Effects of deception in social networks.

PubMed

Iñiguez, Gerardo; Govezensky, Tzipe; Dunbar, Robin; Kaski, Kimmo; Barrio, Rafael A

2014-09-07

Honesty plays a crucial role in any situation where organisms exchange information or resources. Dishonesty can thus be expected to have damaging effects on social coherence if agents cannot trust the information or goods they receive. However, a distinction is often drawn between prosocial lies ('white' lies) and antisocial lying (i.e. deception for personal gain), with the former being considered much less destructive than the latter. We use an agent-based model to show that antisocial lying causes social networks to become increasingly fragmented. Antisocial dishonesty thus places strong constraints on the size and cohesion of social communities, providing a major hurdle that organisms have to overcome (e.g. by evolving counter-deception strategies) in order to evolve large, socially cohesive communities. In contrast, white lies can prove to be beneficial in smoothing the flow of interactions and facilitating a larger, more integrated network. Our results demonstrate that these group-level effects can arise as emergent properties of interactions at the dyadic level. The balance between prosocial and antisocial lies may set constraints on the structure of social networks, and hence the shape of society as a whole. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

[Intraosseous veins of the maxilla in the newborn].

PubMed

Bogdanov, R A

1975-12-01

The intraosseous veins of the maxilla in newborns grow larger with enlargement of the bone and become disposed in three mutually perpendicular planes. The venous plexus of the alveolar process is large. V. v. vallares are thin and interlace forming a network. The veins of interdental septum are well pronounced. The thick venous network of the periosteum and the mucous membrane of the nasal surface of the palatine process includes the vessels transversal and longitudinal to the nasal septum. The venous loops of the incisor part are of triangular, pentagonal and polygonal shape. The veins of the palatine process are connected with 3-4 large vessels falling into the vessels of the tear duct. The transversal and oblique veins of the oral surface of the palatine process are connected with large vessels disposed in parallel to the medial structure of the hard palate. The venous network of the incisor part of the bone is restricted by densified small arc-shaped plexuses. Two-three largest veins lie sagittally and, connected by arc-shaped anastomoses, are tributaries of the vessels of the palate bone, soft palate and pharynx.

Origin of an extensive network of non-tectonic synclines in Eocene limestones of the Western Desert, Egypt

NASA Astrophysics Data System (ADS)

Tewksbury, Barbara J.; Tarabees, Elhamy A.; Mehrtens, Charlotte J.

2017-12-01

Satellite images of the Western Desert of Egypt display conspicuous sinuous color patterning that previous workers have interpreted as erosional flutes formed by catastrophic flooding. Our work with high resolution satellite imagery shows that the patterning is not erosional but, rather, the result of a network of thousands of narrow synclines in the Eocene bedrock capping the Limestone Plateau. Synclines form as isolated, 200-400 meter-wide downwarps in otherwise flat-lying strata. Limb dips are shallow, and doubly plunging hinges form multiple basin closures along syncline lengths. Anticlines form ;accidentally; in inter-syncline areas where two adjacent synclines lie close together. Synclines have two dominant orientations, WNW-ESE and NNW-SSE, parallel to two prominent joint and fault sets, and synclines branch, merge, and change orientation along their lengths. Synclines are all at the same scale with neither larger structures nor parasitic structures and are best described as non-tectonic sag synclines. An Egypt-wide inventory reveals that these synclines are both confined to Eocene limestones and developed, albeit it sporadically, over nearly 100,000 km2. The syncline network predates plateau gravels of the Katkut Formation, which have been interpreted as Oligocene or early Miocene in age, and the network is cut by faults related to Western Desert extension associated with Red Sea rifting. The mechanism that caused sag of overlying layers is not clear. Modern karst collapse, subsurface dissolution of evaporites, and collapse of paleokarst are all unlikely mechanisms given the timing of formation and the underlying stratigraphy. Silica diagenesis and downslope mobilization of underlying shales are possibilities, although uncertainty about the origin of silica in the limestones, plus the consistency of syncline orientations over large areas, make these models problematic. Hypogene karst, perhaps related to aggressive fluids associated with basaltic intrusions, may be the model most consistent with the admittedly limited data we currently have for the network.

Functional neural networks of honesty and dishonesty in children: Evidence from graph theory analysis.

PubMed

Ding, Xiao Pan; Wu, Si Jia; Liu, Jiangang; Fu, Genyue; Lee, Kang

2017-09-21

The present study examined how different brain regions interact with each other during spontaneous honest vs. dishonest communication. More specifically, we took a complex network approach based on the graph-theory to analyze neural response data when children are spontaneously engaged in honest or dishonest acts. Fifty-nine right-handed children between 7 and 12 years of age participated in the study. They lied or told the truth out of their own volition. We found that lying decreased both the global and local efficiencies of children's functional neural network. This finding, for the first time, suggests that lying disrupts the efficiency of children's cortical network functioning. Further, it suggests that the graph theory based network analysis is a viable approach to study the neural development of deception.

Differential Geometry and Lie Groups for Physicists

NASA Astrophysics Data System (ADS)

Fecko, Marián.

2006-10-01

Introduction; 1. The concept of a manifold; 2. Vector and tensor fields; 3. Mappings of tensors induced by mappings of manifolds; 4. Lie derivative; 5. Exterior algebra; 6. Differential calculus of forms; 7. Integral calculus of forms; 8. Particular cases and applications of Stoke's Theorem; 9. Poincaré Lemma and cohomologies; 10. Lie Groups - basic facts; 11. Differential geometry of Lie Groups; 12. Representations of Lie Groups and Lie Algebras; 13. Actions of Lie Groups and Lie Algebras on manifolds; 14. Hamiltonian mechanics and symplectic manifolds; 15. Parallel transport and linear connection on M; 16. Field theory and the language of forms; 17. Differential geometry on TM and T*M; 18. Hamiltonian and Lagrangian equations; 19. Linear connection and the frame bundle; 20. Connection on a principal G-bundle; 21. Gauge theories and connections; 22. Spinor fields and Dirac operator; Appendices; Bibliography; Index.

Differential Geometry and Lie Groups for Physicists

NASA Astrophysics Data System (ADS)

Fecko, Marián.

2011-03-01

Introduction; 1. The concept of a manifold; 2. Vector and tensor fields; 3. Mappings of tensors induced by mappings of manifolds; 4. Lie derivative; 5. Exterior algebra; 6. Differential calculus of forms; 7. Integral calculus of forms; 8. Particular cases and applications of Stoke's Theorem; 9. Poincaré Lemma and cohomologies; 10. Lie Groups - basic facts; 11. Differential geometry of Lie Groups; 12. Representations of Lie Groups and Lie Algebras; 13. Actions of Lie Groups and Lie Algebras on manifolds; 14. Hamiltonian mechanics and symplectic manifolds; 15. Parallel transport and linear connection on M; 16. Field theory and the language of forms; 17. Differential geometry on TM and T*M; 18. Hamiltonian and Lagrangian equations; 19. Linear connection and the frame bundle; 20. Connection on a principal G-bundle; 21. Gauge theories and connections; 22. Spinor fields and Dirac operator; Appendices; Bibliography; Index.

Division Algebras, Supersymmetry and Higher Gauge Theory

NASA Astrophysics Data System (ADS)

Huerta, John Gmerek

2011-12-01

Starting from the four normed division algebras---the real numbers, complex numbers, quaternions and octonions, with dimensions k = 1, 2, 4 and 8, respectively---a systematic procedure gives a 3-cocycle on the Poincare Lie superalgebra in dimensions k + 2 = 3, 4, 6 and 10. A related procedure gives a 4-cocycle on the Poincare Lie superalgebra in dimensions k+3 = 4, 5, 7 and 11. The existence of these cocycles follow from certain spinor identities that hold only in these dimensions, and which are closely related to the existence of superstring and super-Yang--Mills theory in dimensions k + 2, and super-2-brane theory in dimensions k + 3. In general, an (n+1)-cocycle on a Lie superalgebra yields a 'Lie n-superalgebra': that is, roughly speaking, an n-term chain complex equipped with a bracket satisfying the axioms of a Lie superalgebra up to chain homotopy. We thus obtain Lie 2-superalgebras extending the Poincare superalgebra in dimensions 3, 4, 6, and 10, and Lie 3-superalgebras extending the Poincare superalgebra in dimensions 4, 5, 7 and 11. As shown in Sati, Schreiber and Stasheff's work on generalized connections valued in Lie n-superalgebras, Lie 2-superalgebra connections describe the parallel transport of strings, while Lie 3-superalgebra connections describe the parallel transport of 2-branes. Moreover, in the octonionic case, these connections concisely summarize the fields appearing in 10- and 11-dimensional supergravity. Generically, integrating a Lie n-superalgebra to a Lie n-supergroup yields a 'Lie n-supergroup' that is hugely infinite-dimensional. However, when the Lie n-superalgebra is obtained from an (n + 1)-cocycle on a nilpotent Lie superalgebra, there is a geometric procedure to integrate the cocycle to one on the corresponding nilpotent Lie supergroup. In general, a smooth (n+1)-cocycle on a supergroup yields a 'Lie n-supergroup': that is, a weak n-group internal to supermanifolds. Using our geometric procedure to integrate the 3-cocycle in dimensions 3, 4, 6 and 10, we obtain a Lie 2-supergroup extending the Poincare supergroup in those dimensions, and similarly integrating the 4-cocycle in dimensions 4, 5, 7 and 11, we obtain a Lie 3-supergroup extending the Poincare supergroup in those dimensions.

