actions in response to two different visual events (A and B), presented in a serial order. They planned a response to the first event (A) and while maintaining this action plan in memory they then executed a speeded response to the second event (B). Afterward, they executed the action plan for the first event (A) maintained in memory. Speeded responses to the second event (B) were delayed when it shared an action feature (feature overlap) with the first event (A), relative to when it did not (no feature overlap). The size of the feature-overlap delay was greater for low-span than for high-span participants. This indicates that interference due to overlapping action plans is greater when fewer working memory resources are available, suggesting that this interference is due to selection demands imposed on working memory. Thus, working memory plays an important role in managing current and upcoming action plans, at least for newly learned tasks. Also, managing multiple action plans is compromised in individuals who have low versus high working memory spans.
Destination Memory Impairment in Older People
Gopie, Nigel; Craik, Fergus I. M.; Hasher, Lynn
2012-01-01
Older adults are assumed to have poor destination memory— knowing to whom they tell particular information—and anecdotes about them repeating stories to the same people are cited as informal evidence for this claim. Experiment 1 assessed young and older adults’ destination memory by having participants tell facts (e.g., “A dime has 118 ridges around its edge”) to pictures of famous people (e.g., Oprah Winfrey). Surprise recognition memory tests, which also assessed confidence, revealed that older adults, compared to young adults, were disproportionately impaired on destination memory relative to spared memory for the individual components (i.e., facts, faces) of the episode. Older adults also were more confident that they had not told a fact to a particular person when they actually had (i.e., a miss); this presumably causes them to repeat information more often than young adults. When the direction of information transfer was reversed in Experiment 2, such that the famous people shared information with the participants (i.e., a source memory experiment), age-related memory differences disappeared. In contrast to the destination memory experiment, older adults in the source memory experiment were more confident than young adults that someone had shared a fact with them when a different person actually had shared the fact (i.e., a false alarm). Overall, accuracy and confidence jointly influence age-related changes to destination memory, a fundamental component of successful communication. PMID:20718537
MHD Code Optimizations and Jets in Dense Gaseous Halos
NASA Astrophysics Data System (ADS)
Gaibler, Volker; Vigelius, Matthias; Krause, Martin; Camenzind, Max
We have further optimized and extended the 3D-MHD-code NIRVANA. The magnetized part runs in parallel, reaching 19 Gflops per SX-6 node, and has a passively advected particle population. In addition, the code is MPI-parallel now - on top of the shared memory parallelization. On a 512^3 grid, we reach 561 Gflops with 32 nodes on the SX-8. Also, we have successfully used FLASH on the Opteron cluster. Scientific results are preliminary so far. We report one computation of highly resolved cocoon turbulence. While we find some similarities to earlier 2D work by us and others, we note a strange reluctancy of cold material to enter the low density cocoon, which has to be investigated further.
Hierarchically clustered adaptive quantization CMAC and its learning convergence.
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.
ADHD symptoms in healthy adults are associated with stressful life events and negative memory bias.
Vrijsen, Janna N; Tendolkar, Indira; Onnink, Marten; Hoogman, Martine; Schene, Aart H; Fernández, Guillén; van Oostrom, Iris; Franke, Barbara
2018-06-01
Stressful life events, especially Childhood Trauma, predict ADHD symptoms. Childhood Trauma and negatively biased memory are risk factors for affective disorders. The association of life events and bias with ADHD symptoms may inform about the etiology of ADHD. Memory bias was tested using a computer task in N = 675 healthy adults. Life events and ADHD symptoms were assessed using questionnaires. The mediation of the association between life events and ADHD symptoms by memory bias was examined. We explored the roles of different types of life events and of ADHD symptom clusters. Life events and memory bias were associated with overall ADHD symptoms as well as inattention and hyperactivity/impulsivity symptom clusters. Memory bias mediated the association of Lifetime Life Events, specifically Childhood Trauma, with ADHD symptoms. Negatively biased memory may be a cognitive marker of the effects of Childhood Trauma on the development and/or persistence of ADHD symptoms.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ibrahim, Khaled Z.; Epifanovsky, Evgeny; Williams, Samuel W.
Coupled-cluster methods provide highly accurate models of molecular structure by explicit numerical calculation of tensors representing the correlation between electrons. These calculations are dominated by a sequence of tensor contractions, motivating the development of numerical libraries for such operations. While based on matrix-matrix multiplication, these libraries are specialized to exploit symmetries in the molecular structure and in electronic interactions, and thus reduce the size of the tensor representation and the complexity of contractions. The resulting algorithms are irregular and their parallelization has been previously achieved via the use of dynamic scheduling or specialized data decompositions. We introduce our efforts tomore » extend the Libtensor framework to work in the distributed memory environment in a scalable and energy efficient manner. We achieve up to 240 speedup compared with the best optimized shared memory implementation. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures, (Cray XC30&XC40, BlueGene/Q), and on a heterogeneous GPU-CPU system (Cray XK7). As the bottlenecks shift from being compute-bound DGEMM's to communication-bound collectives as the size of the molecular system scales, we adopt two radically different parallelization approaches for handling load-imbalance. Nevertheless, we preserve a uni ed interface to both programming models to maintain the productivity of computational quantum chemists.« less
NASA Astrophysics Data System (ADS)
Rossi, Francesco; Londrillo, Pasquale; Sgattoni, Andrea; Sinigardi, Stefano; Turchetti, Giorgio
2012-12-01
We present `jasmine', an implementation of a fully relativistic, 3D, electromagnetic Particle-In-Cell (PIC) code, capable of running simulations in various laser plasma acceleration regimes on Graphics-Processing-Units (GPUs) HPC clusters. Standard energy/charge preserving FDTD-based algorithms have been implemented using double precision and quadratic (or arbitrary sized) shape functions for the particle weighting. When porting a PIC scheme to the GPU architecture (or, in general, a shared memory environment), the particle-to-grid operations (e.g. the evaluation of the current density) require special care to avoid memory inconsistencies and conflicts. Here we present a robust implementation of this operation that is efficient for any number of particles per cell and particle shape function order. Our algorithm exploits the exposed GPU memory hierarchy and avoids the use of atomic operations, which can hurt performance especially when many particles lay on the same cell. We show the code multi-GPU scalability results and present a dynamic load-balancing algorithm. The code is written using a python-based C++ meta-programming technique which translates in a high level of modularity and allows for easy performance tuning and simple extension of the core algorithms to various simulation schemes.
Low latency memory access and synchronization
DOE Office of Scientific and Technical Information (OSTI.GOV)
Blumrich, Matthias A.; Chen, Dong; Coteus, Paul W.
A low latency memory system access is provided in association with a weakly-ordered multiprocessor system. Each processor in the multiprocessor shares resources, and each shared resource has an associated lock within a locking device that provides support for synchronization between the multiple processors in the multiprocessor and the orderly sharing of the resources. A processor only has permission to access a resource when it owns the lock associated with that resource, and an attempt by a processor to own a lock requires only a single load operation, rather than a traditional atomic load followed by store, such that the processormore » only performs a read operation and the hardware locking device performs a subsequent write operation rather than the processor. A simple prefetching for non-contiguous data structures is also disclosed. A memory line is redefined so that in addition to the normal physical memory data, every line includes a pointer that is large enough to point to any other line in the memory, wherein the pointers to determine which memory line to prefetch rather than some other predictive algorithm. This enables hardware to effectively prefetch memory access patterns that are non-contiguous, but repetitive.« less
Low latency memory access and synchronization
DOE Office of Scientific and Technical Information (OSTI.GOV)
Blumrich, Matthias A.; Chen, Dong; Coteus, Paul W.
A low latency memory system access is provided in association with a weakly-ordered multiprocessor system. Bach processor in the multiprocessor shares resources, and each shared resource has an associated lock within a locking device that provides support for synchronization between the multiple processors in the multiprocessor and the orderly sharing of the resources. A processor only has permission to access a resource when it owns the lock associated with that resource, and an attempt by a processor to own a lock requires only a single load operation, rather than a traditional atomic load followed by store, such that the processormore » only performs a read operation and the hardware locking device performs a subsequent write operation rather than the processor. A simple prefetching for non-contiguous data structures is also disclosed. A memory line is redefined so that in addition to the normal physical memory data, every line includes a pointer that is large enough to point to any other line in the memory, wherein the pointers to determine which memory line to prefetch rather than some other predictive algorithm. This enables hardware to effectively prefetch memory access patterns that are non-contiguous, but repetitive.« less
Location-Unbound Color-Shape Binding Representations in Visual Working Memory.
Saiki, Jun
2016-02-01
The mechanism by which nonspatial features, such as color and shape, are bound in visual working memory, and the role of those features' location in their binding, remains unknown. In the current study, I modified a redundancy-gain paradigm to investigate these issues. A set of features was presented in a two-object memory display, followed by a single object probe. Participants judged whether the probe contained any features of the memory display, regardless of its location. Response time distributions revealed feature coactivation only when both features of a single object in the memory display appeared together in the probe, regardless of the response time benefit from the probe and memory objects sharing the same location. This finding suggests that a shared location is necessary in the formation of bound representations but unnecessary in their maintenance. Electroencephalography data showed that amplitude modulations reflecting location-unbound feature coactivation were different from those reflecting the location-sharing benefit, consistent with the behavioral finding that feature-location binding is unnecessary in the maintenance of color-shape binding. © The Author(s) 2015.
Echterhoff, Gerald; Kopietz, René; Higgins, E Tory
2017-06-01
Communicators typically tune messages to their audience's attitude. Such audience tuning biases communicators' memory for the topic toward the audience's attitude to the extent that they create a shared reality with the audience. To investigate shared reality in intergroup communication, we first established that a reduced memory bias after tuning messages to an out-group (vs. in-group) audience is a subtle index of communicators' denial of shared reality to that out-group audience (Experiments 1a and 1b). We then examined whether the audience-tuning memory bias might emerge when the out-group audience's epistemic authority is enhanced, either by increasing epistemic expertise concerning the communication topic or by creating epistemic consensus among members of a multiperson out-group audience. In Experiment 2, when Germans communicated to a Turkish audience with an attitude about a Turkish (vs. German) target, the audience-tuning memory bias appeared. In Experiment 3, when the audience of German communicators consisted of 3 Turks who all held the same attitude toward the target, the memory bias again appeared. The association between message valence and memory valence was consistently higher when the audience's epistemic authority was high (vs. low). An integrative analysis across all studies also suggested that the memory bias increases with increasing strength of epistemic inputs (epistemic expertise, epistemic consensus, and audience-tuned message production). The findings suggest novel ways of overcoming intergroup biases in intergroup relations. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
The Developmental Influence of Primary Memory Capacity on Working Memory and Academic Achievement
2015-01-01
In this study, we investigate the development of primary memory capacity among children. Children between the ages of 5 and 8 completed 3 novel tasks (split span, interleaved lists, and a modified free-recall task) that measured primary memory by estimating the number of items in the focus of attention that could be spontaneously recalled in serial order. These tasks were calibrated against traditional measures of simple and complex span. Clear age-related changes in these primary memory estimates were observed. There were marked individual differences in primary memory capacity, but each novel measure was predictive of simple span performance. Among older children, each measure shared variance with reading and mathematics performance, whereas for younger children, the interleaved lists task was the strongest single predictor of academic ability. We argue that these novel tasks have considerable potential for the measurement of primary memory capacity and provide new, complementary ways of measuring the transient memory processes that predict academic performance. The interleaved lists task also shared features with interference control tasks, and our findings suggest that young children have a particular difficulty in resisting distraction and that variance in the ability to resist distraction is also shared with measures of educational attainment. PMID:26075630
The developmental influence of primary memory capacity on working memory and academic achievement.
Hall, Debbora; Jarrold, Christopher; Towse, John N; Zarandi, Amy L
2015-08-01
In this study, we investigate the development of primary memory capacity among children. Children between the ages of 5 and 8 completed 3 novel tasks (split span, interleaved lists, and a modified free-recall task) that measured primary memory by estimating the number of items in the focus of attention that could be spontaneously recalled in serial order. These tasks were calibrated against traditional measures of simple and complex span. Clear age-related changes in these primary memory estimates were observed. There were marked individual differences in primary memory capacity, but each novel measure was predictive of simple span performance. Among older children, each measure shared variance with reading and mathematics performance, whereas for younger children, the interleaved lists task was the strongest single predictor of academic ability. We argue that these novel tasks have considerable potential for the measurement of primary memory capacity and provide new, complementary ways of measuring the transient memory processes that predict academic performance. The interleaved lists task also shared features with interference control tasks, and our findings suggest that young children have a particular difficulty in resisting distraction and that variance in the ability to resist distraction is also shared with measures of educational attainment. (c) 2015 APA, all rights reserved).
Conditional load and store in a shared memory
Blumrich, Matthias A; Ohmacht, Martin
2015-02-03
A method, system and computer program product for implementing load-reserve and store-conditional instructions in a multi-processor computing system. The computing system includes a multitude of processor units and a shared memory cache, and each of the processor units has access to the memory cache. In one embodiment, the method comprises providing the memory cache with a series of reservation registers, and storing in these registers addresses reserved in the memory cache for the processor units as a result of issuing load-reserve requests. In this embodiment, when one of the processor units makes a request to store data in the memory cache using a store-conditional request, the reservation registers are checked to determine if an address in the memory cache is reserved for that processor unit. If an address in the memory cache is reserved for that processor, the data are stored at this address.
Loewenstein, Yaniv; Portugaly, Elon; Fromer, Menachem; Linial, Michal
2008-07-01
UPGMA (average linking) is probably the most popular algorithm for hierarchical data clustering, especially in computational biology. However, UPGMA requires the entire dissimilarity matrix in memory. Due to this prohibitive requirement, UPGMA is not scalable to very large datasets. We present a novel class of memory-constrained UPGMA (MC-UPGMA) algorithms. Given any practical memory size constraint, this framework guarantees the correct clustering solution without explicitly requiring all dissimilarities in memory. The algorithms are general and are applicable to any dataset. We present a data-dependent characterization of hardness and clustering efficiency. The presented concepts are applicable to any agglomerative clustering formulation. We apply our algorithm to the entire collection of protein sequences, to automatically build a comprehensive evolutionary-driven hierarchy of proteins from sequence alone. The newly created tree captures protein families better than state-of-the-art large-scale methods such as CluSTr, ProtoNet4 or single-linkage clustering. We demonstrate that leveraging the entire mass embodied in all sequence similarities allows to significantly improve on current protein family clusterings which are unable to directly tackle the sheer mass of this data. Furthermore, we argue that non-metric constraints are an inherent complexity of the sequence space and should not be overlooked. The robustness of UPGMA allows significant improvement, especially for multidomain proteins, and for large or divergent families. A comprehensive tree built from all UniProt sequence similarities, together with navigation and classification tools will be made available as part of the ProtoNet service. A C++ implementation of the algorithm is available on request.
Performance Analysis of Multilevel Parallel Applications on Shared Memory Architectures
NASA Technical Reports Server (NTRS)
Biegel, Bryan A. (Technical Monitor); Jost, G.; Jin, H.; Labarta J.; Gimenez, J.; Caubet, J.
2003-01-01
Parallel programming paradigms include process level parallelism, thread level parallelization, and multilevel parallelism. This viewgraph presentation describes a detailed performance analysis of these paradigms for Shared Memory Architecture (SMA). This analysis uses the Paraver Performance Analysis System. The presentation includes diagrams of a flow of useful computations.
Measuring Transactiving Memory Systems Using Network Analysis
ERIC Educational Resources Information Center
King, Kylie Goodell
2017-01-01
Transactive memory systems (TMSs) describe the structures and processes that teams use to share information, work together, and accomplish shared goals. First introduced over three decades ago, TMSs have been measured in a variety of ways. This dissertation proposes the use of network analysis in measuring TMS. This is accomplished by describing…
Operator Influence of Unexploded Ordnance Sensor Technologies
2007-03-01
chart display ActiveX control Mscomct2.dll – date/time display ActiveX control Pnpscr.dll – Systran SCRAMNet replicated shared memory device...response value database rgm_p2.dll – Phase 2 shared memory API and implementation Commercial components StripM.ocx – strip chart display ActiveX
Runtime support for parallelizing data mining algorithms
NASA Astrophysics Data System (ADS)
Jin, Ruoming; Agrawal, Gagan
2002-03-01
With recent technological advances, shared memory parallel machines have become more scalable, and offer large main memories and high bus bandwidths. They are emerging as good platforms for data warehousing and data mining. In this paper, we focus on shared memory parallelization of data mining algorithms. We have developed a series of techniques for parallelization of data mining algorithms, including full replication, full locking, fixed locking, optimized full locking, and cache-sensitive locking. Unlike previous work on shared memory parallelization of specific data mining algorithms, all of our techniques apply to a large number of common data mining algorithms. In addition, we propose a reduction-object based interface for specifying a data mining algorithm. We show how our runtime system can apply any of the technique we have developed starting from a common specification of the algorithm.
Concurrent working memory load can facilitate selective attention: evidence for specialized load.
Park, Soojin; Kim, Min-Shik; Chun, Marvin M
2007-10-01
Load theory predicts that concurrent working memory load impairs selective attention and increases distractor interference (N. Lavie, A. Hirst, J. W. de Fockert, & E. Viding). Here, the authors present new evidence that the type of concurrent working memory load determines whether load impairs selective attention or not. Working memory load was paired with a same/different matching task that required focusing on targets while ignoring distractors. When working memory items shared the same limited-capacity processing mechanisms with targets in the matching task, distractor interference increased. However, when working memory items shared processing with distractors in the matching task, distractor interference decreased, facilitating target selection. A specialized load account is proposed to describe the dissociable effects of working memory load on selective processing depending on whether the load overlaps with targets or with distractors. (c) 2007 APA
Transactive memory systems scale for couples: development and validation
Hewitt, Lauren Y.; Roberts, Lynne D.
2015-01-01
People in romantic relationships can develop shared memory systems by pooling their cognitive resources, allowing each person access to more information but with less cognitive effort. Research examining such memory systems in romantic couples largely focuses on remembering word lists or performing lab-based tasks, but these types of activities do not capture the processes underlying couples’ transactive memory systems, and may not be representative of the ways in which romantic couples use their shared memory systems in everyday life. We adapted an existing measure of transactive memory systems for use with romantic couples (TMSS-C), and conducted an initial validation study. In total, 397 participants who each identified as being a member of a romantic relationship of at least 3 months duration completed the study. The data provided a good fit to the anticipated three-factor structure of the components of couples’ transactive memory systems (specialization, credibility and coordination), and there was reasonable evidence of both convergent and divergent validity, as well as strong evidence of test–retest reliability across a 2-week period. The TMSS-C provides a valuable tool that can quickly and easily capture the underlying components of romantic couples’ transactive memory systems. It has potential to help us better understand this intriguing feature of romantic relationships, and how shared memory systems might be associated with other important features of romantic relationships. PMID:25999873
Carpenter, Joanne S; Robillard, Rébecca; Lee, Rico S C; Hermens, Daniel F; Naismith, Sharon L; White, Django; Whitwell, Bradley; Scott, Elizabeth M; Hickie, Ian B
2015-01-01
Although early-stage affective disorders are associated with both cognitive dysfunction and sleep-wake disruptions, relationships between these factors have not been specifically examined in young adults. Sleep and circadian rhythm disturbances in those with affective disorders are considerably heterogeneous, and may not relate to cognitive dysfunction in a simple linear fashion. This study aimed to characterise profiles of sleep and circadian disturbance in young people with affective disorders and examine associations between these profiles and cognitive performance. Actigraphy monitoring was completed in 152 young people (16-30 years; 66% female) with primary diagnoses of affective disorders, and 69 healthy controls (18-30 years; 57% female). Patients also underwent detailed neuropsychological assessment. Actigraphy data were processed to estimate both sleep and circadian parameters. Overall neuropsychological performance in patients was poor on tasks relating to mental flexibility and visual memory. Two hierarchical cluster analyses identified three distinct patient groups based on sleep variables and three based on circadian variables. Sleep clusters included a 'long sleep' cluster, a 'disrupted sleep' cluster, and a 'delayed and disrupted sleep' cluster. Circadian clusters included a 'strong circadian' cluster, a 'weak circadian' cluster, and a 'delayed circadian' cluster. Medication use differed between clusters. The 'long sleep' cluster displayed significantly worse visual memory performance compared to the 'disrupted sleep' cluster. No other cognitive functions differed between clusters. These results highlight the heterogeneity of sleep and circadian profiles in young people with affective disorders, and provide preliminary evidence in support of a relationship between sleep and visual memory, which may be mediated by use of antipsychotic medication. These findings have implications for the personalisation of treatments and improvement of functioning in young adults early in the course of affective illness.
DMA shared byte counters in a parallel computer
Chen, Dong; Gara, Alan G.; Heidelberger, Philip; Vranas, Pavlos
2010-04-06
A parallel computer system is constructed as a network of interconnected compute nodes. Each of the compute nodes includes at least one processor, a memory and a DMA engine. The DMA engine includes a processor interface for interfacing with the at least one processor, DMA logic, a memory interface for interfacing with the memory, a DMA network interface for interfacing with the network, injection and reception byte counters, injection and reception FIFO metadata, and status registers and control registers. The injection FIFOs maintain memory locations of the injection FIFO metadata memory locations including its current head and tail, and the reception FIFOs maintain the reception FIFO metadata memory locations including its current head and tail. The injection byte counters and reception byte counters may be shared between messages.
Division of attention as a function of the number of steps, visual shifts, and memory load
NASA Technical Reports Server (NTRS)
Chechile, R. A.; Butler, K.; Gutowski, W.; Palmer, E. A.
1986-01-01
The effects on divided attention of visual shifts and long-term memory retrieval during a monitoring task are considered. A concurrent vigilance task was standardized under all experimental conditions. The results show that subjects can perform nearly perfectly on all of the time-shared tasks if long-term memory retrieval is not required for monitoring. With the requirement of memory retrieval, however, there was a large decrease in accuracy for all of the time-shared activities. It was concluded that the attentional demand of longterm memory retrieval is appreciable (even for a well-learned motor sequence), and thus memory retrieval results in a sizable reduction in the capability of subjects to divide their attention. A selected bibliography on the divided attention literature is provided.
Luo, Ze; Baoping, Yan; Takekawa, John Y.; Prosser, Diann J.
2012-01-01
We propose a new method to help ornithologists and ecologists discover shared segments on the migratory pathway of the bar-headed geese by time-based plane-sweeping trajectory clustering. We present a density-based time parameterized line segment clustering algorithm, which extends traditional comparable clustering algorithms from temporal and spatial dimensions. We present a time-based plane-sweeping trajectory clustering algorithm to reveal the dynamic evolution of spatial-temporal object clusters and discover common motion patterns of bar-headed geese in the process of migration. Experiments are performed on GPS-based satellite telemetry data from bar-headed geese and results demonstrate our algorithms can correctly discover shared segments of the bar-headed geese migratory pathway. We also present findings on the migratory behavior of bar-headed geese determined from this new analytical approach.
Welcoming nora: a family event.
Walsh, Allison J; Walsh, Paul R; Walsh, Jane M; Walsh, Gavin T
2011-01-01
In this column, Allison and Paul Walsh share the story of the birth of Nora, their third baby and their second child to be born at home. Allison and Paul share their individual memories of labor and birth. But their story is only part of the story of Nora's birth. Nora's birth was a family event, with Allison and Paul's other children very much part of the experience. Jane and Gavin share their own memories of their baby sister's birth.
Colouring in the Blanks: Memory Drawings of the 1990 Kuwait Invasion
ERIC Educational Resources Information Center
Pepin-Wakefield, Yvonne
2009-01-01
This study used drawing tasks to examine the similarities and differences between females and males who shared a collective traumatic event in early childhood. Could these childhood memories be recorded, measured, and compared for gender differences in drawings by young adults who had shared a similar experience as children? Exploration of this…
ERIC Educational Resources Information Center
Kulkofsky, Sarah; Wang, Qi; Koh, Jessie Bee Kim
2009-01-01
This study examined maternal beliefs about the functions of memory sharing and the relations between these beliefs and mother-child reminiscing behaviors in a cross-cultural context. Sixty-three European American and 47 Chinese mothers completed an open-ended questionnaire concerning their beliefs about the functions of parent-child memory…
Clustering of neural code words revealed by a first-order phase transition
NASA Astrophysics Data System (ADS)
Huang, Haiping; Toyoizumi, Taro
2016-06-01
A network of neurons in the central nervous system collectively represents information by its spiking activity states. Typically observed states, i.e., code words, occupy only a limited portion of the state space due to constraints imposed by network interactions. Geometrical organization of code words in the state space, critical for neural information processing, is poorly understood due to its high dimensionality. Here, we explore the organization of neural code words using retinal data by computing the entropy of code words as a function of Hamming distance from a particular reference codeword. Specifically, we report that the retinal code words in the state space are divided into multiple distinct clusters separated by entropy-gaps, and that this structure is shared with well-known associative memory networks in a recallable phase. Our analysis also elucidates a special nature of the all-silent state. The all-silent state is surrounded by the densest cluster of code words and located within a reachable distance from most code words. This code-word space structure quantitatively predicts typical deviation of a state-trajectory from its initial state. Altogether, our findings reveal a non-trivial heterogeneous structure of the code-word space that shapes information representation in a biological network.
Stillbirth and stigma: the spoiling and repair of multiple social identities.
Brierley-Jones, Lyn; Crawley, Rosalind; Lomax, Samantha; Ayers, Susan
This study investigated mothers' experiences surrounding stillbirth in the United Kingdom, their memory making and sharing opportunities, and the effect these opportunities had on them. Qualitative data were generated from free text responses to open-ended questions. Thematic content analysis revealed that "stigma" was experienced by most women and Goffman's (1963) work on stigma was subsequently used as an analytical framework. Results suggest that stillbirth can spoil the identities of "patient," "mother," and "full citizen." Stigma was reported as arising from interactions with professionals, family, friends, work colleagues, and even casual acquaintances. Stillbirth produces common learning experiences often requiring "identity work" (Murphy, 2012). Memory making and sharing may be important in this work and further research is needed. Stigma can reduce the memory sharing opportunities for women after stillbirth and this may explain some of the differential mental health effects of memory making after stillbirth that is documented in the literature.
Parallelization of KENO-Va Monte Carlo code
NASA Astrophysics Data System (ADS)
Ramón, Javier; Peña, Jorge
1995-07-01
KENO-Va is a code integrated within the SCALE system developed by Oak Ridge that solves the transport equation through the Monte Carlo Method. It is being used at the Consejo de Seguridad Nuclear (CSN) to perform criticality calculations for fuel storage pools and shipping casks. Two parallel versions of the code: one for shared memory machines and other for distributed memory systems using the message-passing interface PVM have been generated. In both versions the neutrons of each generation are tracked in parallel. In order to preserve the reproducibility of the results in both versions, advanced seeds for random numbers were used. The CONVEX C3440 with four processors and shared memory at CSN was used to implement the shared memory version. A FDDI network of 6 HP9000/735 was employed to implement the message-passing version using proprietary PVM. The speedup obtained was 3.6 in both cases.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bent, John M.; Faibish, Sorin; Pedone, Jr., James M.
A cluster file system is provided having a plurality of distributed metadata servers with shared access to one or more shared low latency persistent key-value metadata stores. A metadata server comprises an abstract storage interface comprising a software interface module that communicates with at least one shared persistent key-value metadata store providing a key-value interface for persistent storage of key-value metadata. The software interface module provides the key-value metadata to the at least one shared persistent key-value metadata store in a key-value format. The shared persistent key-value metadata store is accessed by a plurality of metadata servers. A metadata requestmore » can be processed by a given metadata server independently of other metadata servers in the cluster file system. A distributed metadata storage environment is also disclosed that comprises a plurality of metadata servers having an abstract storage interface to at least one shared persistent key-value metadata store.« less
A simple modern correctness condition for a space-based high-performance multiprocessor
NASA Technical Reports Server (NTRS)
Probst, David K.; Li, Hon F.
1992-01-01
A number of U.S. national programs, including space-based detection of ballistic missile launches, envisage putting significant computing power into space. Given sufficient progress in low-power VLSI, multichip-module packaging and liquid-cooling technologies, we will see design of high-performance multiprocessors for individual satellites. In very high speed implementations, performance depends critically on tolerating large latencies in interprocessor communication; without latency tolerance, performance is limited by the vastly differing time scales in processor and data-memory modules, including interconnect times. The modern approach to tolerating remote-communication cost in scalable, shared-memory multiprocessors is to use a multithreaded architecture, and alter the semantics of shared memory slightly, at the price of forcing the programmer either to reason about program correctness in a relaxed consistency model or to agree to program in a constrained style. The literature on multiprocessor correctness conditions has become increasingly complex, and sometimes confusing, which may hinder its practical application. We propose a simple modern correctness condition for a high-performance, shared-memory multiprocessor; the correctness condition is based on a simple interface between the multiprocessor architecture and a high-performance, shared-memory multiprocessor; the correctness condition is based on a simple interface between the multiprocessor architecture and the parallel programming system.
Parra, Mario A; Mikulan, Ezequiel; Trujillo, Natalia; Sala, Sergio Della; Lopera, Francisco; Manes, Facundo; Starr, John; Ibanez, Agustin
2017-01-01
Alzheimer's disease (AD) as a disconnection syndrome which disrupts both brain information sharing and memory binding functions. The extent to which these two phenotypic expressions share pathophysiological mechanisms remains unknown. To unveil the electrophysiological correlates of integrative memory impairments in AD towards new memory biomarkers for its prodromal stages. Patients with 100% risk of familial AD (FAD) and healthy controls underwent assessment with the Visual Short-Term Memory binding test (VSTMBT) while we recorded their EEG. We applied a novel brain connectivity method (Weighted Symbolic Mutual Information) to EEG data. Patients showed significant deficits during the VSTMBT. A reduction of brain connectivity was observed during resting as well as during correct VSTM binding, particularly over frontal and posterior regions. An increase of connectivity was found during VSTM binding performance over central regions. While decreased connectivity was found in cases in more advanced stages of FAD, increased brain connectivity appeared in cases in earlier stages. Such altered patterns of task-related connectivity were found in 89% of the assessed patients. VSTM binding in the prodromal stages of FAD are associated to altered patterns of brain connectivity thus confirming the link between integrative memory deficits and impaired brain information sharing in prodromal FAD. While significant loss of brain connectivity seems to be a feature of the advanced stages of FAD increased brain connectivity characterizes its earlier stages. These findings are discussed in the light of recent proposals about the earliest pathophysiological mechanisms of AD and their clinical expression. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Loewenstein, Yaniv; Portugaly, Elon; Fromer, Menachem; Linial, Michal
2008-01-01
Motivation: UPGMA (average linking) is probably the most popular algorithm for hierarchical data clustering, especially in computational biology. However, UPGMA requires the entire dissimilarity matrix in memory. Due to this prohibitive requirement, UPGMA is not scalable to very large datasets. Application: We present a novel class of memory-constrained UPGMA (MC-UPGMA) algorithms. Given any practical memory size constraint, this framework guarantees the correct clustering solution without explicitly requiring all dissimilarities in memory. The algorithms are general and are applicable to any dataset. We present a data-dependent characterization of hardness and clustering efficiency. The presented concepts are applicable to any agglomerative clustering formulation. Results: We apply our algorithm to the entire collection of protein sequences, to automatically build a comprehensive evolutionary-driven hierarchy of proteins from sequence alone. The newly created tree captures protein families better than state-of-the-art large-scale methods such as CluSTr, ProtoNet4 or single-linkage clustering. We demonstrate that leveraging the entire mass embodied in all sequence similarities allows to significantly improve on current protein family clusterings which are unable to directly tackle the sheer mass of this data. Furthermore, we argue that non-metric constraints are an inherent complexity of the sequence space and should not be overlooked. The robustness of UPGMA allows significant improvement, especially for multidomain proteins, and for large or divergent families. Availability: A comprehensive tree built from all UniProt sequence similarities, together with navigation and classification tools will be made available as part of the ProtoNet service. A C++ implementation of the algorithm is available on request. Contact: lonshy@cs.huji.ac.il PMID:18586742
Payne, Brennan R.; Gross, Alden L.; Hill, Patrick L.; Parisi, Jeanine M.; Rebok, George W.; Stine-Morrow, Elizabeth A. L.
2018-01-01
With advancing age, episodic memory performance shows marked declines along with concurrent reports of lower subjective memory beliefs. Given that normative age-related declines in episodic memory co-occur with declines in other cognitive domains, we examined the relationship between memory beliefs and multiple domains of cognitive functioning. Confirmatory bi-factor structural equation models were used to parse the shared and independent variance among factors representing episodic memory, psychomotor speed, and executive reasoning in one large cohort study (Senior Odyssey, N = 462), and replicated using another large cohort of healthy older adults (ACTIVE, N = 2,802). Accounting for a general fluid cognitive functioning factor (comprised of the shared variance among measures of episodic memory, speed, and reasoning) attenuated the relationship between objective memory performance and subjective memory beliefs in both samples. Moreover, the general cognitive functioning factor was the strongest predictor of memory beliefs in both samples. These findings are consistent with the notion that dispositional memory beliefs may reflect perceptions of cognition more broadly. This may be one reason why memory beliefs have broad predictive validity for interventions that target fluid cognitive ability. PMID:27685541
Payne, Brennan R; Gross, Alden L; Hill, Patrick L; Parisi, Jeanine M; Rebok, George W; Stine-Morrow, Elizabeth A L
2017-07-01
With advancing age, episodic memory performance shows marked declines along with concurrent reports of lower subjective memory beliefs. Given that normative age-related declines in episodic memory co-occur with declines in other cognitive domains, we examined the relationship between memory beliefs and multiple domains of cognitive functioning. Confirmatory bi-factor structural equation models were used to parse the shared and independent variance among factors representing episodic memory, psychomotor speed, and executive reasoning in one large cohort study (Senior Odyssey, N = 462), and replicated using another large cohort of healthy older adults (ACTIVE, N = 2802). Accounting for a general fluid cognitive functioning factor (comprised of the shared variance among measures of episodic memory, speed, and reasoning) attenuated the relationship between objective memory performance and subjective memory beliefs in both samples. Moreover, the general cognitive functioning factor was the strongest predictor of memory beliefs in both samples. These findings are consistent with the notion that dispositional memory beliefs may reflect perceptions of cognition more broadly. This may be one reason why memory beliefs have broad predictive validity for interventions that target fluid cognitive ability.
Method for prefetching non-contiguous data structures
Blumrich, Matthias A [Ridgefield, CT; Chen, Dong [Croton On Hudson, NY; Coteus, Paul W [Yorktown Heights, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Hoenicke, Dirk [Ossining, NY; Ohmacht, Martin [Brewster, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Takken, Todd E [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY
2009-05-05
A low latency memory system access is provided in association with a weakly-ordered multiprocessor system. Each processor in the multiprocessor shares resources, and each shared resource has an associated lock within a locking device that provides support for synchronization between the multiple processors in the multiprocessor and the orderly sharing of the resources. A processor only has permission to access a resource when it owns the lock associated with that resource, and an attempt by a processor to own a lock requires only a single load operation, rather than a traditional atomic load followed by store, such that the processor only performs a read operation and the hardware locking device performs a subsequent write operation rather than the processor. A simple perfecting for non-contiguous data structures is also disclosed. A memory line is redefined so that in addition to the normal physical memory data, every line includes a pointer that is large enough to point to any other line in the memory, wherein the pointers to determine which memory line to prefect rather than some other predictive algorithm. This enables hardware to effectively prefect memory access patterns that are non-contiguous, but repetitive.
A shared resource between declarative memory and motor memory.
Keisler, Aysha; Shadmehr, Reza
2010-11-03
The neural systems that support motor adaptation in humans are thought to be distinct from those that support the declarative system. Yet, during motor adaptation changes in motor commands are supported by a fast adaptive process that has important properties (rapid learning, fast decay) that are usually associated with the declarative system. The fast process can be contrasted to a slow adaptive process that also supports motor memory, but learns gradually and shows resistance to forgetting. Here we show that after people stop performing a motor task, the fast motor memory can be disrupted by a task that engages declarative memory, but the slow motor memory is immune from this interference. Furthermore, we find that the fast/declarative component plays a major role in the consolidation of the slow motor memory. Because of the competitive nature of declarative and nondeclarative memory during consolidation, impairment of the fast/declarative component leads to improvements in the slow/nondeclarative component. Therefore, the fast process that supports formation of motor memory is not only neurally distinct from the slow process, but it shares critical resources with the declarative memory system.
A shared resource between declarative memory and motor memory
Keisler, Aysha; Shadmehr, Reza
2010-01-01
The neural systems that support motor adaptation in humans are thought to be distinct from those that support the declarative system. Yet, during motor adaptation changes in motor commands are supported by a fast adaptive process that has important properties (rapid learning, fast decay) that are usually associated with the declarative system. The fast process can be contrasted to a slow adaptive process that also supports motor memory, but learns gradually and shows resistance to forgetting. Here we show that after people stop performing a motor task, the fast motor memory can be disrupted by a task that engages declarative memory, but the slow motor memory is immune from this interference. Furthermore, we find that the fast/declarative component plays a major role in the consolidation of the slow motor memory. Because of the competitive nature of declarative and non-declarative memory during consolidation, impairment of the fast/declarative component leads to improvements in the slow/non-declarative component. Therefore, the fast process that supports formation of motor memory is not only neurally distinct from the slow process, but it shares critical resources with the declarative memory system. PMID:21048140
Dissociative Amnesia and DSM-IV-TR Cluster C Personality Traits.
Leong, Stephanie; Waits, Wendi; Diebold, Carroll
2006-01-01
Dissociative amnesia is a disorder characterized by retrospectively reported memory gaps. These gaps involve an inability to recall personal information, usually of a traumatic or stressful nature. Dissociative amnesia most commonly occurs in the presence of other psychiatric conditions, particularly personality disorders. In the literature and in clinical practice, it is often associated with DSM-IV-TR Cluster B personality disorders. However, there is evidence to suggest that dissociative amnesia may be more likely to occur among individuals with Cluster C personality disorders. Presented here is a discussion of the types of memory loss, two cases of dissociative amnesia occurring in patients with Cluster C psychopathology, and a focused literature review.
Dissociative Amnesia and DSM-IV-TR Cluster C Personality Traits
Waits, Wendi; Diebold, Carroll
2006-01-01
Dissociative amnesia is a disorder characterized by retrospectively reported memory gaps. These gaps involve an inability to recall personal information, usually of a traumatic or stressful nature. Dissociative amnesia most commonly occurs in the presence of other psychiatric conditions, particularly personality disorders. In the literature and in clinical practice, it is often associated with DSM-IV-TR Cluster B personality disorders. However, there is evidence to suggest that dissociative amnesia may be more likely to occur among individuals with Cluster C personality disorders. Presented here is a discussion of the types of memory loss, two cases of dissociative amnesia occurring in patients with Cluster C psychopathology, and a focused literature review. PMID:21103150
Discrete-Slots Models of Visual Working-Memory Response Times
Donkin, Christopher; Nosofsky, Robert M.; Gold, Jason M.; Shiffrin, Richard M.
2014-01-01
Much recent research has aimed to establish whether visual working memory (WM) is better characterized by a limited number of discrete all-or-none slots or by a continuous sharing of memory resources. To date, however, researchers have not considered the response-time (RT) predictions of discrete-slots versus shared-resources models. To complement the past research in this field, we formalize a family of mixed-state, discrete-slots models for explaining choice and RTs in tasks of visual WM change detection. In the tasks under investigation, a small set of visual items is presented, followed by a test item in 1 of the studied positions for which a change judgment must be made. According to the models, if the studied item in that position is retained in 1 of the discrete slots, then a memory-based evidence-accumulation process determines the choice and the RT; if the studied item in that position is missing, then a guessing-based accumulation process operates. Observed RT distributions are therefore theorized to arise as probabilistic mixtures of the memory-based and guessing distributions. We formalize an analogous set of continuous shared-resources models. The model classes are tested on individual subjects with both qualitative contrasts and quantitative fits to RT-distribution data. The discrete-slots models provide much better qualitative and quantitative accounts of the RT and choice data than do the shared-resources models, although there is some evidence for “slots plus resources” when memory set size is very small. PMID:24015956
ERIC Educational Resources Information Center
Schweppe, Judith; Rummer, Ralf
2007-01-01
The general idea of language-based accounts of short-term memory is that retention of linguistic materials is based on representations within the language processing system. In the present sentence recall study, we address the question whether the assumption of shared representations holds for morphosyntactic information (here: grammatical gender…
The Precategorical Nature of Visual Short-Term Memory
ERIC Educational Resources Information Center
Quinlan, Philip T.; Cohen, Dale J.
2016-01-01
We conducted a series of recognition experiments that assessed whether visual short-term memory (VSTM) is sensitive to shared category membership of to-be-remembered (tbr) images of common objects. In Experiment 1 some of the tbr items shared the same basic level category (e.g., hand axe): Such items were no better retained than others. In the…
NASA Technical Reports Server (NTRS)
Shalkhauser, Mary JO; Quintana, Jorge A.; Soni, Nitin J.
1994-01-01
The NASA Lewis Research Center is developing a multichannel communication signal processing satellite (MCSPS) system which will provide low data rate, direct to user, commercial communications services. The focus of current space segment developments is a flexible, high-throughput, fault tolerant onboard information switching processor. This information switching processor (ISP) is a destination-directed packet switch which performs both space and time switching to route user information among numerous user ground terminals. Through both industry study contracts and in-house investigations, several packet switching architectures were examined. A contention-free approach, the shared memory per beam architecture, was selected for implementation. The shared memory per beam architecture, fault tolerance insertion, implementation, and demonstration plans are described.
The performance of disk arrays in shared-memory database machines
NASA Technical Reports Server (NTRS)
Katz, Randy H.; Hong, Wei
1993-01-01
In this paper, we examine how disk arrays and shared memory multiprocessors lead to an effective method for constructing database machines for general-purpose complex query processing. We show that disk arrays can lead to cost-effective storage systems if they are configured from suitably small formfactor disk drives. We introduce the storage system metric data temperature as a way to evaluate how well a disk configuration can sustain its workload, and we show that disk arrays can sustain the same data temperature as a more expensive mirrored-disk configuration. We use the metric to evaluate the performance of disk arrays in XPRS, an operational shared-memory multiprocessor database system being developed at the University of California, Berkeley.
Improving Memory Error Handling Using Linux
DOE Office of Scientific and Technical Information (OSTI.GOV)
Carlton, Michael Andrew; Blanchard, Sean P.; Debardeleben, Nathan A.
As supercomputers continue to get faster and more powerful in the future, they will also have more nodes. If nothing is done, then the amount of memory in supercomputer clusters will soon grow large enough that memory failures will be unmanageable to deal with by manually replacing memory DIMMs. "Improving Memory Error Handling Using Linux" is a process oriented method to solve this problem by using the Linux kernel to disable (offline) faulty memory pages containing bad addresses, preventing them from being used again by a process. The process of offlining memory pages simplifies error handling and results in reducingmore » both hardware and manpower costs required to run Los Alamos National Laboratory (LANL) clusters. This process will be necessary for the future of supercomputing to allow the development of exascale computers. It will not be feasible without memory error handling to manually replace the number of DIMMs that will fail daily on a machine consisting of 32-128 petabytes of memory. Testing reveals the process of offlining memory pages works and is relatively simple to use. As more and more testing is conducted, the entire process will be automated within the high-performance computing (HPC) monitoring software, Zenoss, at LANL.« less
McGregor, Karla K.; Oleson, Jacob
2017-01-01
Purpose The purpose of this study is to determine whether deficits in executive function and lexical-semantic memory compromise the linguistic performance of young adults with specific learning disabilities (LD) enrolled in postsecondary studies. Method One hundred eighty-five students with LD (n = 53) or normal language development (ND, n = 132) named items in the categories animals and food for 1 minute for each category and completed tests of lexical-semantic knowledge and executive control of memory. Groups were compared on total names, mean cluster size, frequency of embedded clusters, frequency of cluster switches, and change in fluency over time. Secondary analyses of variability within the LD group were also conducted. Results The LD group was less fluent than the ND group. Within the LD group, lexical-semantic knowledge predicted semantic fluency and cluster size; executive control of memory predicted semantic fluency and cluster switches. The LD group produced smaller clusters and fewer embedded clusters than the ND group. Groups did not differ in switching or change over time. Conclusions Deficits in the lexical-semantic system associated with LD may persist into young adulthood, even among those who have managed their disability well enough to attend college. Lexical-semantic deficits are associated with compromised semantic fluency, and the two problems are more likely among students with more severe disabilities. PMID:28267833
Hall, Jessica; McGregor, Karla K; Oleson, Jacob
2017-03-01
The purpose of this study is to determine whether deficits in executive function and lexical-semantic memory compromise the linguistic performance of young adults with specific learning disabilities (LD) enrolled in postsecondary studies. One hundred eighty-five students with LD (n = 53) or normal language development (ND, n = 132) named items in the categories animals and food for 1 minute for each category and completed tests of lexical-semantic knowledge and executive control of memory. Groups were compared on total names, mean cluster size, frequency of embedded clusters, frequency of cluster switches, and change in fluency over time. Secondary analyses of variability within the LD group were also conducted. The LD group was less fluent than the ND group. Within the LD group, lexical-semantic knowledge predicted semantic fluency and cluster size; executive control of memory predicted semantic fluency and cluster switches. The LD group produced smaller clusters and fewer embedded clusters than the ND group. Groups did not differ in switching or change over time. Deficits in the lexical-semantic system associated with LD may persist into young adulthood, even among those who have managed their disability well enough to attend college. Lexical-semantic deficits are associated with compromised semantic fluency, and the two problems are more likely among students with more severe disabilities.
Farmer, Jocelyn R; Ong, Mei-Sing; Barmettler, Sara; Yonker, Lael M; Fuleihan, Ramsay; Sullivan, Kathleen E; Cunningham-Rundles, Charlotte; Walter, Jolan E
2017-01-01
Common variable immunodeficiency (CVID) is increasingly recognized for its association with autoimmune and inflammatory complications. Despite recent advances in immunophenotypic and genetic discovery, clinical care of CVID remains limited by our inability to accurately model risk for non-infectious disease development. Herein, we demonstrate the utility of unbiased network clustering as a novel method to analyze inter-relationships between non-infectious disease outcomes in CVID using databases at the United States Immunodeficiency Network (USIDNET), the centralized immunodeficiency registry of the United States, and Partners, a tertiary care network in Boston, MA, USA, with a shared electronic medical record amenable to natural language processing. Immunophenotypes were comparable in terms of native antibody deficiencies, low titer response to pneumococcus, and B cell maturation arrest. However, recorded non-infectious disease outcomes were more substantial in the Partners cohort across the spectrum of lymphoproliferation, cytopenias, autoimmunity, atopy, and malignancy. Using unbiased network clustering to analyze 34 non-infectious disease outcomes in the Partners cohort, we further identified unique patterns of lymphoproliferative (two clusters), autoimmune (two clusters), and atopic (one cluster) disease that were defined as CVID non-infectious endotypes according to discrete and non-overlapping immunophenotypes. Markers were both previously described {high serum IgE in the atopic cluster [odds ratio (OR) 6.5] and low class-switched memory B cells in the total lymphoproliferative cluster (OR 9.2)} and novel [low serum C3 in the total lymphoproliferative cluster (OR 5.1)]. Mortality risk in the Partners cohort was significantly associated with individual non-infectious disease outcomes as well as lymphoproliferative cluster 2, specifically (OR 5.9). In contrast, unbiased network clustering failed to associate known comorbidities in the adult USIDNET cohort. Together, these data suggest that unbiased network clustering can be used in CVID to redefine non-infectious disease inter-relationships; however, applicability may be limited to datasets well annotated through mechanisms such as natural language processing. The lymphoproliferative, autoimmune, and atopic Partners CVID endotypes herein described can be used moving forward to streamline genetic and biomarker discovery and to facilitate early screening and intervention in CVID patients at highest risk for autoimmune and inflammatory progression.
Optical memories in digital computing
NASA Technical Reports Server (NTRS)
Alford, C. O.; Gaylord, T. K.
1979-01-01
High capacity optical memories with relatively-high data-transfer rate and multiport simultaneous access capability may serve as basis for new computer architectures. Several computer structures that might profitably use memories are: a) simultaneous record-access system, b) simultaneously-shared memory computer system, and c) parallel digital processing structure.
Hsu, Chien-Chang; Cheng, Ching-Wen; Chiu, Yi-Shiuan
2017-02-15
Electroencephalograms can record wave variations in any brain activity. Beta waves are produced when an external stimulus induces logical thinking, computation, and reasoning during consciousness. This work uses the beta wave of major scale working memory N-back tasks to analyze the differences between young musicians and non-musicians. After the feature analysis uses signal filtering, Hilbert-Huang transformation, and feature extraction methods to identify differences, k-means clustering algorithm are used to group them into different clusters. The results of feature analysis showed that beta waves significantly differ between young musicians and non-musicians from the low memory load of working memory task. Copyright © 2017 Elsevier B.V. All rights reserved.
Pakhomov, Serguei V.S.; Hemmy, Laura S.
2014-01-01
Generative semantic verbal fluency (SVF) tests show early and disproportionate decline relative to other abilities in individuals developing Alzheimer’s disease. Optimal performance on SVF tests depends on the efficiency of using clustered organization of semantically related items and the ability to switch between clusters. Traditional approaches to clustering and switching have relied on manual determination of clusters. We evaluated a novel automated computational linguistic approach for quantifying clustering behavior. Our approach is based on Latent Semantic Analysis (LSA) for computing strength of semantic relatedness between pairs of words produced in response to SVF test. The mean size of semantic clusters (MCS) and semantic chains (MChS) are calculated based on pairwise relatedness values between words. We evaluated the predictive validity of these measures on a set of 239 participants in the Nun Study, a longitudinal study of aging. All were cognitively intact at baseline assessment, measured with the CERAD battery, and were followed in 18 month waves for up to 20 years. The onset of either dementia or memory impairment were used as outcomes in Cox proportional hazards models adjusted for age and education and censored at follow up waves 5 (6.3 years) and 13 (16.96 years). Higher MCS was associated with 38% reduction in dementia risk at wave 5 and 26% reduction at wave 13, but not with the onset of memory impairment. Higher (+1 SD) MChS was associated with 39% dementia risk reduction at wave 5 but not wave 13, and association with memory impairment was not significant. Higher traditional SVF scores were associated with 22–29% memory impairment and 35–40% dementia risk reduction. SVF scores were not correlated with either MCS or MChS. Our study suggests that an automated approach to measuring clustering behavior can be used to estimate dementia risk in cognitively normal individuals. PMID:23845236
Pakhomov, Serguei V S; Hemmy, Laura S
2014-06-01
Generative semantic verbal fluency (SVF) tests show early and disproportionate decline relative to other abilities in individuals developing Alzheimer's disease. Optimal performance on SVF tests depends on the efficiency of using clustered organization of semantically related items and the ability to switch between clusters. Traditional approaches to clustering and switching have relied on manual determination of clusters. We evaluated a novel automated computational linguistic approach for quantifying clustering behavior. Our approach is based on Latent Semantic Analysis (LSA) for computing strength of semantic relatedness between pairs of words produced in response to SVF test. The mean size of semantic clusters (MCS) and semantic chains (MChS) are calculated based on pairwise relatedness values between words. We evaluated the predictive validity of these measures on a set of 239 participants in the Nun Study, a longitudinal study of aging. All were cognitively intact at baseline assessment, measured with the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) battery, and were followed in 18-month waves for up to 20 years. The onset of either dementia or memory impairment were used as outcomes in Cox proportional hazards models adjusted for age and education and censored at follow-up waves 5 (6.3 years) and 13 (16.96 years). Higher MCS was associated with 38% reduction in dementia risk at wave 5 and 26% reduction at wave 13, but not with the onset of memory impairment. Higher [+1 standard deviation (SD)] MChS was associated with 39% dementia risk reduction at wave 5 but not wave 13, and association with memory impairment was not significant. Higher traditional SVF scores were associated with 22-29% memory impairment and 35-40% dementia risk reduction. SVF scores were not correlated with either MCS or MChS. Our study suggests that an automated approach to measuring clustering behavior can be used to estimate dementia risk in cognitively normal individuals. Copyright © 2013 Elsevier Ltd. All rights reserved.
Long memory and volatility clustering: Is the empirical evidence consistent across stock markets?
NASA Astrophysics Data System (ADS)
Bentes, Sónia R.; Menezes, Rui; Mendes, Diana A.
2008-06-01
Long memory and volatility clustering are two stylized facts frequently related to financial markets. Traditionally, these phenomena have been studied based on conditionally heteroscedastic models like ARCH, GARCH, IGARCH and FIGARCH, inter alia. One advantage of these models is their ability to capture nonlinear dynamics. Another interesting manner to study the volatility phenomenon is by using measures based on the concept of entropy. In this paper we investigate the long memory and volatility clustering for the SP 500, NASDAQ 100 and Stoxx 50 indexes in order to compare the US and European Markets. Additionally, we compare the results from conditionally heteroscedastic models with those from the entropy measures. In the latter, we examine Shannon entropy, Renyi entropy and Tsallis entropy. The results corroborate the previous evidence of nonlinear dynamics in the time series considered.
NASA Astrophysics Data System (ADS)
Seyrich, Maximilian; Sornette, Didier
2016-04-01
We present a plausible micro-founded model for the previously postulated power law finite time singular form of the crash hazard rate in the Johansen-Ledoit-Sornette (JLS) model of rational expectation bubbles. The model is based on a percolation picture of the network of traders and the concept that clusters of connected traders share the same opinion. The key ingredient is the notion that a shift of position from buyer to seller of a sufficiently large group of traders can trigger a crash. This provides a formula to estimate the crash hazard rate by summation over percolation clusters above a minimum size of a power sa (with a>1) of the cluster sizes s, similarly to a generalized percolation susceptibility. The power sa of cluster sizes emerges from the super-linear dependence of group activity as a function of group size, previously documented in the literature. The crash hazard rate exhibits explosive finite time singular behaviors when the control parameter (fraction of occupied sites, or density of traders in the network) approaches the percolation threshold pc. Realistic dynamics are generated by modeling the density of traders on the percolation network by an Ornstein-Uhlenbeck process, whose memory controls the spontaneous excursion of the control parameter close to the critical region of bubble formation. Our numerical simulations recover the main stylized properties of the JLS model with intermittent explosive super-exponential bubbles interrupted by crashes.
Reader set encoding for directory of shared cache memory in multiprocessor system
Ahn, Dnaiel; Ceze, Luis H.; Gara, Alan; Ohmacht, Martin; Xiaotong, Zhuang
2014-06-10
In a parallel processing system with speculative execution, conflict checking occurs in a directory lookup of a cache memory that is shared by all processors. In each case, the same physical memory address will map to the same set of that cache, no matter which processor originated that access. The directory includes a dynamic reader set encoding, indicating what speculative threads have read a particular line. This reader set encoding is used in conflict checking. A bitset encoding is used to specify particular threads that have read the line.
Insights on consciousness from taste memory research.
Gallo, Milagros
2016-01-01
Taste research in rodents supports the relevance of memory in order to determine the content of consciousness by modifying both taste perception and later action. Associated with this issue is the fact that taste and visual modalities share anatomical circuits traditionally related to conscious memory. This challenges the view of taste memory as a type of non-declarative unconscious memory.
ERIC Educational Resources Information Center
Hay-McCutcheon, Marcia J.; Hyams, Adriana; Yang, Xin; Parton, Jason; Panasiuk, Brianna; Ondocsin, Sarah; James, Mary Margaret; Scogin, Forrest
2017-01-01
Purpose: The purpose of this preliminary study was to explore the associations among hearing loss, physical health, and visual memory in adults living in rural areas, urban clusters, and an urban city in west Central Alabama. Method: Two hundred ninety-seven adults (182 women, 115 men) from rural areas, urban clusters, and an urban city of west…
Investigating Ground Swarm Robotics Using Agent Based Simulation
2006-12-01
Incorporation of virtual pheromones as a shared memory map is modeled as an additional capability that is found to enhance the robustness and reliability of the...virtual pheromones as a shared memory map is modeled as an additional capability that is found to enhance the robustness and reliability of the swarm... PHEROMONES .......................................... 42 1. Repel Friends under Inorganic SA.................................................. 45 2. Max
Implementing Molecular Dynamics for Hybrid High Performance Computers - 1. Short Range Forces
DOE Office of Scientific and Technical Information (OSTI.GOV)
Brown, W Michael; Wang, Peng; Plimpton, Steven J
The use of accelerators such as general-purpose graphics processing units (GPGPUs) have become popular in scientific computing applications due to their low cost, impressive floating-point capabilities, high memory bandwidth, and low electrical power requirements. Hybrid high performance computers, machines with more than one type of floating-point processor, are now becoming more prevalent due to these advantages. In this work, we discuss several important issues in porting a large molecular dynamics code for use on parallel hybrid machines - 1) choosing a hybrid parallel decomposition that works on central processing units (CPUs) with distributed memory and accelerator cores with shared memory,more » 2) minimizing the amount of code that must be ported for efficient acceleration, 3) utilizing the available processing power from both many-core CPUs and accelerators, and 4) choosing a programming model for acceleration. We present our solution to each of these issues for short-range force calculation in the molecular dynamics package LAMMPS. We describe algorithms for efficient short range force calculation on hybrid high performance machines. We describe a new approach for dynamic load balancing of work between CPU and accelerator cores. We describe the Geryon library that allows a single code to compile with both CUDA and OpenCL for use on a variety of accelerators. Finally, we present results on a parallel test cluster containing 32 Fermi GPGPUs and 180 CPU cores.« less
Comparative Investigation of Shared Filesystems for the LHCb Online Cluster
NASA Astrophysics Data System (ADS)
Vijay Kartik, S.; Neufeld, Niko
2012-12-01
This paper describes the investigative study undertaken to evaluate shared filesystem performance and suitability in the LHCb Online environment. Particular focus is given to the measurements and field tests designed and performed on an in-house OpenAFS setup; related comparisons with NFSv4 and GPFS (a clustered filesystem from IBM) are presented. The motivation for the investigation and the test setup arises from the need to serve common user-space like home directories, experiment software and control areas, and clustered log areas. Since the operational requirements on such user-space are stringent in terms of read-write operations (in frequency and access speed) and unobtrusive data relocation, test results are presented with emphasis on file-level performance, stability and “high-availability” of the shared filesystems. Use cases specific to the experiment operation in LHCb, including the specific handling of shared filesystems served to a cluster of 1500 diskless nodes, are described. Issues of prematurely expiring authenticated sessions are explicitly addressed, keeping in mind long-running analysis jobs on the Online cluster. In addition, quantitative test results are also presented with alternatives including NFSv4. Comparative measurements of filesystem performance benchmarks are presented, which are seen to be used as reference for decisions on potential migration of the current storage solution deployed in the LHCb online cluster.
Centrally managed unified shared virtual address space
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wilkes, John
Systems, apparatuses, and methods for managing a unified shared virtual address space. A host may execute system software and manage a plurality of nodes coupled to the host. The host may send work tasks to the nodes, and for each node, the host may externally manage the node's view of the system's virtual address space. Each node may have a central processing unit (CPU) style memory management unit (MMU) with an internal translation lookaside buffer (TLB). In one embodiment, the host may be coupled to a given node via an input/output memory management unit (IOMMU) interface, where the IOMMU frontendmore » interface shares the TLB with the given node's MMU. In another embodiment, the host may control the given node's view of virtual address space via memory-mapped control registers.« less
Attention and Visuospatial Working Memory Share the Same Processing Resources
Feng, Jing; Pratt, Jay; Spence, Ian
2012-01-01
Attention and visuospatial working memory (VWM) share very similar characteristics; both have the same upper bound of about four items in capacity and they recruit overlapping brain regions. We examined whether both attention and VWM share the same processing resources using a novel dual-task costs approach based on a load-varying dual-task technique. With sufficiently large loads on attention and VWM, considerable interference between the two processes was observed. A further load increase on either process produced reciprocal increases in interference on both processes, indicating that attention and VWM share common resources. More critically, comparison among four experiments on the reciprocal interference effects, as measured by the dual-task costs, demonstrates no significant contribution from additional processing other than the shared processes. These results support the notion that attention and VWM share the same processing resources. PMID:22529826
Contention Modeling for Multithreaded Distributed Shared Memory Machines: The Cray XMT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Secchi, Simone; Tumeo, Antonino; Villa, Oreste
Distributed Shared Memory (DSM) machines are a wide class of multi-processor computing systems where a large virtually-shared address space is mapped on a network of physically distributed memories. High memory latency and network contention are two of the main factors that limit performance scaling of such architectures. Modern high-performance computing DSM systems have evolved toward exploitation of massive hardware multi-threading and fine-grained memory hashing to tolerate irregular latencies, avoid network hot-spots and enable high scaling. In order to model the performance of such large-scale machines, parallel simulation has been proved to be a promising approach to achieve good accuracy inmore » reasonable times. One of the most critical factors in solving the simulation speed-accuracy trade-off is network modeling. The Cray XMT is a massively multi-threaded supercomputing architecture that belongs to the DSM class, since it implements a globally-shared address space abstraction on top of a physically distributed memory substrate. In this paper, we discuss the development of a contention-aware network model intended to be integrated in a full-system XMT simulator. We start by measuring the effects of network contention in a 128-processor XMT machine and then investigate the trade-off that exists between simulation accuracy and speed, by comparing three network models which operate at different levels of accuracy. The comparison and model validation is performed by executing a string-matching algorithm on the full-system simulator and on the XMT, using three datasets that generate noticeably different contention patterns.« less
2012-01-01
Background Postsynaptic density (PSD)-95-like membrane-associated guanylate kinases (PSD-MAGUKs) are scaffold proteins in PSDs that cluster signaling molecules near NMDA receptors. PSD-MAGUKs share a common domain structure, including three PDZ (PDZ1/2/3) domains in their N-terminus. While multiple domains enable the PSD-MAGUKs to bind various ligands, the contribution of each PDZ domain to synaptic organization and function is not fully understood. Here, we focused on the PDZ1/2 domains of PSD-95 that bind NMDA-type receptors, and studied the specific roles of the ligand binding of these domains in the assembly of PSD proteins, synaptic properties of hippocampal neurons, and behavior, using ligand binding-deficient PSD-95 cDNA knockin (KI) mice. Results The KI mice showed decreased accumulation of mutant PSD-95, PSD-93 and AMPA receptor subunits in the PSD fraction of the hippocampus. In the hippocampal CA1 region of young KI mice, basal synaptic efficacy was reduced and long-term potentiation (LTP) was enhanced with intact long-term depression. In adult KI mice, there was no significant change in the magnitude of LTP in CA1, but robustly enhanced LTP was induced at the medial perforant path-dentate gyrus synapses, suggesting that PSD-95 has an age- and subregion-dependent role. In a battery of behavioral tests, KI mice showed markedly abnormal anxiety-like behavior, impaired spatial reference and working memory, and impaired remote memory and pattern separation in fear conditioning test. Conclusions These findings reveal that PSD-95 including its ligand binding of the PDZ1/2 domains controls the synaptic clustering of PSD-MAGUKs and AMPA receptors, which may have an essential role in regulating hippocampal synaptic transmission, plasticity, and hippocampus-dependent behavior. PMID:23268962
Nagura, Hitoshi; Ishikawa, Yasuyuki; Kobayashi, Katsunori; Takao, Keizo; Tanaka, Tomo; Nishikawa, Kouki; Tamura, Hideki; Shiosaka, Sadao; Suzuki, Hidenori; Miyakawa, Tsuyoshi; Fujiyoshi, Yoshinori; Doi, Tomoko
2012-12-26
Postsynaptic density (PSD)-95-like membrane-associated guanylate kinases (PSD-MAGUKs) are scaffold proteins in PSDs that cluster signaling molecules near NMDA receptors. PSD-MAGUKs share a common domain structure, including three PDZ (PDZ1/2/3) domains in their N-terminus. While multiple domains enable the PSD-MAGUKs to bind various ligands, the contribution of each PDZ domain to synaptic organization and function is not fully understood. Here, we focused on the PDZ1/2 domains of PSD-95 that bind NMDA-type receptors, and studied the specific roles of the ligand binding of these domains in the assembly of PSD proteins, synaptic properties of hippocampal neurons, and behavior, using ligand binding-deficient PSD-95 cDNA knockin (KI) mice. The KI mice showed decreased accumulation of mutant PSD-95, PSD-93 and AMPA receptor subunits in the PSD fraction of the hippocampus. In the hippocampal CA1 region of young KI mice, basal synaptic efficacy was reduced and long-term potentiation (LTP) was enhanced with intact long-term depression. In adult KI mice, there was no significant change in the magnitude of LTP in CA1, but robustly enhanced LTP was induced at the medial perforant path-dentate gyrus synapses, suggesting that PSD-95 has an age- and subregion-dependent role. In a battery of behavioral tests, KI mice showed markedly abnormal anxiety-like behavior, impaired spatial reference and working memory, and impaired remote memory and pattern separation in fear conditioning test. These findings reveal that PSD-95 including its ligand binding of the PDZ1/2 domains controls the synaptic clustering of PSD-MAGUKs and AMPA receptors, which may have an essential role in regulating hippocampal synaptic transmission, plasticity, and hippocampus-dependent behavior.
Verbal and Visual Memory Impairments in Bipolar I and II Disorder.
Ha, Tae Hyon; Kim, Ji Sun; Chang, Jae Seung; Oh, Sung Hee; Her, Ju Young; Cho, Hyun Sang; Park, Tae Sung; Shin, Soon Young; Ha, Kyooseob
2012-12-01
To compare verbal and visual memory performances between patients with bipolar I disorder (BD I) and patients with bipolar II disorder (BD II) and to determine whether memory deficits were mediated by impaired organizational strategies. Performances on the Korean-California Verbal Learning Test (K-CVLT) and the Rey-Osterrieth Complex Figure Test (ROCF) in 37 patients with BD I, 46 patients with BD II and 42 healthy subjects were compared. Mediating effects of impaired organization strategies on poor delayed recall was tested by comparing direct and mediated models using multiple regression analysis. Both patients groups recalled fewer words and figure components and showed lower Semantic Clustering compared to controls. Verbal memory impairment was partly mediated by difficulties in Semantic Clustering in both subtypes, whereas the mediating effect of Organization deficit on the visual memory impairment was present only in BD I. In all mediated models, group differences in delayed recall remained significant. Our findings suggest that memory impairment may be one of the fundamental cognitive deficits in bipolar disorders and that executive dysfunctions can exert an additional influence on memory impairments.
Biomarker clusters are differentially associated with longitudinal cognitive decline in late midlife
Racine, Annie M.; Koscik, Rebecca L.; Berman, Sara E.; Nicholas, Christopher R.; Clark, Lindsay R.; Okonkwo, Ozioma C.; Rowley, Howard A.; Asthana, Sanjay; Bendlin, Barbara B.; Blennow, Kaj; Zetterberg, Henrik; Gleason, Carey E.; Carlsson, Cynthia M.
2016-01-01
The ability to detect preclinical Alzheimer’s disease is of great importance, as this stage of the Alzheimer’s continuum is believed to provide a key window for intervention and prevention. As Alzheimer’s disease is characterized by multiple pathological changes, a biomarker panel reflecting co-occurring pathology will likely be most useful for early detection. Towards this end, 175 late middle-aged participants (mean age 55.9 ± 5.7 years at first cognitive assessment, 70% female) were recruited from two longitudinally followed cohorts to undergo magnetic resonance imaging and lumbar puncture. Cluster analysis was used to group individuals based on biomarkers of amyloid pathology (cerebrospinal fluid amyloid-β42/amyloid-β40 assay levels), magnetic resonance imaging-derived measures of neurodegeneration/atrophy (cerebrospinal fluid-to-brain volume ratio, and hippocampal volume), neurofibrillary tangles (cerebrospinal fluid phosphorylated tau181 assay levels), and a brain-based marker of vascular risk (total white matter hyperintensity lesion volume). Four biomarker clusters emerged consistent with preclinical features of (i) Alzheimer’s disease; (ii) mixed Alzheimer’s disease and vascular aetiology; (iii) suspected non-Alzheimer’s disease aetiology; and (iv) healthy ageing. Cognitive decline was then analysed between clusters using longitudinal assessments of episodic memory, semantic memory, executive function, and global cognitive function with linear mixed effects modelling. Cluster 1 exhibited a higher intercept and greater rates of decline on tests of episodic memory. Cluster 2 had a lower intercept on a test of semantic memory and both Cluster 2 and Cluster 3 had steeper rates of decline on a test of global cognition. Additional analyses on Cluster 3, which had the smallest hippocampal volume, suggest that its biomarker profile is more likely due to hippocampal vulnerability and not to detectable specific volume loss exceeding the rate of normal ageing. Our results demonstrate that pathology, as indicated by biomarkers, in a preclinical timeframe is related to patterns of longitudinal cognitive decline. Such biomarker patterns may be useful for identifying at-risk populations to recruit for clinical trials. PMID:27324877
Racine, Annie M; Koscik, Rebecca L; Berman, Sara E; Nicholas, Christopher R; Clark, Lindsay R; Okonkwo, Ozioma C; Rowley, Howard A; Asthana, Sanjay; Bendlin, Barbara B; Blennow, Kaj; Zetterberg, Henrik; Gleason, Carey E; Carlsson, Cynthia M; Johnson, Sterling C
2016-08-01
The ability to detect preclinical Alzheimer's disease is of great importance, as this stage of the Alzheimer's continuum is believed to provide a key window for intervention and prevention. As Alzheimer's disease is characterized by multiple pathological changes, a biomarker panel reflecting co-occurring pathology will likely be most useful for early detection. Towards this end, 175 late middle-aged participants (mean age 55.9 ± 5.7 years at first cognitive assessment, 70% female) were recruited from two longitudinally followed cohorts to undergo magnetic resonance imaging and lumbar puncture. Cluster analysis was used to group individuals based on biomarkers of amyloid pathology (cerebrospinal fluid amyloid-β42/amyloid-β40 assay levels), magnetic resonance imaging-derived measures of neurodegeneration/atrophy (cerebrospinal fluid-to-brain volume ratio, and hippocampal volume), neurofibrillary tangles (cerebrospinal fluid phosphorylated tau181 assay levels), and a brain-based marker of vascular risk (total white matter hyperintensity lesion volume). Four biomarker clusters emerged consistent with preclinical features of (i) Alzheimer's disease; (ii) mixed Alzheimer's disease and vascular aetiology; (iii) suspected non-Alzheimer's disease aetiology; and (iv) healthy ageing. Cognitive decline was then analysed between clusters using longitudinal assessments of episodic memory, semantic memory, executive function, and global cognitive function with linear mixed effects modelling. Cluster 1 exhibited a higher intercept and greater rates of decline on tests of episodic memory. Cluster 2 had a lower intercept on a test of semantic memory and both Cluster 2 and Cluster 3 had steeper rates of decline on a test of global cognition. Additional analyses on Cluster 3, which had the smallest hippocampal volume, suggest that its biomarker profile is more likely due to hippocampal vulnerability and not to detectable specific volume loss exceeding the rate of normal ageing. Our results demonstrate that pathology, as indicated by biomarkers, in a preclinical timeframe is related to patterns of longitudinal cognitive decline. Such biomarker patterns may be useful for identifying at-risk populations to recruit for clinical trials. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
System and method for memory allocation in a multiclass memory system
Loh, Gabriel; Meswani, Mitesh; Ignatowski, Michael; Nutter, Mark
2016-06-28
A system for memory allocation in a multiclass memory system includes a processor coupleable to a plurality of memories sharing a unified memory address space, and a library store to store a library of software functions. The processor identifies a type of a data structure in response to a memory allocation function call to the library for allocating memory to the data structure. Using the library, the processor allocates portions of the data structure among multiple memories of the multiclass memory system based on the type of the data structure.
A Formal Model of Capacity Limits in Working Memory
ERIC Educational Resources Information Center
Oberauer, Klaus; Kliegl, Reinhold
2006-01-01
A mathematical model of working-memory capacity limits is proposed on the key assumption of mutual interference between items in working memory. Interference is assumed to arise from overwriting of features shared by these items. The model was fit to time-accuracy data of memory-updating tasks from four experiments using nonlinear mixed effect…
Ordering of guarded and unguarded stores for no-sync I/O
Gara, Alan; Ohmacht, Martin
2013-06-25
A parallel computing system processes at least one store instruction. A first processor core issues a store instruction. A first queue, associated with the first processor core, stores the store instruction. A second queue, associated with a first local cache memory device of the first processor core, stores the store instruction. The first processor core updates first data in the first local cache memory device according to the store instruction. The third queue, associated with at least one shared cache memory device, stores the store instruction. The first processor core invalidates second data, associated with the store instruction, in the at least one shared cache memory. The first processor core invalidates third data, associated with the store instruction, in other local cache memory devices of other processor cores. The first processor core flushing only the first queue.
NASA Technical Reports Server (NTRS)
Gilbertsen, Noreen D.; Belytschko, Ted
1990-01-01
The implementation of a nonlinear explicit program on a vectorized, concurrent computer with shared memory is described and studied. The conflict between vectorization and concurrency is described and some guidelines are given for optimal block sizes. Several example problems are summarized to illustrate the types of speed-ups which can be achieved by reprogramming as compared to compiler optimization.
LU Factorization with Partial Pivoting for a Multi-CPU, Multi-GPU Shared Memory System
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kurzak, Jakub; Luszczek, Pitior; Faverge, Mathieu
2012-03-01
LU factorization with partial pivoting is a canonical numerical procedure and the main component of the High Performance LINPACK benchmark. This article presents an implementation of the algorithm for a hybrid, shared memory, system with standard CPU cores and GPU accelerators. Performance in excess of one TeraFLOPS is achieved using four AMD Magny Cours CPUs and four NVIDIA Fermi GPUs.
ERIC Educational Resources Information Center
Burgess, Gregory C.; Gray, Jeremy R.; Conway, Andrew R. A.; Braver, Todd S.
2011-01-01
Fluid intelligence (gF) and working memory (WM) span predict success in demanding cognitive situations. Recent studies show that much of the variance in gF and WM span is shared, suggesting common neural mechanisms. This study provides a direct investigation of the degree to which shared variance in gF and WM span can be explained by neural…
Mnemonic Strategies: Creating Schemata for Learning Enhancement
ERIC Educational Resources Information Center
Goll, Paulette S.
2004-01-01
This article investigates the process of remembering and presents techniques to improve memory retention. Examples of association, clustering, imagery, location, mnemonic devices and visualization illustrate strategies that can be used to encode and recall information from the long-term memory. Several memory games offer the opportunity to test…
Spatial overlap links seemingly unconnected genotype-matched TB cases in rural Uganda
Kato-Maeda, Midori; Emperador, Devy M.; Wandera, Bonnie; Mugagga, Olive; Crandall, John; Janes, Michael; Marquez, Carina; Kamya, Moses R.; Charlebois, Edwin D.; Havlir, Diane V.
2018-01-01
Introduction Incomplete understanding of TB transmission dynamics in high HIV prevalence settings remains an obstacle for prevention. Understanding where transmission occurs could provide a platform for case finding and interrupting transmission. Methods From 2012–2015, we sought to recruit all adults starting TB treatment in a Ugandan community. Participants underwent household (HH) contact investigation, and provided names of social contacts, sites of work, healthcare and socializing, and two sputum samples. Mycobacterium tuberculosis culture-positive specimens underwent 24-loci MIRU-VNTR and spoligotyping. We sought to identify epidemiologic links between genotype-matched cases by analyzing social networks and mapping locations where cases reported spending ≥12 hours over the one-month pre-treatment. Sites of spatial overlap (≤100m) between genotype-matched cases were considered potential transmission sites. We analyzed social networks stratified by genotype clustering status, with cases linked by shared locations, and compared network density by location type between clustered vs. non-clustered cases. Results Of 173 adults with TB, 131 (76%) were enrolled, 108 provided sputum, and 84/131 (78%) were MTB culture-positive: 52% (66/131) tested HIV-positive. Of 118 adult HH contacts, 105 (89%) were screened and 3 (2.5%) diagnosed with active TB. Overall, 33 TB cases (39%) belonged to 15 distinct MTB genotype-matched clusters. Within each cluster, no cases shared a HH or reported shared non-HH contacts. In 6/15 (40%) clusters, potential epidemiologic links were identified by spatial overlap at specific locations: 5/6 involved health care settings. Genotype-clustered TB social networks had significantly greater network density based on shared clinics (p<0.001) and decreased density based on shared marketplaces (p<0.001), compared to non-clustered networks. Conclusions In this molecular epidemiologic study, links between MTB genotype-matched cases were only identifiable via shared locations, healthcare locations in particular, rather than named contacts. This suggests most transmission is occurring between casual contacts, and emphasizes the need for improved infection control in healthcare settings in rural Africa. PMID:29438413
Semantic search during divergent thinking.
Hass, Richard W
2017-09-01
Divergent thinking, as a method of examining creative cognition, has not been adequately analyzed in the context of modern cognitive theories. This article casts divergent thinking responding in the context of theories of memory search. First, it was argued that divergent thinking tasks are similar to semantic fluency tasks, but are more constrained, and less well structured. Next, response time distributions from 54 participants were analyzed for temporal and semantic clustering. Participants responded to two prompts from the alternative uses test: uses for a brick and uses for a bottle, for two minutes each. Participants' cumulative response curves were negatively accelerating, in line with theories of search of associative memory. However, results of analyses of semantic and temporal clustering suggested that clustering is less evident in alternative uses responding compared to semantic fluency tasks. This suggests either that divergent thinking responding does not involve an exhaustive search through a clustered memory trace, but rather that the process is more exploratory, yielding fewer overall responses that tend to drift away from close associates of the divergent thinking prompt. Copyright © 2017 Elsevier B.V. All rights reserved.
Vanbinst, Kiran; Ceulemans, Eva; Peters, Lien; Ghesquière, Pol; De Smedt, Bert
2018-02-01
Although symbolic numerical magnitude processing skills are key for learning arithmetic, their developmental trajectories remain unknown. Therefore, we delineated during the first 3years of primary education (5-8years of age) groups with distinguishable developmental trajectories of symbolic numerical magnitude processing skills using a model-based clustering approach. Three clusters were identified and were labeled as inaccurate, accurate but slow, and accurate and fast. The clusters did not differ in age, sex, socioeconomic status, or IQ. We also tested whether these clusters differed in domain-specific (nonsymbolic magnitude processing and digit identification) and domain-general (visuospatial short-term memory, verbal working memory, and processing speed) cognitive competencies that might contribute to children's ability to (efficiently) process the numerical meaning of Arabic numerical symbols. We observed minor differences between clusters in these cognitive competencies except for verbal working memory for which no differences were observed. Follow-up analyses further revealed that the above-mentioned cognitive competencies did not merely account for the cluster differences in children's development of symbolic numerical magnitude processing skills, suggesting that other factors account for these individual differences. On the other hand, the three trajectories of symbolic numerical magnitude processing revealed remarkable and stable differences in children's arithmetic fact retrieval, which stresses the importance of symbolic numerical magnitude processing for learning arithmetic. Copyright © 2017 Elsevier Inc. All rights reserved.
Spatial memory in foraging games.
Kerster, Bryan E; Rhodes, Theo; Kello, Christopher T
2016-03-01
Foraging and foraging-like processes are found in spatial navigation, memory, visual search, and many other search functions in human cognition and behavior. Foraging is commonly theorized using either random or correlated movements based on Lévy walks, or a series of decisions to remain or leave proximal areas known as "patches". Neither class of model makes use of spatial memory, but search performance may be enhanced when information about searched and unsearched locations is encoded. A video game was developed to test the role of human spatial memory in a canonical foraging task. Analyses of search trajectories from over 2000 human players yielded evidence that foraging movements were inherently clustered, and that clustering was facilitated by spatial memory cues and influenced by memory for spatial locations of targets found. A simple foraging model is presented in which spatial memory is used to integrate aspects of Lévy-based and patch-based foraging theories to perform a kind of area-restricted search, and thereby enhance performance as search unfolds. Using only two free parameters, the model accounts for a variety of findings that individually support competing theories, but together they argue for the integration of spatial memory into theories of foraging. Copyright © 2015 Elsevier B.V. All rights reserved.
Audience-tuning effects on memory: the role of shared reality.
Echterhoff, Gerald; Higgins, E Tory; Groll, Stephan
2005-09-01
After tuning to an audience, communicators' own memories for the topic often reflect the biased view expressed in their messages. Three studies examined explanations for this bias. Memories for a target person were biased when feedback signaled the audience's successful identification of the target but not after failed identification (Experiment 1). Whereas communicators tuning to an in-group audience exhibited the bias, communicators tuning to an out-group audience did not (Experiment 2). These differences did not depend on communicators' mood but were mediated by communicators' trust in their audience's judgment about other people (Experiments 2 and 3). Message and memory were more closely associated for high than for low trusters. Apparently, audience-tuning effects depend on the communicators' experience of a shared reality.
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.
Neural Correlates of Sublexical Processing in Phonological Working Memory
ERIC Educational Resources Information Center
McGettigan, Carolyn; Warren, Jane E.; Eisner, Frank; Marshall, Chloe R.; Shanmugalingam, Pradheep; Scott, Sophie K.
2011-01-01
This study investigated links between working memory and speech processing systems. We used delayed pseudoword repetition in fMRI to investigate the neural correlates of sublexical structure in phonological working memory (pWM). We orthogonally varied the number of syllables and consonant clusters in auditory pseudowords and measured the neural…
Path Analysis Tests of Theoretical Models of Children's Memory Performance
ERIC Educational Resources Information Center
DeMarie, Darlene; Miller, Patricia H.; Ferron, John; Cunningham, Walter R.
2004-01-01
Path analysis was used to test theoretical models of relations among variables known to predict differences in children's memory--strategies, capacity, and metamemory. Children in kindergarten to fourth grade (chronological ages 5 to 11) performed different memory tasks. Several strategies (i.e., sorting, clustering, rehearsal, and self-testing)…
Olderbak, Sally; Hildebrandt, Andrea; Wilhelm, Oliver
2015-01-01
The shared decline in cognitive abilities, sensory functions (e.g., vision and hearing), and physical health with increasing age is well documented with some research attributing this shared age-related decline to a single common cause (e.g., aging brain). We evaluate the extent to which the common cause hypothesis predicts associations between vision and physical health with social cognition abilities specifically face perception and face memory. Based on a sample of 443 adults (17–88 years old), we test a series of structural equation models, including Multiple Indicator Multiple Cause (MIMIC) models, and estimate the extent to which vision and self-reported physical health are related to face perception and face memory through a common factor, before and after controlling for their fluid cognitive component and the linear effects of age. Results suggest significant shared variance amongst these constructs, with a common factor explaining some, but not all, of the shared age-related variance. Also, we found that the relations of face perception, but not face memory, with vision and physical health could be completely explained by fluid cognition. Overall, results suggest that a single common cause explains most, but not all age-related shared variance with domain specific aging mechanisms evident. PMID:26321998
Solutions and debugging for data consistency in multiprocessors with noncoherent caches
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bernstein, D.; Mendelson, B.; Breternitz, M. Jr.