THERMOCOUPLE VACUUM GAUGE

DOEpatents

Price, G.W.

1954-08-01

A protector device is described for use in controlling the pressure within a cyclotron. In particular, an electrical circuit functions to actuate a vacuum pump when a predetermined low pressure is reached and disconnect the pump when the pressure increases abcve a certain value. The principal feature of the control circuit lies in the use of a voltage divider network at the input to a relay control tube comprising two parallel, adjustable resistances wherein one resistor is switched into the circuit when the relay connects the pump to a power source. With this arrangement the relay is energized at one input level received from a sensing element within the cyclotron chamber and is de-energized when a second input level, representing the higher pressure limit, is reached.

2-(4-Hy-droxy-phen-yl)-1H-benzimidazol-3-ium chloride monohydrate.

PubMed

González-Padilla, Jazmin E; Rosales-Hernández, Martha Cecila; Padilla-Martínez, Itzia I; García-Báez, Efren V; Rojas-Lima, Susana

2013-01-01

The title mol-ecular salt, C13H11N2O(+)·Cl(-)·H2O, crystallizes as a monohydrate. In the cation, the phenol and benzimidazole rings are almost coplanar, making a dihedral angle of 3.18 (4)°. The chloride anion and benzimidazole cation are linked by two N(+)-H⋯Cl(-) hydrogen bonds, forming chains propagating along [010]. These chains are linked through O-H⋯Cl hydrogen bonds involving the water mol-ecule and the chloride anion, which form a diamond core, giving rise to the formation of two-dimensional networks lying parallel to (10-2). Two π-π inter-actions involving the imidazolium ring with the benzene and phenol rings [centroid-centroid distances = 3.859 (3) and 3.602 (3) Å, respectively], contribute to this second dimension. A strong O-H⋯O hydrogen bond involving the water mol-ecule and the phenol substituent on the benzimidazole unit links the networks, forming a three-dimensional structure.

Parallel processing data network of master and slave transputers controlled by a serial control network

DOEpatents

Crosetto, D.B.

1996-12-31

The present device provides for a dynamically configurable communication network having a multi-processor parallel processing system having a serial communication network and a high speed parallel communication network. The serial communication network is used to disseminate commands from a master processor to a plurality of slave processors to effect communication protocol, to control transmission of high density data among nodes and to monitor each slave processor`s status. The high speed parallel processing network is used to effect the transmission of high density data among nodes in the parallel processing system. Each node comprises a transputer, a digital signal processor, a parallel transfer controller, and two three-port memory devices. A communication switch within each node connects it to a fast parallel hardware channel through which all high density data arrives or leaves the node. 6 figs.

Parallel processing data network of master and slave transputers controlled by a serial control network

DOEpatents

Crosetto, Dario B.

1996-01-01

The present device provides for a dynamically configurable communication network having a multi-processor parallel processing system having a serial communication network and a high speed parallel communication network. The serial communication network is used to disseminate commands from a master processor (100) to a plurality of slave processors (200) to effect communication protocol, to control transmission of high density data among nodes and to monitor each slave processor's status. The high speed parallel processing network is used to effect the transmission of high density data among nodes in the parallel processing system. Each node comprises a transputer (104), a digital signal processor (114), a parallel transfer controller (106), and two three-port memory devices. A communication switch (108) within each node (100) connects it to a fast parallel hardware channel (70) through which all high density data arrives or leaves the node.

A Selectivity based approach to Continuous Pattern Detection in Streaming Graphs

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

Choudhury, Sutanay; Holder, Larry; Chin, George

2015-05-27

Cyber security is one of the most significant technical challenges in current times. Detecting adversarial activities, prevention of theft of intellectual properties and customer data is a high priority for corporations and government agencies around the world. Cyber defenders need to analyze massive-scale, high-resolution network flows to identify, categorize, and mitigate attacks involving networks spanning institutional and national boundaries. Many of the cyber attacks can be described as subgraph patterns, with prominent examples being insider infiltrations (path queries), denial of service (parallel paths) and malicious spreads (tree queries). This motivates us to explore subgraph matching on streaming graphs in amore » continuous setting. The novelty of our work lies in using the subgraph distributional statistics collected from the streaming graph to determine the query processing strategy. We introduce a ``Lazy Search" algorithm where the search strategy is decided on a vertex-to-vertex basis depending on the likelihood of a match in the vertex neighborhood. We also propose a metric named ``Relative Selectivity" that is used to select between different query processing strategies. Our experiments performed on real online news, network traffic stream and a synthetic social network benchmark demonstrate 10-100x speedups over non-incremental, selectivity agnostic approaches.« less

Crystal structure of (±)-1-({[4-(all­yloxy)phen­yl]sulfan­yl}meth­yl)-2-(di­phenyl­thio­phosphor­yl)ferrocene

PubMed Central

Michelot, Audric; Sarda, Stéphanie; Daran, Jean-Claude; Deydier, Eric; Manoury, Eric

2015-01-01

The title compound, [Fe(C5H5)(C27H24OPS2)], is built up from a ferrocene moiety substituted in the 1- and 2-positions by {[4-(all­yloxy)phen­yl]sulfan­yl}methyl and di­phenyl­thio­phosphoryl groups, respectively. The two S atoms lie on opposite sides of the cyclo­penta­dienyl ring plane to which they are attached. In the crystal, C—H⋯S hydrogen bonds link the mol­ecules into a ribbon running parallel to the (-110) plane. C—H⋯π inter­actions link the ribbons to form a three-dimensional network. PMID:26396768

1-(2,4-Di-nitro-phen-yl)-2-[(E)-(3,4,5-tri-meth-oxy-benzyl-idene)]hydrazine.

PubMed

Chantrapromma, Suchada; Ruanwas, Pumsak; Boonnak, Nawong; Chidan Kumar, C S; Fun, Hoong-Kun

2014-02-01

Mol-ecules of the title compound, C16H16N4O7, are not planar with a dihedral angle of 5.50 (11)° between the substituted benzene rings. The two meta-meth-oxy groups of the 3,4,5-tri-meth-oxy-benzene moiety lie in the plane of the attached ring [Cmeth-yl-O-C-C torsion angles -0.1 (4)° and -3.7 (3)°] while the para-meth-oxy substituent lies out of the plane [Cmeth-yl-O-C-C, -86.0 (3)°]. An intra-molecular N-H⋯O hydrogen bond involving the 2-nitro substituent generates an S(6) ring motif. In the crystal structure, mol-ecules are linked by weak C-H⋯O inter-actions into screw chains, that are arranged into a sheet parallel to the bc plane. These sheets are connected by π-π stacking inter-actions between the nitro and meth-oxy substituted aromatic rings with a centroid-centroid separation of 3.9420 (13) Å. C-H⋯π contacts further stabilize the two-dimensional network.

Parallel Algorithms for Switching Edges in Heterogeneous Graphs.

PubMed

Bhuiyan, Hasanuzzaman; Khan, Maleq; Chen, Jiangzhuo; Marathe, Madhav

2017-06-01

An edge switch is an operation on a graph (or network) where two edges are selected randomly and one of their end vertices are swapped with each other. Edge switch operations have important applications in graph theory and network analysis, such as in generating random networks with a given degree sequence, modeling and analyzing dynamic networks, and in studying various dynamic phenomena over a network. The recent growth of real-world networks motivates the need for efficient parallel algorithms. The dependencies among successive edge switch operations and the requirement to keep the graph simple (i.e., no self-loops or parallel edges) as the edges are switched lead to significant challenges in designing a parallel algorithm. Addressing these challenges requires complex synchronization and communication among the processors leading to difficulties in achieving a good speedup by parallelization. In this paper, we present distributed memory parallel algorithms for switching edges in massive networks. These algorithms provide good speedup and scale well to a large number of processors. A harmonic mean speedup of 73.25 is achieved on eight different networks with 1024 processors. One of the steps in our edge switch algorithms requires the computation of multinomial random variables in parallel. This paper presents the first non-trivial parallel algorithm for the problem, achieving a speedup of 925 using 1024 processors.

Parallel Algorithms for Switching Edges in Heterogeneous Graphs☆

PubMed Central

Khan, Maleq; Chen, Jiangzhuo; Marathe, Madhav

2017-01-01

An edge switch is an operation on a graph (or network) where two edges are selected randomly and one of their end vertices are swapped with each other. Edge switch operations have important applications in graph theory and network analysis, such as in generating random networks with a given degree sequence, modeling and analyzing dynamic networks, and in studying various dynamic phenomena over a network. The recent growth of real-world networks motivates the need for efficient parallel algorithms. The dependencies among successive edge switch operations and the requirement to keep the graph simple (i.e., no self-loops or parallel edges) as the edges are switched lead to significant challenges in designing a parallel algorithm. Addressing these challenges requires complex synchronization and communication among the processors leading to difficulties in achieving a good speedup by parallelization. In this paper, we present distributed memory parallel algorithms for switching edges in massive networks. These algorithms provide good speedup and scale well to a large number of processors. A harmonic mean speedup of 73.25 is achieved on eight different networks with 1024 processors. One of the steps in our edge switch algorithms requires the computation of multinomial random variables in parallel. This paper presents the first non-trivial parallel algorithm for the problem, achieving a speedup of 925 using 1024 processors. PMID:28757680

Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment.

PubMed

Lee, Wei-Po; Hsiao, Yu-Ting; Hwang, Wei-Che

2014-01-16

To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high quality solutions can be obtained within relatively short time. This integrated approach is a promising way for inferring large networks.

Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment

PubMed Central

2014-01-01

Background To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. Results This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Conclusions Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high quality solutions can be obtained within relatively short time. This integrated approach is a promising way for inferring large networks. PMID:24428926

Dynamics of deceptive interactions in social networks.

PubMed

Barrio, Rafael A; Govezensky, Tzipe; Dunbar, Robin; Iñiguez, Gerardo; Kaski, Kimmo

2015-11-06

In this paper, we examine the role of lies in human social relations by implementing some salient characteristics of deceptive interactions into an opinion formation model, so as to describe the dynamical behaviour of a social network more realistically. In this model, we take into account such basic properties of social networks as the dynamics of the intensity of interactions, the influence of public opinion and the fact that in every human interaction it might be convenient to deceive or withhold information depending on the instantaneous situation of each individual in the network. We find that lies shape the topology of social networks, especially the formation of tightly linked, small communities with loose connections between them. We also find that agents with a larger proportion of deceptive interactions are the ones that connect communities of different opinion, and, in this sense, they have substantial centrality in the network. We then discuss the consequences of these results for the social behaviour of humans and predict the changes that could arise due to a varying tolerance for lies in society. © 2015 The Author(s).

14. VIEW OF NORTHSOUTH ROAD WHICH PARALLELS ROAD TO HATCH ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

14. VIEW OF NORTH-SOUTH ROAD WHICH PARALLELS ROAD TO HATCH ADIT (FEATURE B-28). NOTE MODERN 'LAY DOWN' FENCE ON ROAD. ROAD LIES TO THE WEST OF THE HATCH ADIT AND PHOTOGRAPH IS VIEW TO THE SOUTH. (OCTOBER, 1995) - Nevada Lucky Tiger Mill & Mine, East slope of Buckskin Mountain, Paradise Valley, Humboldt County, NV

Competitive Parallel Processing For Compression Of Data

NASA Technical Reports Server (NTRS)

Diner, Daniel B.; Fender, Antony R. H.

1990-01-01

Momentarily-best compression algorithm selected. Proposed competitive-parallel-processing system compresses data for transmission in channel of limited band-width. Likely application for compression lies in high-resolution, stereoscopic color-television broadcasting. Data from information-rich source like color-television camera compressed by several processors, each operating with different algorithm. Referee processor selects momentarily-best compressed output.

2-(4-Hy­droxy­phen­yl)-1H-benzimidazol-3-ium chloride monohydrate

PubMed Central

González-Padilla, Jazmin E.; Rosales-Hernández, Martha Cecila; Padilla-Martínez, Itzia I.; García-Báez, Efren V.; Rojas-Lima, Susana

2013-01-01

The title mol­ecular salt, C13H11N2O+·Cl−·H2O, crystallizes as a monohydrate. In the cation, the phenol and benzimidazole rings are almost coplanar, making a dihedral angle of 3.18 (4)°. The chloride anion and benzimidazole cation are linked by two N+—H⋯Cl− hydrogen bonds, forming chains propagating along [010]. These chains are linked through O—H⋯Cl hydrogen bonds involving the water mol­ecule and the chloride anion, which form a diamond core, giving rise to the formation of two-dimensional networks lying parallel to (10-2). Two π–π inter­actions involving the imidazolium ring with the benzene and phenol rings [centroid–centroid distances = 3.859 (3) and 3.602 (3) Å, respectively], contribute to this second dimension. A strong O—H⋯O hydrogen bond involving the water mol­ecule and the phenol substituent on the benzimidazole unit links the networks, forming a three-dimensional structure. PMID:24427105

A Parallel Adaboost-Backpropagation Neural Network for Massive Image Dataset Classification

NASA Astrophysics Data System (ADS)

Cao, Jianfang; Chen, Lichao; Wang, Min; Shi, Hao; Tian, Yun

2016-12-01

Image classification uses computers to simulate human understanding and cognition of images by automatically categorizing images. This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model. First, we construct a strong classifier by assembling the outputs of 15 BP neural networks (which are individually regarded as weak classifiers) based on the Adaboost algorithm. Second, we design Map and Reduce tasks for both the parallel Adaboost-BP neural network and the feature extraction algorithm. Finally, we establish an automated classification model by building a Hadoop cluster. We use the Pascal VOC2007 and Caltech256 datasets to train and test the classification model. The results are superior to those obtained using traditional Adaboost-BP neural network or parallel BP neural network approaches. Our approach increased the average classification accuracy rate by approximately 14.5% and 26.0% compared to the traditional Adaboost-BP neural network and parallel BP neural network, respectively. Furthermore, the proposed approach requires less computation time and scales very well as evaluated by speedup, sizeup and scaleup. The proposed approach may provide a foundation for automated large-scale image classification and demonstrates practical value.

A Parallel Adaboost-Backpropagation Neural Network for Massive Image Dataset Classification.

PubMed

Cao, Jianfang; Chen, Lichao; Wang, Min; Shi, Hao; Tian, Yun

2016-12-01

Image classification uses computers to simulate human understanding and cognition of images by automatically categorizing images. This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model. First, we construct a strong classifier by assembling the outputs of 15 BP neural networks (which are individually regarded as weak classifiers) based on the Adaboost algorithm. Second, we design Map and Reduce tasks for both the parallel Adaboost-BP neural network and the feature extraction algorithm. Finally, we establish an automated classification model by building a Hadoop cluster. We use the Pascal VOC2007 and Caltech256 datasets to train and test the classification model. The results are superior to those obtained using traditional Adaboost-BP neural network or parallel BP neural network approaches. Our approach increased the average classification accuracy rate by approximately 14.5% and 26.0% compared to the traditional Adaboost-BP neural network and parallel BP neural network, respectively. Furthermore, the proposed approach requires less computation time and scales very well as evaluated by speedup, sizeup and scaleup. The proposed approach may provide a foundation for automated large-scale image classification and demonstrates practical value.

A Parallel Adaboost-Backpropagation Neural Network for Massive Image Dataset Classification

PubMed Central

Cao, Jianfang; Chen, Lichao; Wang, Min; Shi, Hao; Tian, Yun

2016-01-01

Image classification uses computers to simulate human understanding and cognition of images by automatically categorizing images. This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model. First, we construct a strong classifier by assembling the outputs of 15 BP neural networks (which are individually regarded as weak classifiers) based on the Adaboost algorithm. Second, we design Map and Reduce tasks for both the parallel Adaboost-BP neural network and the feature extraction algorithm. Finally, we establish an automated classification model by building a Hadoop cluster. We use the Pascal VOC2007 and Caltech256 datasets to train and test the classification model. The results are superior to those obtained using traditional Adaboost-BP neural network or parallel BP neural network approaches. Our approach increased the average classification accuracy rate by approximately 14.5% and 26.0% compared to the traditional Adaboost-BP neural network and parallel BP neural network, respectively. Furthermore, the proposed approach requires less computation time and scales very well as evaluated by speedup, sizeup and scaleup. The proposed approach may provide a foundation for automated large-scale image classification and demonstrates practical value. PMID:27905520

Thermodynamic and Kinematic Flow Characteristics of Some Developing and Non-Developing Disturbances in Predict

DTIC Science & Technology

2014-12-01

normal ( 1S ) and parallel ( 2S ) strain rates squared. U and V are the zonal and meridional velocities and the x and y subscripts indicate partial...between developing and non-developing tropical disturbances appears to lie with the kinematic flow boundary structure and thermodynamic properties ...tropical disturbances appears to lie with the kinematic flow boundary structure and thermodynamic properties hypothesized in the marsupial paradigm

Improving the iterative Linear Interaction Energy approach using automated recognition of configurational transitions.

PubMed

Vosmeer, C Ruben; Kooi, Derk P; Capoferri, Luigi; Terpstra, Margreet M; Vermeulen, Nico P E; Geerke, Daan P

2016-01-01

Recently an iterative method was proposed to enhance the accuracy and efficiency of ligand-protein binding affinity prediction through linear interaction energy (LIE) theory. For ligand binding to flexible Cytochrome P450s (CYPs), this method was shown to decrease the root-mean-square error and standard deviation of error prediction by combining interaction energies of simulations starting from different conformations. Thereby, different parts of protein-ligand conformational space are sampled in parallel simulations. The iterative LIE framework relies on the assumption that separate simulations explore different local parts of phase space, and do not show transitions to other parts of configurational space that are already covered in parallel simulations. In this work, a method is proposed to (automatically) detect such transitions during the simulations that are performed to construct LIE models and to predict binding affinities. Using noise-canceling techniques and splines to fit time series of the raw data for the interaction energies, transitions during simulation between different parts of phase space are identified. Boolean selection criteria are then applied to determine which parts of the interaction energy trajectories are to be used as input for the LIE calculations. Here we show that this filtering approach benefits the predictive quality of our previous CYP 2D6-aryloxypropanolamine LIE model. In addition, an analysis is performed of the gain in computational efficiency that can be obtained from monitoring simulations using the proposed filtering method and by prematurely terminating simulations accordingly.

Big Data: A Parallel Particle Swarm Optimization-Back-Propagation Neural Network Algorithm Based on MapReduce.

PubMed

Cao, Jianfang; Cui, Hongyan; Shi, Hao; Jiao, Lijuan

2016-01-01

A back-propagation (BP) neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural network algorithm, we proposed a parallel design and realization method for a particle swarm optimization (PSO)-optimized BP neural network based on MapReduce on the Hadoop platform using both the PSO algorithm and a parallel design. The PSO algorithm was used to optimize the BP neural network's initial weights and thresholds and improve the accuracy of the classification algorithm. The MapReduce parallel programming model was utilized to achieve parallel processing of the BP algorithm, thereby solving the problems of hardware and communication overhead when the BP neural network addresses big data. Datasets on 5 different scales were constructed using the scene image library from the SUN Database. The classification accuracy of the parallel PSO-BP neural network algorithm is approximately 92%, and the system efficiency is approximately 0.85, which presents obvious advantages when processing big data. The algorithm proposed in this study demonstrated both higher classification accuracy and improved time efficiency, which represents a significant improvement obtained from applying parallel processing to an intelligent algorithm on big data.

Displacement and deformation measurement for large structures by camera network

NASA Astrophysics Data System (ADS)

Shang, Yang; Yu, Qifeng; Yang, Zhen; Xu, Zhiqiang; Zhang, Xiaohu

2014-03-01

A displacement and deformation measurement method for large structures by a series-parallel connection camera network is presented. By taking the dynamic monitoring of a large-scale crane in lifting operation as an example, a series-parallel connection camera network is designed, and the displacement and deformation measurement method by using this series-parallel connection camera network is studied. The movement range of the crane body is small, and that of the crane arm is large. The displacement of the crane body, the displacement of the crane arm relative to the body and the deformation of the arm are measured. Compared with a pure series or parallel connection camera network, the designed series-parallel connection camera network can be used to measure not only the movement and displacement of a large structure but also the relative movement and deformation of some interesting parts of the large structure by a relatively simple optical measurement system.

Computer hardware fault administration

DOEpatents

Archer, Charles J.; Megerian, Mark G.; Ratterman, Joseph D.; Smith, Brian E.

2010-09-14

Computer hardware fault administration carried out in a parallel computer, where the parallel computer includes a plurality of compute nodes. The compute nodes are coupled for data communications by at least two independent data communications networks, where each data communications network includes data communications links connected to the compute nodes. Typical embodiments carry out hardware fault administration by identifying a location of a defective link in the first data communications network of the parallel computer and routing communications data around the defective link through the second data communications network of the parallel computer.

A Selectivity based approach to Continuous Pattern Detection in Streaming Graphs

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

Choudhury, Sutanay; Holder, Larry; Chin, George

2015-02-02

Cyber security is one of the most significant technical challenges in current times. Detecting adversarial activities, prevention of theft of intellectual properties and customer data is a high priority for corporations and government agencies around the world. Cyber defenders need to analyze massive-scale, high-resolution network flows to identify, categorize, and mitigate attacks involving net- works spanning institutional and national boundaries. Many of the cyber attacks can be described as subgraph patterns, with promi- nent examples being insider infiltrations (path queries), denial of service (parallel paths) and malicious spreads (tree queries). This motivates us to explore subgraph matching on streaming graphsmore » in a continuous setting. The novelty of our work lies in using the subgraph distributional statistics collected from the streaming graph to determine the query processing strategy. We introduce a “Lazy Search" algorithm where the search strategy is decided on a vertex-to-vertex basis depending on the likelihood of a match in the vertex neighborhood. We also propose a metric named “Relative Selectivity" that is used to se- lect between different query processing strategies. Our experiments performed on real online news, network traffic stream and a syn- thetic social network benchmark demonstrate 10-100x speedups over selectivity agnostic approaches.« less

1-(2,4-Di­nitro­phen­yl)-2-[(E)-(3,4,5-tri­meth­oxy­benzyl­idene)]hydrazine

PubMed Central

Chantrapromma, Suchada; Ruanwas, Pumsak; Boonnak, Nawong; Chidan Kumar, C. S.; Fun, Hoong-Kun

2014-01-01

Mol­ecules of the title compound, C16H16N4O7, are not planar with a dihedral angle of 5.50 (11)° between the substituted benzene rings. The two meta-meth­oxy groups of the 3,4,5-tri­meth­oxy­benzene moiety lie in the plane of the attached ring [Cmeth­yl–O–C–C torsion angles −0.1 (4)° and −3.7 (3)°] while the para-meth­oxy substituent lies out of the plane [Cmeth­yl—O—C—C, −86.0 (3)°]. An intra­molecular N—H⋯O hydrogen bond involving the 2-nitro substituent generates an S(6) ring motif. In the crystal structure, mol­ecules are linked by weak C—H⋯O inter­actions into screw chains, that are arranged into a sheet parallel to the bc plane. These sheets are connected by π–π stacking inter­actions between the nitro and meth­oxy substituted aromatic rings with a centroid–centroid separation of 3.9420 (13) Å. C—H⋯π contacts further stabilize the two-dimensional network. PMID:24764900

Analysis of diverse regulatory networks in a hierarchical context shows consistent tendencies for collaboration in the middle levels

PubMed Central

Bhardwaj, Nitin; Yan, Koon-Kiu; Gerstein, Mark B.

2010-01-01

Gene regulatory networks have been shown to share some common aspects with commonplace social governance structures. Thus, we can get some intuition into their organization by arranging them into well-known hierarchical layouts. These hierarchies, in turn, can be placed between the extremes of autocracies, with well-defined levels and clear chains of command, and democracies, without such defined levels and with more co-regulatory partnerships between regulators. In general, the presence of partnerships decreases the variation in information flow amongst nodes within a level, more evenly distributing stress. Here we study various regulatory networks (transcriptional, modification, and phosphorylation) for five diverse species, Escherichia coli to human. We specify three levels of regulators—top, middle, and bottom—which collectively govern the non-regulator targets lying in the lowest fourth level. We define quantities for nodes, levels, and entire networks that measure their degree of collaboration and autocratic vs. democratic character. We show individual regulators have a range of partnership tendencies: Some regulate their targets in combination with other regulators in local instantiations of democratic structure, whereas others regulate mostly in isolation, in more autocratic fashion. Overall, we show that in all networks studied the middle level has the highest collaborative propensity and coregulatory partnerships occur most frequently amongst midlevel regulators, an observation that has parallels in corporate settings where middle managers must interact most to ensure organizational effectiveness. There is, however, one notable difference between networks in different species: The amount of collaborative regulation and democratic character increases markedly with overall genomic complexity. PMID:20351254

Distributed parallel messaging for multiprocessor systems

DOEpatents

Chen, Dong; Heidelberger, Philip; Salapura, Valentina; Senger, Robert M; Steinmacher-Burrow, Burhard; Sugawara, Yutaka

2013-06-04

A method and apparatus for distributed parallel messaging in a parallel computing system. The apparatus includes, at each node of a multiprocessor network, multiple injection messaging engine units and reception messaging engine units, each implementing a DMA engine and each supporting both multiple packet injection into and multiple reception from a network, in parallel. The reception side of the messaging unit (MU) includes a switch interface enabling writing of data of a packet received from the network to the memory system. The transmission side of the messaging unit, includes switch interface for reading from the memory system when injecting packets into the network.

A new approach for categorizing pig lying behaviour based on a Delaunay triangulation method.

PubMed

Nasirahmadi, A; Hensel, O; Edwards, S A; Sturm, B

2017-01-01

Machine vision-based monitoring of pig lying behaviour is a fast and non-intrusive approach that could be used to improve animal health and welfare. Four pens with 22 pigs in each were selected at a commercial pig farm and monitored for 15 days using top view cameras. Three thermal categories were selected relative to room setpoint temperature. An image processing technique based on Delaunay triangulation (DT) was utilized. Different lying patterns (close, normal and far) were defined regarding the perimeter of each DT triangle and the percentages of each lying pattern were obtained in each thermal category. A method using a multilayer perceptron (MLP) neural network, to automatically classify group lying behaviour of pigs into three thermal categories, was developed and tested for its feasibility. The DT features (mean value of perimeters, maximum and minimum length of sides of triangles) were calculated as inputs for the MLP classifier. The network was trained, validated and tested and the results revealed that MLP could classify lying features into the three thermal categories with high overall accuracy (95.6%). The technique indicates that a combination of image processing, MLP classification and mathematical modelling can be used as a precise method for quantifying pig lying behaviour in welfare investigations.

Are individuals with higher psychopathic traits better learners at lying? Behavioural and neural evidence.

PubMed

Shao, R; Lee, T M C

2017-07-25

High psychopathy is characterized by untruthfulness and manipulativeness. However, existing evidence on higher propensity or capacity to lie among non-incarcerated high-psychopathic individuals is equivocal. Of particular importance, no research has investigated whether greater psychopathic tendency is associated with better 'trainability' of lying. An understanding of whether the neurobehavioral processes of lying are modifiable through practice offers significant theoretical and practical implications. By employing a longitudinal design involving university students with varying degrees of psychopathic traits, we successfully demonstrate that the performance speed of lying about face familiarity significantly improved following two sessions of practice, which occurred only among those with higher, but not lower, levels of psychopathic traits. Furthermore, this behavioural improvement associated with higher psychopathic tendency was predicted by a reduction in lying-related neural signals and by functional connectivity changes in the frontoparietal and cerebellum networks. Our findings provide novel and pivotal evidence suggesting that psychopathic traits are the key modulating factors of the plasticity of both behavioural and neural processes underpinning lying. These findings broadly support conceptualization of high-functioning individuals with higher psychopathic traits as having preserved, or arguably superior, functioning in neural networks implicated in cognitive executive processing, but deficiencies in affective neural processes, from a neuroplasticity perspective.

The performance of the ZEUS central tracking detector z-by-timing electronics in a transputer based data acquisition system

NASA Astrophysics Data System (ADS)

Foster, B.; Heath, G. P.; Llewellyn, T. J.; Gingrich, D. M.; Harnew, N.; Hallam-Baker, P. M.; Khatri, T.; McArthur, I. C.; Morawitz, P.; Nash, J.; Shield, P. D.; Topp-Jorgensen, S.; Wilson, F. F.; Allen, D. B.; Carter, R. C.; Jeffs, M. D.; Morrissey, M. C.; Quinton, S. P. H.; Lane, J. B.; Postranecky, M.