1995-02-01
We analyze two important problems that arise in shared-memory multiprocessor systems. The stale data problem involves ensuring that data items in local memory of individual processors are current, independent of writes done by other processors. False sharing occurs when two processors have copies of the same shared data block but update different portions of the block. The false sharing problem involves guaranteeing that subsequent writes are properly combined. In modern architectures these problems are usually solved in hardware, by exploiting mechanisms for hardware controlled cache consistency. This leads to more expensive and nonscalable designs. Therefore, we are concentrating on softwaremore » methods for ensuring cache consistency that would allow for affordable and scalable multiprocessing systems. Unfortunately, providing software control is nontrivial, both for the compiler writer and for the application programmer. For this reason we are developing a debugging environment that will facilitate the development of compiler-based techniques and will help the programmer to tune his or her application using explicit cache management mechanisms. We extend the notion of a race condition for IBM Shared Memory System POWER/4, taking into consideration its noncoherent caches, and propose techniques for detection of false sharing problems. Identification of the stale data problem is discussed as well, and solutions are suggested.« less
NASA Astrophysics Data System (ADS)
Guan, W.; Cheng, X.; Huang, J.; Huber, G.; Li, W.; McCammon, J. A.; Zhang, B.
2018-06-01
RPYFMM is a software package for the efficient evaluation of the potential field governed by the Rotne-Prager-Yamakawa (RPY) tensor interactions in biomolecular hydrodynamics simulations. In our algorithm, the RPY tensor is decomposed as a linear combination of four Laplace interactions, each of which is evaluated using the adaptive fast multipole method (FMM) (Greengard and Rokhlin, 1997) where the exponential expansions are applied to diagonalize the multipole-to-local translation operators. RPYFMM offers a unified execution on both shared and distributed memory computers by leveraging the DASHMM library (DeBuhr et al., 2016, 2018). Preliminary numerical results show that the interactions for a molecular system of 15 million particles (beads) can be computed within one second on a Cray XC30 cluster using 12,288 cores, while achieving approximately 54% strong-scaling efficiency.
NASA Astrophysics Data System (ADS)
Payne, Joshua; Taitano, William; Knoll, Dana; Liebs, Chris; Murthy, Karthik; Feltman, Nicolas; Wang, Yijie; McCarthy, Colleen; Cieren, Emanuel
2012-10-01
In order to solve problems such as the ion coalescence and slow MHD shocks fully kinetically we developed a fully implicit 2D energy and charge conserving electromagnetic PIC code, PlasmaApp2D. PlasmaApp2D differs from previous implicit PIC implementations in that it will utilize advanced architectures such as GPUs and shared memory CPU systems, with problems too large to fit into cache. PlasmaApp2D will be a hybrid CPU-GPU code developed primarily to run on the DARWIN cluster at LANL utilizing four 12-core AMD Opteron CPUs and two NVIDIA Tesla GPUs per node. MPI will be used for cross-node communication, OpenMP will be used for on-node parallelism, and CUDA will be used for the GPUs. Development progress and initial results will be presented.
Automatic Generation of OpenMP Directives and Its Application to Computational Fluid Dynamics Codes
NASA Technical Reports Server (NTRS)
Yan, Jerry; Jin, Haoqiang; Frumkin, Michael; Yan, Jerry (Technical Monitor)
2000-01-01
The shared-memory programming model is a very effective way to achieve parallelism on shared memory parallel computers. As great progress was made in hardware and software technologies, performance of parallel programs with compiler directives has demonstrated large improvement. The introduction of OpenMP directives, the industrial standard for shared-memory programming, has minimized the issue of portability. In this study, we have extended CAPTools, a computer-aided parallelization toolkit, to automatically generate OpenMP-based parallel programs with nominal user assistance. We outline techniques used in the implementation of the tool and discuss the application of this tool on the NAS Parallel Benchmarks and several computational fluid dynamics codes. This work demonstrates the great potential of using the tool to quickly port parallel programs and also achieve good performance that exceeds some of the commercial tools.
Oak Ridge Institutional Cluster Autotune Test Drive Report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jibonananda, Sanyal; New, Joshua Ryan
2014-02-01
The Oak Ridge Institutional Cluster (OIC) provides general purpose computational resources for the ORNL staff to run computation heavy jobs that are larger than desktop applications but do not quite require the scale and power of the Oak Ridge Leadership Computing Facility (OLCF). This report details the efforts made and conclusions derived in performing a short test drive of the cluster resources on Phase 5 of the OIC. EnergyPlus was used in the analysis as a candidate user program and the overall software environment was evaluated against anticipated challenges experienced with resources such as the shared memory-Nautilus (JICS) and Titanmore » (OLCF). The OIC performed within reason and was found to be acceptable in the context of running EnergyPlus simulations. The number of cores per node and the availability of scratch space per node allow non-traditional desktop focused applications to leverage parallel ensemble execution. Although only individual runs of EnergyPlus were executed, the software environment on the OIC appeared suitable to run ensemble simulations with some modifications to the Autotune workflow. From a standpoint of general usability, the system supports common Linux libraries, compilers, standard job scheduling software (Torque/Moab), and the OpenMPI library (the only MPI library) for MPI communications. The file system is a Panasas file system which literature indicates to be an efficient file system.« less
HeinzelCluster: accelerated reconstruction for FORE and OSEM3D.
Vollmar, S; Michel, C; Treffert, J T; Newport, D F; Casey, M; Knöss, C; Wienhard, K; Liu, X; Defrise, M; Heiss, W D
2002-08-07
Using iterative three-dimensional (3D) reconstruction techniques for reconstruction of positron emission tomography (PET) is not feasible on most single-processor machines due to the excessive computing time needed, especially so for the large sinogram sizes of our high-resolution research tomograph (HRRT). In our first approach to speed up reconstruction time we transform the 3D scan into the format of a two-dimensional (2D) scan with sinograms that can be reconstructed independently using Fourier rebinning (FORE) and a fast 2D reconstruction method. On our dedicated reconstruction cluster (seven four-processor systems, Intel PIII@700 MHz, switched fast ethernet and Myrinet, Windows NT Server), we process these 2D sinograms in parallel. We have achieved a speedup > 23 using 26 processors and also compared results for different communication methods (RPC, Syngo, Myrinet GM). The other approach is to parallelize OSEM3D (implementation of C Michel), which has produced the best results for HRRT data so far and is more suitable for an adequate treatment of the sinogram gaps that result from the detector geometry of the HRRT. We have implemented two levels of parallelization for four dedicated cluster (a shared memory fine-grain level on each node utilizing all four processors and a coarse-grain level allowing for 15 nodes) reducing the time for one core iteration from over 7 h to about 35 min.
Static Memory Deduplication for Performance Optimization in Cloud Computing.
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.
Static Memory Deduplication for Performance Optimization in Cloud Computing
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
Brain structure and function correlates of cognitive subtypes in schizophrenia.
Geisler, Daniel; Walton, Esther; Naylor, Melissa; Roessner, Veit; Lim, Kelvin O; Charles Schulz, S; Gollub, Randy L; Calhoun, Vince D; Sponheim, Scott R; Ehrlich, Stefan
2015-10-30
Stable neuropsychological deficits may provide a reliable basis for identifying etiological subtypes of schizophrenia. The aim of this study was to identify clusters of individuals with schizophrenia based on dimensions of neuropsychological performance, and to characterize their neural correlates. We acquired neuropsychological data as well as structural and functional magnetic resonance imaging from 129 patients with schizophrenia and 165 healthy controls. We derived eight cognitive dimensions and subsequently applied a cluster analysis to identify possible schizophrenia subtypes. Analyses suggested the following four cognitive clusters of schizophrenia: (1) Diminished Verbal Fluency, (2) Diminished Verbal Memory and Poor Motor Control, (3) Diminished Face Memory and Slowed Processing, and (4) Diminished Intellectual Function. The clusters were characterized by a specific pattern of structural brain changes in areas such as Wernicke's area, lingual gyrus and occipital face area, and hippocampus as well as differences in working memory-elicited neural activity in several fronto-parietal brain regions. Separable measures of cognitive function appear to provide a method for deriving cognitive subtypes meaningfully related to brain structure and function. Because the present study identified brain-based neural correlates of the cognitive clusters, the proposed groups of individuals with schizophrenia have some external validity. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Scheduling for Locality in Shared-Memory Multiprocessors
1993-05-01
Submitted in Partial Fulfillment of the Requirements for the Degree ’)iIC Q(JALfryT INSPECTED 5 DOCTOR OF PHILOSOPHY I Accesion For Supervised by NTIS CRAM... architecture on parallel program performance, explain the implications of this trend on popular parallel programming models, and propose system software to 0...decomoosition and scheduling algorithms. I. SUIUECT TERMS IS. NUMBER OF PAGES shared-memory multiprocessors; architecture trends; loop 110 scheduling
Advanced Development of Certified OS Kernels
2015-06-01
It provides an infrastructure to map a physical page into multiple processes’ page maps in different address spaces. Their ownership mechanism ensures...of their shared memory infrastructure . Trap module The trap module specifies the behaviors of exception handlers and mCertiKOS system calls. In...layers), 1 pm for the shared memory infrastructure (3 layers), 3.5 pm for the thread management (10 layers), 1 pm for the process management (4 layers
6 DOF Nonlinear AUV Simulation Toolbox
1997-01-01
is to supply a flexible 3D -simulation platform for motion visualization, in-lab debugging and testing of mission-specific strategies as well as those...Explorer are modular designed [Smith] in order to cut time and cost for vehicle recontlguration. A flexible 3D -simulation platform is desired to... 3D models. Current implemented modules include a nonlinear dynamic model for the OEX, shared memory and semaphore manager tools, shared memory monitor
A cache-aided multiprocessor rollback recovery scheme
NASA Technical Reports Server (NTRS)
Wu, Kun-Lung; Fuchs, W. Kent
1989-01-01
This paper demonstrates how previous uniprocessor cache-aided recovery schemes can be applied to multiprocessor architectures, for recovering from transient processor failures, utilizing private caches and a global shared memory. As with cache-aided uniprocessor recovery, the multiprocessor cache-aided recovery scheme of this paper can be easily integrated into standard bus-based snoopy cache coherence protocols. A consistent shared memory state is maintained without the necessity of global check-pointing.
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.
Hawkins, Misty A.W.; Schaefer, Julie T.; Gunstad, John; Dolansky, Mary A.; Redle, Joseph D.; Josephson, Richard; Moore, Shirley M.; Hughes, Joel W.
2014-01-01
Purpose To determine whether patients with heart failure (HF) have distinct profiles of cognitive impairment. Background Cognitive impairment is common in HF. Recent work found three cognitive profiles in HF patients— (1) intact, (2) impaired, and (3) memory-impaired. We examined the reproducibility of these profiles and clarified mechanisms. Methods HF patients (68.6±9.7years; N=329) completed neuropsychological testing. Composite scores were created for cognitive domains and used to identify clusters via agglomerative-hierarchical cluster analysis. Results A 3-cluster solution emerged. Cluster 1 (n=109) had intact cognition. Cluster 2 (n=123) was impaired across all domains. Cluster 3 (n=97) had impaired memory only. Clusters differed in age, race, education, SES, IQ, BMI, and diabetes (ps ≤.026) but not in mood, anxiety, cardiovascular, or pulmonary disease (ps≥.118). Conclusions We replicated three distinct patterns of cognitive function in persons with HF. These profiles may help providers offer tailored care to patients with different cognitive and clinical needs. PMID:25510559
Cheung, Wing-Yee; Wildschut, Tim; Sedikides, Constantine
2018-02-01
We compared and contrasted nostalgia with rumination and counterfactual thinking in terms of their autobiographical memory functions. Specifically, we assessed individual differences in nostalgia, rumination, and counterfactual thinking, which we then linked to self-reported functions or uses of autobiographical memory (Self-Regard, Boredom Reduction, Death Preparation, Intimacy Maintenance, Conversation, Teach/Inform, and Bitterness Revival). We tested which memory functions are shared and which are uniquely linked to nostalgia. The commonality among nostalgia, rumination, and counterfactual thinking resides in their shared positive associations with all memory functions: individuals who evinced a stronger propensity towards past-oriented thought (as manifested in nostalgia, rumination, and counterfactual thinking) reported greater overall recruitment of memories in the service of present functioning. The uniqueness of nostalgia resides in its comparatively strong positive associations with Intimacy Maintenance, Teach/Inform, and Self-Regard and weak association with Bitterness Revival. In all, nostalgia possesses a more positive functional signature than do rumination and counterfactual thinking.
Mnemonic convergence in social networks: The emergent properties of cognition at a collective level.
Coman, Alin; Momennejad, Ida; Drach, Rae D; Geana, Andra
2016-07-19
The development of shared memories, beliefs, and norms is a fundamental characteristic of human communities. These emergent outcomes are thought to occur owing to a dynamic system of information sharing and memory updating, which fundamentally depends on communication. Here we report results on the formation of collective memories in laboratory-created communities. We manipulated conversational network structure in a series of real-time, computer-mediated interactions in fourteen 10-member communities. The results show that mnemonic convergence, measured as the degree of overlap among community members' memories, is influenced by both individual-level information-processing phenomena and by the conversational social network structure created during conversational recall. By studying laboratory-created social networks, we show how large-scale social phenomena (i.e., collective memory) can emerge out of microlevel local dynamics (i.e., mnemonic reinforcement and suppression effects). The social-interactionist approach proposed herein points to optimal strategies for spreading information in social networks and provides a framework for measuring and forging collective memories in communities of individuals.
Moreau, Noémie; Viallet, François; Champagne-Lavau, Maud
2013-09-01
Theory of mind (TOM) refers to the ability to infer one's own and other's mental states. Growing evidence highlighted the presence of impairment on the most complex TOM tasks in Alzheimer disease (AD). However, how TOM deficit is related to other cognitive dysfunctions and more specifically to episodic memory impairment - the prominent feature of this disease - is still under debate. Recent neuroanatomical findings have shown that remembering past events and inferring others' states of mind share the same cerebral network suggesting the two abilities share a common process .This paper proposes to review emergent evidence of TOM impairment in AD patients and to discuss the evidence of a relationship between TOM and episodic memory. We will discuss about AD patients' deficit in TOM being possibly related to their difficulties in recollecting memories of past social interactions. Copyright © 2013 Elsevier B.V. All rights reserved.
Mental time travel and the shaping of the human mind
Suddendorf, Thomas; Addis, Donna Rose; Corballis, Michael C.
2009-01-01
Episodic memory, enabling conscious recollection of past episodes, can be distinguished from semantic memory, which stores enduring facts about the world. Episodic memory shares a core neural network with the simulation of future episodes, enabling mental time travel into both the past and the future. The notion that there might be something distinctly human about mental time travel has provoked ingenious attempts to demonstrate episodic memory or future simulation in non-human animals, but we argue that they have not yet established a capacity comparable to the human faculty. The evolution of the capacity to simulate possible future events, based on episodic memory, enhanced fitness by enabling action in preparation of different possible scenarios that increased present or future survival and reproduction chances. Human language may have evolved in the first instance for the sharing of past and planned future events, and, indeed, fictional ones, further enhancing fitness in social settings. PMID:19528013
A communication-avoiding, hybrid-parallel, rank-revealing orthogonalization method.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hoemmen, Mark
2010-11-01
Orthogonalization consumes much of the run time of many iterative methods for solving sparse linear systems and eigenvalue problems. Commonly used algorithms, such as variants of Gram-Schmidt or Householder QR, have performance dominated by communication. Here, 'communication' includes both data movement between the CPU and memory, and messages between processors in parallel. Our Tall Skinny QR (TSQR) family of algorithms requires asymptotically fewer messages between processors and data movement between CPU and memory than typical orthogonalization methods, yet achieves the same accuracy as Householder QR factorization. Furthermore, in block orthogonalizations, TSQR is faster and more accurate than existing approaches formore » orthogonalizing the vectors within each block ('normalization'). TSQR's rank-revealing capability also makes it useful for detecting deflation in block iterative methods, for which existing approaches sacrifice performance, accuracy, or both. We have implemented a version of TSQR that exploits both distributed-memory and shared-memory parallelism, and supports real and complex arithmetic. Our implementation is optimized for the case of orthogonalizing a small number (5-20) of very long vectors. The shared-memory parallel component uses Intel's Threading Building Blocks, though its modular design supports other shared-memory programming models as well, including computation on the GPU. Our implementation achieves speedups of 2 times or more over competing orthogonalizations. It is available now in the development branch of the Trilinos software package, and will be included in the 10.8 release.« less
Shared prefetching to reduce execution skew in multi-threaded systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Eichenberger, Alexandre E; Gunnels, John A
Mechanisms are provided for optimizing code to perform prefetching of data into a shared memory of a computing device that is shared by a plurality of threads that execute on the computing device. A memory stream of a portion of code that is shared by the plurality of threads is identified. A set of prefetch instructions is distributed across the plurality of threads. Prefetch instructions are inserted into the instruction sequences of the plurality of threads such that each instruction sequence has a separate sub-portion of the set of prefetch instructions, thereby generating optimized code. Executable code is generated basedmore » on the optimized code and stored in a storage device. The executable code, when executed, performs the prefetches associated with the distributed set of prefetch instructions in a shared manner across the plurality of threads.« less
NASA Astrophysics Data System (ADS)
Salditch, L.; Brooks, E. M.; Stein, S.; Spencer, B. D.; Campbell, M. R.
2017-12-01
A challenge for earthquake hazard assessment is that geologic records often show large earthquakes occurring in temporal clusters separated by periods of quiescence. For example, in Cascadia, a paleoseismic record going back 10,000 years shows four to five clusters separated by approximately 1,000 year gaps. If we are still in the cluster that began 1700 years ago, a large earthquake is likely to happen soon. If the cluster has ended, a great earthquake is less likely. For a Gaussian distribution of recurrence times, the probability of an earthquake in the next 50 years is six times larger if we are still in the most recent cluster. Earthquake hazard assessments typically employ one of two recurrence models, neither of which directly incorporate clustering. In one, earthquake probability is time-independent and modeled as Poissonian, so an earthquake is equally likely at any time. The fault has no "memory" because when a prior earthquake occurred has no bearing on when the next will occur. The other common model is a time-dependent earthquake cycle in which the probability of an earthquake increases with time until one happens, after which the probability resets to zero. Because the probability is reset after each earthquake, the fault "remembers" only the last earthquake. This approach can be used with any assumed probability density function for recurrence times. We propose an alternative, Long-Term Fault Memory (LTFM), a modified earthquake cycle model where the probability of an earthquake increases with time until one happens, after which it decreases, but not necessarily to zero. Hence the probability of the next earthquake depends on the fault's history over multiple cycles, giving "long-term memory". Physically, this reflects an earthquake releasing only part of the elastic strain stored on the fault. We use the LTFM to simulate earthquake clustering along the San Andreas Fault and Cascadia. In some portions of the simulated earthquake history, events would appear quasiperiodic, while at other times, the events can appear more Poissonian. Hence a given paleoseismic or instrumental record may not reflect the long-term seismicity of a fault, which has important implications for hazard assessment.
Mechanisms of Age-Related Decline in Memory Search across the Adult Life Span
ERIC Educational Resources Information Center
Hills, Thomas T.; Mata, Rui; Wilke, Andreas; Samanez-Larkin, Gregory R.
2013-01-01
Three alternative mechanisms for age-related decline in memory search have been proposed, which result from either reduced processing speed (global slowing hypothesis), overpersistence on categories (cluster-switching hypothesis), or the inability to maintain focus on local cues related to a decline in working memory (cue-maintenance hypothesis).…
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.
Rasmussen, Anne S; Habermas, Tilmann
2011-08-01
According to theory, autobiographical memory serves three broad functions of overall usage: directive, self, and social. However, there is evidence to suggest that the tripartite model may be better conceptualised in terms of a four-factor model with two social functions. In the present study we examined the two models in Danish and German samples, using the Thinking About Life Experiences Questionnaire (TALE; Bluck, Alea, Habermas, & Rubin, 2005), which measures the overall usage of the three functions generalised across concrete memories. Confirmatory factor analysis supported the four-factor model and rejected the theoretical three-factor model in both samples. The results are discussed in relation to cultural differences in overall autobiographical memory usage as well as sharing versus non-sharing aspects of social remembering.
Automated quantitative muscle biopsy analysis system
NASA Technical Reports Server (NTRS)
Castleman, Kenneth R. (Inventor)
1980-01-01
An automated system to aid the diagnosis of neuromuscular diseases by producing fiber size histograms utilizing histochemically stained muscle biopsy tissue. Televised images of the microscopic fibers are processed electronically by a multi-microprocessor computer, which isolates, measures, and classifies the fibers and displays the fiber size distribution. The architecture of the multi-microprocessor computer, which is iterated to any required degree of complexity, features a series of individual microprocessors P.sub.n each receiving data from a shared memory M.sub.n-1 and outputing processed data to a separate shared memory M.sub.n+1 under control of a program stored in dedicated memory M.sub.n.
Experimental evaluation of multiprocessor cache-based error recovery
NASA Technical Reports Server (NTRS)
Janssens, Bob; Fuchs, W. K.
1991-01-01
Several variations of cache-based checkpointing for rollback error recovery in shared-memory multiprocessors have been recently developed. By modifying the cache replacement policy, these techniques use the inherent redundancy in the memory hierarchy to periodically checkpoint the computation state. Three schemes, different in the manner in which they avoid rollback propagation, are evaluated. By simulation with address traces from parallel applications running on an Encore Multimax shared-memory multiprocessor, the performance effect of integrating the recovery schemes in the cache coherence protocol are evaluated. The results indicate that the cache-based schemes can provide checkpointing capability with low performance overhead but uncontrollable high variability in the checkpoint interval.
The FORCE - A highly portable parallel programming language
NASA Technical Reports Server (NTRS)
Jordan, Harry F.; Benten, Muhammad S.; Alaghband, Gita; Jakob, Ruediger
1989-01-01
This paper explains why the FORCE parallel programming language is easily portable among six different shared-memory multiprocessors, and how a two-level macro preprocessor makes it possible to hide low-level machine dependencies and to build machine-independent high-level constructs on top of them. These FORCE constructs make it possible to write portable parallel programs largely independent of the number of processes and the specific shared-memory multiprocessor executing them.
The FORCE: A highly portable parallel programming language
NASA Technical Reports Server (NTRS)
Jordan, Harry F.; Benten, Muhammad S.; Alaghband, Gita; Jakob, Ruediger
1989-01-01
Here, it is explained why the FORCE parallel programming language is easily portable among six different shared-memory microprocessors, and how a two-level macro preprocessor makes it possible to hide low level machine dependencies and to build machine-independent high level constructs on top of them. These FORCE constructs make it possible to write portable parallel programs largely independent of the number of processes and the specific shared memory multiprocessor executing them.
Performing a local reduction operation on a parallel computer
Blocksome, Michael A; Faraj, Daniel A
2013-06-04
A parallel computer including compute nodes, each including two reduction processing cores, a network write processing core, and a network read processing core, each processing core assigned an input buffer. Copying, in interleaved chunks by the reduction processing cores, contents of the reduction processing cores' input buffers to an interleaved buffer in shared memory; copying, by one of the reduction processing cores, contents of the network write processing core's input buffer to shared memory; copying, by another of the reduction processing cores, contents of the network read processing core's input buffer to shared memory; and locally reducing in parallel by the reduction processing cores: the contents of the reduction processing core's input buffer; every other interleaved chunk of the interleaved buffer; the copied contents of the network write processing core's input buffer; and the copied contents of the network read processing core's input buffer.
Performing a local reduction operation on a parallel computer
Blocksome, Michael A.; Faraj, Daniel A.
2012-12-11
A parallel computer including compute nodes, each including two reduction processing cores, a network write processing core, and a network read processing core, each processing core assigned an input buffer. Copying, in interleaved chunks by the reduction processing cores, contents of the reduction processing cores' input buffers to an interleaved buffer in shared memory; copying, by one of the reduction processing cores, contents of the network write processing core's input buffer to shared memory; copying, by another of the reduction processing cores, contents of the network read processing core's input buffer to shared memory; and locally reducing in parallel by the reduction processing cores: the contents of the reduction processing core's input buffer; every other interleaved chunk of the interleaved buffer; the copied contents of the network write processing core's input buffer; and the copied contents of the network read processing core's input buffer.
... this page: //medlineplus.gov/ency/article/003257.htm Memory loss To use the sharing features on this ... Bethesda, MD 20894 U.S. Department of Health and Human Services National Institutes of Health Page last updated: ...
Hutchens, Rachel L; Kinsella, Glynda J; Ong, Ben; Pike, Kerryn E; Clare, Linda; Ames, David; Saling, Michael M; Storey, Elsdon; Mullaly, Elizabeth; Rand, Elizabeth; Parsons, Samuel
2013-11-01
Little information is available regarding the extent of strategy use and factors that affect strategy use in amnestic mild cognitive impairment (aMCI). This study aimed to compare spontaneous strategy use and beliefs about the controllability of memory between aMCI and healthy older adult (HOA) samples and to explore the relationships between beliefs, strategy use, and memory performance for both groups. The aMCI and HOA groups each composed of 60 individuals matched for age and education. The Memory Controllability Inventory was used to assess control beliefs, and the extent of semantic clustering on a list-learning task provided a measure of spontaneous strategy use. The aMCI group endorsed lower control beliefs and demonstrated poorer semantic clustering and memory performance compared with the HOA group. Although strategy use partially mediated the control beliefs-memory performance relationship for the HOA group, this was not replicated for the aMCI group. Despite the weak relationship between control beliefs and strategy use, and control beliefs and memory performance for the aMCI group, the strong relationship between strategy use and memory performance provides impetus for further research into factors that can be used as a means of enhancing strategy use in interventions for aMCI.
We Remember, We Forget: Collaborative Remembering in Older Couples
ERIC Educational Resources Information Center
Harris, Celia B.; Keil, Paul G.; Sutton, John; Barnier, Amanda J.; McIlwain, Doris J. F.
2011-01-01
Transactive memory theory describes the processes by which benefits for memory can occur when remembering is shared in dyads or groups. In contrast, cognitive psychology experiments demonstrate that social influences on memory disrupt and inhibit individual recall. However, most research in cognitive psychology has focused on groups of strangers…
76 FR 12821 - 150th Anniversary of the Inauguration of Abraham Lincoln
Federal Register 2010, 2011, 2012, 2013, 2014
2011-03-09
... together by shared memories and common hopes. As we observe the 150th anniversary of his Inauguration, we... his memory enabled America to move beyond a young collection of States to become a free and unified... memory and uphold the principles he so nobly advanced. [[Page 12822
Expert Systems on Multiprocessor Architectures. Volume 2. Technical Reports
1991-06-01
Report RC 12936 (#58037). IBM T. J. Wartson Reiearch Center. July 1987. Alan Jay Smith. Cache memories. Coniputing Sitrry., 1.1(3): I.3-5:30...basic-shared is an instrument for ashared memory design. The components panels are processor- qload-scrolling-bar-panel, memory-qload-scrolling-bar-panel
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.
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.
The potential of multi-port optical memories in digital computing
NASA Technical Reports Server (NTRS)
Alford, C. O.; Gaylord, T. K.
1975-01-01
A high-capacity memory with a relatively high data transfer rate and multi-port simultaneous access capability may serve as the basis for new computer architectures. The implementation of a multi-port optical memory is discussed. Several computer structures are presented that might profitably use such a memory. These structures include (1) a simultaneous record access system, (2) a simultaneously shared memory computer system, and (3) a parallel digital processing structure.
FPGA cluster for high-performance AO real-time control system
NASA Astrophysics Data System (ADS)
Geng, Deli; Goodsell, Stephen J.; Basden, Alastair G.; Dipper, Nigel A.; Myers, Richard M.; Saunter, Chris D.
2006-06-01
Whilst the high throughput and low latency requirements for the next generation AO real-time control systems have posed a significant challenge to von Neumann architecture processor systems, the Field Programmable Gate Array (FPGA) has emerged as a long term solution with high performance on throughput and excellent predictability on latency. Moreover, FPGA devices have highly capable programmable interfacing, which lead to more highly integrated system. Nevertheless, a single FPGA is still not enough: multiple FPGA devices need to be clustered to perform the required subaperture processing and the reconstruction computation. In an AO real-time control system, the memory bandwidth is often the bottleneck of the system, simply because a vast amount of supporting data, e.g. pixel calibration maps and the reconstruction matrix, need to be accessed within a short period. The cluster, as a general computing architecture, has excellent scalability in processing throughput, memory bandwidth, memory capacity, and communication bandwidth. Problems, such as task distribution, node communication, system verification, are discussed.
Alden, Eva C; Cobia, Derin J; Reilly, James L; Smith, Matthew J
2015-10-01
Schizophrenia is characterized by impairment in multiple aspects of community functioning. Available literature suggests that community functioning may be enhanced through cognitive remediation, however, evidence is limited regarding whether specific neurocognitive domains may be treatment targets. We characterized schizophrenia subjects based on their level of community functioning through cluster analysis in an effort to identify whether specific neurocognitive domains were associated with variation in functioning. Schizophrenia (SCZ, n=60) and control (CON, n=45) subjects completed a functional capacity task, social competence role-play, functional attainment interview, and a neuropsychological battery. Multiple cluster analytic techniques were used on the measures of functioning in the schizophrenia subjects to generate functionally-defined subgroups. MANOVA evaluated between-group differences in neurocognition. The cluster analysis revealed two distinct groups, consisting of 36 SCZ characterized by high levels of community functioning (HF-SCZ) and 24 SCZ with low levels of community functioning (LF-SCZ). There was a main group effect for neurocognitive performance (p<0.001) with CON outperforming both SCZ groups in all neurocognitive domains. Post-hoc tests revealed that HF-SCZ had higher verbal working memory compared to LF-SCZ (p≤0.05, Cohen's d=0.78) but the two groups did not differ in remaining domains. The cluster analysis classified schizophrenia subjects in HF-SCZ and LF-SCZ using a multidimensional assessment of community functioning. Moreover, HF-SCZ demonstrated rather preserved verbal working memory relative to LF-SCZ. The results suggest that verbal working memory may play a critical role in community functioning, and is a potential cognitive treatment target for schizophrenia subjects. Copyright © 2015 Elsevier B.V. All rights reserved.
Milestoning with coarse memory
NASA Astrophysics Data System (ADS)
Hawk, Alexander T.
2013-04-01
Milestoning is a method used to calculate the kinetics of molecular processes occurring on timescales inaccessible to traditional molecular dynamics (MD) simulations. In the method, the phase space of the system is partitioned by milestones (hypersurfaces), trajectories are initialized on each milestone, and short MD simulations are performed to calculate transitions between neighboring milestones. Long trajectories of the system are then reconstructed with a semi-Markov process from the observed statistics of transition. The procedure is typically justified by the assumption that trajectories lose memory between crossing successive milestones. Here we present Milestoning with Coarse Memory (MCM), a generalization of Milestoning that relaxes the memory loss assumption of conventional Milestoning. In the method, milestones are defined and sample transitions are calculated in the standard Milestoning way. Then, after it is clear where trajectories sample milestones, the milestones are broken up into distinct neighborhoods (clusters), and each sample transition is associated with two clusters: the cluster containing the coordinates the trajectory was initialized in, and the cluster (on the terminal milestone) containing trajectory's final coordinates. Long trajectories of the system are then reconstructed with a semi-Markov process in an extended state space built from milestone and cluster indices. To test the method, we apply it to a process that is particularly ill suited for Milestoning: the dynamics of a polymer confined to a narrow cylinder. We show that Milestoning calculations of both the mean first passage time and the mean transit time of reversal—which occurs when the end-to-end vector reverses direction—are significantly improved when MCM is applied. Finally, we note the overhead of performing MCM on top of conventional Milestoning is negligible.
Methodology for fast detection of false sharing in threaded scientific codes
Chung, I-Hsin; Cong, Guojing; Murata, Hiroki; Negishi, Yasushi; Wen, Hui-Fang
2014-11-25
A profiling tool identifies a code region with a false sharing potential. A static analysis tool classifies variables and arrays in the identified code region. A mapping detection library correlates memory access instructions in the identified code region with variables and arrays in the identified code region while a processor is running the identified code region. The mapping detection library identifies one or more instructions at risk, in the identified code region, which are subject to an analysis by a false sharing detection library. A false sharing detection library performs a run-time analysis of the one or more instructions at risk while the processor is re-running the identified code region. The false sharing detection library determines, based on the performed run-time analysis, whether two different portions of the cache memory line are accessed by the generated binary code.
Clusternomics: Integrative context-dependent clustering for heterogeneous datasets
Wernisch, Lorenz
2017-01-01
Integrative clustering is used to identify groups of samples by jointly analysing multiple datasets describing the same set of biological samples, such as gene expression, copy number, methylation etc. Most existing algorithms for integrative clustering assume that there is a shared consistent set of clusters across all datasets, and most of the data samples follow this structure. However in practice, the structure across heterogeneous datasets can be more varied, with clusters being joined in some datasets and separated in others. In this paper, we present a probabilistic clustering method to identify groups across datasets that do not share the same cluster structure. The proposed algorithm, Clusternomics, identifies groups of samples that share their global behaviour across heterogeneous datasets. The algorithm models clusters on the level of individual datasets, while also extracting global structure that arises from the local cluster assignments. Clusters on both the local and the global level are modelled using a hierarchical Dirichlet mixture model to identify structure on both levels. We evaluated the model both on simulated and on real-world datasets. The simulated data exemplifies datasets with varying degrees of common structure. In such a setting Clusternomics outperforms existing algorithms for integrative and consensus clustering. In a real-world application, we used the algorithm for cancer subtyping, identifying subtypes of cancer from heterogeneous datasets. We applied the algorithm to TCGA breast cancer dataset, integrating gene expression, miRNA expression, DNA methylation and proteomics. The algorithm extracted clinically meaningful clusters with significantly different survival probabilities. We also evaluated the algorithm on lung and kidney cancer TCGA datasets with high dimensionality, again showing clinically significant results and scalability of the algorithm. PMID:29036190
Clusternomics: Integrative context-dependent clustering for heterogeneous datasets.
Gabasova, Evelina; Reid, John; Wernisch, Lorenz
2017-10-01
Integrative clustering is used to identify groups of samples by jointly analysing multiple datasets describing the same set of biological samples, such as gene expression, copy number, methylation etc. Most existing algorithms for integrative clustering assume that there is a shared consistent set of clusters across all datasets, and most of the data samples follow this structure. However in practice, the structure across heterogeneous datasets can be more varied, with clusters being joined in some datasets and separated in others. In this paper, we present a probabilistic clustering method to identify groups across datasets that do not share the same cluster structure. The proposed algorithm, Clusternomics, identifies groups of samples that share their global behaviour across heterogeneous datasets. The algorithm models clusters on the level of individual datasets, while also extracting global structure that arises from the local cluster assignments. Clusters on both the local and the global level are modelled using a hierarchical Dirichlet mixture model to identify structure on both levels. We evaluated the model both on simulated and on real-world datasets. The simulated data exemplifies datasets with varying degrees of common structure. In such a setting Clusternomics outperforms existing algorithms for integrative and consensus clustering. In a real-world application, we used the algorithm for cancer subtyping, identifying subtypes of cancer from heterogeneous datasets. We applied the algorithm to TCGA breast cancer dataset, integrating gene expression, miRNA expression, DNA methylation and proteomics. The algorithm extracted clinically meaningful clusters with significantly different survival probabilities. We also evaluated the algorithm on lung and kidney cancer TCGA datasets with high dimensionality, again showing clinically significant results and scalability of the algorithm.
ERIC Educational Resources Information Center
Messer, Marielle H.; Leseman, Paul P. M.; Boom, Jan; Mayo, Aziza Y.
2010-01-01
The current study examined to what extent information in long-term memory concerning the distribution of phoneme clusters in a language, so-called long-term phonotactic knowledge, increased the capacity of verbal short-term memory in young language learners and, through increased verbal short-term memory capacity, supported these children's first…
A Multi-Level Parallelization Concept for High-Fidelity Multi-Block Solvers
NASA Technical Reports Server (NTRS)
Hatay, Ferhat F.; Jespersen, Dennis C.; Guruswamy, Guru P.; Rizk, Yehia M.; Byun, Chansup; Gee, Ken; VanDalsem, William R. (Technical Monitor)
1997-01-01
The integration of high-fidelity Computational Fluid Dynamics (CFD) analysis tools with the industrial design process benefits greatly from the robust implementations that are transportable across a wide range of computer architectures. In the present work, a hybrid domain-decomposition and parallelization concept was developed and implemented into the widely-used NASA multi-block Computational Fluid Dynamics (CFD) packages implemented in ENSAERO and OVERFLOW. The new parallel solver concept, PENS (Parallel Euler Navier-Stokes Solver), employs both fine and coarse granularity in data partitioning as well as data coalescing to obtain the desired load-balance characteristics on the available computer platforms. This multi-level parallelism implementation itself introduces no changes to the numerical results, hence the original fidelity of the packages are identically preserved. The present implementation uses the Message Passing Interface (MPI) library for interprocessor message passing and memory accessing. By choosing an appropriate combination of the available partitioning and coalescing capabilities only during the execution stage, the PENS solver becomes adaptable to different computer architectures from shared-memory to distributed-memory platforms with varying degrees of parallelism. The PENS implementation on the IBM SP2 distributed memory environment at the NASA Ames Research Center obtains 85 percent scalable parallel performance using fine-grain partitioning of single-block CFD domains using up to 128 wide computational nodes. Multi-block CFD simulations of complete aircraft simulations achieve 75 percent perfect load-balanced executions using data coalescing and the two levels of parallelism. SGI PowerChallenge, SGI Origin 2000, and a cluster of workstations are the other platforms where the robustness of the implementation is tested. The performance behavior on the other computer platforms with a variety of realistic problems will be included as this on-going study progresses.
Effect of data truncation in an implementation of pixel clustering on a custom computing machine
NASA Astrophysics Data System (ADS)
Leeser, Miriam E.; Theiler, James P.; Estlick, Michael; Kitaryeva, Natalya V.; Szymanski, John J.
2000-10-01
We investigate the effect of truncating the precision of hyperspectral image data for the purpose of more efficiently segmenting the image using a variant of k-means clustering. We describe the implementation of the algorithm on field-programmable gate array (FPGA) hardware. Truncating the data to only a few bits per pixel in each spectral channel permits a more compact hardware design, enabling greater parallelism, and ultimately a more rapid execution. It also enables the storage of larger images in the onboard memory. In exchange for faster clustering, however, one trades off the quality of the produced segmentation. We find, however, that the clustering algorithm can tolerate considerable data truncation with little degradation in cluster quality. This robustness to truncated data can be extended by computing the cluster centers to a few more bits of precision than the data. Since there are so many more pixels than centers, the more aggressive data truncation leads to significant gains in the number of pixels that can be stored in memory and processed in hardware concurrently.
Kernel spectral clustering with memory effect
NASA Astrophysics Data System (ADS)
Langone, Rocco; Alzate, Carlos; Suykens, Johan A. K.
2013-05-01
Evolving graphs describe many natural phenomena changing over time, such as social relationships, trade markets, metabolic networks etc. In this framework, performing community detection and analyzing the cluster evolution represents a critical task. Here we propose a new model for this purpose, where the smoothness of the clustering results over time can be considered as a valid prior knowledge. It is based on a constrained optimization formulation typical of Least Squares Support Vector Machines (LS-SVM), where the objective function is designed to explicitly incorporate temporal smoothness. The latter allows the model to cluster the current data well and to be consistent with the recent history. We also propose new model selection criteria in order to carefully choose the hyper-parameters of our model, which is a crucial issue to achieve good performances. We successfully test the model on four toy problems and on a real world network. We also compare our model with Evolutionary Spectral Clustering, which is a state-of-the-art algorithm for community detection of evolving networks, illustrating that the kernel spectral clustering with memory effect can achieve better or equal performances.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chin, George; Marquez, Andres; Choudhury, Sutanay
2012-09-01
Triadic analysis encompasses a useful set of graph mining methods that is centered on the concept of a triad, which is a subgraph of three nodes and the configuration of directed edges across the nodes. Such methods are often applied in the social sciences as well as many other diverse fields. Triadic methods commonly operate on a triad census that counts the number of triads of every possible edge configuration in a graph. Like other graph algorithms, triadic census algorithms do not scale well when graphs reach tens of millions to billions of nodes. To enable the triadic analysis ofmore » large-scale graphs, we developed and optimized a triad census algorithm to efficiently execute on shared memory architectures. We will retrace the development and evolution of a parallel triad census algorithm. Over the course of several versions, we continually adapted the code’s data structures and program logic to expose more opportunities to exploit parallelism on shared memory that would translate into improved computational performance. We will recall the critical steps and modifications that occurred during code development and optimization. Furthermore, we will compare the performances of triad census algorithm versions on three specific systems: Cray XMT, HP Superdome, and AMD multi-core NUMA machine. These three systems have shared memory architectures but with markedly different hardware capabilities to manage parallelism.« less
An Adaptive Insertion and Promotion Policy for Partitioned Shared Caches
NASA Astrophysics Data System (ADS)
Mahrom, Norfadila; Liebelt, Michael; Raof, Rafikha Aliana A.; Daud, Shuhaizar; Hafizah Ghazali, Nur
2018-03-01
Cache replacement policies in chip multiprocessors (CMP) have been investigated extensively and proven able to enhance shared cache management. However, competition among multiple processors executing different threads that require simultaneous access to a shared memory may cause cache contention and memory coherence problems on the chip. These issues also exist due to some drawbacks of the commonly used Least Recently Used (LRU) policy employed in multiprocessor systems, which are because of the cache lines residing in the cache longer than required. In image processing analysis of for example extra pulmonary tuberculosis (TB), an accurate diagnosis for tissue specimen is required. Therefore, a fast and reliable shared memory management system to execute algorithms for processing vast amount of specimen image is needed. In this paper, the effects of the cache replacement policy in a partitioned shared cache are investigated. The goal is to quantify whether better performance can be achieved by using less complex replacement strategies. This paper proposes a Middle Insertion 2 Positions Promotion (MI2PP) policy to eliminate cache misses that could adversely affect the access patterns and the throughput of the processors in the system. The policy employs a static predefined insertion point, near distance promotion, and the concept of ownership in the eviction policy to effectively improve cache thrashing and to avoid resource stealing among the processors.