1993-05-01

The Central Tracking Detector of the ZEUS experiment employs a time difference technique to measure the z coordinate of each hit. The method provides fast, three-dimensional space point measurements which are used as input to all levels of the ZEUS trigger. Such a tracking trigger is essential in order to discriminate against events with vertices lying outside the nominal electron-proton interaction region. Since the beam crossing interval of the HERA collider is 96 ns, all data must be pipelined through the front-end readout electronics. Subsequent data aquisition employs a novel technique which utilizes a network of approximately 120 INMOS transputers to process the data in parallel. The z-by-timing method and its data aquisition have been employed successfully in recording and reconstructing tracks from electron-proton interactions in ZEUS.

ORIENTATION AND LOCUS OF TROPIC PHOTORECEPTOR MOLECULES IN SPORES OF BOTRYTIS AND OSMUNDA

PubMed Central

Jaffe, Lionel; Etzold, Helmut

1962-01-01

Study of the tropic responses of Botrytis cinerea and Osmunda cinnamomea spores to blue light shows the photoreceptor molecules to be highly dichroic and oriented: in Botrytis their axes of maximum absorption lie perpendicular to the nearby cell surface; in Osmunda, parallel. The chief evidence lies in a comparison of their responses to plane polarized light—both germinate parallel to the vibration planes (defined by the axis of vibration of the electric vector and the axis of light propagation)—with those to partial illumination with unpolarized light: Botrytis grows from its brighter part; Osmunda, from its darker. The degree of orientation produced by polarized light corresponds, at high intensities, to that produced by the imposition of such large (about 100 per cent) intensity differences across a cell as to preclude all alternatives to oriented dichroic receptors. The photoreceptors of the Botrytis spore lie within the cell wall's inner half. The chief evidence lies in the component of its tropic responses to polarized light within the vibration plane: germination peaks about 10° off the vibration axis. This deviation arises from focusing which is effective only in the wall's inner half. At high intensities, anomalies appear in Botrytis which are interpreted as "centering," i.e., a tendency toward growth from the center of two or more equally illuminated points of a cell rather than from one of them. PMID:14450869

Big Data: A Parallel Particle Swarm Optimization-Back-Propagation Neural Network Algorithm Based on MapReduce

PubMed Central

Cao, Jianfang; Cui, Hongyan; Shi, Hao; Jiao, Lijuan

2016-01-01

A back-propagation (BP) neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural network algorithm, we proposed a parallel design and realization method for a particle swarm optimization (PSO)-optimized BP neural network based on MapReduce on the Hadoop platform using both the PSO algorithm and a parallel design. The PSO algorithm was used to optimize the BP neural network’s initial weights and thresholds and improve the accuracy of the classification algorithm. The MapReduce parallel programming model was utilized to achieve parallel processing of the BP algorithm, thereby solving the problems of hardware and communication overhead when the BP neural network addresses big data. Datasets on 5 different scales were constructed using the scene image library from the SUN Database. The classification accuracy of the parallel PSO-BP neural network algorithm is approximately 92%, and the system efficiency is approximately 0.85, which presents obvious advantages when processing big data. The algorithm proposed in this study demonstrated both higher classification accuracy and improved time efficiency, which represents a significant improvement obtained from applying parallel processing to an intelligent algorithm on big data. PMID:27304987

Performance Evaluation in Network-Based Parallel Computing

NASA Technical Reports Server (NTRS)

Dezhgosha, Kamyar

1996-01-01

Network-based parallel computing is emerging as a cost-effective alternative for solving many problems which require use of supercomputers or massively parallel computers. The primary objective of this project has been to conduct experimental research on performance evaluation for clustered parallel computing. First, a testbed was established by augmenting our existing SUNSPARCs' network with PVM (Parallel Virtual Machine) which is a software system for linking clusters of machines. Second, a set of three basic applications were selected. The applications consist of a parallel search, a parallel sort, a parallel matrix multiplication. These application programs were implemented in C programming language under PVM. Third, we conducted performance evaluation under various configurations and problem sizes. Alternative parallel computing models and workload allocations for application programs were explored. The performance metric was limited to elapsed time or response time which in the context of parallel computing can be expressed in terms of speedup. The results reveal that the overhead of communication latency between processes in many cases is the restricting factor to performance. That is, coarse-grain parallelism which requires less frequent communication between processes will result in higher performance in network-based computing. Finally, we are in the final stages of installing an Asynchronous Transfer Mode (ATM) switch and four ATM interfaces (each 155 Mbps) which will allow us to extend our study to newer applications, performance metrics, and configurations.

Dissipation, Voltage Profile and Levy Dragon in a Special Ladder Network

ERIC Educational Resources Information Center

Ucak, C.

2009-01-01

A ladder network constructed by an elementary two-terminal network consisting of a parallel resistor-inductor block in series with a parallel resistor-capacitor block sometimes is said to have a non-dispersive dissipative response. This special ladder network is created iteratively by replacing the elementary two-terminal network in place of the…

Design of a MIMD neural network processor

NASA Astrophysics Data System (ADS)

Saeks, Richard E.; Priddy, Kevin L.; Pap, Robert M.; Stowell, S.

1994-03-01

The Accurate Automation Corporation (AAC) neural network processor (NNP) module is a fully programmable multiple instruction multiple data (MIMD) parallel processor optimized for the implementation of neural networks. The AAC NNP design fully exploits the intrinsic sparseness of neural network topologies. Moreover, by using a MIMD parallel processing architecture one can update multiple neurons in parallel with efficiency approaching 100 percent as the size of the network increases. Each AAC NNP module has 8 K neurons and 32 K interconnections and is capable of 140,000,000 connections per second with an eight processor array capable of over one billion connections per second.

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

Not Available

We present preliminary hypocenter determinations for 52 earthquakes recorded by a large multiinstitutional network of ocean bottom seismometers and ocean bottom hydrophones in the Orozco Fracture Zone in the eastern Pacific during late February to mid-March 1979. The network was deployed as part of the Rivera Ocean Seismic Experiment, also known as Project ROSE. The Orozco Fracture Zone is Physiographically complex, and the pattern of microearthquake hypocenters at least partly reflects this complexity. All of the well-located epicenters lie within the active transform fault segment of the fracture zone. About half of the recorded earthquakes were aligned along a narrowmore » trough that extends eastward from the northern rise crest intersection in the approximate direction of the Cocos-Pacific relative plate motion; these events appear to be characterized by strike-slip faulting. The second major group of activity occurred in the central portion of the transform fault; the microearthquakes in this group do not display a preferred alignment parallel to the direction of spreading, and several are not obviously associated with distinct topographic features. Hypocentral depth was well resolved for many of the earthquakes reported here. Nominal depths range from 0 to 17 km below the seafloor.« less

HeNCE: A Heterogeneous Network Computing Environment

DOE PAGES

Beguelin, Adam; Dongarra, Jack J.; Geist, George Al; ...

1994-01-01

Network computing seeks to utilize the aggregate resources of many networked computers to solve a single problem. In so doing it is often possible to obtain supercomputer performance from an inexpensive local area network. The drawback is that network computing is complicated and error prone when done by hand, especially if the computers have different operating systems and data formats and are thus heterogeneous. The heterogeneous network computing environment (HeNCE) is an integrated graphical environment for creating and running parallel programs over a heterogeneous collection of computers. It is built on a lower level package called parallel virtual machine (PVM).more » The HeNCE philosophy of parallel programming is to have the programmer graphically specify the parallelism of a computation and to automate, as much as possible, the tasks of writing, compiling, executing, debugging, and tracing the network computation. Key to HeNCE is a graphical language based on directed graphs that describe the parallelism and data dependencies of an application. Nodes in the graphs represent conventional Fortran or C subroutines and the arcs represent data and control flow. This article describes the present state of HeNCE, its capabilities, limitations, and areas of future research.« less

Proceedings from the Workshop on Large-Grained Parallelism (2nd) Held in Hidden Valley, Pennsylvania on October 11-14, 1987.

DTIC Science & Technology

1987-11-01

The purpose of the workshop was to bring together people whose interests lie in the areas of operating I systems , programming languages, and formal... operating system support, and applications. There were parallel discussions on scheduling and distributed languages, and on real-time and operating ...number of key challenges: * Distributed systems , languages, environments - Make transactions efficient. Integrate them into the operating system

Constructing Neuronal Network Models in Massively Parallel Environments.

PubMed

Ippen, Tammo; Eppler, Jochen M; Plesser, Hans E; Diesmann, Markus

2017-01-01

Recent advances in the development of data structures to represent spiking neuron network models enable us to exploit the complete memory of petascale computers for a single brain-scale network simulation. In this work, we investigate how well we can exploit the computing power of such supercomputers for the creation of neuronal networks. Using an established benchmark, we divide the runtime of simulation code into the phase of network construction and the phase during which the dynamical state is advanced in time. We find that on multi-core compute nodes network creation scales well with process-parallel code but exhibits a prohibitively large memory consumption. Thread-parallel network creation, in contrast, exhibits speedup only up to a small number of threads but has little overhead in terms of memory. We further observe that the algorithms creating instances of model neurons and their connections scale well for networks of ten thousand neurons, but do not show the same speedup for networks of millions of neurons. Our work uncovers that the lack of scaling of thread-parallel network creation is due to inadequate memory allocation strategies and demonstrates that thread-optimized memory allocators recover excellent scaling. An analysis of the loop order used for network construction reveals that more complex tests on the locality of operations significantly improve scaling and reduce runtime by allowing construction algorithms to step through large networks more efficiently than in existing code. The combination of these techniques increases performance by an order of magnitude and harnesses the increasingly parallel compute power of the compute nodes in high-performance clusters and supercomputers.