Next-generation acceleration and code optimization for light transport in turbid media using GPUs
Alerstam, Erik; Lo, William Chun Yip; Han, Tianyi David; Rose, Jonathan; Andersson-Engels, Stefan; Lilge, Lothar
2010-01-01
A highly optimized Monte Carlo (MC) code package for simulating light transport is developed on the latest graphics processing unit (GPU) built for general-purpose computing from NVIDIA - the Fermi GPU. In biomedical optics, the MC method is the gold standard approach for simulating light transport in biological tissue, both due to its accuracy and its flexibility in modelling realistic, heterogeneous tissue geometry in 3-D. However, the widespread use of MC simulations in inverse problems, such as treatment planning for PDT, is limited by their long computation time. Despite its parallel nature, optimizing MC code on the GPU has been shown to be a challenge, particularly when the sharing of simulation result matrices among many parallel threads demands the frequent use of atomic instructions to access the slow GPU global memory. This paper proposes an optimization scheme that utilizes the fast shared memory to resolve the performance bottleneck caused by atomic access, and discusses numerous other optimization techniques needed to harness the full potential of the GPU. Using these techniques, a widely accepted MC code package in biophotonics, called MCML, was successfully accelerated on a Fermi GPU by approximately 600x compared to a state-of-the-art Intel Core i7 CPU. A skin model consisting of 7 layers was used as the standard simulation geometry. To demonstrate the possibility of GPU cluster computing, the same GPU code was executed on four GPUs, showing a linear improvement in performance with an increasing number of GPUs. The GPU-based MCML code package, named GPU-MCML, is compatible with a wide range of graphics cards and is released as an open-source software in two versions: an optimized version tuned for high performance and a simplified version for beginners (http://code.google.com/p/gpumcml). PMID:21258498
High order parallel numerical schemes for solving incompressible flows
NASA Technical Reports Server (NTRS)
Lin, Avi; Milner, Edward J.; Liou, May-Fun; Belch, Richard A.
1992-01-01
The use of parallel computers for numerically solving flow fields has gained much importance in recent years. This paper introduces a new high order numerical scheme for computational fluid dynamics (CFD) specifically designed for parallel computational environments. A distributed MIMD system gives the flexibility of treating different elements of the governing equations with totally different numerical schemes in different regions of the flow field. The parallel decomposition of the governing operator to be solved is the primary parallel split. The primary parallel split was studied using a hypercube like architecture having clusters of shared memory processors at each node. The approach is demonstrated using examples of simple steady state incompressible flows. Future studies should investigate the secondary split because, depending on the numerical scheme that each of the processors applies and the nature of the flow in the specific subdomain, it may be possible for a processor to seek better, or higher order, schemes for its particular subcase.
Basic Requirements for Systems Software Research and Development
NASA Technical Reports Server (NTRS)
Kuszmaul, Chris; Nitzberg, Bill
1996-01-01
Our success over the past ten years evaluating and developing advanced computing technologies has been due to a simple research and development (R/D) model. Our model has three phases: (a) evaluating the state-of-the-art, (b) identifying problems and creating innovations, and (c) developing solutions, improving the state- of-the-art. This cycle has four basic requirements: a large production testbed with real users, a diverse collection of state-of-the-art hardware, facilities for evalua- tion of emerging technologies and development of innovations, and control over system management on these testbeds. Future research will be irrelevant and future products will not work if any of these requirements is eliminated. In order to retain our effectiveness, the numerical aerospace simulator (NAS) must replace out-of-date production testbeds in as timely a fashion as possible, and cannot afford to ignore innovative designs such as new distributed shared memory machines, clustered commodity-based computers, and multi-threaded architectures.
Networking and AI systems: Requirements and benefits
NASA Technical Reports Server (NTRS)
1988-01-01
The price performance benefits of network systems is well documented. The ability to share expensive resources sold timesharing for mainframes, department clusters of minicomputers, and now local area networks of workstations and servers. In the process, other fundamental system requirements emerged. These have now been generalized with open system requirements for hardware, software, applications and tools. The ability to interconnect a variety of vendor products has led to a specification of interfaces that allow new techniques to extend existing systems for new and exciting applications. As an example of the message passing system, local area networks provide a testbed for many of the issues addressed by future concurrent architectures: synchronization, load balancing, fault tolerance and scalability. Gold Hill has been working with a number of vendors on distributed architectures that range from a network of workstations to a hypercube of microprocessors with distributed memory. Results from early applications are promising both for performance and scalability.
Hierarchical Traces for Reduced NSM Memory Requirements
NASA Astrophysics Data System (ADS)
Dahl, Torbjørn S.
This paper presents work on using hierarchical long term memory to reduce the memory requirements of nearest sequence memory (NSM) learning, a previously published, instance-based reinforcement learning algorithm. A hierarchical memory representation reduces the memory requirements by allowing traces to share common sub-sequences. We present moderated mechanisms for estimating discounted future rewards and for dealing with hidden state using hierarchical memory. We also present an experimental analysis of how the sub-sequence length affects the memory compression achieved and show that the reduced memory requirements do not effect the speed of learning. Finally, we analyse and discuss the persistence of the sub-sequences independent of specific trace instances.
The Contribution of Working Memory to Fluid Reasoning: Capacity, Control, or Both?
ERIC Educational Resources Information Center
Chuderski, Adam; Necka, Edward
2012-01-01
Fluid reasoning shares a large part of its variance with working memory capacity (WMC). The literature on working memory (WM) suggests that the capacity of the focus of attention responsible for simultaneous maintenance and integration of information within WM, as well as the effectiveness of executive control exerted over WM, determines…
ERIC Educational Resources Information Center
Olivers, Christian N. L.; Meijer, Frank; Theeuwes, Jan
2006-01-01
In 7 experiments, the authors explored whether visual attention (the ability to select relevant visual information) and visual working memory (the ability to retain relevant visual information) share the same content representations. The presence of singleton distractors interfered more strongly with a visual search task when it was accompanied by…
Time-Related Decay or Interference-Based Forgetting in Working Memory?
ERIC Educational Resources Information Center
Portrat, Sophie; Barrouillet, Pierre; Camos, Valerie
2008-01-01
The time-based resource-sharing model of working memory assumes that memory traces suffer from a time-related decay when attention is occupied by concurrent activities. Using complex continuous span tasks in which temporal parameters are carefully controlled, P. Barrouillet, S. Bernardin, S. Portrat, E. Vergauwe, & V. Camos (2007) recently…
Developmental Change in Working Memory Strategies: From Passive Maintenance to Active Refreshing
ERIC Educational Resources Information Center
Camos, Valerie; Barrouillet, Pierre
2011-01-01
Change in strategies is often mentioned as a source of memory development. However, though performance in working memory tasks steadily improves during childhood, theories differ in linking this development to strategy changes. Whereas some theories, such as the time-based resource-sharing model, invoke the age-related increase in use and…
Cache write generate for parallel image processing on shared memory architectures.
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.
Mnemonic convergence in social networks: The emergent properties of cognition at a collective level
Coman, Alin; Momennejad, Ida; Drach, Rae D.; Geana, Andra
2016-01-01
The development of shared memories, beliefs, and norms is a fundamental characteristic of human communities. These emergent outcomes are thought to occur owing to a dynamic system of information sharing and memory updating, which fundamentally depends on communication. Here we report results on the formation of collective memories in laboratory-created communities. We manipulated conversational network structure in a series of real-time, computer-mediated interactions in fourteen 10-member communities. The results show that mnemonic convergence, measured as the degree of overlap among community members’ memories, is influenced by both individual-level information-processing phenomena and by the conversational social network structure created during conversational recall. By studying laboratory-created social networks, we show how large-scale social phenomena (i.e., collective memory) can emerge out of microlevel local dynamics (i.e., mnemonic reinforcement and suppression effects). The social-interactionist approach proposed herein points to optimal strategies for spreading information in social networks and provides a framework for measuring and forging collective memories in communities of individuals. PMID:27357678
Nakahara, Kiyoshi; Adachi, Ken; Kawasaki, Keisuke; Matsuo, Takeshi; Sawahata, Hirohito; Majima, Kei; Takeda, Masaki; Sugiyama, Sayaka; Nakata, Ryota; Iijima, Atsuhiko; Tanigawa, Hisashi; Suzuki, Takafumi; Kamitani, Yukiyasu; Hasegawa, Isao
2016-01-01
Highly localized neuronal spikes in primate temporal cortex can encode associative memory; however, whether memory formation involves area-wide reorganization of ensemble activity, which often accompanies rhythmicity, or just local microcircuit-level plasticity, remains elusive. Using high-density electrocorticography, we capture local-field potentials spanning the monkey temporal lobes, and show that the visual pair-association (PA) memory is encoded in spatial patterns of theta activity in areas TE, 36, and, partially, in the parahippocampal cortex, but not in the entorhinal cortex. The theta patterns elicited by learned paired associates are distinct between pairs, but similar within pairs. This pattern similarity, emerging through novel PA learning, allows a machine-learning decoder trained on theta patterns elicited by a particular visual item to correctly predict the identity of those elicited by its paired associate. Our results suggest that the formation and sharing of widespread cortical theta patterns via learning-induced reorganization are involved in the mechanisms of associative memory representation. PMID:27282247
Spiegel, M A; Koester, D; Weigelt, M; Schack, T
2012-02-16
How much cognitive effort does it take to change a movement plan? In previous studies, it has been shown that humans plan and represent actions in advance, but it remains unclear whether or not action planning and verbal working memory share cognitive resources. Using a novel experimental paradigm, we combined in two experiments a grasp-to-place task with a verbal working memory task. Participants planned a placing movement toward one of two target positions and subsequently encoded and maintained visually presented letters. Both experiments revealed that re-planning the intended action reduced letter recall performance; execution time, however, was not influenced by action modifications. The results of Experiment 2 suggest that the action's interference with verbal working memory arose during the planning rather than the execution phase of the movement. Together, our results strongly suggest that movement planning and verbal working memory share common cognitive resources. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Design and fabrication of memory devices based on nanoscale polyoxometalate clusters
NASA Astrophysics Data System (ADS)
Busche, Christoph; Vilà-Nadal, Laia; Yan, Jun; Miras, Haralampos N.; Long, De-Liang; Georgiev, Vihar P.; Asenov, Asen; Pedersen, Rasmus H.; Gadegaard, Nikolaj; Mirza, Muhammad M.; Paul, Douglas J.; Poblet, Josep M.; Cronin, Leroy
2014-11-01
Flash memory devices--that is, non-volatile computer storage media that can be electrically erased and reprogrammed--are vital for portable electronics, but the scaling down of metal-oxide-semiconductor (MOS) flash memory to sizes of below ten nanometres per data cell presents challenges. Molecules have been proposed to replace MOS flash memory, but they suffer from low electrical conductivity, high resistance, low device yield, and finite thermal stability, limiting their integration into current MOS technologies. Although great advances have been made in the pursuit of molecule-based flash memory, there are a number of significant barriers to the realization of devices using conventional MOS technologies. Here we show that core-shell polyoxometalate (POM) molecules can act as candidate storage nodes for MOS flash memory. Realistic, industry-standard device simulations validate our approach at the nanometre scale, where the device performance is determined mainly by the number of molecules in the storage media and not by their position. To exploit the nature of the core-shell POM clusters, we show, at both the molecular and device level, that embedding [(Se(IV)O3)2]4- as an oxidizable dopant in the cluster core allows the oxidation of the molecule to a [Se(V)2O6]2- moiety containing a {Se(V)-Se(V)} bond (where curly brackets indicate a moiety, not a molecule) and reveals a new 5+ oxidation state for selenium. This new oxidation state can be observed at the device level, resulting in a new type of memory, which we call `write-once-erase'. Taken together, these results show that POMs have the potential to be used as a realistic nanoscale flash memory. Also, the configuration of the doped POM core may lead to new types of electrical behaviour. This work suggests a route to the practical integration of configurable molecules in MOS technologies as the lithographic scales approach the molecular limit.
Sunderaraman, Preeti; Blumen, Helena M; DeMatteo, David; Apa, Zoltan L; Cosentino, Stephanie
2013-06-01
We compared the relationships among sex, clustering strategy, and recall across different task demands using the 16-word California Verbal Learning Test-Second Edition (CVLT-II) and the 9-word Philadelphia (repeatable) Verbal Learning Test (PrVLT). Women generally score higher than men on verbal memory tasks, possibly because women tend to use semantic clustering. This sex difference has been established via word-list learning tests such as the CVLT-II. In a retrospective between-group study, we compared how 2 separate groups of cognitively healthy older adults performed on a longer and a shorter verbal learning test. The group completing the CVLT-II had 36 women and 26 men; the group completing the PrVLT had 27 women and 21 men. Overall, multiple regression analyses revealed that semantic clustering was significantly associated with total recall on both tests' lists (P<0.001). Sex differences in recall and semantic clustering diminished with the shorter PrVLT word list. Semantic clustering uniquely influenced recall on both the longer and shorter word lists. However, serial clustering and sex influenced recall depending on the length of the word list (ie, the task demand). These findings suggest a complex nonlinear relationship among verbal memory, clustering strategies, and task demand.
Sunderaraman, Preeti; Blumen, Helena M.; DeMatteo, David; Apa, Zoltan; Cosentino, Stephanie
2013-01-01
Objective We compared the relationships among sex, clustering strategy, and recall across different task demands using the 16-word California Verbal Learning Test–Second Edition (CVLT-II) and the 9-word Philadelphia (repeatable) Verbal Learning Test (PrVLT). Background Women generally score higher than men on verbal memory tasks, possibly because women tend to use semantic clustering. This sex difference has been established via word-list learning tests such as the CVLT-II. Methods In a retrospective between-group study, we compared how 2 separate groups of cognitively healthy older adults performed on a longer and a shorter verbal learning test. The group completing the CVLT-II had 36 women and 26 men; the group completing the PrVLT had 27 women and 21 men. Results Overall, multiple regression analyses revealed that semantic clustering was significantly associated with total recall on both tests’ lists (P < 0.001). Sex differences in recall and semantic clustering diminished with the shorter PrVLT word list. Conclusions Semantic clustering uniquely influenced recall on both the longer and shorter word lists. However, serial clustering and sex influenced recall depending on the length of the word list (ie, the task demand). These findings suggest a complex nonlinear relationship among verbal memory, clustering strategies, and task demand. PMID:23812171
A Probabilistic Clustering Theory of the Organization of Visual Short-Term Memory
ERIC Educational Resources Information Center
Orhan, A. Emin; Jacobs, Robert A.
2013-01-01
Experimental evidence suggests that the content of a memory for even a simple display encoded in visual short-term memory (VSTM) can be very complex. VSTM uses organizational processes that make the representation of an item dependent on the feature values of all displayed items as well as on these items' representations. Here, we develop a…
Johnsen, Grethe E; Asbjørnsen, Arve E
2009-01-30
The present study examined mechanisms underlying verbal memory impairments in patients with posttraumatic stress disorder (PTSD). Earlier studies have reported that the verbal learning and memory alterations in PTSD are related to impaired encoding, but the use of encoding and organizational strategies in patients with PTSD has not been fully explored. This study examined organizational strategies in 21 refugees/immigrants exposed to war and political violence who fulfilled DSM-IV criteria for chronic PTSD compared with a control sample of 21 refugees/immigrants with similar exposure, but without PTSD. The California Verbal Learning Test was administered to examine differences in organizational strategies and memory. The semantic clustering score was slightly reduced in both groups, but the serial cluster score was significantly impaired in the PTSD group and they also reported more items from the recency region of the list. In addition, intrusive errors were significantly increased in the PTSD group. The data support an assumption of changed memory strategies in patients with PTSD associated with a specific impairment in executive control. However, memory impairment and the use of ineffective learning strategies may not be related to PTSD symptomatology only, but also to self-reported symptoms of depression and general distress.
Organizational Learning Strategies and Verbal Memory Deficits in Bipolar Disorder.
Nitzburg, George C; Cuesta-Diaz, Armando; Ospina, Luz H; Russo, Manuela; Shanahan, Megan; Perez-Rodriguez, Mercedes; Larsen, Emmett; Mulaimovic, Sandra; Burdick, Katherine E
2017-04-01
Verbal memory (VM) impairment is prominent in bipolar disorder (BD) and is linked to functional outcomes. However, the intricacies of VM impairment have not yet been studied in a large sample of BD patients. Moreover, some have proposed VM deficits that may be mediated by organizational strategies, such as semantic or serial clustering. Thus, the exact nature of VM break-down in BD patients is not well understood, limiting remediation efforts. We investigated the intricacies of VM deficits in BD patients versus healthy controls (HCs) and examined whether verbal learning differences were mediated by use of clustering strategies. The California Verbal Learning Test (CVLT) was administered to 113 affectively stable BD patients and 106 HCs. We compared diagnostic groups on all CVLT indices and investigated whether group differences in verbal learning were mediated by clustering strategies. Although BD patients showed significantly poorer attention, learning, and memory, these indices were only mildly impaired. However, BD patients evidenced poorer use of effective learning strategies and lower recall consistency, with these indices falling in the moderately impaired range. Moreover, relative reliance on semantic clustering fully mediated the relationship between diagnostic category and verbal learning, while reliance on serial clustering partially mediated this relationship. VM deficits in affectively stable bipolar patients were widespread but were generally mildly impaired. However, patients displayed inadequate use of organizational strategies with clear separation from HCs on semantic and serial clustering. Remediation efforts may benefit from education about mnemonic devices or "chunking" techniques to attenuate VM deficits in BD. (JINS, 2017, 23, 358-366).
Molsberry, Samantha A; Cheng, Yu; Kingsley, Lawrence; Jacobson, Lisa; Levine, Andrew J; Martin, Eileen; Miller, Eric N; Munro, Cynthia A; Ragin, Ann; Sacktor, Ned; Becker, James T
2018-05-11
Mild forms of HIV-associated neurocognitive disorder (HAND) remain prevalent in the combination anti-retroviral therapy (cART) era. This study's objective was to identify neuropsychological subgroups within the Multicenter AIDS Cohort Study (MACS) based on the participant-based latent structure of cognitive function and to identify factors associated with subgroups. The MACS is a four-site longitudinal study of the natural and treated history of HIV disease among gay and bisexual men. Using neuropsychological domain scores we used a cluster variable selection algorithm to identify the optimal subset of domains with cluster information. Latent profile analysis was applied using scores from identified domains. Exploratory and post-hoc analyses were conducted to identify factors associated with cluster membership and the drivers of the observed associations. Cluster variable selection identified all domains as containing cluster information except for Working Memory. A three-profile solution produced the best fit for the data. Profile 1 performed below average on all domains, Profile 2 performed average on executive functioning, motor, and speed and below average on learning and memory, Profile 3 performed at or above average across all domains. Several demographic, cognitive, and social factors were associated with profile membership; these associations were driven by differences between Profile 1 and the other profiles. There is an identifiable pattern of neuropsychological performance among MACS members determined by all domains except Working Memory. Neither HIV nor HIV-related biomarkers were related with cluster membership, consistent with other findings that cognitive performance patterns do not map directly onto HIV serostatus.
Synapsin Determines Memory Strength after Punishment- and Relief-Learning
Niewalda, Thomas; Michels, Birgit; Jungnickel, Roswitha; Diegelmann, Sören; Kleber, Jörg; Kähne, Thilo
2015-01-01
Adverse life events can induce two kinds of memory with opposite valence, dependent on timing: “negative” memories for stimuli preceding them and “positive” memories for stimuli experienced at the moment of “relief.” Such punishment memory and relief memory are found in insects, rats, and man. For example, fruit flies (Drosophila melanogaster) avoid an odor after odor-shock training (“forward conditioning” of the odor), whereas after shock-odor training (“backward conditioning” of the odor) they approach it. Do these timing-dependent associative processes share molecular determinants? We focus on the role of Synapsin, a conserved presynaptic phosphoprotein regulating the balance between the reserve pool and the readily releasable pool of synaptic vesicles. We find that a lack of Synapsin leaves task-relevant sensory and motor faculties unaffected. In contrast, both punishment memory and relief memory scores are reduced. These defects reflect a true lessening of associative memory strength, as distortions in nonassociative processing (e.g., susceptibility to handling, adaptation, habituation, sensitization), discrimination ability, and changes in the time course of coincidence detection can be ruled out as alternative explanations. Reductions in punishment- and relief-memory strength are also observed upon an RNAi-mediated knock-down of Synapsin, and are rescued both by acutely restoring Synapsin and by locally restoring it in the mushroom bodies of mutant flies. Thus, both punishment memory and relief memory require the Synapsin protein and in this sense share genetic and molecular determinants. We note that corresponding molecular commonalities between punishment memory and relief memory in humans would constrain pharmacological attempts to selectively interfere with excessive associative punishment memories, e.g., after traumatic experiences. PMID:25972175
Synapsin determines memory strength after punishment- and relief-learning.
Niewalda, Thomas; Michels, Birgit; Jungnickel, Roswitha; Diegelmann, Sören; Kleber, Jörg; Kähne, Thilo; Gerber, Bertram
2015-05-13
Adverse life events can induce two kinds of memory with opposite valence, dependent on timing: "negative" memories for stimuli preceding them and "positive" memories for stimuli experienced at the moment of "relief." Such punishment memory and relief memory are found in insects, rats, and man. For example, fruit flies (Drosophila melanogaster) avoid an odor after odor-shock training ("forward conditioning" of the odor), whereas after shock-odor training ("backward conditioning" of the odor) they approach it. Do these timing-dependent associative processes share molecular determinants? We focus on the role of Synapsin, a conserved presynaptic phosphoprotein regulating the balance between the reserve pool and the readily releasable pool of synaptic vesicles. We find that a lack of Synapsin leaves task-relevant sensory and motor faculties unaffected. In contrast, both punishment memory and relief memory scores are reduced. These defects reflect a true lessening of associative memory strength, as distortions in nonassociative processing (e.g., susceptibility to handling, adaptation, habituation, sensitization), discrimination ability, and changes in the time course of coincidence detection can be ruled out as alternative explanations. Reductions in punishment- and relief-memory strength are also observed upon an RNAi-mediated knock-down of Synapsin, and are rescued both by acutely restoring Synapsin and by locally restoring it in the mushroom bodies of mutant flies. Thus, both punishment memory and relief memory require the Synapsin protein and in this sense share genetic and molecular determinants. We note that corresponding molecular commonalities between punishment memory and relief memory in humans would constrain pharmacological attempts to selectively interfere with excessive associative punishment memories, e.g., after traumatic experiences. Copyright © 2015 Niewalda et al.
Audience tuning effects in the context of situated and embodied processes.
Semin, Gün R
2018-03-05
This review provides an overview of the research on communication and the 'Saying is Believing' paradigm in the context of different perspectives on communication. The process of 'audience tuning' is shaped by a variety of situated factors in contexts that affect the communicators' confidence in their message. The overwhelming common denominator is that the combination of features that create ambiguity yields the optimal condition for the formation of shared realities. I conclude with an argument that the implied invariance of memory processes in shared reality work needs to be more attentive to the regulatory function of memories driving the expression of shared realities. Copyright © 2018 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Kajiyama, Shinya; Fujito, Masamichi; Kasai, Hideo; Mizuno, Makoto; Yamaguchi, Takanori; Shinagawa, Yutaka
A novel 300MHz embedded flash memory for dual-core microcontrollers with a shared ROM architecture is proposed. One of its features is a three-stage pipeline read operation, which enables reduced access pitch and therefore reduces performance penalty due to conflict of shared ROM accesses. Another feature is a highly sensitive sense amplifier that achieves efficient pipeline operation with two-cycle latency one-cycle pitch as a result of a shortened sense time of 0.63ns. The combination of the pipeline architecture and proposed sense amplifiers significantly reduces access-conflict penalties with shared ROM and enhances performance of 32-bit RISC dual-core microcontrollers by 30%.
Synaptic Tagging During Memory Allocation
Rogerson, Thomas; Cai, Denise; Frank, Adam; Sano, Yoshitake; Shobe, Justin; Aranda, Manuel L.; Silva, Alcino J.
2014-01-01
There is now compelling evidence that the allocation of memory to specific neurons (neuronal allocation) and synapses (synaptic allocation) in a neurocircuit is not random and that instead specific mechanisms, such as increases in neuronal excitability and synaptic tagging and capture, determine the exact sites where memories are stored. We propose an integrated view of these processes, such that neuronal allocation, synaptic tagging and capture, spine clustering and metaplasticity reflect related aspects of memory allocation mechanisms. Importantly, the properties of these mechanisms suggest a set of rules that profoundly affect how memories are stored and recalled. PMID:24496410
Vergauwe, Evie; Hartstra, Egbert; Barrouillet, Pierre; Brass, Marcel
2015-07-15
Working memory is often defined in cognitive psychology as a system devoted to the simultaneous processing and maintenance of information. In line with the time-based resource-sharing model of working memory (TBRS; Barrouillet and Camos, 2015; Barrouillet et al., 2004), there is accumulating evidence that, when memory items have to be maintained while performing a concurrent activity, memory performance depends on the cognitive load of this activity, independently of the domain involved. The present study used fMRI to identify regions in the brain that are sensitive to variations in cognitive load in a domain-general way. More precisely, we aimed at identifying brain areas that activate during maintenance of memory items as a direct function of the cognitive load induced by both verbal and spatial concurrent tasks. Results show that the right IFJ and bilateral SPL/IPS are the only areas showing an increased involvement as cognitive load increases and do so in a domain general manner. When correlating the fMRI signal with the approximated cognitive load as defined by the TBRS model, it was shown that the main focus of the cognitive load-related activation is located in the right IFJ. The present findings indicate that the IFJ makes domain-general contributions to time-based resource-sharing in working memory and allowed us to generate the novel hypothesis by which the IFJ might be the neural basis for the process of rapid switching. We argue that the IFJ might be a crucial part of a central attentional bottleneck in the brain because of its inability to upload more than one task rule at once. Copyright © 2015 Elsevier Inc. All rights reserved.
Cox, Gregory E; Hemmer, Pernille; Aue, William R; Criss, Amy H
2018-04-01
The development of memory theory has been constrained by a focus on isolated tasks rather than the processes and information that are common to situations in which memory is engaged. We present results from a study in which 453 participants took part in five different memory tasks: single-item recognition, associative recognition, cued recall, free recall, and lexical decision. Using hierarchical Bayesian techniques, we jointly analyzed the correlations between tasks within individuals-reflecting the degree to which tasks rely on shared cognitive processes-and within items-reflecting the degree to which tasks rely on the same information conveyed by the item. Among other things, we find that (a) the processes involved in lexical access and episodic memory are largely separate and rely on different kinds of information, (b) access to lexical memory is driven primarily by perceptual aspects of a word, (c) all episodic memory tasks rely to an extent on a set of shared processes which make use of semantic features to encode both single words and associations between words, and (d) recall involves additional processes likely related to contextual cuing and response production. These results provide a large-scale picture of memory across different tasks which can serve to drive the development of comprehensive theories of memory. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Yoon, Eun Jin; Choi, Jung-Seok; Kim, Heejung; Sohn, Bo Kyung; Jung, Hee Yeon; Lee, Jun-Young; Kim, Dai-Jin; Park, Sun-Won; Kim, Yu Kyeong
2017-07-18
Internet gaming disorder (IGD) has been conceptualized as a behavioral addiction and shares clinical, neuropsychological, and personality characteristics with alcohol use disorder (AUD), but IGD dose not entail brain exposure to toxic agents, which renders it different from AUD. To achieve a clear understanding of the neurobiological features of IGD, we aimed to identify morphological and functional changes in IGD and compare them with those in AUD. Individuals with IGD showed larger volume in the hippocampus/amygdala and precuneus than healthy controls (HCs). The volume in the hippocampus positively correlated with the symptom severity of IGD. Moreover, functional connectivity analysis with the hippocampus/amygdala cluster revealed that the left ventromedial prefrontal cortex showed stronger functional connectivity in individuals with IGD compared to those with AUD. In contrast, individuals with AUD exhibited the smaller cerebellar volume and thinner medial frontal cortex than HCs. The volume in the cerebellum correlated with impaired working memory function as well as duration of illness in AUD group. Findings suggested that altered volume and functional connectivity in the hippocampus/amygdala in IGD might be associated with abnormally enhanced memory process of gaming-related cues, while abnormal cortical changes and cognitive impairments in AUD might be associated with neurotoxic effects of alcohol.
ERIC Educational Resources Information Center
Olivers, Christian N. L.
2009-01-01
An important question is whether visual attention (the ability to select relevant visual information) and visual working memory (the ability to retain relevant visual information) share the same content representations. Some past research has indicated that they do: Singleton distractors interfered more strongly with a visual search task when they…
Discrete Resource Allocation in Visual Working Memory
ERIC Educational Resources Information Center
Barton, Brian; Ester, Edward F.; Awh, Edward
2009-01-01
Are resources in visual working memory allocated in a continuous or a discrete fashion? On one hand, flexible resource models suggest that capacity is determined by a central resource pool that can be flexibly divided such that items of greater complexity receive a larger share of resources. On the other hand, if capacity in working memory is…
Principe, Gabrielle F.; Schindewolf, Erica
2012-01-01
Research on factors that can affect the accuracy of children’s autobiographical remembering has important implications for understanding the abilities of young witnesses to provide legal testimony. In this article, we review our own recent research on one factor that has much potential to induce errors in children’s event recall, namely natural memory sharing conversations with peers and parents. Our studies provide compelling evidence that not only can the content of conversations about the past intrude into later memory but that such exchanges can prompt the generation of entirely false narratives that are more detailed than true accounts of experienced events. Further, our work show that deeper and more creative participation in memory sharing dialogues can boost the damaging effects of conversationally conveyed misinformation. Implications of this collection of findings for children’s testimony are discussed. PMID:23129880
On nonlinear finite element analysis in single-, multi- and parallel-processors
NASA Technical Reports Server (NTRS)
Utku, S.; Melosh, R.; Islam, M.; Salama, M.
1982-01-01
Numerical solution of nonlinear equilibrium problems of structures by means of Newton-Raphson type iterations is reviewed. Each step of the iteration is shown to correspond to the solution of a linear problem, therefore the feasibility of the finite element method for nonlinear analysis is established. Organization and flow of data for various types of digital computers, such as single-processor/single-level memory, single-processor/two-level-memory, vector-processor/two-level-memory, and parallel-processors, with and without sub-structuring (i.e. partitioning) are given. The effect of the relative costs of computation, memory and data transfer on substructuring is shown. The idea of assigning comparable size substructures to parallel processors is exploited. Under Cholesky type factorization schemes, the efficiency of parallel processing is shown to decrease due to the occasional shared data, just as that due to the shared facilities.
Blocksome, Michael A.; Mamidala, Amith R.
2013-09-03
Fencing direct memory access (`DMA`) data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint including specifications of a client, a context, and a task, the endpoints coupled for data communications through the PAMI and through DMA controllers operatively coupled to segments of shared random access memory through which the DMA controllers deliver data communications deterministically, including initiating execution through the PAMI of an ordered sequence of active DMA instructions for DMA data transfers between two endpoints, effecting deterministic DMA data transfers through a DMA controller and a segment of shared memory; and executing through the PAMI, with no FENCE accounting for DMA data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all DMA instructions initiated prior to execution of the FENCE instruction for DMA data transfers between the two endpoints.
Blocksome, Michael A; Mamidala, Amith R
2014-02-11
Fencing direct memory access (`DMA`) data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint including specifications of a client, a context, and a task, the endpoints coupled for data communications through the PAMI and through DMA controllers operatively coupled to segments of shared random access memory through which the DMA controllers deliver data communications deterministically, including initiating execution through the PAMI of an ordered sequence of active DMA instructions for DMA data transfers between two endpoints, effecting deterministic DMA data transfers through a DMA controller and a segment of shared memory; and executing through the PAMI, with no FENCE accounting for DMA data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all DMA instructions initiated prior to execution of the FENCE instruction for DMA data transfers between the two endpoints.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Allada, Veerendra, Benjegerdes, Troy; Bode, Brett
Commodity clusters augmented with application accelerators are evolving as competitive high performance computing systems. The Graphical Processing Unit (GPU) with a very high arithmetic density and performance per price ratio is a good platform for the scientific application acceleration. In addition to the interconnect bottlenecks among the cluster compute nodes, the cost of memory copies between the host and the GPU device have to be carefully amortized to improve the overall efficiency of the application. Scientific applications also rely on efficient implementation of the BAsic Linear Algebra Subroutines (BLAS), among which the General Matrix Multiply (GEMM) is considered as themore » workhorse subroutine. In this paper, they study the performance of the memory copies and GEMM subroutines that are critical to port the computational chemistry algorithms to the GPU clusters. To that end, a benchmark based on the NetPIPE framework is developed to evaluate the latency and bandwidth of the memory copies between the host and the GPU device. The performance of the single and double precision GEMM subroutines from the NVIDIA CUBLAS 2.0 library are studied. The results have been compared with that of the BLAS routines from the Intel Math Kernel Library (MKL) to understand the computational trade-offs. The test bed is a Intel Xeon cluster equipped with NVIDIA Tesla GPUs.« less
Parallelization of NAS Benchmarks for Shared Memory Multiprocessors
NASA Technical Reports Server (NTRS)
Waheed, Abdul; Yan, Jerry C.; Saini, Subhash (Technical Monitor)
1998-01-01
This paper presents our experiences of parallelizing the sequential implementation of NAS benchmarks using compiler directives on SGI Origin2000 distributed shared memory (DSM) system. Porting existing applications to new high performance parallel and distributed computing platforms is a challenging task. Ideally, a user develops a sequential version of the application, leaving the task of porting to new generations of high performance computing systems to parallelization tools and compilers. Due to the simplicity of programming shared-memory multiprocessors, compiler developers have provided various facilities to allow the users to exploit parallelism. Native compilers on SGI Origin2000 support multiprocessing directives to allow users to exploit loop-level parallelism in their programs. Additionally, supporting tools can accomplish this process automatically and present the results of parallelization to the users. We experimented with these compiler directives and supporting tools by parallelizing sequential implementation of NAS benchmarks. Results reported in this paper indicate that with minimal effort, the performance gain is comparable with the hand-parallelized, carefully optimized, message-passing implementations of the same benchmarks.
Alavash, Mohsen; Doebler, Philipp; Holling, Heinz; Thiel, Christiane M; Gießing, Carsten
2015-03-01
Is there one optimal topology of functional brain networks at rest from which our cognitive performance would profit? Previous studies suggest that functional integration of resting state brain networks is an important biomarker for cognitive performance. However, it is still unknown whether higher network integration is an unspecific predictor for good cognitive performance or, alternatively, whether specific network organization during rest predicts only specific cognitive abilities. Here, we investigated the relationship between network integration at rest and cognitive performance using two tasks that measured different aspects of working memory; one task assessed visual-spatial and the other numerical working memory. Network clustering, modularity and efficiency were computed to capture network integration on different levels of network organization, and to statistically compare their correlations with the performance in each working memory test. The results revealed that each working memory aspect profits from a different resting state topology, and the tests showed significantly different correlations with each of the measures of network integration. While higher global network integration and modularity predicted significantly better performance in visual-spatial working memory, both measures showed no significant correlation with numerical working memory performance. In contrast, numerical working memory was superior in subjects with highly clustered brain networks, predominantly in the intraparietal sulcus, a core brain region of the working memory network. Our findings suggest that a specific balance between local and global functional integration of resting state brain networks facilitates special aspects of cognitive performance. In the context of working memory, while visual-spatial performance is facilitated by globally integrated functional resting state brain networks, numerical working memory profits from increased capacities for local processing, especially in brain regions involved in working memory performance. Copyright © 2014 Elsevier Inc. All rights reserved.
A numerical differentiation library exploiting parallel architectures
NASA Astrophysics Data System (ADS)
Voglis, C.; Hadjidoukas, P. E.; Lagaris, I. E.; Papageorgiou, D. G.
2009-08-01
We present a software library for numerically estimating first and second order partial derivatives of a function by finite differencing. Various truncation schemes are offered resulting in corresponding formulas that are accurate to order O(h), O(h), and O(h), h being the differencing step. The derivatives are calculated via forward, backward and central differences. Care has been taken that only feasible points are used in the case where bound constraints are imposed on the variables. The Hessian may be approximated either from function or from gradient values. There are three versions of the software: a sequential version, an OpenMP version for shared memory architectures and an MPI version for distributed systems (clusters). The parallel versions exploit the multiprocessing capability offered by computer clusters, as well as modern multi-core systems and due to the independent character of the derivative computation, the speedup scales almost linearly with the number of available processors/cores. Program summaryProgram title: NDL (Numerical Differentiation Library) Catalogue identifier: AEDG_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEDG_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 73 030 No. of bytes in distributed program, including test data, etc.: 630 876 Distribution format: tar.gz Programming language: ANSI FORTRAN-77, ANSI C, MPI, OPENMP Computer: Distributed systems (clusters), shared memory systems Operating system: Linux, Solaris Has the code been vectorised or parallelized?: Yes RAM: The library uses O(N) internal storage, N being the dimension of the problem Classification: 4.9, 4.14, 6.5 Nature of problem: The numerical estimation of derivatives at several accuracy levels is a common requirement in many computational tasks, such as optimization, solution of nonlinear systems, etc. The parallel implementation that exploits systems with multiple CPUs is very important for large scale and computationally expensive problems. Solution method: Finite differencing is used with carefully chosen step that minimizes the sum of the truncation and round-off errors. The parallel versions employ both OpenMP and MPI libraries. Restrictions: The library uses only double precision arithmetic. Unusual features: The software takes into account bound constraints, in the sense that only feasible points are used to evaluate the derivatives, and given the level of the desired accuracy, the proper formula is automatically employed. Running time: Running time depends on the function's complexity. The test run took 15 ms for the serial distribution, 0.6 s for the OpenMP and 4.2 s for the MPI parallel distribution on 2 processors.
Lee, R S C; Hermens, D F; Naismith, S L; Lagopoulos, J; Jones, A; Scott, J; Chitty, K M; White, D; Robillard, R; Scott, E M; Hickie, I B
2015-01-01
Functional disability is the lead contributor to burden of mental illness. Cognitive deficits frequently limit functional recovery, although whether changes in cognition and disability are longitudinally associated in recent-onset individuals remains unclear. Using a prospective, cohort design, 311 patients were recruited and assessed at baseline. One hundred and sixty-seven patients met eligibility criteria (M=21.5 years old, s.d.=4.8) and returned for follow-up (M=20.6 months later, s.d.=7.8). Two-hundred and thirty participants were included in the final analysis, comprising clinically stable patients with major depression (n=71), bipolar disorder (BD; n=61), schizophrenia-spectrum disorders (n=35) and 63 healthy controls. Neuropsychological functioning and self-rated functional disability were examined using mixed-design, repeated-measures analysis, across diagnoses and cognitive clusters, covarying for relevant confounds. Clinical, neuropsychological and functional changes did not differ between diagnoses (all P>0.05). Three reliable neuropsychological subgroups emerged through cluster analysis, characterized by psychomotor slowing, improved sustained attention, and improved verbal memory. Controlling for diagnosis and changes in residual symptoms, clusters with improved neuropsychological functioning observed greater reductions in functional disability than the psychomotor slowing cluster, which instead demonstrated a worsening in disability (P<0.01). Improved sustained attention was independently associated with greater likelihood of follow-up employment (P<0.01). Diagnosis of BD uniquely predicted both follow-up employment and independent living. Neuropsychological course appears to be independently predictive of subjective and objective functional outcomes. Importantly, cognitive phenotypes may reflect distinct pathophysiologies shared across major psychiatric conditions, and be ideal targets for personalized early intervention. PMID:25918992
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
NASA Astrophysics Data System (ADS)
Sindrilaru, Elvin A.; Peters, Andreas J.; Adde, Geoffray M.; Duellmann, Dirk
2017-10-01
CERN has been developing and operating EOS as a disk storage solution successfully for over 6 years. The CERN deployment provides 135 PB and stores 1.2 billion replicas distributed over two computer centres. Deployment includes four LHC instances, a shared instance for smaller experiments and since last year an instance for individual user data as well. The user instance represents the backbone of the CERNBOX service for file sharing. New use cases like synchronisation and sharing, the planned migration to reduce AFS usage at CERN and the continuous growth has brought EOS to new challenges. Recent developments include the integration and evaluation of various technologies to do the transition from a single active in-memory namespace to a scale-out implementation distributed over many meta-data servers. The new architecture aims to separate the data from the application logic and user interface code, thus providing flexibility and scalability to the namespace component. Another important goal is to provide EOS as a CERN-wide mounted filesystem with strong authentication making it a single storage repository accessible via various services and front- ends (/eos initiative). This required new developments in the security infrastructure of the EOS FUSE implementation. Furthermore, there were a series of improvements targeting the end-user experience like tighter consistency and latency optimisations. In collaboration with Seagate as Openlab partner, EOS has a complete integration of OpenKinetic object drive cluster as a high-throughput, high-availability, low-cost storage solution. This contribution will discuss these three main development projects and present new performance metrics.