Constructing Neuronal Network Models in Massively Parallel Environments

PubMed Central

Ippen, Tammo; Eppler, Jochen M.; Plesser, Hans E.; Diesmann, Markus

2017-01-01

Recent advances in the development of data structures to represent spiking neuron network models enable us to exploit the complete memory of petascale computers for a single brain-scale network simulation. In this work, we investigate how well we can exploit the computing power of such supercomputers for the creation of neuronal networks. Using an established benchmark, we divide the runtime of simulation code into the phase of network construction and the phase during which the dynamical state is advanced in time. We find that on multi-core compute nodes network creation scales well with process-parallel code but exhibits a prohibitively large memory consumption. Thread-parallel network creation, in contrast, exhibits speedup only up to a small number of threads but has little overhead in terms of memory. We further observe that the algorithms creating instances of model neurons and their connections scale well for networks of ten thousand neurons, but do not show the same speedup for networks of millions of neurons. Our work uncovers that the lack of scaling of thread-parallel network creation is due to inadequate memory allocation strategies and demonstrates that thread-optimized memory allocators recover excellent scaling. An analysis of the loop order used for network construction reveals that more complex tests on the locality of operations significantly improve scaling and reduce runtime by allowing construction algorithms to step through large networks more efficiently than in existing code. The combination of these techniques increases performance by an order of magnitude and harnesses the increasingly parallel compute power of the compute nodes in high-performance clusters and supercomputers. PMID:28559808

Anatomically constrained neural network models for the categorization of facial expression

NASA Astrophysics Data System (ADS)

McMenamin, Brenton W.; Assadi, Amir H.

2004-12-01

The ability to recognize facial expression in humans is performed with the amygdala which uses parallel processing streams to identify the expressions quickly and accurately. Additionally, it is possible that a feedback mechanism may play a role in this process as well. Implementing a model with similar parallel structure and feedback mechanisms could be used to improve current facial recognition algorithms for which varied expressions are a source for error. An anatomically constrained artificial neural-network model was created that uses this parallel processing architecture and feedback to categorize facial expressions. The presence of a feedback mechanism was not found to significantly improve performance for models with parallel architecture. However the use of parallel processing streams significantly improved accuracy over a similar network that did not have parallel architecture. Further investigation is necessary to determine the benefits of using parallel streams and feedback mechanisms in more advanced object recognition tasks.

Anatomically constrained neural network models for the categorization of facial expression

NASA Astrophysics Data System (ADS)

McMenamin, Brenton W.; Assadi, Amir H.

2005-01-01

The ability to recognize facial expression in humans is performed with the amygdala which uses parallel processing streams to identify the expressions quickly and accurately. Additionally, it is possible that a feedback mechanism may play a role in this process as well. Implementing a model with similar parallel structure and feedback mechanisms could be used to improve current facial recognition algorithms for which varied expressions are a source for error. An anatomically constrained artificial neural-network model was created that uses this parallel processing architecture and feedback to categorize facial expressions. The presence of a feedback mechanism was not found to significantly improve performance for models with parallel architecture. However the use of parallel processing streams significantly improved accuracy over a similar network that did not have parallel architecture. Further investigation is necessary to determine the benefits of using parallel streams and feedback mechanisms in more advanced object recognition tasks.

Use of artificial intelligence in analytical systems for the clinical laboratory

PubMed Central

Truchaud, Alain; Ozawa, Kyoichi; Pardue, Harry; Schnipelsky, Paul

1995-01-01

The incorporation of information-processing technology into analytical systems in the form of standard computing software has recently been advanced by the introduction of artificial intelligence (AI), both as expert systems and as neural networks. This paper considers the role of software in system operation, control and automation, and attempts to define intelligence. AI is characterized by its ability to deal with incomplete and imprecise information and to accumulate knowledge. Expert systems, building on standard computing techniques, depend heavily on the domain experts and knowledge engineers that have programmed them to represent the real world. Neural networks are intended to emulate the pattern-recognition and parallel processing capabilities of the human brain and are taught rather than programmed. The future may lie in a combination of the recognition ability of the neural network and the rationalization capability of the expert system. In the second part of the paper, examples are given of applications of AI in stand-alone systems for knowledge engineering and medical diagnosis and in embedded systems for failure detection, image analysis, user interfacing, natural language processing, robotics and machine learning, as related to clinical laboratories. It is concluded that AI constitutes a collective form of intellectual propery, and that there is a need for better documentation, evaluation and regulation of the systems already being used in clinical laboratories. PMID:18924784

Broadcasting a message in a parallel computer

DOEpatents

Berg, Jeremy E [Rochester, MN; Faraj, Ahmad A [Rochester, MN

2011-08-02

Methods, systems, and products are disclosed for broadcasting a message in a parallel computer. The parallel computer includes a plurality of compute nodes connected together using a data communications network. The data communications network optimized for point to point data communications and is characterized by at least two dimensions. The compute nodes are organized into at least one operational group of compute nodes for collective parallel operations of the parallel computer. One compute node of the operational group assigned to be a logical root. Broadcasting a message in a parallel computer includes: establishing a Hamiltonian path along all of the compute nodes in at least one plane of the data communications network and in the operational group; and broadcasting, by the logical root to the remaining compute nodes, the logical root's message along the established Hamiltonian path.

Exploring time- and frequency- dependent functional connectivity and brain networks during deception with single-trial event-related potentials

NASA Astrophysics Data System (ADS)

Gao, Jun-Feng; Yang, Yong; Huang, Wen-Tao; Lin, Pan; Ge, Sheng; Zheng, Hong-Mei; Gu, Ling-Yun; Zhou, Hui; Li, Chen-Hong; Rao, Ni-Ni

2016-11-01

To better characterize the cognitive processes and mechanisms that are associated with deception, wavelet coherence was employed to evaluate functional connectivity between different brain regions. Two groups of subjects were evaluated for this purpose: 32 participants were required to either tell the truth or to lie when facing certain stimuli, and their electroencephalogram signals on 12 electrodes were recorded. The experimental results revealed that deceptive responses elicited greater connectivity strength than truthful responses, particularly in the θ band on specific electrode pairs primarily involving connections between the prefrontal/frontal and central regions and between the prefrontal/frontal and left parietal regions. These results indicate that these brain regions play an important role in executing lying responses. Additionally, three time- and frequency-dependent functional connectivity networks were proposed to thoroughly reflect the functional coupling of brain regions that occurs during lying. Furthermore, the wavelet coherence values for the connections shown in the networks were extracted as features for support vector machine training. High classification accuracy suggested that the proposed network effectively characterized differences in functional connectivity between the two groups of subjects over a specific time-frequency area and hence could be a sensitive measurement for identifying deception.

Hybrid Parallelism for Volume Rendering on Large-, Multi-, and Many-Core Systems

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

Howison, Mark; Bethel, E. Wes; Childs, Hank

2012-01-01

With the computing industry trending towards multi- and many-core processors, we study how a standard visualization algorithm, ray-casting volume rendering, can benefit from a hybrid parallelism approach. Hybrid parallelism provides the best of both worlds: using distributed-memory parallelism across a large numbers of nodes increases available FLOPs and memory, while exploiting shared-memory parallelism among the cores within each node ensures that each node performs its portion of the larger calculation as efficiently as possible. We demonstrate results from weak and strong scaling studies, at levels of concurrency ranging up to 216,000, and with datasets as large as 12.2 trillion cells.more » The greatest benefit from hybrid parallelism lies in the communication portion of the algorithm, the dominant cost at higher levels of concurrency. We show that reducing the number of participants with a hybrid approach significantly improves performance.« less

MapReduce Based Parallel Neural Networks in Enabling Large Scale Machine Learning

PubMed Central

Yang, Jie; Huang, Yuan; Xu, Lixiong; Li, Siguang; Qi, Man

2015-01-01

Artificial neural networks (ANNs) have been widely used in pattern recognition and classification applications. However, ANNs are notably slow in computation especially when the size of data is large. Nowadays, big data has received a momentum from both industry and academia. To fulfill the potentials of ANNs for big data applications, the computation process must be speeded up. For this purpose, this paper parallelizes neural networks based on MapReduce, which has become a major computing model to facilitate data intensive applications. Three data intensive scenarios are considered in the parallelization process in terms of the volume of classification data, the size of the training data, and the number of neurons in the neural network. The performance of the parallelized neural networks is evaluated in an experimental MapReduce computer cluster from the aspects of accuracy in classification and efficiency in computation. PMID:26681933

Evaluation of a parallel implementation of the learning portion of the backward error propagation neural network: experiments in artifact identification.

PubMed Central

Sittig, D. F.; Orr, J. A.

1991-01-01

Various methods have been proposed in an attempt to solve problems in artifact and/or alarm identification including expert systems, statistical signal processing techniques, and artificial neural networks (ANN). ANNs consist of a large number of simple processing units connected by weighted links. To develop truly robust ANNs, investigators are required to train their networks on huge training data sets, requiring enormous computing power. We implemented a parallel version of the backward error propagation neural network training algorithm in the widely portable parallel programming language C-Linda. A maximum speedup of 4.06 was obtained with six processors. This speedup represents a reduction in total run-time from approximately 6.4 hours to 1.5 hours. We conclude that use of the master-worker model of parallel computation is an excellent method for obtaining speedups in the backward error propagation neural network training algorithm. PMID:1807607

MapReduce Based Parallel Neural Networks in Enabling Large Scale Machine Learning.