Younger and older adults' collaborative recall of shared and unshared emotional pictures.
Barber, Sarah J; Castrellon, Jaime J; Opitz, Philipp; Mather, Mara
2017-07-01
Although a group of people working together recalls more items than any one individual, they recall fewer unique items than the same number of people working apart whose responses are combined. This is known as collaborative inhibition, and it is a robust effect that occurs for both younger and older adults. However, almost all previous studies documenting collaborative inhibition have used stimuli that were neutral in emotional valence, low in arousal, and studied by all group members. In the current experiments, we tested the impact of picture-stimuli valence, picture-stimuli arousal, and information distribution in modulating the magnitude of collaborative inhibition. We included both younger and older adults because there are age differences in how people remember emotional pictures that could modulate any effects of emotion on collaborative inhibition. Results revealed that when information was shared (i.e., studied by all group members), there were robust collaborative inhibition effects for both neutral and emotional stimuli for both younger and older adults. However, when information was unshared (i.e., studied by only a single group member), these effects were attenuated. Together, these results provide mixed support for the retrieval strategy disruption account of collaborative inhibition. Supporting the retrieval strategy disruption account, unshared study information was less susceptible to collaborative inhibition than shared study information. Contradicting the retrieval strategy disruption account, emotional valence and arousal did not modulate the magnitude of collaborative inhibition despite the fact that participants clustered the emotional, but not neutral, information together in memory.
Enhanced HMAX model with feedforward feature learning for multiclass categorization.
Li, Yinlin; Wu, Wei; Zhang, Bo; Li, Fengfu
2015-01-01
In recent years, the interdisciplinary research between neuroscience and computer vision has promoted the development in both fields. Many biologically inspired visual models are proposed, and among them, the Hierarchical Max-pooling model (HMAX) is a feedforward model mimicking the structures and functions of V1 to posterior inferotemporal (PIT) layer of the primate visual cortex, which could generate a series of position- and scale- invariant features. However, it could be improved with attention modulation and memory processing, which are two important properties of the primate visual cortex. Thus, in this paper, based on recent biological research on the primate visual cortex, we still mimic the first 100-150 ms of visual cognition to enhance the HMAX model, which mainly focuses on the unsupervised feedforward feature learning process. The main modifications are as follows: (1) To mimic the attention modulation mechanism of V1 layer, a bottom-up saliency map is computed in the S1 layer of the HMAX model, which can support the initial feature extraction for memory processing; (2) To mimic the learning, clustering and short-term memory to long-term memory conversion abilities of V2 and IT, an unsupervised iterative clustering method is used to learn clusters with multiscale middle level patches, which are taken as long-term memory; (3) Inspired by the multiple feature encoding mode of the primate visual cortex, information including color, orientation, and spatial position are encoded in different layers of the HMAX model progressively. By adding a softmax layer at the top of the model, multiclass categorization experiments can be conducted, and the results on Caltech101 show that the enhanced model with a smaller memory size exhibits higher accuracy than the original HMAX model, and could also achieve better accuracy than other unsupervised feature learning methods in multiclass categorization task.
Implementing Shared Memory Parallelism in MCBEND
NASA Astrophysics Data System (ADS)
Bird, Adam; Long, David; Dobson, Geoff
2017-09-01
MCBEND is a general purpose radiation transport Monte Carlo code from AMEC Foster Wheelers's ANSWERS® Software Service. MCBEND is well established in the UK shielding community for radiation shielding and dosimetry assessments. The existing MCBEND parallel capability effectively involves running the same calculation on many processors. This works very well except when the memory requirements of a model restrict the number of instances of a calculation that will fit on a machine. To more effectively utilise parallel hardware OpenMP has been used to implement shared memory parallelism in MCBEND. This paper describes the reasoning behind the choice of OpenMP, notes some of the challenges of multi-threading an established code such as MCBEND and assesses the performance of the parallel method implemented in MCBEND.
Properties of a memory network in psychology
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wedemann, Roseli S.; Donangelo, Raul; Carvalho, Luis A. V. de
We have previously described neurotic psychopathology and psychoanalytic working-through by an associative memory mechanism, based on a neural network model, where memory was modelled by a Boltzmann machine (BM). Since brain neural topology is selectively structured, we simulated known microscopic mechanisms that control synaptic properties, showing that the network self-organizes to a hierarchical, clustered structure. Here, we show some statistical mechanical properties of the complex networks which result from this self-organization. They indicate that a generalization of the BM may be necessary to model memory.
Properties of a memory network in psychology
NASA Astrophysics Data System (ADS)
Wedemann, Roseli S.; Donangelo, Raul; de Carvalho, Luís A. V.
2007-12-01
We have previously described neurotic psychopathology and psychoanalytic working-through by an associative memory mechanism, based on a neural network model, where memory was modelled by a Boltzmann machine (BM). Since brain neural topology is selectively structured, we simulated known microscopic mechanisms that control synaptic properties, showing that the network self-organizes to a hierarchical, clustered structure. Here, we show some statistical mechanical properties of the complex networks which result from this self-organization. They indicate that a generalization of the BM may be necessary to model memory.
The Use of Cluster Analysis in Typological Research on Community College Students
ERIC Educational Resources Information Center
Bahr, Peter Riley; Bielby, Rob; House, Emily
2011-01-01
One useful and increasingly popular method of classifying students is known commonly as cluster analysis. The variety of techniques that comprise the cluster analytic family are intended to sort observations (for example, students) within a data set into subsets (clusters) that share similar characteristics and differ in meaningful ways from other…
Sensory Clusters of Toddlers with Autism Spectrum Disorders: Differences in Affective Symptoms
ERIC Educational Resources Information Center
Ben-Sasson, A.; Cermak, S. A.; Orsmond, G. I.; Tager-Flusberg, H.; Kadlec, M. B.; Carter, A. S.
2008-01-01
Background: Individuals with autism spectrum disorders (ASDs) show variability in their sensory behaviors. In this study we identified clusters of toddlers with ASDs who shared sensory profiles and examined differences in affective symptoms across these clusters. Method: Using cluster analysis 170 toddlers with ASDs were grouped based on parent…
JuxtaView - A tool for interactive visualization of large imagery on scalable tiled displays
Krishnaprasad, N.K.; Vishwanath, V.; Venkataraman, S.; Rao, A.G.; Renambot, L.; Leigh, J.; Johnson, A.E.; Davis, B.
2004-01-01
JuxtaView is a cluster-based application for viewing ultra-high-resolution images on scalable tiled displays. We present in JuxtaView, a new parallel computing and distributed memory approach for out-of-core montage visualization, using LambdaRAM, a software-based network-level cache system. The ultimate goal of JuxtaView is to enable a user to interactively roam through potentially terabytes of distributed, spatially referenced image data such as those from electron microscopes, satellites and aerial photographs. In working towards this goal, we describe our first prototype implemented over a local area network, where the image is distributed using LambdaRAM, on the memory of all nodes of a PC cluster driving a tiled display wall. Aggressive pre-fetching schemes employed by LambdaRAM help to reduce latency involved in remote memory access. We compare LambdaRAM with a more traditional memory-mapped file approach for out-of-core visualization. ?? 2004 IEEE.
High Performance Data Transfer for Distributed Data Intensive Sciences
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fang, Chin; Cottrell, R 'Les' A.; Hanushevsky, Andrew B.
We report on the development of ZX software providing high performance data transfer and encryption. The design scales in: computation power, network interfaces, and IOPS while carefully balancing the available resources. Two U.S. patent-pending algorithms help tackle data sets containing lots of small files and very large files, and provide insensitivity to network latency. It has a cluster-oriented architecture, using peer-to-peer technologies to ease deployment, operation, usage, and resource discovery. Its unique optimizations enable effective use of flash memory. Using a pair of existing data transfer nodes at SLAC and NERSC, we compared its performance to that of bbcp andmore » GridFTP and determined that they were comparable. With a proof of concept created using two four-node clusters with multiple distributed multi-core CPUs, network interfaces and flash memory, we achieved 155Gbps memory-to-memory over a 2x100Gbps link aggregated channel and 70Gbps file-to-file with encryption over a 5000 mile 100Gbps link.« less
Evolutionarily conserved mechanisms for the selection and maintenance of behavioural activity.
Fiore, Vincenzo G; Dolan, Raymond J; Strausfeld, Nicholas J; Hirth, Frank
2015-12-19
Survival and reproduction entail the selection of adaptive behavioural repertoires. This selection manifests as phylogenetically acquired activities that depend on evolved nervous system circuitries. Lorenz and Tinbergen already postulated that heritable behaviours and their reliable performance are specified by genetically determined programs. Here we compare the functional anatomy of the insect central complex and vertebrate basal ganglia to illustrate their role in mediating selection and maintenance of adaptive behaviours. Comparative analyses reveal that central complex and basal ganglia circuitries share comparable lineage relationships within clusters of functionally integrated neurons. These clusters are specified by genetic mechanisms that link birth time and order to their neuronal identities and functions. Their subsequent connections and associated functions are characterized by similar mechanisms that implement dimensionality reduction and transition through attractor states, whereby spatially organized parallel-projecting loops integrate and convey sensorimotor representations that select and maintain behavioural activity. In both taxa, these neural systems are modulated by dopamine signalling that also mediates memory-like processes. The multiplicity of similarities between central complex and basal ganglia suggests evolutionarily conserved computational mechanisms for action selection. We speculate that these may have originated from ancestral ground pattern circuitries present in the brain of the last common ancestor of insects and vertebrates. © 2015 The Authors.
Evolutionarily conserved mechanisms for the selection and maintenance of behavioural activity
Fiore, Vincenzo G.; Dolan, Raymond J.; Strausfeld, Nicholas J.; Hirth, Frank
2015-01-01
Survival and reproduction entail the selection of adaptive behavioural repertoires. This selection manifests as phylogenetically acquired activities that depend on evolved nervous system circuitries. Lorenz and Tinbergen already postulated that heritable behaviours and their reliable performance are specified by genetically determined programs. Here we compare the functional anatomy of the insect central complex and vertebrate basal ganglia to illustrate their role in mediating selection and maintenance of adaptive behaviours. Comparative analyses reveal that central complex and basal ganglia circuitries share comparable lineage relationships within clusters of functionally integrated neurons. These clusters are specified by genetic mechanisms that link birth time and order to their neuronal identities and functions. Their subsequent connections and associated functions are characterized by similar mechanisms that implement dimensionality reduction and transition through attractor states, whereby spatially organized parallel-projecting loops integrate and convey sensorimotor representations that select and maintain behavioural activity. In both taxa, these neural systems are modulated by dopamine signalling that also mediates memory-like processes. The multiplicity of similarities between central complex and basal ganglia suggests evolutionarily conserved computational mechanisms for action selection. We speculate that these may have originated from ancestral ground pattern circuitries present in the brain of the last common ancestor of insects and vertebrates. PMID:26554043
Meng, Zhi Bin; Chen, Li Qian; Suo, Dong; Li, Gui Xin; Tang, Cai Xian; Zheng, Shao Jian
2012-01-01
Background and Aims Formation of cluster roots is one of the most specific root adaptations to nutrient deficiency. In white lupin (Lupinus albus), cluster roots can be induced by phosphorus (P) or iron (Fe) deficiency. The aim of the present work was to investigate the potential shared signalling pathway in P- and Fe-deficiency-induced cluster root formation. Methods Measurements were made of the internal concentration of nutrients, levels of nitric oxide (NO), citrate exudation and expression of some specific genes under four P × Fe combinations, namely (1) 50 µm P and 10 µm Fe (+P + Fe); (2) 0 P and 10 µm Fe (–P + Fe); (3) 50 µm P and 0 Fe (+P–Fe); and (4) 0 P and 0 Fe (–P–Fe), and these were examined in relation to the formation of cluster roots. Key Results The deficiency of P, Fe or both increased the cluster root number and cluster zones. It also enhanced NO accumulation in pericycle cells and rootlet primordia at various stages of cluster root development. The formation of cluster roots and rootlet primordia, together with the expression of LaSCR1 and LaSCR2 which is crucial in cluster root formation, were induced by the exogenous NO donor S-nitrosoglutathione (GSNO) under the +P + Fe condition, but were inhibited by the NO-specific endogenous scavenger 2-(4-carboxyphenyl)-4, 4, 5, 5-tetramethylimidazoline-1-oxyl- 3-oxide (cPTIO) under –P + Fe, +P–Fe and –P–Fe conditions. However, cluster roots induced by an exogenous supply of the NO donor did not secrete citrate, unlike those formed under –P or –Fe conditions. Conclusions NO plays an important role in the shared signalling pathway of the P- and Fe-deficiency-induced formation of cluster roots in white lupin. PMID:22351487
Effects of Aging on True and False Memory Formation: An fMRI Study
ERIC Educational Resources Information Center
Dennis, Nancy A.; Kim, Hongkeun; Cabeza, Roberto
2007-01-01
Compared to young, older adults are more likely to forget events that occurred in the past as well as remember events that never happened. Previous studies examining false memories and aging have shown that these memories are more likely to occur when new items share perceptual or semantic similarities with those presented during encoding. It is…
Ad Hoc Categories and False Memories: Memory Illusions for Categories Created On-The-Spot
ERIC Educational Resources Information Center
Soro, Jerônimo C.; Ferreira, Mário B.; Semin, Gün R.; Mata, André; Carneiro, Paula
2017-01-01
Three experiments were designed to test whether experimentally created ad hoc associative networks evoke false memories. We used the DRM (Deese, Roediger, McDermott) paradigm with lists of ad hoc categories composed of exemplars aggregated toward specific goals (e.g., going for a picnic) that do not share any consistent set of features. Experiment…
NASA Astrophysics Data System (ADS)
Hill, C.
2008-12-01
Low cost graphic cards today use many, relatively simple, compute cores to deliver support for memory bandwidth of more than 100GB/s and theoretical floating point performance of more than 500 GFlop/s. Right now this performance is, however, only accessible to highly parallel algorithm implementations that, (i) can use a hundred or more, 32-bit floating point, concurrently executing cores, (ii) can work with graphics memory that resides on the graphics card side of the graphics bus and (iii) can be partially expressed in a language that can be compiled by a graphics programming tool. In this talk we describe our experiences implementing a complete, but relatively simple, time dependent shallow-water equations simulation targeting a cluster of 30 computers each hosting one graphics card. The implementation takes into account the considerations (i), (ii) and (iii) listed previously. We code our algorithm as a series of numerical kernels. Each kernel is designed to be executed by multiple threads of a single process. Kernels are passed memory blocks to compute over which can be persistent blocks of memory on a graphics card. Each kernel is individually implemented using the NVidia CUDA language but driven from a higher level supervisory code that is almost identical to a standard model driver. The supervisory code controls the overall simulation timestepping, but is written to minimize data transfer between main memory and graphics memory (a massive performance bottle-neck on current systems). Using the recipe outlined we can boost the performance of our cluster by nearly an order of magnitude, relative to the same algorithm executing only on the cluster CPU's. Achieving this performance boost requires that many threads are available to each graphics processor for execution within each numerical kernel and that the simulations working set of data can fit into the graphics card memory. As we describe, this puts interesting upper and lower bounds on the problem sizes for which this technology is currently most useful. However, many interesting problems fit within this envelope. Looking forward, we extrapolate our experience to estimate full-scale ocean model performance and applicability. Finally we describe preliminary hybrid mixed 32-bit and 64-bit experiments with graphics cards that support 64-bit arithmetic, albeit at a lower performance.
Austin, John R
2003-10-01
Previous research on transactive memory has found a positive relationship between transactive memory system development and group performance in single project laboratory and ad hoc groups. Closely related research on shared mental models and expertise recognition supports these findings. In this study, the author examined the relationship between transactive memory systems and performance in mature, continuing groups. A group's transactive memory system, measured as a combination of knowledge stock, knowledge specialization, transactive memory consensus, and transactive memory accuracy, is positively related to group goal performance, external group evaluations, and internal group evaluations. The positive relationship with group performance was found to hold for both task and external relationship transactive memory systems.
Virtual memory support for distributed computing environments using a shared data object model
NASA Astrophysics Data System (ADS)
Huang, F.; Bacon, J.; Mapp, G.
1995-12-01
Conventional storage management systems provide one interface for accessing memory segments and another for accessing secondary storage objects. This hinders application programming and affects overall system performance due to mandatory data copying and user/kernel boundary crossings, which in the microkernel case may involve context switches. Memory-mapping techniques may be used to provide programmers with a unified view of the storage system. This paper extends such techniques to support a shared data object model for distributed computing environments in which good support for coherence and synchronization is essential. The approach is based on a microkernel, typed memory objects, and integrated coherence control. A microkernel architecture is used to support multiple coherence protocols and the addition of new protocols. Memory objects are typed and applications can choose the most suitable protocols for different types of object to avoid protocol mismatch. Low-level coherence control is integrated with high-level concurrency control so that the number of messages required to maintain memory coherence is reduced and system-wide synchronization is realized without severely impacting the system performance. These features together contribute a novel approach to the support for flexible coherence under application control.
Social Transmission of False Memory in Small Groups and Large Networks.
Maswood, Raeya; Rajaram, Suparna
2018-05-21
Sharing information and memories is a key feature of social interactions, making social contexts important for developing and transmitting accurate memories and also false memories. False memory transmission can have wide-ranging effects, including shaping personal memories of individuals as well as collective memories of a network of people. This paper reviews a collection of key findings and explanations in cognitive research on the transmission of false memories in small groups. It also reviews the emerging experimental work on larger networks and collective false memories. Given the reconstructive nature of memory, the abundance of misinformation in everyday life, and the variety of social structures in which people interact, an understanding of transmission of false memories has both scientific and societal implications. © 2018 Cognitive Science Society, Inc.
The doctor and the patient--how is a clinical encounter perceived?
Adams, Robert; Price, Kay; Tucker, Graeme; Nguyen, Anh-Minh; Wilson, David
2012-01-01
To examine the population distribution of different types of relationships between people with chronic conditions and their doctors that influence decisions being made from a shared-decision making perspective. A survey questionnaire based on recurring themes about the doctor/patient relationship identified from qualitative in-depth interviews with people with chronic conditions and doctors was administered to a national population sample (n=999) of people with chronic conditions. Three factors explained the doctor/patient relationship. Factor 1 identified a positive partnership characteristic of involvement and shared decision-making; Factor 2 doctor-controlled relationship; Factor 3 relationship with negative dimensions. Cluster analysis identified four population groups. Cluster 1 doctor is in control (9.7% of the population); Cluster 2 ambivalent (27.6%); Cluster 3 positive long-term relationship (58.6%); Cluster 4 unhappy relationship (4.4%). The proportion of 18-34 year olds is significantly higher than expected in Cluster 4. The proportion of 65+ year olds is significantly higher than expected in Cluster 1, and significantly lower than expected in Cluster 4. This study adds to shared decision-making literature in that it shows in a representative sample of people with chronic illnesses how their perceptions of their experiences of the doctor-patient relationship are distributed across the population. Consideration needs to be given as to whether it is better to help doctors to alter their styles of interactions to suit the preferences of different patients or if it is feasible to match patients with doctors by style of decision-making and patient preference. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
MULTI: a shared memory approach to cooperative molecular modeling.
Darden, T; Johnson, P; Smith, H
1991-03-01
A general purpose molecular modeling system, MULTI, based on the UNIX shared memory and semaphore facilities for interprocess communication is described. In addition to the normal querying or monitoring of geometric data, MULTI also provides processes for manipulating conformations, and for displaying peptide or nucleic acid ribbons, Connolly surfaces, close nonbonded contacts, crystal-symmetry related images, least-squares superpositions, and so forth. This paper outlines the basic techniques used in MULTI to ensure cooperation among these specialized processes, and then describes how they can work together to provide a flexible modeling environment.
SMT-Aware Instantaneous Footprint Optimization
DOE Office of Scientific and Technical Information (OSTI.GOV)
Roy, Probir; Liu, Xu; Song, Shuaiwen
Modern architectures employ simultaneous multithreading (SMT) to increase thread-level parallelism. SMT threads share many functional units and the whole memory hierarchy of a physical core. Without a careful code design, SMT threads can easily contend with each other for these shared resources, causing severe performance degradation. Minimizing SMT thread contention for HPC applications running on dedicated platforms is very challenging, because they usually spawn threads within Single Program Multiple Data (SPMD) models. To address this important issue, we introduce a simple scheme for SMT-aware code optimization, which aims to reduce the memory contention across SMT threads.
Performance Analysis of Multilevel Parallel Applications on Shared Memory Architectures
NASA Technical Reports Server (NTRS)
Jost, Gabriele; Jin, Haoqiang; Labarta, Jesus; Gimenez, Judit; Caubet, Jordi; Biegel, Bryan A. (Technical Monitor)
2002-01-01
In this paper we describe how to apply powerful performance analysis techniques to understand the behavior of multilevel parallel applications. We use the Paraver/OMPItrace performance analysis system for our study. This system consists of two major components: The OMPItrace dynamic instrumentation mechanism, which allows the tracing of processes and threads and the Paraver graphical user interface for inspection and analyses of the generated traces. We describe how to use the system to conduct a detailed comparative study of a benchmark code implemented in five different programming paradigms applicable for shared memory
Cache-based error recovery for shared memory multiprocessor systems
NASA Technical Reports Server (NTRS)
Wu, Kun-Lung; Fuchs, W. Kent; Patel, Janak H.
1989-01-01
A multiprocessor cache-based checkpointing and recovery scheme for of recovering from transient processor errors in a shared-memory multiprocessor with private caches is presented. New implementation techniques that use checkpoint identifiers and recovery stacks to reduce performance degradation in processor utilization during normal execution are examined. This cache-based checkpointing technique prevents rollback propagation, provides for rapid recovery, and can be integrated into standard cache coherence protocols. An analytical model is used to estimate the relative performance of the scheme during normal execution. Extensions that take error latency into account are presented.
Fast and Accurate Simulation of the Cray XMT Multithreaded Supercomputer
DOE Office of Scientific and Technical Information (OSTI.GOV)
Villa, Oreste; Tumeo, Antonino; Secchi, Simone
Irregular applications, such as data mining and analysis or graph-based computations, show unpredictable memory/network access patterns and control structures. Highly multithreaded architectures with large processor counts, like the Cray MTA-1, MTA-2 and XMT, appear to address their requirements better than commodity clusters. However, the research on highly multithreaded systems is currently limited by the lack of adequate architectural simulation infrastructures due to issues such as size of the machines, memory footprint, simulation speed, accuracy and customization. At the same time, Shared-memory MultiProcessors (SMPs) with multi-core processors have become an attractive platform to simulate large scale machines. In this paper, wemore » introduce a cycle-level simulator of the highly multithreaded Cray XMT supercomputer. The simulator runs unmodified XMT applications. We discuss how we tackled the challenges posed by its development, detailing the techniques introduced to make the simulation as fast as possible while maintaining a high accuracy. By mapping XMT processors (ThreadStorm with 128 hardware threads) to host computing cores, the simulation speed remains constant as the number of simulated processors increases, up to the number of available host cores. The simulator supports zero-overhead switching among different accuracy levels at run-time and includes a network model that takes into account contention. On a modern 48-core SMP host, our infrastructure simulates a large set of irregular applications 500 to 2000 times slower than real time when compared to a 128-processor XMT, while remaining within 10\\% of accuracy. Emulation is only from 25 to 200 times slower than real time.« less
Batistuzzo, Marcelo Camargo; Balardin, Joana Bisol; Martin, Maria da Graça Morais; Hoexter, Marcelo Queiroz; Bernardes, Elisa Teixeira; Borcato, Sonia; Souza, Marina de Marco E; Querido, Cicero Nardini; Morais, Rosa Magaly; de Alvarenga, Pedro Gomes; Lopes, Antonio Carlos; Shavitt, Roseli Gedanke; Savage, Cary R; Amaro, Edson; Miguel, Euripedes C; Polanczyk, Guilherme V; Miotto, Eliane C
2015-10-01
Patients with obsessive-compulsive disorder (OCD) often present with deficits in episodic memory, and there is evidence that these difficulties may be secondary to executive dysfunction, that is, impaired selection and/or application of memory-encoding strategies (mediation hypothesis). Semantic clustering is an effective strategy to enhance encoding of verbal episodic memory (VEM) when word lists are semantically related. Self-initiated mobilization of this strategy has been associated with increased activity in the prefrontal cortex, particularly the orbitofrontal cortex, a key region in the pathophysiology of OCD. We therefore studied children and adolescents with OCD during uncued semantic clustering strategy application in a VEM functional magnetic resonance imaging (fMRI)-encoding paradigm. A total of 25 pediatric patients with OCD (aged 8.1-17.5 years) and 25 healthy controls (HC, aged 8.1-16.9) matched for age, gender, handedness, and IQ were evaluated using a block design VEM paradigm that manipulated semantically related and unrelated words. The semantic clustering strategy score (SCS) predicted VEM performance in HC (p < .001, R(2) = 0.635), but not in patients (p = .099). Children with OCD also presented hypoactivation in the dorsomedial prefrontal cortex (cluster-corrected p < .001). Within-group analysis revealed a negative correlation between Yale-Brown Obsessive Compulsive Scale scores and activation of orbitofrontal cortex in the group with OCD. Finally, a positive correlation between age and SCS was found in HC (p = .001, r = 0.635), but not in patients with OCD (p = .936, r = 0.017). Children with OCD presented altered brain activation during the VEM paradigm and absence of expected correlation between SCS and age, and between SCS and total words recalled. These results suggest that different neural mechanisms underlie self-initiated semantic clustering in OCD. Copyright © 2015 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.
Richards, Todd L; Abbott, Robert D; Yagle, Kevin; Peterson, Dan; Raskind, Wendy; Berninger, Virginia W
2017-01-01
To understand mental self-government of the developing reading and writing brain, correlations of clustering coefficients on fMRI reading or writing tasks with BASC 2 Adaptivity ratings (time 1 only) or working memory components (time 1 before and time 2 after instruction previously shown to improve achievement and change magnitude of fMRI connectivity) were investigated in 39 students in grades 4 to 9 who varied along a continuum of reading and writing skills. A Philips 3T scanner measured connectivity during six leveled fMRI reading tasks (subword-letters and sounds, word-word-specific spellings or affixed words, syntax comprehension-with and without homonym foils or with and without affix foils, and text comprehension) and three fMRI writing tasks-writing next letter in alphabet, adding missing letter in word spelling, and planning for composing. The Brain Connectivity Toolbox generated clustering coefficients based on the cingulo-opercular (CO) network; after controlling for multiple comparisons and movement, significant fMRI connectivity clustering coefficients for CO were identified in 8 brain regions bilaterally (cingulate gyrus, superior frontal gyrus, middle frontal gyrus, inferior frontal gyrus, superior temporal gyrus, insula, cingulum-cingulate gyrus, and cingulum-hippocampus). BASC2 Parent Ratings for Adaptivity were correlated with CO clustering coefficients on three reading tasks (letter-sound, word affix judgments and sentence comprehension) and one writing task (writing next letter in alphabet). Before instruction, each behavioral working memory measure (phonology, orthography, morphology, and syntax coding, phonological and orthographic loops for integrating internal language and output codes, and supervisory focused and switching attention) correlated significantly with at least one CO clustering coefficient. After instruction, the patterning of correlations changed with new correlations emerging. Results show that the reading and writing brain's mental government, supported by both CO Adaptive Control and multiple working memory components, had changed in response to instruction during middle childhood/early adolescence.
Incorporation of memory effects in coarse-grained modeling via the Mori-Zwanzig formalism
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Zhen; Bian, Xin; Karniadakis, George Em, E-mail: george-karniadakis@brown.edu
2015-12-28
The Mori-Zwanzig formalism for coarse-graining a complex dynamical system typically introduces memory effects. The Markovian assumption of delta-correlated fluctuating forces is often employed to simplify the formulation of coarse-grained (CG) models and numerical implementations. However, when the time scales of a system are not clearly separated, the memory effects become strong and the Markovian assumption becomes inaccurate. To this end, we incorporate memory effects into CG modeling by preserving non-Markovian interactions between CG variables, and the memory kernel is evaluated directly from microscopic dynamics. For a specific example, molecular dynamics (MD) simulations of star polymer melts are performed while themore » corresponding CG system is defined by grouping many bonded atoms into single clusters. Then, the effective interactions between CG clusters as well as the memory kernel are obtained from the MD simulations. The constructed CG force field with a memory kernel leads to a non-Markovian dissipative particle dynamics (NM-DPD). Quantitative comparisons between the CG models with Markovian and non-Markovian approximations indicate that including the memory effects using NM-DPD yields similar results as the Markovian-based DPD if the system has clear time scale separation. However, for systems with small separation of time scales, NM-DPD can reproduce correct short-time properties that are related to how the system responds to high-frequency disturbances, which cannot be captured by the Markovian-based DPD model.« less
Holocaust Survivors' Memories of Past Trauma and the Functions of Reminiscence.
O'Rourke, Norm; Canham, Sarah; Wertman, Annette; Chaudhury, Habib; Carmel, Sara; Bachner, Yaacov G; Peres, Hagit
2016-08-01
Existing research suggests that specific ways of recalling autobiographical memories of one's past cluster in self-positive, self-negative, and prosocial reminiscence functions. We undertook the present qualitative study to gain understanding of reminiscence functions as described by 269 Israeli Holocaust survivors and to see whether groupings of themes that emerged would correspond to our tripartite model of the reminiscence functions. Participants (M = 80.4 years; SD = 6.87) were asked to describe memories that typify a reminiscence function in which they frequently or very frequently engage. Thematic analyses were conducted in English (translated) and Hebrew. Responses reflect the range of ways in which Holocaust survivors reminisce. The task of describing early life memories was difficult for some participants, while others' lived experiences enabled them to teach others to ensure that their collective memory remains in the consciousness of the next generation of Israelis and the Jewish state. Data are imbued with examples of horror, resilience, generativity, and gratitude. As hypothesized, survivors' memories cluster in self-positive, self-negative, and prosocial groupings consistent with the tripartite model of reminiscence functions. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Identifying Memory Allocation Patterns in HEP Software
NASA Astrophysics Data System (ADS)
Kama, S.; Rauschmayr, N.
2017-10-01
HEP applications perform an excessive amount of allocations/deallocations within short time intervals which results in memory churn, poor locality and performance degradation. These issues are already known for a decade, but due to the complexity of software frameworks and billions of allocations for a single job, up until recently no efficient mechanism has been available to correlate these issues with source code lines. However, with the advent of the Big Data era, many tools and platforms are now available to do large scale memory profiling. This paper presents, a prototype program developed to track and identify each single (de-)allocation. The CERN IT Hadoop cluster is used to compute memory key metrics, like locality, variation, lifetime and density of allocations. The prototype further provides a web based visualization back-end that allows the user to explore the results generated on the Hadoop cluster. Plotting these metrics for every single allocation over time gives a new insight into application’s memory handling. For instance, it shows which algorithms cause which kind of memory allocation patterns, which function flow causes how many short-lived objects, what are the most commonly allocated sizes etc. The paper will give an insight into the prototype and will show profiling examples for the LHC reconstruction, digitization and simulation jobs.
Avoiding and tolerating latency in large-scale next-generation shared-memory multiprocessors
NASA Technical Reports Server (NTRS)
Probst, David K.
1993-01-01
A scalable solution to the memory-latency problem is necessary to prevent the large latencies of synchronization and memory operations inherent in large-scale shared-memory multiprocessors from reducing high performance. We distinguish latency avoidance and latency tolerance. Latency is avoided when data is brought to nearby locales for future reference. Latency is tolerated when references are overlapped with other computation. Latency-avoiding locales include: processor registers, data caches used temporally, and nearby memory modules. Tolerating communication latency requires parallelism, allowing the overlap of communication and computation. Latency-tolerating techniques include: vector pipelining, data caches used spatially, prefetching in various forms, and multithreading in various forms. Relaxing the consistency model permits increased use of avoidance and tolerance techniques. Each model is a mapping from the program text to sets of partial orders on program operations; it is a convention about which temporal precedences among program operations are necessary. Information about temporal locality and parallelism constrains the use of avoidance and tolerance techniques. Suitable architectural primitives and compiler technology are required to exploit the increased freedom to reorder and overlap operations in relaxed models.
Power/Performance Trade-offs of Small Batched LU Based Solvers on GPUs
DOE Office of Scientific and Technical Information (OSTI.GOV)
Villa, Oreste; Fatica, Massimiliano; Gawande, Nitin A.
In this paper we propose and analyze a set of batched linear solvers for small matrices on Graphic Processing Units (GPUs), evaluating the various alternatives depending on the size of the systems to solve. We discuss three different solutions that operate with different level of parallelization and GPU features. The first, exploiting the CUBLAS library, manages matrices of size up to 32x32 and employs Warp level (one matrix, one Warp) parallelism and shared memory. The second works at Thread-block level parallelism (one matrix, one Thread-block), still exploiting shared memory but managing matrices up to 76x76. The third is Thread levelmore » parallel (one matrix, one thread) and can reach sizes up to 128x128, but it does not exploit shared memory and only relies on the high memory bandwidth of the GPU. The first and second solution only support partial pivoting, the third one easily supports partial and full pivoting, making it attractive to problems that require greater numerical stability. We analyze the trade-offs in terms of performance and power consumption as function of the size of the linear systems that are simultaneously solved. We execute the three implementations on a Tesla M2090 (Fermi) and on a Tesla K20 (Kepler).« less
A neuropsychological comparison of obsessive-compulsive disorder and trichotillomania.
Chamberlain, Samuel R; Fineberg, Naomi A; Blackwell, Andrew D; Clark, Luke; Robbins, Trevor W; Sahakian, Barbara J
2007-03-02
Obsessive-compulsive disorder (OCD) and trichotillomania (compulsive hair-pulling) share overlapping co-morbidity, familial transmission, and phenomenology. However, the extent to which these disorders share a common cognitive phenotype has yet to be elucidated using patients without confounding co-morbidities. To compare neurocognitive functioning in co-morbidity-free patients with OCD and trichotillomania, focusing on domains of learning and memory, executive function, affective processing, reflection-impulsivity and decision-making. Twenty patients with OCD, 20 patients with trichotillomania, and 20 matched controls undertook neuropsychological assessment after meeting stringent inclusion criteria. Groups were matched for age, education, verbal IQ, and gender. The OCD and trichotillomania groups were impaired on spatial working memory. Only OCD patients showed additional impairments on executive planning and visual pattern recognition memory, and missed more responses to sad target words than other groups on an affective go/no-go task. Furthermore, OCD patients failed to modulate their behaviour between conditions on the reflection-impulsivity test, suggestive of cognitive inflexibility. Both clinical groups showed intact decision-making and probabilistic reversal learning. OCD and trichotillomania shared overlapping spatial working memory problems, but neuropsychological dysfunction in OCD spanned additional domains that were intact in trichotillomania. Findings are discussed in relation to likely fronto-striatal neural substrates and future research directions.
Dynamic provisioning of a HEP computing infrastructure on a shared hybrid HPC system
NASA Astrophysics Data System (ADS)
Meier, Konrad; Fleig, Georg; Hauth, Thomas; Janczyk, Michael; Quast, Günter; von Suchodoletz, Dirk; Wiebelt, Bernd
2016-10-01
Experiments in high-energy physics (HEP) rely on elaborate hardware, software and computing systems to sustain the high data rates necessary to study rare physics processes. The Institut fr Experimentelle Kernphysik (EKP) at KIT is a member of the CMS and Belle II experiments, located at the LHC and the Super-KEKB accelerators, respectively. These detectors share the requirement, that enormous amounts of measurement data must be processed and analyzed and a comparable amount of simulated events is required to compare experimental results with theoretical predictions. Classical HEP computing centers are dedicated sites which support multiple experiments and have the required software pre-installed. Nowadays, funding agencies encourage research groups to participate in shared HPC cluster models, where scientist from different domains use the same hardware to increase synergies. This shared usage proves to be challenging for HEP groups, due to their specialized software setup which includes a custom OS (often Scientific Linux), libraries and applications. To overcome this hurdle, the EKP and data center team of the University of Freiburg have developed a system to enable the HEP use case on a shared HPC cluster. To achieve this, an OpenStack-based virtualization layer is installed on top of a bare-metal cluster. While other user groups can run their batch jobs via the Moab workload manager directly on bare-metal, HEP users can request virtual machines with a specialized machine image which contains a dedicated operating system and software stack. In contrast to similar installations, in this hybrid setup, no static partitioning of the cluster into a physical and virtualized segment is required. As a unique feature, the placement of the virtual machine on the cluster nodes is scheduled by Moab and the job lifetime is coupled to the lifetime of the virtual machine. This allows for a seamless integration with the jobs sent by other user groups and honors the fairshare policies of the cluster. The developed thin integration layer between OpenStack and Moab can be adapted to other batch servers and virtualization systems, making the concept also applicable for other cluster operators. This contribution will report on the concept and implementation of an OpenStack-virtualized cluster used for HEP workflows. While the full cluster will be installed in spring 2016, a test-bed setup with 800 cores has been used to study the overall system performance and dedicated HEP jobs were run in a virtualized environment over many weeks. Furthermore, the dynamic integration of the virtualized worker nodes, depending on the workload at the institute's computing system, will be described.
ERIC Educational Resources Information Center
Floyd, Randy G.; McCormack, Allison C.; Ingram, Elizabeth L.; Davis, Amy E.; Bergeron, Renee; Hamilton, Gloria
2006-01-01
This study examined the convergent relations between scores from four clinical clusters from the Woodcock-Johnson III Tests of Cognitive Abilities (WJ III) and measures of executive functions using a sample of school-aged children and a sample of adults. The WJ III clinical clusters included the Working Memory, Cognitive Fluency, Broad Attention,…
Pradzynski, Christoph C.; Dierking, Christoph W.; Zurheide, Florian; ...
2014-09-01
Water clusters containing fully coordinated water molecules are model systems that mimic the local environment of the condensed phase. Present knowledge about the water cluster size regime in which the transition from the allsurface to the fully solvated water molecules occurs is mainly based on theoretical predictions in lieu of the absence of precisely size resolved experimental measurements. Here, we report size and isomer selective infrared (IR) spectra of (H 2O) 20 clusters tagged with a sodium atom by employing IR excitation modulated photoionization spectroscopy. The observed absorption patterns in the OH stretching ”fingerprint” region are consistent with the theoreticallymore » predicted spectra of two structurally distinct isomers: A drop-like cluster with a fully coordinated (interior) water and an edge-sharing pentagonal prism cluster in which all atoms are on the surface. The observed isomers show exceptional stability and are predicted to be nearly isoenergetic.« less
Clustering change patterns using Fourier transformation with time-course gene expression data.
Kim, Jaehee
2011-01-01
To understand the behavior of genes, it is important to explore how the patterns of gene expression change over a period of time because biologically related gene groups can share the same change patterns. In this study, the problem of finding similar change patterns is induced to clustering with the derivative Fourier coefficients. This work is aimed at discovering gene groups with similar change patterns which share similar biological properties. We developed a statistical model using derivative Fourier coefficients to identify similar change patterns of gene expression. We used a model-based method to cluster the Fourier series estimation of derivatives. We applied our model to cluster change patterns of yeast cell cycle microarray expression data with alpha-factor synchronization. It showed that, as the method clusters with the probability-neighboring data, the model-based clustering with our proposed model yielded biologically interpretable results. We expect that our proposed Fourier analysis with suitably chosen smoothing parameters could serve as a useful tool in classifying genes and interpreting possible biological change patterns.
Turner, Arlener D.; Furey, Maura; Drevets, Wayne C.; Zarate, Carlos; Nugent, Allison
2012-01-01
Research has shown poor performance on verbal memory tasks in patients with major depressive disorder relative to healthy controls, as well as structural abnormalities in the subcortical structures that form the limbic-cortical-striatal-pallidal-thalamic circuitry. Few studies, however, have attempted to link the impairments in learning and memory in depression with these structural abnormalities, and of those which have done so, most have included patients medicated with psychotropic agents likely to influence cognitive performance. This study thus examines the relationship between subcortical structural abnormalities and verbal memory using the California Verbal Learning Test (CVLT) in unmedicated depressed patients. A T1 weighted Magnetic Resonance Imaging scan and the CVLT were obtained on 45 subjects with major depressive disorder and 44 healthy controls. Using the FMRIB’s Integrated Registration and Segmentation Tool (FIRST) volumes of selected subcortical structures were segmented and correlated with CVLT performance. Depressed participants showed significantly smaller right thalamus and right hippocampus volumes than healthy controls. Depressed participants also showed impaired performance on global verbal learning ability, and appeared to depend upon an inferior memory strategy (serial clustering). Measures of serial clustering were correlated significantly with right hippocampal volumes in depressed participants. Our findings indicate that depressed participants and healthy controls differ in the memory strategies they employ, and that while depressed participants had a smaller hippocampal volume, there was a positive correlation between volume and use of an inferior memory strategy. This suggests that larger hippocampal volume is related to better memory recall in depression, but specifically with regard to utilizing an inferior memory strategy. PMID:22714007
Taconnat, Laurence; Baudouin, Alexia; Fay, Severine; Raz, Naftali; Bouazzaoui, Badiaa; El-Hage, Wissam; Isingrini, Michel; Ergis, Anne-Marie
2010-08-01
Executive functioning and memory impairment have been demonstrated in adults with depression. Executive functions and memory are related, mainly when the memory tasks require controlled processes (attentional resource demanding processes)--that is, when a low cognitive support (external aid) is provided. A cross-sectional study was carried out on 45 participants: 21 with depression, and 24 healthy controls matched for age, verbal ability, education level, and anxiety score. Cognitive support was manipulated by providing a categorized word list at encoding, presented either clustered (high cognitive support) or randomized (low cognitive support) to both depressed and healthy adults. The number of words recalled was calculated, and an index of clustering was computed to assess organizational strategies. Participants were also administered cognitive tests (executive functions, cognitive speed, and categorical fluency) to explore the mediators of organizational strategies. Depressed participants had greater difficulty recalling and organizing the words, but the differences between the two groups were reduced for both measures when high cognitive support was provided at encoding. Healthy adults performed better on all cognitive tests. Statistical analyses revealed that in the depressed group, executive functions were the only variable associated with clustering and only when low cognitive support was provided. These findings support the view that the decrement in executive function due to depression may lead to impairment in organization when this mnemonic strategy has to be self-initiated.
Ho, ThienLuan; Oh, Seung-Rohk
2017-01-01
Approximate string matching with k-differences has a number of practical applications, ranging from pattern recognition to computational biology. This paper proposes an efficient memory-access algorithm for parallel approximate string matching with k-differences on Graphics Processing Units (GPUs). In the proposed algorithm, all threads in the same GPUs warp share data using warp-shuffle operation instead of accessing the shared memory. Moreover, we implement the proposed algorithm by exploiting the memory structure of GPUs to optimize its performance. Experiment results for real DNA packages revealed that the performance of the proposed algorithm and its implementation archived up to 122.64 and 1.53 times compared to that of sequential algorithm on CPU and previous parallel approximate string matching algorithm on GPUs, respectively. PMID:29016700
Vent modification of large ribbon parachutes to enhance cluster performance
NASA Technical Reports Server (NTRS)
Kolega, D. J.; Woodis, W. R.; Reuter, J. D.
1986-01-01
Due to uneven load sharing and lagging inflation rates, the design of the Large Main Parachute (LMP) cluster, used to recover the Space Shuttle steel case Solid Rocket Boosters, had to be modified. The cause of the problem was excessive variation in effective porosity in the crown area of the LMP during first stage inflation. The design modification consisted of adding horizontal ribbons above the existing vent band to reduce the vent porosity and better control the position and attitude of the vent lines. Performance of modified LMP's since introduction indicates that the load sharing between the clustered chutes has been significantly improved.
Buhusi, Catalin V; Meck, Warren H
2009-07-12
Individuals time as if using a stopwatch that can be stopped or reset on command. Here, we review behavioural and neurobiological data supporting the time-sharing hypothesis that perceived time depends on the attentional and memory resources allocated to the timing process. Neuroimaging studies in humans suggest that timekeeping tasks engage brain circuits typically involved in attention and working memory. Behavioural, pharmacological, lesion and electrophysiological studies in lower animals support this time-sharing hypothesis. When subjects attend to a second task, or when intruder events are presented, estimated durations are shorter, presumably due to resources being taken away from timing. Here, we extend the time-sharing hypothesis by proposing that resource reallocation is proportional to the perceived contrast, both in temporal and non-temporal features, between intruders and the timed events. New findings support this extension by showing that the effect of an intruder event is dependent on the relative duration of the intruder to the intertrial interval. The conclusion is that the brain circuits engaged by timekeeping comprise not only those primarily involved in time accumulation, but also those involved in the maintenance of attentional and memory resources for timing, and in the monitoring and reallocation of those resources among tasks.
Lockhart, Samuel N.; Mayda, Adriane B. V.; Roach, Alexandra E.; Fletcher, Evan; Carmichael, Owen; Maillard, Pauline; Schwarz, Christopher G.; Yonelinas, Andrew P.; Ranganath, Charan; DeCarli, Charles
2011-01-01
Previous neuroimaging research indicates that white matter injury and integrity, measured respectively by white matter hyperintensities (WMH) and fractional anisotropy (FA) obtained from diffusion tensor imaging (DTI), differ with aging and cerebrovascular disease (CVD) and are associated with episodic memory deficits in cognitively normal older adults. However, knowledge about tract-specific relationships between WMH, FA, and episodic memory in aging remains limited. We hypothesized that white matter connections between frontal cortex and subcortical structures as well as connections between frontal and temporo-parietal cortex would be most affected. In the current study, we examined relationships between WMH, FA and episodic memory in 15 young adults, 13 elders with minimal WMH and 15 elders with extensive WMH, using an episodic recognition memory test for object-color associations. Voxel-based statistics were used to identify voxel clusters where white matter measures were specifically associated with variations in episodic memory performance, and white matter tracts intersecting these clusters were analyzed to examine white matter-memory relationships. White matter injury and integrity measures were significantly associated with episodic memory in extensive regions of white matter, located predominantly in frontal, parietal, and subcortical regions. Template based tractography indicated that white matter injury, as measured by WMH, in the uncinate and inferior longitudinal fasciculi were significantly negatively associated with episodic memory performance. Other tracts such as thalamo-frontal projections, superior longitudinal fasciculus, and dorsal cingulum bundle demonstrated strong negative associations as well. The results suggest that white matter injury to multiple pathways, including connections of frontal and temporal cortex and frontal-subcortical white matter tracts, plays a critical role in memory differences seen in older individuals. PMID:22438841
Characterization of a normal control group: are they healthy?
Aine, C J; Sanfratello, L; Adair, J C; Knoefel, J E; Qualls, C; Lundy, S L; Caprihan, A; Stone, D; Stephen, J M
2014-01-01
We examined the health of a control group (18-81years) in our aging study, which is similar to control groups used in other neuroimaging studies. The current study was motivated by our previous results showing that one third of the elder control group had moderate to severe white matter hyperintensities and/or cortical volume loss which correlated with poor performance on memory tasks. Therefore, we predicted that cardiovascular risk factors (e.g., hypertension, high cholesterol) within the control group would account for significant variance on working memory task performance. Fifty-five participants completed 4 verbal and spatial working memory tasks, neuropsychological exams, diffusion tensor imaging (DTI), and blood tests to assess vascular risk. In addition to using a repeated measures ANOVA design, a cluster analysis was applied to the vascular risk measures as a data reduction step to characterize relationships between conjoint risk factors. The cluster groupings were used to predict working memory performance. The results show that higher levels of systolic blood pressure were associated with: 1) poor spatial working memory accuracy; and 2) lower fractional anisotropy (FA) values in multiple brain regions. In contrast, higher levels of total cholesterol corresponded with increased accuracy in verbal working memory. An association between lower FA values and higher cholesterol levels were identified in different brain regions from those associated with systolic blood pressure. The conjoint risk analysis revealed that Risk Cluster Group 3 (the group with the greatest number of risk factors) displayed: 1) the poorest performance on the spatial working memory tasks; 2) the longest reaction times across both spatial and verbal memory tasks; and 3) the lowest FA values across widespread brain regions. Our results confirm that a considerable range of vascular risk factors are present in a typical control group, even in younger individuals, which have robust effects on brain anatomy and function. These results present a new challenge to neuroimaging studies both for defining a cohort from which to characterize 'normative' brain circuitry and for establishing a control group to compare with other clinical populations. © 2013.
Focal retrograde amnesia and the episodic-semantic distinction.
Wheeler, M A; McMillan, C T
2001-03-01
This article reports a review of focal retrograde amnesia (FRA), or the phenomenon of organically based severe memory loss restricted to retrograde, or pretraumatic, memory. Cases of FRA are classified according to the type of memory loss: episodic, semantic, or both. A few different clusters of the disorder were identified. Lesions to either the anterior temporal lobes or the posterior/visual cortex can result in an FRA that devastates retrograde episodic memory, while having smaller effects on semantic memory. A number of left-hemisphere patients have FRA confined to semantic memory. There are several additional examples of FRA following minor cerebral trauma that disrupts either episodic memory alone or both episodic and semantic memory that are not accompanied by evidence of structural brain lesions. We discuss these different profiles of FRA and their implications for the understanding of memory retrieval.
NASA Technical Reports Server (NTRS)
Mejzak, R. S.
1980-01-01
The distributed processing concept is defined in terms of control primitives, variables, and structures and their use in performing a decomposed discrete Fourier transform (DET) application function. The design assumes interprocessor communications to be anonymous. In this scheme, all processors can access an entire common database by employing control primitives. Access to selected areas within the common database is random, enforced by a hardware lock, and determined by task and subtask pointers. This enables the number of processors to be varied in the configuration without any modifications to the control structure. Decompositional elements of the DFT application function in terms of tasks and subtasks are also described. The experimental hardware configuration consists of IMSAI 8080 chassis which are independent, 8 bit microcomputer units. These chassis are linked together to form a multiple processing system by means of a shared memory facility. This facility consists of hardware which provides a bus structure to enable up to six microcomputers to be interconnected. It provides polling and arbitration logic so that only one processor has access to shared memory at any one time.
NASA Astrophysics Data System (ADS)
Calafiura, Paolo; Leggett, Charles; Seuster, Rolf; Tsulaia, Vakhtang; Van Gemmeren, Peter
2015-12-01
AthenaMP is a multi-process version of the ATLAS reconstruction, simulation and data analysis framework Athena. By leveraging Linux fork and copy-on-write mechanisms, it allows for sharing of memory pages between event processors running on the same compute node with little to no change in the application code. Originally targeted to optimize the memory footprint of reconstruction jobs, AthenaMP has demonstrated that it can reduce the memory usage of certain configurations of ATLAS production jobs by a factor of 2. AthenaMP has also evolved to become the parallel event-processing core of the recently developed ATLAS infrastructure for fine-grained event processing (Event Service) which allows the running of AthenaMP inside massively parallel distributed applications on hundreds of compute nodes simultaneously. We present the architecture of AthenaMP, various strategies implemented by AthenaMP for scheduling workload to worker processes (for example: Shared Event Queue and Shared Distributor of Event Tokens) and the usage of AthenaMP in the diversity of ATLAS event processing workloads on various computing resources: Grid, opportunistic resources and HPC.
Optimized Infrastructure for the Earth System Prediction Capability
2013-09-30
for referencing memory between its native coupling datatype (MCT Attribute Vectors) and ESMF Arrays. This will reduce the copies required and will...introduced ability within CESM to share memory between ESMF and MCT datatypes makes using both tools together much easier. Using both is appealing
Chen, Vicky; Paisley, John; Lu, Xinghua
2017-03-14
Cancer is a complex disease driven by somatic genomic alterations (SGAs) that perturb signaling pathways and consequently cellular function. Identifying patterns of pathway perturbations would provide insights into common disease mechanisms shared among tumors, which is important for guiding treatment and predicting outcome. However, identifying perturbed pathways is challenging, because different tumors can have the same perturbed pathways that are perturbed by different SGAs. Here, we designed novel semantic representations that capture the functional similarity of distinct SGAs perturbing a common pathway in different tumors. Combining this representation with topic modeling would allow us to identify patterns in altered signaling pathways. We represented each gene with a vector of words describing its function, and we represented the SGAs of a tumor as a text document by pooling the words representing individual SGAs. We applied the nested hierarchical Dirichlet process (nHDP) model to a collection of tumors of 5 cancer types from TCGA. We identified topics (consisting of co-occurring words) representing the common functional themes of different SGAs. Tumors were clustered based on their topic associations, such that each cluster consists of tumors sharing common functional themes. The resulting clusters contained mixtures of cancer types, which indicates that different cancer types can share disease mechanisms. Survival analysis based on the clusters revealed significant differences in survival among the tumors of the same cancer type that were assigned to different clusters. The results indicate that applying topic modeling to semantic representations of tumors identifies patterns in the combinations of altered functional pathways in cancer.
Application of cluster technology in location-based service
NASA Astrophysics Data System (ADS)
Chen, Jing; Wang, Xiaoman; Gong, Jianya
2005-10-01
This paper introduces the principle, algorithmic and realization of the Load Balancing Technology. It also designs a clustered method in the application of Location-Based Service (LBS), and explains its function characteristics and its whole system structure, followed by some experimental comparisons, showing that the Cluster Technology could ensure a LBS's continuous running and the sharing of fault-tolerance and cluster.
Coman, Alin; Berry, Jessica N
2015-12-01
When speakers selectively retrieve previously learned information, listeners often concurrently, and covertly, retrieve their memories of that information. This concurrent retrieval typically enhances memory for mentioned information (the rehearsal effect) and impairs memory for unmentioned but related information (socially shared retrieval-induced forgetting, SSRIF), relative to memory for unmentioned and unrelated information. Building on research showing that anxiety leads to increased attention to threat-relevant information, we explored whether concurrent retrieval is facilitated in high-anxiety real-world contexts. Participants first learned category-exemplar facts about meningococcal disease. Following a manipulation of perceived risk of infection (low vs. high risk), they listened to a mock radio show in which some of the facts were selectively practiced. Final recall tests showed that the rehearsal effect was equivalent between the two risk conditions, but SSRIF was significantly larger in the high-risk than in the low-risk condition. Thus, the tendency to exaggerate consequences of news events was found to have deleterious consequences. © The Author(s) 2015.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Blocksome, Michael A.; Mamidala, Amith R.
2013-09-03
Fencing direct memory access (`DMA`) data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint including specifications of a client, a context, and a task, the endpoints coupled for data communications through the PAMI and through DMA controllers operatively coupled to segments of shared random access memory through which the DMA controllers deliver data communications deterministically, including initiating execution through the PAMI of an ordered sequence of active DMA instructions for DMA data transfers between two endpoints, effecting deterministic DMA data transfers through a DMA controller and a segmentmore » of shared memory; and executing through the PAMI, with no FENCE accounting for DMA data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all DMA instructions initiated prior to execution of the FENCE instruction for DMA data transfers between the two endpoints.« less
The Work's Not Over- Roll Up Your Sleeves and Make a Difference!
NASA Astrophysics Data System (ADS)
Sarquis, Mickey
1997-01-01
As my 17-year tenure as the first editor of the Secondary School Chemistry Section draws to a close, John Moore has invited me to share some reflections on my experiences. It's hard for me to believe that this many years have passed; in some ways, it seems like only yesterday that I took on this position. Looking back over my term as Section editor recalls wonderful memories, but it also stimulates me to seek out and take on new challenges as I move into a new phase of involvement in chemical education. In response to John's kind invitation, I'd like to share some of these memories and ideas with you who share my vision of quality chemical education, particularly at the secondary level.
1982-04-30
clusters of rooms or areas. The fairly localized property of architectural patterns at the lowest level in the hierarchy is reminiscent of the localized...three digits. We have termed these clusters of groups "supergroups". Finally, when these supergroups became too large (more than 4 or 5 groups), SF...Supergroups -.> Clusters of Supergroups. Insert Figure 4 about here .... .... o.... In another study, run separately on SF and DD, after an hour’s
Bacciu, Davide; Starita, Antonina
2008-11-01
Determining a compact neural coding for a set of input stimuli is an issue that encompasses several biological memory mechanisms as well as various artificial neural network models. In particular, establishing the optimal network structure is still an open problem when dealing with unsupervised learning models. In this paper, we introduce a novel learning algorithm, named competitive repetition-suppression (CoRe) learning, inspired by a cortical memory mechanism called repetition suppression (RS). We show how such a mechanism is used, at various levels of the cerebral cortex, to generate compact neural representations of the visual stimuli. From the general CoRe learning model, we derive a clustering algorithm, named CoRe clustering, that can automatically estimate the unknown cluster number from the data without using a priori information concerning the input distribution. We illustrate how CoRe clustering, besides its biological plausibility, posses strong theoretical properties in terms of robustness to noise and outliers, and we provide an error function describing CoRe learning dynamics. Such a description is used to analyze CoRe relationships with the state-of-the art clustering models and to highlight CoRe similitude with rival penalized competitive learning (RPCL), showing how CoRe extends such a model by strengthening the rival penalization estimation by means of loss functions from robust statistics.
Arousal-biased competition in perception and memory
Mather, Mara; Sutherland, Matthew R.
2010-01-01
Our everyday surroundings besiege us with information. The battle is for a share of our limited attention and memory, with the brain selecting the winners and discarding the losers. Previous research shows that both bottom-up and top-down factors bias competition in favor of high priority stimuli. We propose that arousal during an event increases this bias both in perception and in long-term memory of the event. Arousal-biased competition theory provides specific predictions about when arousal will enhance and when it will impair memory for events, accounting for some puzzling contradictions in the emotional memory literature. PMID:21660127
Aspects of GPU perfomance in algorithms with random memory access
NASA Astrophysics Data System (ADS)
Kashkovsky, Alexander V.; Shershnev, Anton A.; Vashchenkov, Pavel V.
2017-10-01
The numerical code for solving the Boltzmann equation on the hybrid computational cluster using the Direct Simulation Monte Carlo (DSMC) method showed that on Tesla K40 accelerators computational performance drops dramatically with increase of percentage of occupied GPU memory. Testing revealed that memory access time increases tens of times after certain critical percentage of memory is occupied. Moreover, it seems to be the common problem of all NVidia's GPUs arising from its architecture. Few modifications of the numerical algorithm were suggested to overcome this problem. One of them, based on the splitting the memory into "virtual" blocks, resulted in 2.5 times speed up.
On the Performance of an Algebraic MultigridSolver on Multicore Clusters
DOE Office of Scientific and Technical Information (OSTI.GOV)
Baker, A H; Schulz, M; Yang, U M
2010-04-29
Algebraic multigrid (AMG) solvers have proven to be extremely efficient on distributed-memory architectures. However, when executed on modern multicore cluster architectures, we face new challenges that can significantly harm AMG's performance. We discuss our experiences on such an architecture and present a set of techniques that help users to overcome the associated problems, including thread and process pinning and correct memory associations. We have implemented most of the techniques in a MultiCore SUPport library (MCSup), which helps to map OpenMP applications to multicore machines. We present results using both an MPI-only and a hybrid MPI/OpenMP model.
Exploring the Structure of Spatial Representations
Madl, Tamas; Franklin, Stan; Chen, Ke; Trappl, Robert; Montaldi, Daniela
2016-01-01
It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these ‘cognitive maps’ are not well understood. We propose that the structure of the representations of navigation space arises from clustering within individual psychological spaces, i.e. from a process that groups together objects that are close in these spaces. Building on the ideas of representational geometry and similarity-based representations in cognitive science, we formulate methods for learning dissimilarity functions (metrics) characterizing participants’ psychological spaces. We show that these learned metrics, together with a probabilistic model of clustering based on the Bayesian cognition paradigm, allow prediction of participants’ cognitive map structures in advance. Apart from insights into spatial representation learning in human cognition, these methods could facilitate novel computational tools capable of using human-like spatial concepts. We also compare several features influencing spatial memory structure, including spatial distance, visual similarity and functional similarity, and report strong correlations between these dimensions and the grouping probability in participants’ spatial representations, providing further support for clustering in spatial memory. PMID:27347681
Barsegyan, Areg; Mackenzie, Scott M.; Kurose, Brian D.; McGaugh, James L.; Roozendaal, Benno
2010-01-01
It is well established that acute administration of adrenocortical hormones enhances the consolidation of memories of emotional experiences and, concurrently, impairs working memory. These different glucocorticoid effects on these two memory functions have generally been considered to be independently regulated processes. Here we report that a glucocorticoid receptor agonist administered into the medial prefrontal cortex (mPFC) of male Sprague-Dawley rats both enhances memory consolidation and impairs working memory. Both memory effects are mediated by activation of a membrane-bound steroid receptor and depend on noradrenergic activity within the mPFC to increase levels of cAMP-dependent protein kinase. These findings provide direct evidence that glucocorticoid effects on both memory consolidation and working memory share a common neural influence within the mPFC. PMID:20810923
Benefits and Costs of Context Reinstatement in Episodic Memory: An ERP Study.
Bramão, Inês; Johansson, Mikael
2017-01-01
This study investigated context-dependent episodic memory retrieval. An influential idea in the memory literature is that performance benefits when the retrieval context overlaps with the original encoding context. However, such memory facilitation may not be driven by the encoding-retrieval overlap per se but by the presence of diagnostic features in the reinstated context that discriminate the target episode from competing episodes. To test this prediction, the encoding-retrieval overlap and the diagnostic value of the context were manipulated in a novel associative recognition memory task. Participants were asked to memorize word pairs presented together with diagnostic (unique) and nondiagnostic (shared) background scenes. At test, participants recognized the word pairs in the presence and absence of the previously encoded contexts. Behavioral data show facilitated memory performance in the presence of the original context but, importantly, only when the context was diagnostic of the target episode. The electrophysiological data reveal an early anterior ERP encoding-retrieval overlap effect that tracks the cost associated with having nondiagnostic contexts present at retrieval, that is, shared by multiple previous episodes, and a later posterior encoding-retrieval overlap effect that reflects facilitated access to the target episode during retrieval in diagnostic contexts. Taken together, our results underscore the importance of the diagnostic value of the context and suggest that context-dependent episodic memory effects are multiple determined.
Brown, Thackery I.; Stern, Chantal E.
2014-01-01
Many life experiences share information with other memories. In order to make decisions based on overlapping memories, we need to distinguish between experiences to determine the appropriate behavior for the current situation. Previous work suggests that the medial temporal lobe (MTL) and medial caudate interact to support the retrieval of overlapping navigational memories in different contexts. The present study used functional magnetic resonance imaging (fMRI) in humans to test the prediction that the MTL and medial caudate play complementary roles in learning novel mazes that cross paths with, and must be distinguished from, previously learned routes. During fMRI scanning, participants navigated virtual routes that were well learned from prior training while also learning new mazes. Critically, some routes learned during scanning shared hallways with those learned during pre-scan training. Overlap between mazes required participants to use contextual cues to select between alternative behaviors. Results demonstrated parahippocampal cortex activity specific for novel spatial cues that distinguish between overlapping routes. The hippocampus and medial caudate were active for learning overlapping spatial memories, and increased their activity for previously learned routes when they became context dependent. Our findings provide novel evidence that the MTL and medial caudate play complementary roles in the learning, updating, and execution of context-dependent navigational behaviors. PMID:23448868
Symbiosis of executive and selective attention in working memory
Vandierendonck, André
2014-01-01
The notion of working memory (WM) was introduced to account for the usage of short-term memory resources by other cognitive tasks such as reasoning, mental arithmetic, language comprehension, and many others. This collaboration between memory and other cognitive tasks can only be achieved by a dedicated WM system that controls task coordination. To that end, WM models include executive control. Nevertheless, other attention control systems may be involved in coordination of memory and cognitive tasks calling on memory resources. The present paper briefly reviews the evidence concerning the role of selective attention in WM activities. A model is proposed in which selective attention control is directly linked to the executive control part of the WM system. The model assumes that apart from storage of declarative information, the system also includes an executive WM module that represents the current task set. Control processes are automatically triggered when particular conditions in these modules are met. As each task set represents the parameter settings and the actions needed to achieve the task goal, it will depend on the specific settings and actions whether selective attention control will have to be shared among the active tasks. Only when such sharing is required, task performance will be affected by the capacity limits of the control system involved. PMID:25152723
Symbiosis of executive and selective attention in working memory.
Vandierendonck, André
2014-01-01
The notion of working memory (WM) was introduced to account for the usage of short-term memory resources by other cognitive tasks such as reasoning, mental arithmetic, language comprehension, and many others. This collaboration between memory and other cognitive tasks can only be achieved by a dedicated WM system that controls task coordination. To that end, WM models include executive control. Nevertheless, other attention control systems may be involved in coordination of memory and cognitive tasks calling on memory resources. The present paper briefly reviews the evidence concerning the role of selective attention in WM activities. A model is proposed in which selective attention control is directly linked to the executive control part of the WM system. The model assumes that apart from storage of declarative information, the system also includes an executive WM module that represents the current task set. Control processes are automatically triggered when particular conditions in these modules are met. As each task set represents the parameter settings and the actions needed to achieve the task goal, it will depend on the specific settings and actions whether selective attention control will have to be shared among the active tasks. Only when such sharing is required, task performance will be affected by the capacity limits of the control system involved.
Brønnick, Kolbjørn; Alves, Guido; Aarsland, Dag; Tysnes, Ole-Bjørn; Larsen, Jan Petter
2011-01-01
The retrieval deficit hypothesis on memory impairment in patients with Parkinson's disease (PD) implies a selective impairment in recall of learned material with normal encoding, retention, and recognition. This hypothesis has been challenged by new data. We have therefore investigated verbal memory and learning in a large sample of newly diagnosed, drug naïve, non-demented patients with PD. From a sample of patients with PD from the Norwegian ParkWest study, 133 PD patients and 133 controls matched on sex, age, and education were included. The California Verbal Learning Test-2 (CVLT-2) was used to assess verbal memory. Patients performed significantly worse than controls on free and cued recall as well as on recognition memory. Patients used the semantic clustering learning strategy significantly less extensively than the controls and the learning slope of the PD patients was significantly less steep. There was no difference in retention when controlling for encoding. Patients did not perform better on the recognition measure or on cued recall (d-prime), as compared to free recall. Executive functions explained a substantial part of the memory deficits. This study suggests that memory impairment in drug naïve early PD to a large degree is a deficit of learning/ encoding and not of retention or retrieval. An implication is that the retrieval deficit hypothesis should be moderated in its general form. Executive deficits and less extensive use of the efficient semantic clustering learning strategy had a strong impact on learning and memory. (c) 2010 APA, all rights reserved.
Mechanisms of Age-Related Decline in Memory Search Across the Adult Life Span
Hills, Thomas T.; Mata, Rui; Wilke, Andreas; Samanez-Larkin, Gregory R.
2013-01-01
Three alternative mechanisms for age-related decline in memory search have been proposed, which result from either reduced processing speed (global slowing hypothesis), overpersistence on categories (cluster-switching hypothesis), or the inability to maintain focus on local cues related to a decline in working memory (cue-maintenance hypothesis). We investigated these 3 hypotheses by formally modeling the semantic recall patterns of 185 adults between 27 to 99 years of age in the animal fluency task (Thurstone, 1938). The results indicate that people switch between global frequency-based retrieval cues and local item-based retrieval cues to navigate their semantic memory. Contrary to the global slowing hypothesis that predicts no qualitative differences in dynamic search processes and the cluster-switching hypothesis that predicts reduced switching between retrieval cues, the results indicate that as people age, they tend to switch more often between local and global cues per item recalled, supporting the cue-maintenance hypothesis. Additional support for the cue-maintenance hypothesis is provided by a negative correlation between switching and digit span scores and between switching and total items recalled, which suggests that cognitive control may be involved in cue maintenance and the effective search of memory. Overall, the results are consistent with age-related decline in memory search being a consequence of reduced cognitive control, consistent with models suggesting that working memory is related to goal perseveration and the ability to inhibit distracting information. PMID:23586941
Alpha Oscillations during Incidental Encoding Predict Subsequent Memory for New "Foil" Information.
Vogelsang, David A; Gruber, Matthias; Bergström, Zara M; Ranganath, Charan; Simons, Jon S
2018-05-01
People can employ adaptive strategies to increase the likelihood that previously encoded information will be successfully retrieved. One such strategy is to constrain retrieval toward relevant information by reimplementing the neurocognitive processes that were engaged during encoding. Using EEG, we examined the temporal dynamics with which constraining retrieval toward semantic versus nonsemantic information affects the processing of new "foil" information encountered during a memory test. Time-frequency analysis of EEG data acquired during an initial study phase revealed that semantic compared with nonsemantic processing was associated with alpha decreases in a left frontal electrode cluster from around 600 msec after stimulus onset. Successful encoding of semantic versus nonsemantic foils during a subsequent memory test was related to decreases in alpha oscillatory activity in the same left frontal electrode cluster, which emerged relatively late in the trial at around 1000-1600 msec after stimulus onset. Across participants, left frontal alpha power elicited by semantic processing during the study phase correlated significantly with left frontal alpha power associated with semantic foil encoding during the memory test. Furthermore, larger left frontal alpha power decreases elicited by semantic foil encoding during the memory test predicted better subsequent semantic foil recognition in an additional surprise foil memory test, although this effect did not reach significance. These findings indicate that constraining retrieval toward semantic information involves reimplementing semantic encoding operations that are mediated by alpha oscillations and that such reimplementation occurs at a late stage of memory retrieval, perhaps reflecting additional monitoring processes.
Differential pattern of semantic memory organization between bipolar I and II disorders.
Chang, Jae Seung; Choi, Sungwon; Ha, Kyooseob; Ha, Tae Hyon; Cho, Hyun Sang; Choi, Jung Eun; Cha, Boseok; Moon, Eunsoo
2011-06-01
Semantic cognition is one of the key factors in psychosocial functioning. The aim of this study was to explore the differences in pattern of semantic memory organization between euthymic patients with bipolar I and II disorders using the category fluency task. Study participants included 23 euthymic subjects with bipolar I disorder, 23 matched euthymic subjects with bipolar II disorder and 23 matched control subjects. All participants were assessed for verbal learning, recall, learning strategies, and fluency. The combined methods of hierarchical clustering and multidimensional scaling were used to compare the pattern of semantic memory organization among the three groups. Quantitative measures of verbal learning, recall, learning strategies, and fluency did not differ between the three groups. A two-cluster structure of semantic memory organization was identified for the three groups. Semantic structure was more disorganized in the bipolar I disorder group compared to the bipolar II disorder. In addition, patients with bipolar II disorder used less elaborate strategies of semantic memory organization than those of controls. Compared to healthy controls, strategies for categorization in semantic memory appear to be less knowledge-based in patients with bipolar disorders. A differential pattern of semantic memory organization between bipolar I and II disorders indicates a higher risk of cognitive abnormalities in patients with bipolar I disorder compared to patients with bipolar II disorder. Exploring qualitative nature of neuropsychological domains may provide an explanatory insight into the characteristic behaviors of patients with bipolar disorders. Copyright © 2011 Elsevier Inc. All rights reserved.
Alea, Nicole
2010-02-01
Two separate studies examined the prevalence and quality of silent (infrequently recalled), socially silent (i.e., recalled but not shared), and disclosed autobiographical memories. In Study 1 young and older men and women remembered positive events. Positive memories were more likely to be disclosed than to be kept socially silent or completely silent. However, socially silent and disclosed memories did not differ in memory quality: the memories were equally vivid, significant, and emotional. Silent memories were less qualitatively rich. This pattern of results was generally replicated in Study 2 with a lifespan sample for both positive and negative memories, and with additional qualitative variables. The exception was that negative memories were kept silent more often. Age differences were minimal. Women disclosed their autobiographical memories more, but men told a greater variety of people. Results are discussed in terms of the functions that memory telling and silences might serve for individuals.
The computational nature of memory modification.
Gershman, Samuel J; Monfils, Marie-H; Norman, Kenneth A; Niv, Yael
2017-03-15
Retrieving a memory can modify its influence on subsequent behavior. We develop a computational theory of memory modification, according to which modification of a memory trace occurs through classical associative learning, but which memory trace is eligible for modification depends on a structure learning mechanism that discovers the units of association by segmenting the stream of experience into statistically distinct clusters (latent causes). New memories are formed when the structure learning mechanism infers that a new latent cause underlies current sensory observations. By the same token, old memories are modified when old and new sensory observations are inferred to have been generated by the same latent cause. We derive this framework from probabilistic principles, and present a computational implementation. Simulations demonstrate that our model can reproduce the major experimental findings from studies of memory modification in the Pavlovian conditioning literature.
Chen, Xiaoli; Zhou, Ye; Roy, Vellaisamy A L; Han, Su-Ting
2018-01-01
Because of current fabrication limitations, miniaturizing nonvolatile memory devices for managing the explosive increase in big data is challenging. Molecular memories constitute a promising candidate for next-generation memories because their properties can be readily modulated through chemical synthesis. Moreover, these memories can be fabricated through mild solution processing, which can be easily scaled up. Among the various materials, polyoxometalate (POM) molecules have attracted considerable attention for use as novel data-storage nodes for nonvolatile memories. Here, an overview of recent advances in the development of POMs for nonvolatile memories is presented. The general background knowledge of the structure and property diversity of POMs is also summarized. Finally, the challenges and perspectives in the application of POMs in memories are discussed. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Langley, Stuart K; Moubarakia, Boujemaa; Murray, Keith S
2010-06-07
A heterometallic, heptadecanuclear cluster of formula [Mn(III)9Dy(III)8O8(OH)8(tea)2(teaH)2(teaH2)4(Ac)4(NO3)2(H2O)4](NO3)7·8H2O (1) is reported. The core of 1 displays two edge sharing Mn(III)5Dy(III)5 supertetrahedra and represents one of the largest Mn/4f cluster compound so far reported. Magnetic studies show that 1 displays probable SMM behaviour as observed via non-zero values in the χM''vs T plot.
Personal semantics: at the crossroads of semantic and episodic memory.
Renoult, Louis; Davidson, Patrick S R; Palombo, Daniela J; Moscovitch, Morris; Levine, Brian
2012-11-01
Declarative memory is usually described as consisting of two systems: semantic and episodic memory. Between these two poles, however, may lie a third entity: personal semantics (PS). PS concerns knowledge of one's past. Although typically assumed to be an aspect of semantic memory, it is essentially absent from existing models of knowledge. Furthermore, like episodic memory (EM), PS is idiosyncratically personal (i.e., not culturally-shared). We show that, depending on how it is operationalized, the neural correlates of PS can look more similar to semantic memory, more similar to EM, or dissimilar to both. We consider three different perspectives to better integrate PS into existing models of declarative memory and suggest experimental strategies for disentangling PS from semantic and episodic memory. Copyright © 2012 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
OKeefe, Matthew (Editor); Kerr, Christopher L. (Editor)
1998-01-01
This report contains the abstracts and technical papers from the Second International Workshop on Software Engineering and Code Design in Parallel Meteorological and Oceanographic Applications, held June 15-18, 1998, in Scottsdale, Arizona. The purpose of the workshop is to bring together software developers in meteorology and oceanography to discuss software engineering and code design issues for parallel architectures, including Massively Parallel Processors (MPP's), Parallel Vector Processors (PVP's), Symmetric Multi-Processors (SMP's), Distributed Shared Memory (DSM) multi-processors, and clusters. Issues to be discussed include: (1) code architectures for current parallel models, including basic data structures, storage allocation, variable naming conventions, coding rules and styles, i/o and pre/post-processing of data; (2) designing modular code; (3) load balancing and domain decomposition; (4) techniques that exploit parallelism efficiently yet hide the machine-related details from the programmer; (5) tools for making the programmer more productive; and (6) the proliferation of programming models (F--, OpenMP, MPI, and HPF).
IGA-ADS: Isogeometric analysis FEM using ADS solver
NASA Astrophysics Data System (ADS)
Łoś, Marcin M.; Woźniak, Maciej; Paszyński, Maciej; Lenharth, Andrew; Hassaan, Muhamm Amber; Pingali, Keshav
2017-08-01
In this paper we present a fast explicit solver for solution of non-stationary problems using L2 projections with isogeometric finite element method. The solver has been implemented within GALOIS framework. It enables parallel multi-core simulations of different time-dependent problems, in 1D, 2D, or 3D. We have prepared the solver framework in a way that enables direct implementation of the selected PDE and corresponding boundary conditions. In this paper we describe the installation, implementation of exemplary three PDEs, and execution of the simulations on multi-core Linux cluster nodes. We consider three case studies, including heat transfer, linear elasticity, as well as non-linear flow in heterogeneous media. The presented package generates output suitable for interfacing with Gnuplot and ParaView visualization software. The exemplary simulations show near perfect scalability on Gilbert shared-memory node with four Intel® Xeon® CPU E7-4860 processors, each possessing 10 physical cores (for a total of 40 cores).
Automatic Parallelization of Numerical Python Applications using the Global Arrays Toolkit
DOE Office of Scientific and Technical Information (OSTI.GOV)
Daily, Jeffrey A.; Lewis, Robert R.
2011-11-30
Global Arrays is a software system from Pacific Northwest National Laboratory that enables an efficient, portable, and parallel shared-memory programming interface to manipulate distributed dense arrays. The NumPy module is the de facto standard for numerical calculation in the Python programming language, a language whose use is growing rapidly in the scientific and engineering communities. NumPy provides a powerful N-dimensional array class as well as other scientific computing capabilities. However, like the majority of the core Python modules, NumPy is inherently serial. Using a combination of Global Arrays and NumPy, we have reimplemented NumPy as a distributed drop-in replacement calledmore » Global Arrays in NumPy (GAiN). Serial NumPy applications can become parallel, scalable GAiN applications with only minor source code changes. Scalability studies of several different GAiN applications will be presented showing the utility of developing serial NumPy codes which can later run on more capable clusters or supercomputers.« less
Vinkhuyzen, Anna A E; van der Sluis, Sophie; Posthuma, Danielle; Boomsma, Dorret I
2009-07-01
The origin of individual differences in aptitude, defined as a domain-specific skill within the normal ability range, and talent, defined as a domain specific skill of exceptional quality, is under debate. The nature of the variation in aptitudes and exceptional talents across different domains was investigated in a population based twin sample. Self-report data from 1,685 twin pairs (12-24 years) were analyzed for Music, Arts, Writing, Language, Chess, Mathematics, Sports, Memory, and Knowledge. The influence of shared environment was small for both aptitude and talent. Additive and non-additive genetic effects explained the major part of the substantial familial clustering in the aptitude measures with heritability estimates ranging between .32 and .71. Heritability estimates for talents were higher and ranged between .50 and .92. In general, the genetic architecture for aptitude and talent was similar in men and women. Genetic factors contribute to a large extent to variation in aptitude and talent across different domains of intellectual, creative, and sports abilities.
HEC Applications on Columbia Project
NASA Technical Reports Server (NTRS)
Taft, Jim
2004-01-01
NASA's Columbia system consists of a cluster of twenty 512 processor SGI Altix systems. Each of these systems is 3 TFLOP/s in peak performance - approximately the same as the entire compute capability at NAS just one year ago. Each 512p system is a single system image machine with one Linunx O5, one high performance file system, and one globally shared memory. The NAS Terascale Applications Group (TAG) is chartered to assist in scaling NASA's mission critical codes to at least 512p in order to significantly improve emergency response during flight operations, as well as provide significant improvements in the codes. and rate of scientific discovery across the scientifc disciplines within NASA's Missions. Recent accomplishments are 4x improvements to codes in the ocean modeling community, 10x performance improvements in a number of computational fluid dynamics codes used in aero-vehicle design, and 5x improvements in a number of space science codes dealing in extreme physics. The TAG group will continue its scaling work to 2048p and beyond (10240 cpus) as the Columbia system becomes fully operational and the upgrades to the SGI NUMAlink memory fabric are in place. The NUMlink uprades dramatically improve system scalability for a single application. These upgrades will allow a number of codes to execute faster at higher fidelity than ever before on any other system, thus increasing the rate of scientific discovery even further
Parallel, Distributed Scripting with Python
DOE Office of Scientific and Technical Information (OSTI.GOV)
Miller, P J
2002-05-24
Parallel computers used to be, for the most part, one-of-a-kind systems which were extremely difficult to program portably. With SMP architectures, the advent of the POSIX thread API and OpenMP gave developers ways to portably exploit on-the-box shared memory parallelism. Since these architectures didn't scale cost-effectively, distributed memory clusters were developed. The associated MPI message passing libraries gave these systems a portable paradigm too. Having programmers effectively use this paradigm is a somewhat different question. Distributed data has to be explicitly transported via the messaging system in order for it to be useful. In high level languages, the MPI librarymore » gives access to data distribution routines in C, C++, and FORTRAN. But we need more than that. Many reasonable and common tasks are best done in (or as extensions to) scripting languages. Consider sysadm tools such as password crackers, file purgers, etc ... These are simple to write in a scripting language such as Python (an open source, portable, and freely available interpreter). But these tasks beg to be done in parallel. Consider the a password checker that checks an encrypted password against a 25,000 word dictionary. This can take around 10 seconds in Python (6 seconds in C). It is trivial to parallelize if you can distribute the information and co-ordinate the work.« less
Performance upgrades to the MCNP6 burnup capability for large scale depletion calculations
Fensin, M. L.; Galloway, J. D.; James, M. R.