PubMed

Liu, Yang; Yang, Jie; Huang, Yuan; Xu, Lixiong; Li, Siguang; Qi, Man

2015-01-01

Artificial neural networks (ANNs) have been widely used in pattern recognition and classification applications. However, ANNs are notably slow in computation especially when the size of data is large. Nowadays, big data has received a momentum from both industry and academia. To fulfill the potentials of ANNs for big data applications, the computation process must be speeded up. For this purpose, this paper parallelizes neural networks based on MapReduce, which has become a major computing model to facilitate data intensive applications. Three data intensive scenarios are considered in the parallelization process in terms of the volume of classification data, the size of the training data, and the number of neurons in the neural network. The performance of the parallelized neural networks is evaluated in an experimental MapReduce computer cluster from the aspects of accuracy in classification and efficiency in computation.

Parallel-wire grid assembly with method and apparatus for construction thereof

DOEpatents

Lewandowski, E.F.; Vrabec, J.

1981-10-26

Disclosed is a parallel wire grid and an apparatus and method for making the same. The grid consists of a generally coplanar array of parallel spaced-apart wires secured between metallic frame members by an electrically conductive epoxy. The method consists of continuously winding a wire about a novel winding apparatus comprising a plurality of spaced-apart generally parallel spindles. Each spindle is threaded with a number of predeterminedly spaced-apart grooves which receive and accurately position the wire at predetermined positions along the spindle. Overlying frame members coated with electrically conductive epoxy are then placed on either side of the wire array and are drawn together. After the epoxy hardens, portions of the wire array lying outside the frame members are trimmed away.

Parallel-wire grid assembly with method and apparatus for construction thereof

DOEpatents

Lewandowski, Edward F.; Vrabec, John

1984-01-01

Disclosed is a parallel wire grid and an apparatus and method for making the same. The grid consists of a generally coplanar array of parallel spaced-apart wires secured between metallic frame members by an electrically conductive epoxy. The method consists of continuously winding a wire about a novel winding apparatus comprising a plurality of spaced-apart generally parallel spindles. Each spindle is threaded with a number of predeterminedly spaced-apart grooves which receive and accurately position the wire at predetermined positions along the spindle. Overlying frame members coated with electrically conductive epoxy are then placed on either side of the wire array and are drawn together. After the epoxy hardens, portions of the wire array lying outside the frame members are trimmed away.

Integration of isoelectric focusing with parallel sodium dodecyl sulfate gel electrophoresis for multidimensional protein separations in a plastic microfluidic [correction of microfludic] network.

PubMed

Li, Yan; Buch, Jesse S; Rosenberger, Frederick; DeVoe, Don L; Lee, Cheng S

2004-02-01

An integrated protein concentration/separation system, combining non-native isoelectric focusing (IEF) with sodium dodecyl sulfate (SDS) gel electrophoresis on a polymer microfluidic chip, is reported. The system provides significant analyte concentration and extremely high resolving power for separated protein mixtures. The ability to introduce and isolate multiple separation media in a plastic microfluidic network is one of two key requirements for achieving multidimensional protein separations. The second requirement lies in the quantitative transfer of focused proteins from the first to second separation dimensions without significant loss in the resolution acquired from the first dimension. Rather than sequentially sampling protein analytes eluted from IEF, focused proteins are electrokinetically transferred into an array of orthogonal microchannels and further resolved by SDS gel electrophoresis in a parallel and high-throughput format. Resolved protein analytes are monitored using noncovalent, environment-sensitive, fluorescent probes such as Sypro Red. In comparison with covalently labeling proteins, the use of Sypro staining during electrophoretic separations not only presents a generic detection approach for the analysis of complex protein mixtures such as cell lysates but also avoids additional introduction of protein microheterogeneity as the result of labeling reaction. A comprehensive 2-D protein separation is completed in less than 10 min with an overall peak capacity of approximately 1700 using a chip with planar dimensions of as small as 2 cm x 3 cm. Significant enhancement in the peak capacity can be realized by simply raising the density of microchannels in the array, thereby increasing the number of IEF fractions further analyzed in the size-based separation dimension.

Everybody Else Is Doing It: Exploring Social Transmission of Lying Behavior

PubMed Central

Mann, Heather; Garcia-Rada, Ximena; Houser, Daniel; Ariely, Dan

2014-01-01

Lying is a common occurrence in social interactions, but what predicts whether an individual will tell a lie? While previous studies have focused on personality factors, here we asked whether lying tendencies might be transmitted through social networks. Using an international sample of 1,687 socially connected pairs, we investigated whether lying tendencies were related in socially connected individuals, and tested two moderators of observed relationships. Participants recruited through a massive open online course reported how likely they would be to engage in specific lies; a friend or relative responded to the same scenarios independently. We classified lies according to their beneficiary (antisocial vs. prosocial lies), and their directness (lies of commission vs. omission), resulting in four unique lying categories. Regression analyses showed that antisocial commission, antisocial omission, and prosocial commission lying tendencies were all uniquely related in connected pairs, even when the analyses were limited to pairs that were not biologically related. For antisocial lies of commission, these relationships were strongest, and were moderated by amount of time spent together. Randomly paired individuals from the same countries were also related in their antisocial commission lying tendencies, signifying country-level norms. Our results indicate that a person's lying tendencies can be predicted by the lying tendencies of his or her friends and family members. PMID:25333483

Reducing neural network training time with parallel processing

NASA Technical Reports Server (NTRS)

Rogers, James L., Jr.; Lamarsh, William J., II

1995-01-01

Obtaining optimal solutions for engineering design problems is often expensive because the process typically requires numerous iterations involving analysis and optimization programs. Previous research has shown that a near optimum solution can be obtained in less time by simulating a slow, expensive analysis with a fast, inexpensive neural network. A new approach has been developed to further reduce this time. This approach decomposes a large neural network into many smaller neural networks that can be trained in parallel. Guidelines are developed to avoid some of the pitfalls when training smaller neural networks in parallel. These guidelines allow the engineer: to determine the number of nodes on the hidden layer of the smaller neural networks; to choose the initial training weights; and to select a network configuration that will capture the interactions among the smaller neural networks. This paper presents results describing how these guidelines are developed.

Adaptive parallel logic networks

NASA Technical Reports Server (NTRS)

Martinez, Tony R.; Vidal, Jacques J.

1988-01-01

Adaptive, self-organizing concurrent systems (ASOCS) that combine self-organization with massive parallelism for such applications as adaptive logic devices, robotics, process control, and system malfunction management, are presently discussed. In ASOCS, an adaptive network composed of many simple computing elements operating in combinational and asynchronous fashion is used and problems are specified by presenting if-then rules to the system in the form of Boolean conjunctions. During data processing, which is a different operational phase from adaptation, the network acts as a parallel hardware circuit.

Plasma Generator Using Spiral Conductors

NASA Technical Reports Server (NTRS)

Szatkowski, George N. (Inventor); Dudley, Kenneth L. (Inventor); Ticatch, Larry A. (Inventor); Smith, Laura J. (Inventor); Koppen, Sandra V. (Inventor); Nguyen, Truong X. (Inventor); Ely, Jay J. (Inventor)

2016-01-01

A plasma generator includes a pair of identical spiraled electrical conductors separated by dielectric material. Both spiraled conductors have inductance and capacitance wherein, in the presence of a time-varying electromagnetic field, the spiraled conductors resonate to generate a harmonic electromagnetic field response. The spiraled conductors lie in parallel planes and partially overlap one another in a direction perpendicular to the parallel planes. The geometric centers of the spiraled conductors define endpoints of a line that is non-perpendicular with respect to the parallel planes. A voltage source coupled across the spiraled conductors applies a voltage sufficient to generate a plasma in at least a portion of the dielectric material.

Seeing the forest for the trees: Networked workstations as a parallel processing computer

NASA Technical Reports Server (NTRS)

Breen, J. O.; Meleedy, D. M.

1992-01-01

Unlike traditional 'serial' processing computers in which one central processing unit performs one instruction at a time, parallel processing computers contain several processing units, thereby, performing several instructions at once. Many of today's fastest supercomputers achieve their speed by employing thousands of processing elements working in parallel. Few institutions can afford these state-of-the-art parallel processors, but many already have the makings of a modest parallel processing system. Workstations on existing high-speed networks can be harnessed as nodes in a parallel processing environment, bringing the benefits of parallel processing to many. While such a system can not rival the industry's latest machines, many common tasks can be accelerated greatly by spreading the processing burden and exploiting idle network resources. We study several aspects of this approach, from algorithms to select nodes to speed gains in specific tasks. With ever-increasing volumes of astronomical data, it becomes all the more necessary to utilize our computing resources fully.