2015-04-11
The first MCNP based inline Monte Carlo depletion capability was officially released from the Radiation Safety Information and Computational Center as MCNPX 2.6.0. With the merger of MCNPX and MCNP5, MCNP6 combined the capability of both simulation tools, as well as providing new advanced technology, in a single radiation transport code. The new MCNP6 depletion capability was first showcased at the International Congress for Advancements in Nuclear Power Plants (ICAPP) meeting in 2012. At that conference the new capabilities addressed included the combined distributive and shared memory parallel architecture for the burnup capability, improved memory management, physics enhancements, and newmore » predictability as compared to the H.B Robinson Benchmark. At Los Alamos National Laboratory, a special purpose cluster named “tebow,” was constructed such to maximize available RAM per CPU, as well as leveraging swap space with solid state hard drives, to allow larger scale depletion calculations (allowing for significantly more burnable regions than previously examined). As the MCNP6 burnup capability was scaled to larger numbers of burnable regions, a noticeable slowdown was realized.This paper details two specific computational performance strategies for improving calculation speedup: (1) retrieving cross sections during transport; and (2) tallying mechanisms specific to burnup in MCNP. To combat this slowdown new performance upgrades were developed and integrated into MCNP6 1.2.« less
Etiological Distinction of Working Memory Components in Relation to Mathematics
Lukowski, Sarah L.; Soden, Brooke; Hart, Sara A.; Thompson, Lee A.; Kovas, Yulia; Petrill, Stephen A.
2014-01-01
Working memory has been consistently associated with mathematics achievement, although the etiology of these relations remains poorly understood. The present study examined the genetic and environmental underpinnings of math story problem solving, timed calculation, and untimed calculation alongside working memory components in 12-year-old monozygotic (n = 105) and same-sex dizygotic (n = 143) twin pairs. Results indicated significant phenotypic correlation between each working memory component and all mathematics outcomes (r = 0.18 – 0.33). Additive genetic influences shared between the visuo-spatial sketchpad and mathematics achievement was significant, accounting for roughly 89% of the observed correlation. In addition, genetic covariance was found between the phonological loop and math story problem solving. In contrast, despite there being a significant observed relationship between phonological loop and timed and untimed calculation, there was no significant genetic or environmental covariance between the phonological loop and timed or untimed calculation skills. Further analyses indicated that genetic overlap between the visuo-spatial sketchpad and math story problem solving and math fluency was distinct from general genetic factors, whereas g, phonological loop, and mathematics shared generalist genes. Thus, although each working memory component was related to mathematics, the etiology of their relationships may be distinct. PMID:25477699
Outsmarting Poison Ivy and Other Poisonous Plants
... Consumer Updates Outsmarting Poison Ivy and Other Poisonous Plants Share Tweet Linkedin Pin it More sharing options ... whitish-green fruits hang in loose clusters. Poison Plant Rashes Aren’t Contagious Poison ivy and other ...
Test Sequence Priming in Recognition Memory
ERIC Educational Resources Information Center
Johns, Elizabeth E.; Mewhort, D. J. K.
2009-01-01
The authors examined priming within the test sequence in 3 recognition memory experiments. A probe primed its successor whenever both probes shared a feature with the same studied item ("interjacent priming"), indicating that the study item like the probe is central to the decision. Interjacent priming occurred even when the 2 probes did…
Two Maintenance Mechanisms of Verbal Information in Working Memory
ERIC Educational Resources Information Center
Camos, V.; Lagner, P.; Barrouillet, P.
2009-01-01
The present study evaluated the interplay between two mechanisms of maintenance of verbal information in working memory, namely articulatory rehearsal as described in Baddeley's model, and attentional refreshing as postulated in Barrouillet and Camos's Time-Based Resource-Sharing (TBRS) model. In four experiments using complex span paradigm, we…
Down Memory Lane: Recollections of Lamaze International's First 50 Years
Zwelling, Elaine
2010-01-01
The 42-year involvement of one member of Lamaze International is chronicled through a decade-by-decade review of personal memories. The history of Lamaze International is shared through the recollections of her roles as a childbirth educator, faculty member, and member of the board of directors. PMID:21629385
Paul Ricoeur, Memory, and the Historical Gaze: Implications for Education Histories
ERIC Educational Resources Information Center
Colby, Sherri Rae
2012-01-01
In this article, the author shares the potential applications of Paul Ricoeur's philosophies of history, memory, and narrative to the interpretation of educational histories, and those histories' life spans: moving cyclically from early conception, to evidentiary construction, to published dissemination; and ultimately to death or immortality. Her…
Enrichment Clusters: A Practical Plan for Real-World, Student-Driven Learning.
ERIC Educational Resources Information Center
Renzulli, Joseph S.; Gentry, Marcia; Reis, Sally M.
This guidebook provides a rationale and guidelines for implementing a student-driven learning approach using enrichment clusters. Enrichment clusters allow students who share a common interest to meet each week to produce a product, performance, or targeted service based on that common interest. Chapter 1 discusses different models of learning.…
Module Cluster: UG - 001.00 (GSC) Urban Geography.
ERIC Educational Resources Information Center
Currier, Wade R.
This is one of several module clusters developed for the Camden Teacher Corps project. This module cluster is designed to introduce students to urban studies through the application of a geographic approach. Although geography shares with other social sciences many concepts and methods, it has contributed a distinctive set of viewpoints and a…
1988-02-29
by memory copyin g will degrade system performance on shared-memory multiprocessors. Virtual memor y (VM) remapping, as opposed to memory copying...Bershad, G.D. Giuseppe Facchetti, Kevin Fall, G . Scott Graham, Ellen Nelson , P. Venkat Rangan, Bruno Sartirana, Shin-Yuan Tzou, Raj Vaswani, and Robert...Remote Execution in NEST", IEEE Trans. on Software Eng. 13, 8 (August 1987), 905-912. 3. G . T. Almes, A. P. Black, E. Lazowska and J. Noe, "The Eden
Language Networks Associated with Computerized Semantic Indices
Pakhomov, Serguei V. S.; Jones, David T.; Knopman, David S.
2014-01-01
Tests of generative semantic verbal fluency are widely used to study organization and representation of concepts in the human brain. Previous studies demonstrated that clustering and switching behavior during verbal fluency tasks is supported by multiple brain mechanisms associated with semantic memory and executive control. Previous work relied on manual assessments of semantic relatedness between words and grouping of words into semantic clusters. We investigated a computational linguistic approach to measuring the strength of semantic relatedness between words based on latent semantic analysis of word co-occurrences in a subset of a large online encyclopedia. We computed semantic clustering indices and compared them to brain network connectivity measures obtained with task-free fMRI in a sample consisting of healthy participants and those differentially affected by cognitive impairment. We found that semantic clustering indices were associated with brain network connectivity in distinct areas including fronto-temporal, fronto-parietal and fusiform gyrus regions. This study shows that computerized semantic indices complement traditional assessments of verbal fluency to provide a more complete account of the relationship between brain and verbal behavior involved organization and retrieval of lexical information from memory. PMID:25315785
Measuring the representational space of music with fMRI: a case study with Sting.
Levitin, Daniel J; Grafton, Scott T
2016-12-01
Functional brain imaging has revealed much about the neuroanatomical substrates of higher cognition, including music, language, learning, and memory. The technique lends itself to studying of groups of individuals. In contrast, the nature of expert performance is typically studied through the examination of exceptional individuals using behavioral case studies and retrospective biography. Here, we combined fMRI and the study of an individual who is a world-class expert musician and composer in order to better understand the neural underpinnings of his music perception and cognition, in particular, his mental representations for music. We used state of the art multivoxel pattern analysis (MVPA) and representational dissimilarity analysis (RDA) in a fixed set of brain regions to test three exploratory hypotheses with the musician Sting: (1) Composing would recruit neutral structures that are both unique and distinguishable from other creative acts, such as composing prose or visual art; (2) listening and imagining music would recruit similar neural regions, indicating that musical memory shares anatomical substrates with music listening; (3) the MVPA and RDA results would help us to map the representational space for music, revealing which musical pieces and genres are perceived to be similar in the musician's mental models for music. Our hypotheses were confirmed. The act of composing, and even of imagining elements of the composed piece separately, such as melody and rhythm, activated a similar cluster of brain regions, and were distinct from prose and visual art. Listened and imagined music showed high similarity, and in addition, notable similarity/dissimilarity patterns emerged among the various pieces used as stimuli: Muzak and Top 100/Pop songs were far from all other musical styles in Mahalanobis distance (Euclidean representational space), whereas jazz, R&B, tango and rock were comparatively close. Closer inspection revealed principaled explanations for the similarity clusters found, based on key, tempo, motif, and orchestration.
Deficits in Category Learning in Older Adults: Rule-Based Versus Clustering Accounts
2017-01-01
Memory research has long been one of the key areas of investigation for cognitive aging researchers but only in the last decade or so has categorization been used to understand age differences in cognition. Categorization tasks focus more heavily on the grouping and organization of items in memory, and often on the process of learning relationships through trial and error. Categorization studies allow researchers to more accurately characterize age differences in cognition: whether older adults show declines in the way in which they represent categories with simple rules or declines in representing categories by similarity to past examples. In the current study, young and older adults participated in a set of classic category learning problems, which allowed us to distinguish between three hypotheses: (a) rule-complexity: categories were represented exclusively with rules and older adults had differential difficulty when more complex rules were required, (b) rule-specific: categories could be represented either by rules or by similarity, and there were age deficits in using rules, and (c) clustering: similarity was mainly used and older adults constructed a less-detailed representation by lumping more items into fewer clusters. The ordinal levels of performance across different conditions argued against rule-complexity, as older adults showed greater deficits on less complex categories. The data also provided evidence against rule-specificity, as single-dimensional rules could not explain age declines. Instead, computational modeling of the data indicated that older adults utilized fewer conceptual clusters of items in memory than did young adults. PMID:28816474
Reich, Richard R; Ariel, Idan; Darkes, Jack; Goldman, Mark S
2012-09-01
The configuration and activation of memory networks have been theorized as mechanisms that underlie the often observed link between alcohol expectancies and drinking. A key component of this network is the expectancy "drunk." The memory network configuration of "drunk" was mapped by using cluster analysis of data gathered from the paired-similarities task (PST) and the Alcohol Expectancy Multi-Axial Assessment (AEMAX). A third task, the free associates task (FA), assessed participants' strongest alcohol expectancy associates and was used as a validity check for the cluster analyses. Six hundred forty-seven 18-19-year-olds completed these measures and a measure of alcohol consumption at baseline assessment for a 5-year longitudinal study. For both the PST and AEMAX, "drunk" clustered with mainly negative and sedating effects (e.g., "sick," "dizzy," "sleepy") in lighter drinkers and with more positive and arousing effects (e.g., "happy," "horny," "outgoing") in heavier drinkers, showing that the cognitive organization of expectancies reflected drinker type (and might influence the choice to drink). Consistent with the cluster analyses, in participants who gave "drunk" as an FA response, heavier drinkers rated the word as more positive and arousing than lighter drinkers. Additionally, gender did not account for the observed drinker-type differences. These results support the notion that for some emerging adults, drinking may be linked to what they mean by the word "drunk." PsycINFO Database Record (c) 2012 APA, all rights reserved.
Robust sequential working memory recall in heterogeneous cognitive networks
Rabinovich, Mikhail I.; Sokolov, Yury; Kozma, Robert
2014-01-01
Psychiatric disorders are often caused by partial heterogeneous disinhibition in cognitive networks, controlling sequential and spatial working memory (SWM). Such dynamic connectivity changes suggest that the normal relationship between the neuronal components within the network deteriorates. As a result, competitive network dynamics is qualitatively altered. This dynamics defines the robust recall of the sequential information from memory and, thus, the SWM capacity. To understand pathological and non-pathological bifurcations of the sequential memory dynamics, here we investigate the model of recurrent inhibitory-excitatory networks with heterogeneous inhibition. We consider the ensemble of units with all-to-all inhibitory connections, in which the connection strengths are monotonically distributed at some interval. Based on computer experiments and studying the Lyapunov exponents, we observed and analyzed the new phenomenon—clustered sequential dynamics. The results are interpreted in the context of the winnerless competition principle. Accordingly, clustered sequential dynamics is represented in the phase space of the model by two weakly interacting quasi-attractors. One of them is similar to the sequential heteroclinic chain—the regular image of SWM, while the other is a quasi-chaotic attractor. Coexistence of these quasi-attractors means that the recall of the normal information sequence is intermittently interrupted by episodes with chaotic dynamics. We indicate potential dynamic ways for augmenting damaged working memory and other cognitive functions. PMID:25452717
Meeting the memory challenges of brain-scale network simulation.
Kunkel, Susanne; Potjans, Tobias C; Eppler, Jochen M; Plesser, Hans Ekkehard; Morrison, Abigail; Diesmann, Markus
2011-01-01
The development of high-performance simulation software is crucial for studying the brain connectome. Using connectome data to generate neurocomputational models requires software capable of coping with models on a variety of scales: from the microscale, investigating plasticity, and dynamics of circuits in local networks, to the macroscale, investigating the interactions between distinct brain regions. Prior to any serious dynamical investigation, the first task of network simulations is to check the consistency of data integrated in the connectome and constrain ranges for yet unknown parameters. Thanks to distributed computing techniques, it is possible today to routinely simulate local cortical networks of around 10(5) neurons with up to 10(9) synapses on clusters and multi-processor shared-memory machines. However, brain-scale networks are orders of magnitude larger than such local networks, in terms of numbers of neurons and synapses as well as in terms of computational load. Such networks have been investigated in individual studies, but the underlying simulation technologies have neither been described in sufficient detail to be reproducible nor made publicly available. Here, we discover that as the network model sizes approach the regime of meso- and macroscale simulations, memory consumption on individual compute nodes becomes a critical bottleneck. This is especially relevant on modern supercomputers such as the Blue Gene/P architecture where the available working memory per CPU core is rather limited. We develop a simple linear model to analyze the memory consumption of the constituent components of neuronal simulators as a function of network size and the number of cores used. This approach has multiple benefits. The model enables identification of key contributing components to memory saturation and prediction of the effects of potential improvements to code before any implementation takes place. As a consequence, development cycles can be shorter and less expensive. Applying the model to our freely available Neural Simulation Tool (NEST), we identify the software components dominant at different scales, and develop general strategies for reducing the memory consumption, in particular by using data structures that exploit the sparseness of the local representation of the network. We show that these adaptations enable our simulation software to scale up to the order of 10,000 processors and beyond. As memory consumption issues are likely to be relevant for any software dealing with complex connectome data on such architectures, our approach and our findings should be useful for researchers developing novel neuroinformatics solutions to the challenges posed by the connectome project.
High Resolution Diffusion Tensor Imaging of Cortical-Subcortical White Matter Tracts in TBI
2010-10-01
by the individual (e.g., car full of lettuce ) or words that share phonemic qualities (e.g., chair/cat; sofa/soup). The observed bidirectional...subjective clustering score minus the expected subjective clustering score. An example is if the word pair car/ lettuce (subjective observed score of 1) is...adjusted subjective clustering formula of observed subjective clustering (car/ lettuce , subjective observed score of 1) minus expected subjective
Oh, Jeongsu; Choi, Chi-Hwan; Park, Min-Kyu; Kim, Byung Kwon; Hwang, Kyuin; Lee, Sang-Heon; Hong, Soon Gyu; Nasir, Arshan; Cho, Wan-Sup; Kim, Kyung Mo
2016-01-01
High-throughput sequencing can produce hundreds of thousands of 16S rRNA sequence reads corresponding to different organisms present in the environmental samples. Typically, analysis of microbial diversity in bioinformatics starts from pre-processing followed by clustering 16S rRNA reads into relatively fewer operational taxonomic units (OTUs). The OTUs are reliable indicators of microbial diversity and greatly accelerate the downstream analysis time. However, existing hierarchical clustering algorithms that are generally more accurate than greedy heuristic algorithms struggle with large sequence datasets. To keep pace with the rapid rise in sequencing data, we present CLUSTOM-CLOUD, which is the first distributed sequence clustering program based on In-Memory Data Grid (IMDG) technology-a distributed data structure to store all data in the main memory of multiple computing nodes. The IMDG technology helps CLUSTOM-CLOUD to enhance both its capability of handling larger datasets and its computational scalability better than its ancestor, CLUSTOM, while maintaining high accuracy. Clustering speed of CLUSTOM-CLOUD was evaluated on published 16S rRNA human microbiome sequence datasets using the small laboratory cluster (10 nodes) and under the Amazon EC2 cloud-computing environments. Under the laboratory environment, it required only ~3 hours to process dataset of size 200 K reads regardless of the complexity of the human microbiome data. In turn, one million reads were processed in approximately 20, 14, and 11 hours when utilizing 20, 30, and 40 nodes on the Amazon EC2 cloud-computing environment. The running time evaluation indicates that CLUSTOM-CLOUD can handle much larger sequence datasets than CLUSTOM and is also a scalable distributed processing system. The comparative accuracy test using 16S rRNA pyrosequences of a mock community shows that CLUSTOM-CLOUD achieves higher accuracy than DOTUR, mothur, ESPRIT-Tree, UCLUST and Swarm. CLUSTOM-CLOUD is written in JAVA and is freely available at http://clustomcloud.kopri.re.kr.
Park, Min-Kyu; Kim, Byung Kwon; Hwang, Kyuin; Lee, Sang-Heon; Hong, Soon Gyu; Nasir, Arshan; Cho, Wan-Sup; Kim, Kyung Mo
2016-01-01
High-throughput sequencing can produce hundreds of thousands of 16S rRNA sequence reads corresponding to different organisms present in the environmental samples. Typically, analysis of microbial diversity in bioinformatics starts from pre-processing followed by clustering 16S rRNA reads into relatively fewer operational taxonomic units (OTUs). The OTUs are reliable indicators of microbial diversity and greatly accelerate the downstream analysis time. However, existing hierarchical clustering algorithms that are generally more accurate than greedy heuristic algorithms struggle with large sequence datasets. To keep pace with the rapid rise in sequencing data, we present CLUSTOM-CLOUD, which is the first distributed sequence clustering program based on In-Memory Data Grid (IMDG) technology–a distributed data structure to store all data in the main memory of multiple computing nodes. The IMDG technology helps CLUSTOM-CLOUD to enhance both its capability of handling larger datasets and its computational scalability better than its ancestor, CLUSTOM, while maintaining high accuracy. Clustering speed of CLUSTOM-CLOUD was evaluated on published 16S rRNA human microbiome sequence datasets using the small laboratory cluster (10 nodes) and under the Amazon EC2 cloud-computing environments. Under the laboratory environment, it required only ~3 hours to process dataset of size 200 K reads regardless of the complexity of the human microbiome data. In turn, one million reads were processed in approximately 20, 14, and 11 hours when utilizing 20, 30, and 40 nodes on the Amazon EC2 cloud-computing environment. The running time evaluation indicates that CLUSTOM-CLOUD can handle much larger sequence datasets than CLUSTOM and is also a scalable distributed processing system. The comparative accuracy test using 16S rRNA pyrosequences of a mock community shows that CLUSTOM-CLOUD achieves higher accuracy than DOTUR, mothur, ESPRIT-Tree, UCLUST and Swarm. CLUSTOM-CLOUD is written in JAVA and is freely available at http://clustomcloud.kopri.re.kr. PMID:26954507
Lee, Junghee; Rizzo, Shemra; Altshuler, Lori; Glahn, David C; Miklowitz, David J; Sugar, Catherine A; Wynn, Jonathan K; Green, Michael F
2017-02-01
Bipolar disorder (BD) and schizophrenia (SZ) show substantial overlap. It has been suggested that a subgroup of patients might contribute to these overlapping features. This study employed a cross-diagnostic cluster analysis to identify subgroups of individuals with shared cognitive phenotypes. 143 participants (68 BD patients, 39 SZ patients and 36 healthy controls) completed a battery of EEG and performance assessments on perception, nonsocial cognition and social cognition. A K-means cluster analysis was conducted with all participants across diagnostic groups. Clinical symptoms, functional capacity, and functional outcome were assessed in patients. A two-cluster solution across 3 groups was the most stable. One cluster including 44 BD patients, 31 controls and 5 SZ patients showed better cognition (High cluster) than the other cluster with 24 BD patients, 35 SZ patients and 5 controls (Low cluster). BD patients in the High cluster performed better than BD patients in the Low cluster across cognitive domains. Within each cluster, participants with different clinical diagnoses showed different profiles across cognitive domains. All patients are in the chronic phase and out of mood episode at the time of assessment and most of the assessment were behavioral measures. This study identified two clusters with shared cognitive phenotype profiles that were not proxies for clinical diagnoses. The finding of better social cognitive performance of BD patients than SZ patients in the Lowe cluster suggest that relatively preserved social cognition may be important to identify disease process distinct to each disorder. Copyright © 2016 Elsevier B.V. All rights reserved.
The computational nature of memory modification
Gershman, Samuel J; Monfils, Marie-H; Norman, Kenneth A; Niv, Yael
2017-01-01
Retrieving a memory can modify its influence on subsequent behavior. We develop a computational theory of memory modification, according to which modification of a memory trace occurs through classical associative learning, but which memory trace is eligible for modification depends on a structure learning mechanism that discovers the units of association by segmenting the stream of experience into statistically distinct clusters (latent causes). New memories are formed when the structure learning mechanism infers that a new latent cause underlies current sensory observations. By the same token, old memories are modified when old and new sensory observations are inferred to have been generated by the same latent cause. We derive this framework from probabilistic principles, and present a computational implementation. Simulations demonstrate that our model can reproduce the major experimental findings from studies of memory modification in the Pavlovian conditioning literature. DOI: http://dx.doi.org/10.7554/eLife.23763.001 PMID:28294944
Initial Performance Results on IBM POWER6
NASA Technical Reports Server (NTRS)
Saini, Subbash; Talcott, Dale; Jespersen, Dennis; Djomehri, Jahed; Jin, Haoqiang; Mehrotra, Piysuh
2008-01-01
The POWER5+ processor has a faster memory bus than that of the previous generation POWER5 processor (533 MHz vs. 400 MHz), but the measured per-core memory bandwidth of the latter is better than that of the former (5.7 GB/s vs. 4.3 GB/s). The reason for this is that in the POWER5+, the two cores on the chip share the L2 cache, L3 cache and memory bus. The memory controller is also on the chip and is shared by the two cores. This serializes the path to memory. For consistently good performance on a wide range of applications, the performance of the processor, the memory subsystem, and the interconnects (both latency and bandwidth) should be balanced. Recognizing this, IBM has designed the Power6 processor so as to avoid the bottlenecks due to the L2 cache, memory controller and buffer chips of the POWER5+. Unlike the POWER5+, each core in the POWER6 has its own L2 cache (4 MB - double that of the Power5+), memory controller and buffer chips. Each core in the POWER6 runs at 4.7 GHz instead of 1.9 GHz in POWER5+. In this paper, we evaluate the performance of a dual-core Power6 based IBM p6-570 system, and we compare its performance with that of a dual-core Power5+ based IBM p575+ system. In this evaluation, we have used the High- Performance Computing Challenge (HPCC) benchmarks, NAS Parallel Benchmarks (NPB), and four real-world applications--three from computational fluid dynamics and one from climate modeling.
Source memory enhancement for emotional words.
Doerksen, S; Shimamura, A P
2001-03-01
The influence of emotional stimuli on source memory was investigated by using emotionally valenced words. The words were colored blue or yellow (Experiment 1) or surrounded by a blue or yellow frame (Experiment 2). Participants were asked to associate the words with the colors. In both experiments, emotionally valenced words elicited enhanced free recall compared with nonvalenced words; however, recognition memory was not affected. Source memory for the associated color was also enhanced for emotional words, suggesting that even memory for contextual information is benefited by emotional stimuli. This effect was not due to the ease of semantic clustering of emotional words because semantically related words were not associated with enhanced source memory, despite enhanced recall (Experiment 3). It is suggested that enhancement resulted from facilitated arousal or attention, which may act to increase organization processes important for source memory.
NASA Technical Reports Server (NTRS)
Lawson, Gary; Poteat, Michael; Sosonkina, Masha; Baurle, Robert; Hammond, Dana
2016-01-01
In this work, several mini-apps have been created to enhance a real-world application performance, namely the VULCAN code for complex flow analysis developed at the NASA Langley Research Center. These mini-apps explore hybrid parallel programming paradigms with Message Passing Interface (MPI) for distributed memory access and either Shared MPI (SMPI) or OpenMP for shared memory accesses. Performance testing shows that MPI+SMPI yields the best execution performance, while requiring the largest number of code changes. A maximum speedup of 23X was measured for MPI+SMPI, but only 10X was measured for MPI+OpenMP.
Implementation and performance of parallel Prolog interpreter
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wei, S.; Kale, L.V.; Balkrishna, R.
1988-01-01
In this paper, the authors discuss the implementation of a parallel Prolog interpreter on different parallel machines. The implementation is based on the REDUCE--OR process model which exploits both AND and OR parallelism in logic programs. It is machine independent as it runs on top of the chare-kernel--a machine-independent parallel programming system. The authors also give the performance of the interpreter running a diverse set of benchmark pargrams on parallel machines including shared memory systems: an Alliant FX/8, Sequent and a MultiMax, and a non-shared memory systems: Intel iPSC/32 hypercube, in addition to its performance on a multiprocessor simulation system.
Parallel discrete event simulation using shared memory
NASA Technical Reports Server (NTRS)
Reed, Daniel A.; Malony, Allen D.; Mccredie, Bradley D.
1988-01-01
With traditional event-list techniques, evaluating a detailed discrete-event simulation-model can often require hours or even days of computation time. By eliminating the event list and maintaining only sufficient synchronization to ensure causality, parallel simulation can potentially provide speedups that are linear in the numbers of processors. A set of shared-memory experiments, using the Chandy-Misra distributed-simulation algorithm, to simulate networks of queues is presented. Parameters of the study include queueing network topology and routing probabilities, number of processors, and assignment of network nodes to processors. These experiments show that Chandy-Misra distributed simulation is a questionable alternative to sequential-simulation of most queueing network models.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jones, J.P.; Bangs, A.L.; Butler, P.L.
Hetero Helix is a programming environment which simulates shared memory on a heterogeneous network of distributed-memory computers. The machines in the network may vary with respect to their native operating systems and internal representation of numbers. Hetero Helix presents a simple programming model to developers, and also considers the needs of designers, system integrators, and maintainers. The key software technology underlying Hetero Helix is the use of a compiler'' which analyzes the data structures in shared memory and automatically generates code which translates data representations from the format native to each machine into a common format, and vice versa. Themore » design of Hetero Helix was motivated in particular by the requirements of robotics applications. Hetero Helix has been used successfully in an integration effort involving 27 CPUs in a heterogeneous network and a body of software totaling roughly 100,00 lines of code. 25 refs., 6 figs.« less
Olivers, Christian N L; Meijer, Frank; Theeuwes, Jan
2006-10-01
In 7 experiments, the authors explored whether visual attention (the ability to select relevant visual information) and visual working memory (the ability to retain relevant visual information) share the same content representations. The presence of singleton distractors interfered more strongly with a visual search task when it was accompanied by an additional memory task. Singleton distractors interfered even more when they were identical or related to the object held in memory, but only when it was difficult to verbalize the memory content. Furthermore, this content-specific interaction occurred for features that were relevant to the memory task but not for irrelevant features of the same object or for once-remembered objects that could be forgotten. Finally, memory-related distractors attracted more eye movements but did not result in longer fixations. The results demonstrate memory-driven attentional capture on the basis of content-specific representations. Copyright 2006 APA.
Singer, Jefferson A; Blagov, Pavel; Berry, Meredith; Oost, Kathryn M
2013-12-01
An integrative model of narrative identity builds on a dual memory system that draws on episodic memory and a long-term self to generate autobiographical memories. Autobiographical memories related to critical goals in a lifetime period lead to life-story memories, which in turn become self-defining memories when linked to an individual's enduring concerns. Self-defining memories that share repetitive emotion-outcome sequences yield narrative scripts, abstracted templates that filter cognitive-affective processing. The life story is the individual's overarching narrative that provides unity and purpose over the life course. Healthy narrative identity combines memory specificity with adaptive meaning-making to achieve insight and well-being, as demonstrated through a literature review of personality and clinical research, as well as new findings from our own research program. A clinical case study drawing on this narrative identity model is also presented with implications for treatment and research. © 2012 Wiley Periodicals, Inc.
Working Memory in Children: A Time-Constrained Functioning Similar to Adults
ERIC Educational Resources Information Center
Portrat, Sophie; Camos, Valerie; Barrouillet, Pierre
2009-01-01
Within the time-based resource-sharing (TBRS) model, we tested a new conception of the relationships between processing and storage in which the core mechanisms of working memory (WM) are time constrained. However, our previous studies were restricted to adults. The current study aimed at demonstrating that these mechanisms are present and…
Close Associations and Memory in Brainwriting Groups
ERIC Educational Resources Information Center
Coskun, Hamit
2011-01-01
The present experiment examined whether or not the type of associations (close (e.g. apple-pear) and distant (e.g. apple-fish) word associations) and memory instruction (paying attention to the ideas of others) had effects on the idea generation performances in the brainwriting paradigm in which all participants shared their ideas by using paper…
NASA Technical Reports Server (NTRS)
Byrne, F.
1981-01-01
Time-shared interface speeds data processing in distributed computer network. Two-level high-speed scanning approach routes information to buffer, portion of which is reserved for series of "first-in, first-out" memory stacks. Buffer address structure and memory are protected from noise or failed components by error correcting code. System is applicable to any computer or processing language.
Accumulating Evidence about What Prospective Memory Costs Actually Reveal
ERIC Educational Resources Information Center
Strickland, Luke; Heathcote, Andrew; Remington, Roger W.; Loft, Shayne
2017-01-01
Event-based prospective memory (PM) tasks require participants to substitute an atypical PM response for an ongoing task response when presented with PM targets. Responses to ongoing tasks are often slower with the addition of PM demands ("PM costs"). Prominent PM theories attribute costs to capacity-sharing between the ongoing and PM…
How communication goals determine when audience tuning biases memory.
Echterhoff, Gerald; Higgins, E Tory; Kopietz, René; Groll, Stephan
2008-02-01
After tuning their message to suit their audience's attitude, communicators' own memories for the original information (e.g., a target person's behaviors) often reflect the biased view expressed in their message--producing an audience-congruent memory bias. Exploring the motivational circumstances of message production, the authors investigated whether this bias depends on the goals driving audience tuning. In 4 experiments, the memory bias was found to a greater extent when audience tuning served the creation of a shared reality than when it served alternative, nonshared reality goals (being polite toward a stigmatized-group audience; obtaining incentives; being entertaining; complying with a blatant demand). In addition, the authors found that these effects were mediated by the epistemic trust in the audience-congruent view but not by the rehearsal or accurate retrieval of the original input information, the ability to discriminate between the original and the message information, or a contrast away from extremely tuned messages. The central role of epistemic trust, a measure of the communicators' experience of shared reality, was supported in meta-analyses across the experiments. PsycINFO Database Record (c) 2008 APA, all rights reserved.
Schneider, Daniel; Barth, Anna; Wascher, Edmund
2017-11-15
Attention can be allocated toward mental representations in working memory also after the initial encoding of information has been completed. It was shown that focusing on only one item within working memory transfers this representation into a protected state, reducing its susceptibility to interference by incoming signals. The present study investigated the nature of this retroactive cue (retro-cue) benefit by means of oscillatory activity in the EEG. In a working memory task with a retro-cue indicating one, two or three memory representations as relevant and a block-wise distractor display presented after the retro-cue, participants had to remember the orientation of a colored bar. On behavioral level, we found that the interfering effect of the distractor display on memory performance could be prevented when a retro-cue reduced the number of attended representations in working memory. However, only the one-item retro-cue led to an overall increase in task performance compared to a condition without a retro-cue. The neural basis of this special representational status was investigated by means of oscillatory parameters in the EEG and a clustering approach on level of the independent components (ICs) in the signal. The retroactive reduction of attended working memory representations was reflected in a suppression of alpha power over right parietal and parieto-occipital sites. In addition, we found that an IC cluster representing oscillatory activity in the mu/beta range (10-12 Hz and 20-24 Hz) with a source in sensorimotor cortex revealed a power suppression already prior to the memory probe following the one-item retro-cue. This suggests that the retro-cue benefit results in large parts from the possibility to focus attention on one particular item in working memory and initiate motor planning processes already ahead of the probe stimulus indicating the respective response. Copyright © 2017 Elsevier Inc. All rights reserved.
[Semantic verbal fluency of animals in amnesia-type mild cognitive impairment].
Lopez-Higes, Ramón; Prados, José M; del Rio, David; Galindo-Fuentes, Marta; Reinoso, Ana Isabel; Lozano-Ibanez, Montserrat
2014-06-01
The quantitative and qualitative analysis of the semantic verbal fluency task has revealed that people with dementia produced fewer words and smaller semantic clustering than people without dementia. However, in people with amnestic mild cognitive impairment (aMCI), research has shown conflicting results regarding the amount and number of semantic clusters that are made. The aim of this study was to provide new data to this controversial issue. Twenty-two older adults diagnosed with aMCI (8 men and 14 women) and 43 older adults (7 men and 36 women) with normal cognitive functioning that served as control group, participated in this study. All patients were evaluated at the Center for Prevention of Cognitive Decline of Madrid (Spain), completing the verbal fluency test (animals) besides other neuropsychological tests. As expected, animal production was lower in the aMCI group than in the control group, but no differences were observed either in the average size of the semantic clusters or the number of switches between them. The results are consistent with previous research suggesting aMCI is not only characterized by episodic memory and working memory deficits. Semantic memory decline is also present. However, the data do not clarify how strategic executive processes are involved, as seems to be in Alzheimer's disease.
De Lillo, Carlo; Kirby, Melissa; Poole, Daniel
2016-01-01
Immediate serial spatial recall measures the ability to retain sequences of locations in short-term memory and is considered the spatial equivalent of digit span. It is tested by requiring participants to reproduce sequences of movements performed by an experimenter or displayed on a monitor. Different organizational factors dramatically affect serial spatial recall but they are often confounded or underspecified. Untangling them is crucial for the characterization of working-memory models and for establishing the contribution of structure and memory capacity to spatial span. We report five experiments assessing the relative role and independence of factors that have been reported in the literature. Experiment 1 disentangled the effects of spatial clustering and path-length by manipulating the distance of items displayed on a touchscreen monitor. Long-path sequences segregated by spatial clusters were compared with short-path sequences not segregated by clusters. Recall was more accurate for sequences segregated by clusters independently from path-length. Experiment 2 featured conditions where temporal pauses were introduced between or within cluster boundaries during the presentation of sequences with the same paths. Thus, the temporal structure of the sequences was either consistent or inconsistent with a hierarchical representation based on segmentation by spatial clusters but the effect of structure could not be confounded with effects of path-characteristics. Pauses at cluster boundaries yielded more accurate recall, as predicted by a hierarchical model. In Experiment 3, the systematic manipulation of sequence structure, path-length, and presence of path-crossings of sequences showed that structure explained most of the variance, followed by the presence/absence of path-crossings, and path-length. Experiments 4 and 5 replicated the results of the previous experiments in immersive virtual reality navigation tasks where the viewpoint of the observer changed dynamically during encoding and recall. This suggested that the effects of structure in spatial span are not dependent on perceptual grouping processes induced by the aerial view of the stimulus array typically afforded by spatial recall tasks. These results demonstrate the independence of coding strategies based on structure from effects of path characteristics and perceptual grouping in immediate serial spatial recall. PMID:27891101
Shared filtering processes link attentional and visual short-term memory capacity limits.
Bettencourt, Katherine C; Michalka, Samantha W; Somers, David C
2011-09-30
Both visual attention and visual short-term memory (VSTM) have been shown to have capacity limits of 4 ± 1 objects, driving the hypothesis that they share a visual processing buffer. However, these capacity limitations also show strong individual differences, making the degree to which these capacities are related unclear. Moreover, other research has suggested a distinction between attention and VSTM buffers. To explore the degree to which capacity limitations reflect the use of a shared visual processing buffer, we compared individual subject's capacities on attentional and VSTM tasks completed in the same testing session. We used a multiple object tracking (MOT) and a VSTM change detection task, with varying levels of distractors, to measure capacity. Significant correlations in capacity were not observed between the MOT and VSTM tasks when distractor filtering demands differed between the tasks. Instead, significant correlations were seen when the tasks shared spatial filtering demands. Moreover, these filtering demands impacted capacity similarly in both attention and VSTM tasks. These observations fail to support the view that visual attention and VSTM capacity limits result from a shared buffer but instead highlight the role of the resource demands of underlying processes in limiting capacity.
Kaczkurkin, Antonia N; Zang, Yinyin; Gay, Natalie G; Peterson, Alan L; Yarvis, Jeffrey S; Borah, Elisa V; Dondanville, Katherine A; Hembree, Elizabeth A; Litz, Brett T; Mintz, Jim; Young-McCaughan, Stacey; Foa, Edna B
2017-08-01
Maladaptive cognitive emotion regulation strategies have been proposed to contribute to the maintenance of posttraumatic stress disorder (PTSD). Prior work has focused on the relationship between these strategies and PTSD as a whole, rather than on how they are related to each PTSD symptom cluster. The purpose of the current study was to determine whether cognitive emotion regulation strategies are predictive of certain PTSD symptom clusters under the Diagnostic and Statistical Manual of Mental Disorders 5th ed. (DSM-5; American Psychiatric Association, 2013) criteria (intrusive thoughts, avoidance, negative alterations in cognitions and mood, and hyperarousal). Participants included 365 treatment-seeking, active-duty military personnel with PTSD. The negative alterations in cognitions and mood cluster were associated with dysfunctional cognitions: greater negative cognitions about the self, negative cognitions about the world, and self-blame, as well as catastrophizing (Rc2 = .519). The negative alterations in cognitions and mood cluster did not show a strong relationship with blaming others, possibly due to the complex nature of self- and other-blame in this primarily deployment-related PTSD sample. Finally, the intrusive thoughts cluster was associated with catastrophizing (Rc2 = .211), suggesting an association between frequent intrusive memories and excessively negative interpretation of those memories. Copyright © 2017 International Society for Traumatic Stress Studies.
NASA Astrophysics Data System (ADS)
Inamura, T.; Hosoda, H.; Miyazaki, S.
2013-02-01
The frequency distribution of habit plane variant (HPV) clusters and the deviation from twin orientation relationships (ORs) at the junction plane (JP) are investigated by transmission electron microscopy together with theoretical evaluation of the kinematic compatibility (KC) at the JP in a β-titanium shape memory alloy. Even though there are more than 10 types of possible HPV clusters, only three types are formed. V-shaped couplings of HPVs by {111} type I twins (VI: 49%) and by ⟨211⟩ type II twins (VII: 42%) are the predominant types. A triangular morphology due to coupling of {111} type I twins is observed with a frequency of only 9%. These preferred morphologies are well explained by the degree of incompatibility (the rotation necessary for compatible connection of HPVs). The exact twin OR and KC are maintained at the JP in a VI cluster instead of KC at the habit plane (HP), whereas the JP in a VII cluster is incompatible and the ⟨211⟩ type II twin OR shows slight deviation at the JP by about 0.4°. The competition between KC at the JP and KC at the HP (invariant plane) is responsible for the frequency distribution of HPV clusters and the character of the interfaces in the self-accommodation microstructure.
A class Hierarchical, object-oriented approach to virtual memory management
NASA Technical Reports Server (NTRS)
Russo, Vincent F.; Campbell, Roy H.; Johnston, Gary M.
1989-01-01
The Choices family of operating systems exploits class hierarchies and object-oriented programming to facilitate the construction of customized operating systems for shared memory and networked multiprocessors. The software is being used in the Tapestry laboratory to study the performance of algorithms, mechanisms, and policies for parallel systems. Described here are the architectural design and class hierarchy of the Choices virtual memory management system. The software and hardware mechanisms and policies of a virtual memory system implement a memory hierarchy that exploits the trade-off between response times and storage capacities. In Choices, the notion of a memory hierarchy is captured by abstract classes. Concrete subclasses of those abstractions implement a virtual address space, segmentation, paging, physical memory management, secondary storage, and remote (that is, networked) storage. Captured in the notion of a memory hierarchy are classes that represent memory objects. These classes provide a storage mechanism that contains encapsulated data and have methods to read or write the memory object. Each of these classes provides specializations to represent the memory hierarchy.
Werner-Seidler, Aliza; Hitchcock, Caitlin; Bevan, Anna; McKinnon, Anna; Gillard, Julia; Dahm, Theresa; Chadwick, Isobel; Panesar, Inderpal; Breakwell, Lauren; Mueller, Viola; Rodrigues, Evangeline; Rees, Catrin; Gormley, Siobhan; Schweizer, Susanne; Watson, Peter; Raes, Filip; Jobson, Laura; Dalgleish, Tim
2018-06-01
Impaired ability to recall specific autobiographical memories is characteristic of depression, which when reversed, may have therapeutic benefits. This cluster-randomized controlled pilot trial investigated efficacy and aspects of acceptability, and feasibility of MEmory Specificity Training (MEST) relative to Psychoeducation and Supportive Counselling (PSC) for Major Depressive Disorder (N = 62). A key aim of this study was to determine a range of effect size estimates to inform a later phase trial. Assessments were completed at baseline, post-treatment and 3-month follow-up. The cognitive process outcome was memory specificity. The primary clinical outcome was symptoms on the Beck Depression Inventory-II at 3-month follow-up. The MEST group demonstrated greater improvement in memory specificity relative to PSC at post-intervention (d = 0.88) and follow-up (d = 0.74), relative to PSC. Both groups experienced a reduction in depressive symptoms at 3-month follow-up (d = 0.67). However, there was no support for a greater improvement in depressive symptoms at 3 months following MEST relative to PSC (d = -0.04). Although MEST generated changes on memory specificity and improved depressive symptoms, results provide no indication that MEST is superior to PSC in the resolution of self-reported depressive symptoms. Implications for later-phase definitive trials of MEST are discussed. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.
Finkel, Deborah; Pedersen, Nancy L
2014-01-01
Intraindividual variability (IIV) in reaction time has been related to cognitive decline, but questions remain about the nature of this relationship. Mean and range in movement and decision time for simple reaction time were available from 241 individuals aged 51-86 years at the fifth testing wave of the Swedish Adoption/Twin Study of Aging. Cognitive performance on four factors was also available: verbal, spatial, memory, and speed. Analyses indicated that range in reaction time could be used as an indicator of IIV. Heritability estimates were 35% for mean reaction and 20% for range in reaction. Multivariate analysis indicated that the genetic variance on the memory, speed, and spatial factors is shared with genetic variance for mean or range in reaction time. IIV shares significant genetic variance with fluid ability in late adulthood, over and above and genetic variance shared with mean reaction time.
A Study of Shared-Memory Mutual Exclusion Protocols Using CADP
NASA Astrophysics Data System (ADS)
Mateescu, Radu; Serwe, Wendelin
Mutual exclusion protocols are an essential building block of concurrent systems: indeed, such a protocol is required whenever a shared resource has to be protected against concurrent non-atomic accesses. Hence, many variants of mutual exclusion protocols exist in the shared-memory setting, such as Peterson's or Dekker's well-known protocols. Although the functional correctness of these protocols has been studied extensively, relatively little attention has been paid to their non-functional aspects, such as their performance in the long run. In this paper, we report on experiments with the performance evaluation of mutual exclusion protocols using Interactive Markov Chains. Steady-state analysis provides an additional criterion for comparing protocols, which complements the verification of their functional properties. We also carefully re-examined the functional properties, whose accurate formulation as temporal logic formulas in the action-based setting turns out to be quite involved.
Handling debugger breakpoints in a shared instruction system
Gooding, Thomas Michael; Shok, Richard Michael
2014-01-21
A debugger debugs processes that execute shared instructions so that a breakpoint set for one process will not cause a breakpoint to occur in the other processes. A breakpoint is set by recording the original instruction at the desired location and writing a trap instruction to the shared instructions at that location. When a process encounters the breakpoint, the process passes control to the debugger for breakpoint processing if the breakpoint was set at that location for that process. If the trap was not set at that location for that process, the cacheline containing the trap is copied to a small scratchpad memory, and the virtual memory mappings are changed to translate the virtual address of the cacheline to the scratchpad. The original instruction is then written to replace the trap instruction in the scratchpad, so that process can execute the instructions in the scatchpad thereby avoiding the trap instruction.
An Army dentist in the combat zone during WWII.
Orden, C Q
2001-11-01
It is 60 years since the bombing of Pearl Harbor and the outbreak of World War II for the United States. Some of the men and women who served in the armed forces at the time are willing to share some of their reminiscences with those of us who could not serve for one reason or another or who may not even have been born at the time. One of the dentists who is willing to share some of his memories is Dr. Charles Q. Orden of New York. Unless these people share their memories much history will be lost forever in the next years, and we will all be poorer for it. We sincerely thank Dr. Orden for his offer of information and for allowing us to reproduce Fig. 1 in which he is seen as the dentist using a field dental chair, a foot-powered drill, and with a black dental corpsman as his assistant.
Reder, Lynne M.; Park, Heekyeong; Kieffaber, Paul D.
2009-01-01
There is a popular hypothesis that performance on implicit and explicit memory tasks reflects 2 distinct memory systems. Explicit memory is said to store those experiences that can be consciously recollected, and implicit memory is said to store experiences and affect subsequent behavior but to be unavailable to conscious awareness. Although this division based on awareness is a useful taxonomy for memory tasks, the authors review the evidence that the unconscious character of implicit memory does not necessitate that it be treated as a separate system of human memory. They also argue that some implicit and explicit memory tasks share the same memory representations and that the important distinction is whether the task (implicit or explicit) requires the formation of a new association. The authors review and critique dissociations from the behavioral, amnesia, and neuroimaging literatures that have been advanced in support of separate explicit and implicit memory systems by highlighting contradictory evidence and by illustrating how the data can be accounted for using a simple computational memory model that assumes the same memory representation for those disparate tasks. PMID:19210052
Gonneaud, Julie; Kalpouzos, Grégoria; Bon, Laetitia; Viader, Fausto; Eustache, Francis; Desgranges, Béatrice
2011-01-01
Prospective memory (PM) is the ability to remember to perform an action at a specific point in the future. Regarded as multidimensional, PM involves several cognitive functions that are known to be impaired in normal aging. In the present study, we set out to investigate the cognitive correlates of PM impairment in normal aging. Manipulating cognitive load, we assessed event- and time-based PM, as well as several cognitive functions, including executive functions, working memory and retrospective episodic memory, in healthy subjects covering the entire adulthood. We found that normal aging was characterized by PM decline in all conditions and that event-based PM was more sensitive to the effects of aging than time-based PM. Whatever the conditions, PM was linked to inhibition and processing speed. However, while event-based PM was mainly mediated by binding and retrospective memory processes, time-based PM was mainly related to inhibition. The only distinction between high- and low-load PM cognitive correlates lays in an additional, but marginal, correlation between updating and the high-load PM condition. The association of distinct cognitive functions, as well as shared mechanisms with event- and time-based PM confirms that each type of PM relies on a different set of processes. PMID:21678154
de la Serna, Elena; Sugranyes, Gisela; Sanchez-Gistau, Vanessa; Rodriguez-Toscano, Elisa; Baeza, Immaculada; Vila, Montserrat; Romero, Soledad; Sanchez-Gutierrez, Teresa; Penzol, Mª José; Moreno, Dolores; Castro-Fornieles, Josefina
2017-05-01
Schizophrenia (SZ) and bipolar disorder (BD) are considered neurobiological disorders which share some clinical, cognitive and neuroimaging characteristics. Studying child and adolescent offspring of patients diagnosed with bipolar disorder (BDoff) or schizophrenia (SZoff) is regarded as a reliable method for investigating early alterations and vulnerability factors for these disorders. This study compares the neuropsychological characteristics of SZoff, BDoff and a community control offspring group (CC) with the aim of examining shared and differential cognitive characteristics among groups. 41 SZoff, 90 BDoff and 107 CC were recruited. They were all assessed with a complete neuropsychological battery which included intelligence quotient, working memory (WM), processing speed, verbal memory and learning, visual memory, executive functions and sustained attention. SZoff and BDoff showed worse performance in some cognitive areas compared with CC. Some of these difficulties (visual memory) were common to both offspring groups, whereas others, such as verbal learning and WM in SZoff or PSI in BDoff, were group-specific. The cognitive difficulties in visual memory shown by both the SZoff and BDoff groups might point to a common endophenotype in the two disorders. Difficulties in other cognitive functions would be specific depending on the family diagnosis. Copyright © 2016 Elsevier B.V. All rights reserved.
Working memory costs of task switching.
Liefooghe, Baptist; Barrouillet, Pierre; Vandierendonck, André; Camos, Valérie
2008-05-01
Although many accounts of task switching emphasize the importance of working memory as a substantial source of the switch cost, there is a lack of evidence demonstrating that task switching actually places additional demands on working memory. The present study addressed this issue by implementing task switching in continuous complex span tasks with strictly controlled time parameters. A series of 4 experiments demonstrate that recall performance decreased as a function of the number of task switches and that the concurrent load of item maintenance had no influence on task switching. These results indicate that task switching induces a cost on working memory functioning. Implications for theories of task switching, working memory, and resource sharing are addressed.
Lee, Jinmin; Sengupta, Prabuddha; Brzostowski, Joseph; Lippincott-Schwartz, Jennifer; Pierce, Susan K
2017-02-15
B-cell activation is initiated by the binding of antigen to the B-cell receptor (BCR). Here we used dSTORM superresolution imaging to characterize the nanoscale spatial organization of immunoglobulin M (IgM) and IgG BCRs on the surfaces of resting and antigen--activated human peripheral blood B-cells. We provide insights into both the fundamental process of antigen-driven BCR clustering and differences in the spatial organization of IgM and IgG BCRs that may contribute to the characteristic differences in the responses of naive and memory B-cells to antigen. We provide evidence that although both IgM and IgG BCRs reside in highly heterogeneous protein islands that vary in size and number of BCR single-molecule localizations, both resting and activated B-cells intrinsically maintain a high -frequency of single isolated BCR localizations, which likely represent BCR monomers. IgG BCRs are more clustered than IgM BCRs on resting cells and form larger protein islands after antigen activation. Small, dense BCR clusters likely formed via protein-protein interactions are present on the surface of resting cells, and antigen activation induces these to come together to form less dense, larger islands, a process likely governed, at least in part, by protein-lipid interactions. © 2017 Lee, Sengupta, et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
The Amish furniture cluster in Ohio: competitive factors and wood use estimates
Matthew Bumgardner; Robert Romig; William Luppold
2008-01-01
This paper is an assessment of wood use by the Amish furniture cluster located in northeastern Ohio. The paper also highlights the competitive and demographic factors that have enabled cluster growth and new business formation in a time of declining market share for the overall U.S. furniture industry. Several secondary information sources and discussions with local...
Komaki, Hisayuki; Sakurai, Kenta; Hosoyama, Akira; Kimura, Akane; Igarashi, Yasuhiro; Tamura, Tomohiko
2018-05-02
To identify the species of butyrolactol-producing Streptomyces strain TP-A0882, whole genome-sequencing of three type strains in a close taxonomic relationship was performed. In silico DNA-DNA hybridization using the genome sequences suggested that Streptomyces sp. TP-A0882 is classified as Streptomyces diastaticus subsp. ardesiacus. Strain TP-A0882, S. diastaticus subsp. ardesiacus NBRC 15402 T , Streptomyces coelicoflavus NBRC 15399 T , and Streptomyces rubrogriseus NBRC 15455 T harbor at least 14, 14, 10, and 12 biosynthetic gene clusters (BGCs), respectively, coding for nonribosomal peptide synthetases (NRPSs) and polyketide synthases (PKSs). All 14 gene clusters were shared by S. diastaticus subsp. ardesiacus strains TP-A0882 and NBRC 15402 T , while only four gene clusters were shared by the three distinct species. Although BGCs for bacteriocin, ectoine, indole, melanine, siderophores such as deferrioxamine, terpenes such as albaflavenone, hopene, carotenoid and geosmin are shared by the three species, many BGCs for secondary metabolites such as butyrolactone, lantipeptides, oligosaccharide, some terpenes are species-specific. These results indicate the possibility that strains belonging to the same species possess the same set of secondary metabolite-biosynthetic pathways, whereas strains belonging to distinct species have species-specific pathways, in addition to some common pathways, even if the strains are taxonomically close.
Method of up-front load balancing for local memory parallel processors
NASA Technical Reports Server (NTRS)
Baffes, Paul Thomas (Inventor)
1990-01-01
In a parallel processing computer system with multiple processing units and shared memory, a method is disclosed for uniformly balancing the aggregate computational load in, and utilizing minimal memory by, a network having identical computations to be executed at each connection therein. Read-only and read-write memory are subdivided into a plurality of process sets, which function like artificial processing units. Said plurality of process sets is iteratively merged and reduced to the number of processing units without exceeding the balance load. Said merger is based upon the value of a partition threshold, which is a measure of the memory utilization. The turnaround time and memory savings of the instant method are functions of the number of processing units available and the number of partitions into which the memory is subdivided. Typical results of the preferred embodiment yielded memory savings of from sixty to seventy five percent.
Zeithamova, Dagmar; Dominick, April L; Preston, Alison R
2012-07-12
Memory enables flexible use of past experience to inform new behaviors. Although leading theories hypothesize that this fundamental flexibility results from the formation of integrated memory networks relating multiple experiences, the neural mechanisms that support memory integration are not well understood. Here, we demonstrate that retrieval-mediated learning, whereby prior event details are reinstated during encoding of related experiences, supports participants' ability to infer relationships between distinct events that share content. Furthermore, we show that activation changes in a functionally coupled hippocampal and ventral medial prefrontal cortical circuit track the formation of integrated memories and successful inferential memory performance. These findings characterize the respective roles of these regions in retrieval-mediated learning processes that support relational memory network formation and inferential memory in the human brain. More broadly, these data reveal fundamental mechanisms through which memory representations are constructed into prospectively useful formats. Copyright © 2012 Elsevier Inc. All rights reserved.
Zeithamova, Dagmar; Dominick, April L.; Preston, Alison R.
2012-01-01
SUMMARY Memory enables flexible use of past experience to inform new behaviors. Though leading theories hypothesize that this fundamental flexibility results from the formation of integrated memory networks relating multiple experiences, the neural mechanisms that support memory integration are not well understood. Here, we demonstrate that retrieval-mediated learning, whereby prior event details are reinstated during encoding of related experiences, supports participants’ ability to infer relationships between distinct events that share content. Furthermore, we show that activation changes in a functionally coupled hippocampal and ventral medial prefrontal cortical circuit track the formation of integrated memories and successful inferential memory performance. These findings characterize the respective roles of these regions in retrieval-mediated learning processes that support relational memory network formation and inferential memory in the human brain. More broadly, these data reveal fundamental mechanisms through which memory representations are constructed into prospectively useful formats. PMID:22794270
Method and system for data clustering for very large databases
NASA Technical Reports Server (NTRS)
Livny, Miron (Inventor); Zhang, Tian (Inventor); Ramakrishnan, Raghu (Inventor)
1998-01-01
Multi-dimensional data contained in very large databases is efficiently and accurately clustered to determine patterns therein and extract useful information from such patterns. Conventional computer processors may be used which have limited memory capacity and conventional operating speed, allowing massive data sets to be processed in a reasonable time and with reasonable computer resources. The clustering process is organized using a clustering feature tree structure wherein each clustering feature comprises the number of data points in the cluster, the linear sum of the data points in the cluster, and the square sum of the data points in the cluster. A dense region of data points is treated collectively as a single cluster, and points in sparsely occupied regions can be treated as outliers and removed from the clustering feature tree. The clustering can be carried out continuously with new data points being received and processed, and with the clustering feature tree being restructured as necessary to accommodate the information from the newly received data points.
Jim Thomas: A Collection of Memories
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wong, Pak C.
Jim Thomas, a guest editor and a long-time associate editor of Information Visualization (IVS), died in Richland, WA, on August 6, 2010 due to complications from a brain tumor. His friends and colleagues from around the world have since expressed their sadness and paid tribute to a visionary scientist in multiple public forums. For those who didn't get the chance to know Jim, I share a collection of my own memories of Jim Thomas and memories from some of his colleagues.
Wang, Jong-Yi; Liang, Yia-Wen; Yeh, Chun-Chen; Liu, Chiu-Shong; Wang, Chen-Yu
2018-02-21
Spousal clustering of cancer warrants attention. Whether the common environment or high-age vulnerability determines cancer clustering is unclear. The risk of clustering in couples versus non-couples is undetermined. The time to cancer clustering after the first cancer diagnosis is yet to be reported. This study investigated cancer clustering over time among couples by using nationwide data. A cohort of 5643 married couples in the 2002-2013 Taiwan National Health Insurance Research Database was identified and randomly matched with 5643 non-couple pairs through dual propensity score matching. Factors associated with clustering (both spouses with tumours) were analysed by using the Cox proportional hazard model. Propensity-matched analysis revealed that the risk of clustering of all tumours among couples (13.70%) was significantly higher than that among non-couples (11.84%) (OR=1.182, 95% CI 1.058 to 1.321, P=0.0031). The median time to clustering of all tumours and of malignant tumours was 2.92 and 2.32 years, respectively. Risk characteristics associated with clustering included high age and comorbidity. Shared environmental factors among spouses might be linked to a high incidence of cancer clustering. Cancer incidence in one spouse may signal cancer vulnerability in the other spouse. Promoting family-oriented cancer care in vulnerable families and preventing shared lifestyle risk factors for cancer are suggested. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Effects of motor congruence on visual working memory.
Quak, Michel; Pecher, Diane; Zeelenberg, Rene
2014-10-01
Grounded-cognition theories suggest that memory shares processing resources with perception and action. The motor system could be used to help memorize visual objects. In two experiments, we tested the hypothesis that people use motor affordances to maintain object representations in working memory. Participants performed a working memory task on photographs of manipulable and nonmanipulable objects. The manipulable objects were objects that required either a precision grip (i.e., small items) or a power grip (i.e., large items) to use. A concurrent motor task that could be congruent or incongruent with the manipulable objects caused no difference in working memory performance relative to nonmanipulable objects. Moreover, the precision- or power-grip motor task did not affect memory performance on small and large items differently. These findings suggest that the motor system plays no part in visual working memory.
ERIC Educational Resources Information Center
Lucas, Heather D.; Taylor, Jason R.; Henson, Richard N.; Paller, Ken A.
2012-01-01
The neural mechanisms that underlie familiarity memory have been extensively investigated, but a consensus understanding remains elusive. Behavioral evidence suggests that familiarity sometimes shares sources with instances of implicit memory known as priming, in that the same increases in processing fluency that give rise to priming can engender…
Forward Association, Backward Association, and the False-Memory Illusion
ERIC Educational Resources Information Center
Brainerd, C. J.; Wright, Ron
2005-01-01
In the Deese-Roediger-McDermott false-memory illusion, forward associative strength (FAS) is unrelated to the strength of the illusion; this is puzzling, because high-FAS lists ought to share more semantic features with critical unpresented words than should low-FAS lists. The authors show that this null result is probably a truncated range…
The Impact of Storage on Processing: How Is Information Maintained in Working Memory?
ERIC Educational Resources Information Center
Vergauwe, Evie; Camos, Valérie; Barrouillet, Pierre
2014-01-01
Working memory is typically defined as a system devoted to the simultaneous maintenance and processing of information. However, the interplay between these 2 functions is still a matter of debate in the literature, with views ranging from complete independence to complete dependence. The time-based resource-sharing model assumes that a central…
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…
Android Protection Mechanism: A Signed Code Security Mechanism for Smartphone Applications
2011-03-01
status registers, exceptions, endian support, unaligned access support, synchronization primitives , the Jazelle Extension, and saturated integer...supports comprehensive non-blocking shared-memory synchronization primitives that scale for multiple-processor system designs. This is an improvement... synchronization . Memory semaphores can be loaded and altered without interruption because the load and store operations are atomic. Processor
Senior Citizens' Personal Stories...Literacy through Narrative...Sharing the Richness of the Past.
ERIC Educational Resources Information Center
Lineberry, Colleen
Using simple writing strategies, senior citizens at an elder camp workshop collected memories in journals. In some cases, readings were used to trigger memories. The exercise enabled students to make connections between their own life experiences and the life experiences of others. Workshops encouraging participants to tell their own stories for…
Processes and Content of Narrative Identity Development in Adolescence: Gender and Well-Being
ERIC Educational Resources Information Center
McLean, Kate C.; Breen, Andrea V.
2009-01-01
The present study examined narrative identity in adolescence (14-18 years) in terms of narrative content and processes of identity development. Age- and gender-related differences in narrative patterns in turning point memories and gender differences in the content and functions for sharing those memories were examined, as was the relationship…
ERIC Educational Resources Information Center
Burdette, Kimberly
2007-01-01
In this article, the author recalls and shares the first half of her college journey. Her memories do not play back to her in bursts of sounds or colors; friends or lovers; feelings, touches, tastes, or ideas. They play, rather, as silent images of herself that flicker disjointedly across her mind, the lens of her memory having recorded her…
Schools of the Past: A Treasury of Photographs. Fastback 80.
ERIC Educational Resources Information Center
Davis, O. L., Jr.
The experience of schooling in America is recalled through a memory-sharing essay and an album of photographs. The intent of the article is to prompt readers to remember their personal schooling experiences and relate them to the larger framework of national memories. The essay, focusing on schools at the turn of the 20th century, discusses…
Shared Etiology of Phonological Memory and Vocabulary Deficits in School-Age Children
ERIC Educational Resources Information Center
Peterson, Robin L.; Pennington, Bruce F.; Samuelsson, Stefan; Byrne, Brian; Olson, Richard K.
2013-01-01
Purpose: The goal of this study was to investigate the etiologic basis for the association between deficits in phonological memory (PM) and vocabulary in school-age children. Method: Children with deficits in PM or vocabulary were identified within the International Longitudinal Twin Study (ILTS; Samuelsson et al., 2005). The ILTS includes 1,045…
The CA3 Network as a Memory Store for Spatial Representations
ERIC Educational Resources Information Center
Papp, Gergely; Witter, Menno P.; Treves, Alessandro
2007-01-01
Comparative neuroanatomy suggests that the CA3 region of the mammalian hippocampus is directly homologous with the medio-dorsal pallium in birds and reptiles, with which it largely shares the basic organization of primitive cortex. Autoassociative memory models, which are generically applicable to cortical networks, then help assess how well CA3…
ERIC Educational Resources Information Center
Chang, Christine
2010-01-01
In this article, the author shares her memories of Sally Smith, the founder of The Lab School of Washington, where she works as the director of the Occupational Therapy. When the author first met Smith, Smith asked her what brought her to The Lab School at that point in her career. She told Smith that her background was rather eclectic, since she…
ERIC Educational Resources Information Center
Razook, Nim
2009-01-01
The author began teaching at the University of Oklahoma in the late 1970s. In this article, the author shares two memories of those times on campus. The first was looking out his office window and seeing Iranian students marching on campus, shouting, "The Shah is a Fascist Pig." The second memory provoked this paper. It made the author…
ERIC Educational Resources Information Center
Gross, Gwen E.
2008-01-01
In this article, the author shares her experience when she was still a student until she became a superintendent. In her 17th year in the superintendency, the author finds the joys of her work all around her, grateful to be bestowed with the gift of leadership. She shares with colleagues a few especially meaningful moments from her professional…
Neurodevelopmental disorders: cluster 2 of the proposed meta-structure for DSM-V and ICD-11.
Andrews, G; Pine, D S; Hobbs, M J; Anderson, T M; Sunderland, M
2009-12-01
DSM-IV and ICD-10 are atheoretical and largely descriptive. Although this achieves good reliability, the validity of diagnoses can be increased by an understanding of risk factors and other clinical features. In an effort to group mental disorders on this basis, five clusters have been proposed. We now consider the second cluster, namely neurodevelopmental disorders. We reviewed the literature in relation to 11 validating criteria proposed by a DSM-V Task Force Study Group. This cluster reflects disorders of neurodevelopment rather than a 'childhood' disorders cluster. It comprises disorders subcategorized in DSM-IV and ICD-10 as Mental Retardation; Learning, Motor, and Communication Disorders; and Pervasive Developmental Disorders. Although these disorders seem to be heterogeneous, they share similarities on some risk and clinical factors. There is evidence of a neurodevelopmental genetic phenotype, the disorders have an early emerging and continuing course, and all have salient cognitive symptoms. Within-cluster co-morbidity also supports grouping these disorders together. Other childhood disorders currently listed in DSM-IV share similarities with the Externalizing and Emotional clusters. These include Conduct Disorder, Attention Deficit Hyperactivity Disorder and Separation Anxiety Disorder. The Tic, Eating/Feeding and Elimination disorders, and Selective Mutisms were allocated to the 'Not Yet Assigned' group. Neurodevelopmental disorders meet some of the salient criteria proposed by the American Psychiatric Association (APA) to suggest a classification cluster.
NASA Astrophysics Data System (ADS)
Kleemann, W.; Shvartsman, V. V.; Borisov, P.; Kania, A.
2010-12-01
The coexistence of cluster glass with long-range antiferromagnetic order in the relaxor ferroelectric PbFe0.5Nb0.5O3 is elucidated. While the transition at TN=153K on the infinite antiferromagnetic cluster induces 3m symmetry with large EH2 magnetoelectric response, the disconnected subspace of isolated Fe3+ ions and finite clusters accommodates the cluster glass below Tg=10.6K with field-induced m' symmetry and EH-type magnetoelectric response. Critical slowing-down, memory and rejuvenation after aging, occurrence of a de Almeida-Thouless phase line, and stretched exponential relaxation of remanence corroborate the glass nature.
2-Way k-Means as a Model for Microbiome Samples.
Jackson, Weston J; Agarwal, Ipsita; Pe'er, Itsik
2017-01-01
Motivation . Microbiome sequencing allows defining clusters of samples with shared composition. However, this paradigm poorly accounts for samples whose composition is a mixture of cluster-characterizing ones and which therefore lie in between them in the cluster space. This paper addresses unsupervised learning of 2-way clusters. It defines a mixture model that allows 2-way cluster assignment and describes a variant of generalized k -means for learning such a model. We demonstrate applicability to microbial 16S rDNA sequencing data from the Human Vaginal Microbiome Project.
2-Way k-Means as a Model for Microbiome Samples
2017-01-01
Motivation. Microbiome sequencing allows defining clusters of samples with shared composition. However, this paradigm poorly accounts for samples whose composition is a mixture of cluster-characterizing ones and which therefore lie in between them in the cluster space. This paper addresses unsupervised learning of 2-way clusters. It defines a mixture model that allows 2-way cluster assignment and describes a variant of generalized k-means for learning such a model. We demonstrate applicability to microbial 16S rDNA sequencing data from the Human Vaginal Microbiome Project. PMID:29177026
NASA Astrophysics Data System (ADS)
Kuroda, Koji; Maskawa, Jun-ichi; Murai, Joshin
2013-08-01
Empirical studies of the high frequency data in stock markets show that the time series of trade signs or signed volumes has a long memory property. In this paper, we present a discrete time stochastic process for polymer model which describes trader's trading strategy, and show that a scale limit of the process converges to superposition of fractional Brownian motions with Hurst exponents and Brownian motion, provided that the index γ of the time scale about the trader's investment strategy coincides with the index δ of the interaction range in the discrete time process. The main tool for the investigation is the method of cluster expansion developed in the mathematical study of statistical mechanics.
SLIC superpixels compared to state-of-the-art superpixel methods.
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.
fMRI brain activation in patients with insomnia disorder during a working memory task.
Son, Young-Don; Kang, Jae Myeong; Cho, Seong-Jin; Lee, Jung-Sun; Hwang, Hee Young; Kang, Seung-Gul
2018-05-01
This study used functional magnetic resonance imaging (fMRI) to investigate differences in the functional brain activation of patients with insomnia disorder (n = 21, mean age = 36.6) and of good sleepers (n = 26, mean age = 33.2) without other comorbidities or structural brain abnormalities during a working memory task. All participants completed a clinical questionnaire, were subjected to portable polysomnography (PSG), and performed the working memory task during an fMRI scan. The subjects who were suspected of major sleep disorder and comorbid psychiatric disorders except insomnia disorder were excluded. To compare the brain activation on working memory from the insomnia group with those from the good-sleeper group, a two-sample t test was performed. Statistical significance was determined using 3DClustSim with the updated algorithm to obtain a reasonable cluster size and p value for each analysis. We observed higher levels of brain activation in the right lateral inferior frontal cortex and the right superior temporal pole in the insomnia group compared to good sleepers (cluster-based multiple comparison correction, p < 0.001, k = 34 @ α = 0.01). Thus, patients with insomnia disorder showed increased brain activation during working memory relative to good sleepers, and this may be indicative of compensatory brain activation to maintain cognitive performance in patients with insomnia disorder without other comorbidities.
High performance data transfer
NASA Astrophysics Data System (ADS)
Cottrell, R.; Fang, C.; Hanushevsky, A.; Kreuger, W.; Yang, W.
2017-10-01
The exponentially increasing need for high speed data transfer is driven by big data, and cloud computing together with the needs of data intensive science, High Performance Computing (HPC), defense, the oil and gas industry etc. We report on the Zettar ZX software. This has been developed since 2013 to meet these growing needs by providing high performance data transfer and encryption in a scalable, balanced, easy to deploy and use way while minimizing power and space utilization. In collaboration with several commercial vendors, Proofs of Concept (PoC) consisting of clusters have been put together using off-the- shelf components to test the ZX scalability and ability to balance services using multiple cores, and links. The PoCs are based on SSD flash storage that is managed by a parallel file system. Each cluster occupies 4 rack units. Using the PoCs, between clusters we have achieved almost 200Gbps memory to memory over two 100Gbps links, and 70Gbps parallel file to parallel file with encryption over a 5000 mile 100Gbps link.
Memory color assisted illuminant estimation through pixel clustering
NASA Astrophysics Data System (ADS)
Zhang, Heng; Quan, Shuxue
2010-01-01
The under constrained nature of illuminant estimation determines that in order to resolve the problem, certain assumptions are needed, such as the gray world theory. Including more constraints in this process may help explore the useful information in an image and improve the accuracy of the estimated illuminant, providing that the constraints hold. Based on the observation that most personal images have contents of one or more of the following categories: neutral objects, human beings, sky, and plants, we propose a method for illuminant estimation through the clustering of pixels of gray and three dominant memory colors: skin tone, sky blue, and foliage green. Analysis shows that samples of the above colors cluster around small areas under different illuminants and their characteristics can be used to effectively detect pixels falling into each of the categories. The algorithm requires the knowledge of the spectral sensitivity response of the camera, and a spectral database consisted of the CIE standard illuminants and reflectance or radiance database of samples of the above colors.
NASA Astrophysics Data System (ADS)
Chen, Naijin
2013-03-01
Level Based Partitioning (LBP) algorithm, Cluster Based Partitioning (CBP) algorithm and Enhance Static List (ESL) temporal partitioning algorithm based on adjacent matrix and adjacent table are designed and implemented in this paper. Also partitioning time and memory occupation based on three algorithms are compared. Experiment results show LBP partitioning algorithm possesses the least partitioning time and better parallel character, as far as memory occupation and partitioning time are concerned, algorithms based on adjacent table have less partitioning time and less space memory occupation.
Google Classroom and Open Clusters: An Authentic Science Research Project for High School Students
NASA Astrophysics Data System (ADS)
Johnson, Chelen H.; Linahan, Marcella; Cuba, Allison Frances; Dickmann, Samantha Rose; Hogan, Eleanor B.; Karos, Demetra N.; Kozikowski, Kendall G.; Kozikowski, Lauren Paige; Nelson, Samantha Brooks; O'Hara, Kevin Thomas; Ropinski, Brandi Lucia; Scarpa, Gabriella; Garmany, Catharine D.
2016-01-01
STEM education is about offering unique opportunities to our students. For the past three years, students from two high schools (Breck School in Minneapolis, MN, and Carmel Catholic High School in Mundelein, IL) have collaborated on authentic astronomy research projects. This past year they surveyed archival data of open clusters to determine if a clear turnoff point could be unequivocally determined. Age and distance to each open cluster were calculated. Additionally, students requested time on several telescopes to obtain original data to compare to the archival data. Students from each school worked in collaborative teams, sharing and verifying results through regular online hangouts and chats. Work papers were stored in a shared drive and on a student-designed Google site to facilitate dissemination of documents between the two schools.
Ageing-related stereotypes in memory: When the beliefs come true.
Bouazzaoui, Badiâa; Follenfant, Alice; Ric, François; Fay, Séverine; Croizet, Jean-Claude; Atzeni, Thierry; Taconnat, Laurence
2016-01-01
Age-related stereotype concerns culturally shared beliefs about the inevitable decline of memory with age. In this study, stereotype priming and stereotype threat manipulations were used to explore the impact of age-related stereotype on metamemory beliefs and episodic memory performance. Ninety-two older participants who reported the same perceived memory functioning were divided into two groups: a threatened group and a non-threatened group (control). First, the threatened group was primed with an ageing stereotype questionnaire. Then, both groups were administered memory complaints and memory self-efficacy questionnaires to measure metamemory beliefs. Finally, both groups were administered the Logical Memory task to measure episodic memory, for the threatened group the instructions were manipulated to enhance the stereotype threat. Results indicated that the threatened individuals reported more memory complaints and less memory efficacy, and had lower scores than the control group on the logical memory task. A multiple mediation analysis revealed that the stereotype threat effect on the episodic memory performance was mediated by both memory complaints and memory self-efficacy. This study revealed that stereotype threat impacts belief in one's own memory functioning, which in turn impairs episodic memory performance.
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.
MPF: A portable message passing facility for shared memory multiprocessors
NASA Technical Reports Server (NTRS)
Malony, Allen D.; Reed, Daniel A.; Mcguire, Patrick J.
1987-01-01
The design, implementation, and performance evaluation of a message passing facility (MPF) for shared memory multiprocessors are presented. The MPF is based on a message passing model conceptually similar to conversations. Participants (parallel processors) can enter or leave a conversation at any time. The message passing primitives for this model are implemented as a portable library of C function calls. The MPF is currently operational on a Sequent Balance 21000, and several parallel applications were developed and tested. Several simple benchmark programs are presented to establish interprocess communication performance for common patterns of interprocess communication. Finally, performance figures are presented for two parallel applications, linear systems solution, and iterative solution of partial differential equations.
Vadnais, Sarah A; Kibby, Michelle Y; Jagger-Rickels, Audreyana C
2018-01-01
We identified statistical predictors of four processing speed (PS) components in a sample of 151 children with and without attention-deficit/hyperactivity disorder (ADHD). Performance on perceptual speed was predicted by visual attention/short-term memory, whereas incidental learning/psychomotor speed was predicted by verbal working memory. Rapid naming was predictive of each PS component assessed, and inhibition predicted all but one task, suggesting a shared need to identify/retrieve stimuli rapidly and inhibit incorrect responding across PS components. Hence, we found both shared and unique predictors of perceptual, cognitive, and output speed, suggesting more specific terminology should be used in future research on PS in ADHD.
A multiarchitecture parallel-processing development environment
NASA Technical Reports Server (NTRS)
Townsend, Scott; Blech, Richard; Cole, Gary
1993-01-01
A description is given of the hardware and software of a multiprocessor test bed - the second generation Hypercluster system. The Hypercluster architecture consists of a standard hypercube distributed-memory topology, with multiprocessor shared-memory nodes. By using standard, off-the-shelf hardware, the system can be upgraded to use rapidly improving computer technology. The Hypercluster's multiarchitecture nature makes it suitable for researching parallel algorithms in computational field simulation applications (e.g., computational fluid dynamics). The dedicated test-bed environment of the Hypercluster and its custom-built software allows experiments with various parallel-processing concepts such as message passing algorithms, debugging tools, and computational 'steering'. Such research would be difficult, if not impossible, to achieve on shared, commercial systems.
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.
Error recovery in shared memory multiprocessors using private caches
NASA Technical Reports Server (NTRS)
Wu, Kun-Lung; Fuchs, W. Kent; Patel, Janak H.
1990-01-01
The problem of recovering from processor transient faults in shared memory multiprocesses systems is examined. A user-transparent checkpointing and recovery scheme using private caches is presented. Processes can recover from errors due to faulty processors by restarting from the checkpointed computation state. Implementation techniques using checkpoint identifiers and recovery stacks are examined as a means of reducing performance degradation in processor utilization during normal execution. This cache-based checkpointing technique prevents rollback propagation, provides rapid recovery, and can be integrated into standard cache coherence protocols. An analytical model is used to estimate the relative performance of the scheme during normal execution. Extensions to take error latency into account are presented.
Reducing Interprocessor Dependence in Recoverable Distributed Shared Memory
NASA Technical Reports Server (NTRS)
Janssens, Bob; Fuchs, W. Kent
1994-01-01
Checkpointing techniques in parallel systems use dependency tracking and/or message logging to ensure that a system rolls back to a consistent state. Traditional dependency tracking in distributed shared memory (DSM) systems is expensive because of high communication frequency. In this paper we show that, if designed correctly, a DSM system only needs to consider dependencies due to the transfer of blocks of data, resulting in reduced dependency tracking overhead and reduced potential for rollback propagation. We develop an ownership timestamp scheme to tolerate the loss of block state information and develop a passive server model of execution where interactions between processors are considered atomic. With our scheme, dependencies are significantly reduced compared to the traditional message-passing model.
Adamczak, Rafal; Meller, Jarek
2016-12-28
Advances in computing have enabled current protein and RNA structure prediction and molecular simulation methods to dramatically increase their sampling of conformational spaces. The quickly growing number of experimentally resolved structures, and databases such as the Protein Data Bank, also implies large scale structural similarity analyses to retrieve and classify macromolecular data. Consequently, the computational cost of structure comparison and clustering for large sets of macromolecular structures has become a bottleneck that necessitates further algorithmic improvements and development of efficient software solutions. uQlust is a versatile and easy-to-use tool for ultrafast ranking and clustering of macromolecular structures. uQlust makes use of structural profiles of proteins and nucleic acids, while combining a linear-time algorithm for implicit comparison of all pairs of models with profile hashing to enable efficient clustering of large data sets with a low memory footprint. In addition to ranking and clustering of large sets of models of the same protein or RNA molecule, uQlust can also be used in conjunction with fragment-based profiles in order to cluster structures of arbitrary length. For example, hierarchical clustering of the entire PDB using profile hashing can be performed on a typical laptop, thus opening an avenue for structural explorations previously limited to dedicated resources. The uQlust package is freely available under the GNU General Public License at https://github.com/uQlust . uQlust represents a drastic reduction in the computational complexity and memory requirements with respect to existing clustering and model quality assessment methods for macromolecular structure analysis, while yielding results on par with traditional approaches for both proteins and RNAs.
Towards memory-aware services and browsing through lifelogging sensing.
Arcega, Lorena; Font, Jaime; Cetina, Carlos
2013-11-05
Every day we receive lots of information through our senses that is lost forever, because it lacked the strength or the repetition needed to generate a lasting memory. Combining the emerging Internet of Things and lifelogging sensors, we believe it is possible to build up a Digital Memory (Dig-Mem) in order to complement the fallible memory of people. This work shows how to realize the Dig-Mem in terms of interactions, affinities, activities, goals and protocols. We also complement this Dig-Mem with memory-aware services and a Dig-Mem browser. Furthermore, we propose a RFID Tag-Sharing technique to speed up the adoption of Dig-Mem. Experimentation reveals an improvement of the user understanding of Dig-Mem as time passes, compared to natural memories where the level of detail decreases over time.
Language networks associated with computerized semantic indices.
Pakhomov, Serguei V S; Jones, David T; Knopman, David S
2015-01-01
Tests of generative semantic verbal fluency are widely used to study organization and representation of concepts in the human brain. Previous studies demonstrated that clustering and switching behavior during verbal fluency tasks is supported by multiple brain mechanisms associated with semantic memory and executive control. Previous work relied on manual assessments of semantic relatedness between words and grouping of words into semantic clusters. We investigated a computational linguistic approach to measuring the strength of semantic relatedness between words based on latent semantic analysis of word co-occurrences in a subset of a large online encyclopedia. We computed semantic clustering indices and compared them to brain network connectivity measures obtained with task-free fMRI in a sample consisting of healthy participants and those differentially affected by cognitive impairment. We found that semantic clustering indices were associated with brain network connectivity in distinct areas including fronto-temporal, fronto-parietal and fusiform gyrus regions. This study shows that computerized semantic indices complement traditional assessments of verbal fluency to provide a more complete account of the relationship between brain and verbal behavior involved organization and retrieval of lexical information from memory. Copyright © 2014 Elsevier Inc. All rights reserved.
Jajou, Rana; de Neeling, Albert; van Hunen, Rianne; de Vries, Gerard; Schimmel, Henrieke; Mulder, Arnout; Anthony, Richard; van der Hoek, Wim; van Soolingen, Dick
2018-01-01
Patients with Mycobacterium tuberculosis isolates sharing identical DNA fingerprint patterns can be epidemiologically linked. However, municipal health services in the Netherlands are able to confirm an epidemiological link in only around 23% of the patients with isolates clustered by the conventional variable number of tandem repeat (VNTR) genotyping. This research aims to investigate whether whole genome sequencing (WGS) is a more reliable predictor of epidemiological links between tuberculosis patients than VNTR genotyping. VNTR genotyping and WGS were performed in parallel on all Mycobacterium tuberculosis complex isolates received at the Netherlands National Institute for Public Health and the Environment in 2016. Isolates were clustered by VNTR when they shared identical 24-loci VNTR patterns; isolates were assigned to a WGS cluster when the pair-wise genetic distance was ≤ 12 single nucleotide polymorphisms (SNPs). Cluster investigation was performed by municipal health services on all isolates clustered by VNTR in 2016. The proportion of epidemiological links identified among patients clustered by either method was calculated. In total, 535 isolates were genotyped, of which 25% (134/535) were clustered by VNTR and 14% (76/535) by WGS; the concordance between both typing methods was 86%. The proportion of epidemiological links among WGS clustered cases (57%) was twice as common than among VNTR clustered cases (31%). When WGS was applied, the number of clustered isolates was halved, while all epidemiologically linked cases remained clustered. WGS is therefore a more reliable tool to predict epidemiological links between tuberculosis cases than VNTR genotyping and will allow more efficient transmission tracing, as epidemiological investigations based on false clustering can be avoided.
ERIC Educational Resources Information Center
Hitchcock, Caitlin; Westwell, Martin S.
2017-01-01
Background: We explored whether school-based Cogmed Working Memory Training (CWMT) may optimise both academic and psychological outcomes at school. Training of executive control skills may form a novel approach to enhancing processes that predict academic achievement, such as task-related attention, and thereby academic performance, but also has…