Ultrascalable petaflop parallel supercomputer

DOEpatents

Blumrich, Matthias A [Ridgefield, CT; Chen, Dong [Croton On Hudson, NY; Chiu, George [Cross River, NY; Cipolla, Thomas M [Katonah, NY; Coteus, Paul W [Yorktown Heights, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Hall, Shawn [Pleasantville, NY; Haring, Rudolf A [Cortlandt Manor, NY; Heidelberger, Philip [Cortlandt Manor, NY; Kopcsay, Gerard V [Yorktown Heights, NY; Ohmacht, Martin [Yorktown Heights, NY; Salapura, Valentina [Chappaqua, NY; Sugavanam, Krishnan [Mahopac, NY; Takken, Todd [Brewster, NY

2010-07-20

A massively parallel supercomputer of petaOPS-scale includes node architectures based upon System-On-a-Chip technology, where each processing node comprises a single Application Specific Integrated Circuit (ASIC) having up to four processing elements. The ASIC nodes are interconnected by multiple independent networks that optimally maximize the throughput of packet communications between nodes with minimal latency. The multiple networks may include three high-speed networks for parallel algorithm message passing including a Torus, collective network, and a Global Asynchronous network that provides global barrier and notification functions. These multiple independent networks may be collaboratively or independently utilized according to the needs or phases of an algorithm for optimizing algorithm processing performance. The use of a DMA engine is provided to facilitate message passing among the nodes without the expenditure of processing resources at the node.

The Dixmier Map for Nilpotent Super Lie Algebras

NASA Astrophysics Data System (ADS)

Herscovich, Estanislao

2012-07-01

In this article we prove that there exists a Dixmier map for nilpotent super Lie algebras. In other words, if we denote by {Prim({U}({g}))} the set of (graded) primitive ideals of the enveloping algebra {{U}({g})} of a nilpotent Lie superalgebra {{g}} and {{A}d0} the adjoint group of {{g}0}, we prove that the usual Dixmier map for nilpotent Lie algebras can be naturally extended to the context of nilpotent super Lie algebras, i.e. there exists a bijective map I : {g}0^{*}/{A}d0 rightarrow Prim({U}({g})) defined by sending the equivalence class [ λ] of a functional λ to a primitive ideal I( λ) of {{U}({g})}, and which coincides with the Dixmier map in the case of nilpotent Lie algebras. Moreover, the construction of the previous map is explicit, and more or less parallel to the one for Lie algebras, a major difference with a previous approach ( cf. [18]). One key fact in the construction is the existence of polarizations for super Lie algebras, generalizing the concept defined for Lie algebras. As a corollary of the previous description, we obtain the isomorphism {{U}({g})/I(λ) ˜eq Cliffq(k) ⊗ Ap(k)}, where {(p,q) = (dim({g}0/{g}0^{λ})/2,dim({g}1/{g}1^{λ}))}, we get a direct construction of the maximal ideals of the underlying algebra of {{U}({g})} and also some properties of the stabilizers of the primitive ideals of {{U}({g})}.

Compact holographic optical neural network system for real-time pattern recognition

NASA Astrophysics Data System (ADS)

Lu, Taiwei; Mintzer, David T.; Kostrzewski, Andrew A.; Lin, Freddie S.

1996-08-01

One of the important characteristics of artificial neural networks is their capability for massive interconnection and parallel processing. Recently, specialized electronic neural network processors and VLSI neural chips have been introduced in the commercial market. The number of parallel channels they can handle is limited because of the limited parallel interconnections that can be implemented with 1D electronic wires. High-resolution pattern recognition problems can require a large number of neurons for parallel processing of an image. This paper describes a holographic optical neural network (HONN) that is based on high- resolution volume holographic materials and is capable of performing massive 3D parallel interconnection of tens of thousands of neurons. A HONN with more than 16,000 neurons packaged in an attache case has been developed. Rotation- shift-scale-invariant pattern recognition operations have been demonstrated with this system. System parameters such as the signal-to-noise ratio, dynamic range, and processing speed are discussed.

Can beneficial ends justify lying? Neural responses to the passive reception of lies and truth-telling with beneficial and harmful monetary outcomes

PubMed Central

Weber, Bernd

2016-01-01

Can beneficial ends justify morally questionable means? To investigate how monetary outcomes influence the neural responses to lying, we used a modified, cheap talk sender–receiver game in which participants were the direct recipients of lies and truthful statements resulting in either beneficial or harmful monetary outcomes. Both truth-telling (vs lying) as well as beneficial (vs harmful) outcomes elicited higher activity in the nucleus accumbens. Lying (vs truth-telling) elicited higher activity in the supplementary motor area, right inferior frontal gyrus, superior temporal sulcus and left anterior insula. Moreover, the significant interaction effect was found in the left amygdala, which showed that the monetary outcomes modulated the neural activity in the left amygdala only when truth-telling rather than lying. Our study identified a neural network associated with the reception of lies and truth, including the regions linked to the reward process, recognition and emotional experiences of being treated (dis)honestly. PMID:26454816

Fault detection for hydraulic pump based on chaotic parallel RBF network

NASA Astrophysics Data System (ADS)

Lu, Chen; Ma, Ning; Wang, Zhipeng

2011-12-01

In this article, a parallel radial basis function network in conjunction with chaos theory (CPRBF network) is presented, and applied to practical fault detection for hydraulic pump, which is a critical component in aircraft. The CPRBF network consists of a number of radial basis function (RBF) subnets connected in parallel. The number of input nodes for each RBF subnet is determined by different embedding dimension based on chaotic phase-space reconstruction. The output of CPRBF is a weighted sum of all RBF subnets. It was first trained using the dataset from normal state without fault, and then a residual error generator was designed to detect failures based on the trained CPRBF network. Then, failure detection can be achieved by the analysis of the residual error. Finally, two case studies are introduced to compare the proposed CPRBF network with traditional RBF networks, in terms of prediction and detection accuracy.

Line-plane broadcasting in a data communications network of a parallel computer

DOEpatents

Archer, Charles J.; Berg, Jeremy E.; Blocksome, Michael A.; Smith, Brian E.

2010-06-08

Methods, apparatus, and products are disclosed for line-plane broadcasting in a data communications network of a parallel computer, the parallel computer comprising a plurality of compute nodes connected together through the network, the network optimized for point to point data communications and characterized by at least a first dimension, a second dimension, and a third dimension, that include: initiating, by a broadcasting compute node, a broadcast operation, including sending a message to all of the compute nodes along an axis of the first dimension for the network; sending, by each compute node along the axis of the first dimension, the message to all of the compute nodes along an axis of the second dimension for the network; and sending, by each compute node along the axis of the second dimension, the message to all of the compute nodes along an axis of the third dimension for the network.

Line-plane broadcasting in a data communications network of a parallel computer

DOEpatents

Archer, Charles J.; Berg, Jeremy E.; Blocksome, Michael A.; Smith, Brian E.

2010-11-23

Methods, apparatus, and products are disclosed for line-plane broadcasting in a data communications network of a parallel computer, the parallel computer comprising a plurality of compute nodes connected together through the network, the network optimized for point to point data communications and characterized by at least a first dimension, a second dimension, and a third dimension, that include: initiating, by a broadcasting compute node, a broadcast operation, including sending a message to all of the compute nodes along an axis of the first dimension for the network; sending, by each compute node along the axis of the first dimension, the message to all of the compute nodes along an axis of the second dimension for the network; and sending, by each compute node along the axis of the second dimension, the message to all of the compute nodes along an axis of the third dimension for the network.

Parallel Mutual Information Based Construction of Genome-Scale Networks on the Intel® Xeon Phi™ Coprocessor.

PubMed

Misra, Sanchit; Pamnany, Kiran; Aluru, Srinivas

2015-01-01

Construction of whole-genome networks from large-scale gene expression data is an important problem in systems biology. While several techniques have been developed, most cannot handle network reconstruction at the whole-genome scale, and the few that can, require large clusters. In this paper, we present a solution on the Intel Xeon Phi coprocessor, taking advantage of its multi-level parallelism including many x86-based cores, multiple threads per core, and vector processing units. We also present a solution on the Intel® Xeon® processor. Our solution is based on TINGe, a fast parallel network reconstruction technique that uses mutual information and permutation testing for assessing statistical significance. We demonstrate the first ever inference of a plant whole genome regulatory network on a single chip by constructing a 15,575 gene network of the plant Arabidopsis thaliana from 3,137 microarray experiments in only 22 minutes. In addition, our optimization for parallelizing mutual information computation on the Intel Xeon Phi coprocessor holds out lessons that are applicable to other domains.

Crystal structure of bis[bis(4-azaniumylphenyl) sulfone] tetranitrate monohydrate

PubMed Central

Benahsene, Amani Hind; Bendjeddou, Lamia; Merazig, Hocine

2017-01-01

In the title compound, the hydrated tetra­(nitrate) salt of dapsone (4,4′-di­amino­diphenyl­sulfone), 2C12H14N2O2S2+·4NO3 −·H2O {alternative name: bis[bis­(4,4′-di­aza­niumylphen­yl) sulfone] tetra­nitrate monohydrate}, the cations are conformationally similar, with comparable dihedral angles between the two benzene rings in each of 70.03 (18) and 69.69 (19)°. In the crystal, mixed cation–anion–water mol­ecule layers lying parallel to the (001) plane are formed through N—H⋯O, O—H⋯O and C—H⋯O hydrogen-bonding inter­actions and these layers are further extended into an overall three-dimensional supra­molecular network structure. Inter-ring π–π inter­actions are also present [minimum ring centroid separation = 3.693 (3) Å]. PMID:29152359

Teach for America, Relay Graduate School, and the Charter School Networks: The Making of a Parallel Education Structure

ERIC Educational Resources Information Center

Mungal, Angus Shiva

2016-01-01

In New York City, a partnership between Teach For America (TFA), the New York City Department of Education (NYCDOE), the Relay Graduate School of Education (Relay), and three charter school networks produced a "parallel education structure" within the public school system. Driving the partnership and the parallel education structure are…

Streaming parallel GPU acceleration of large-scale filter-based spiking neural networks.

PubMed

Slażyński, Leszek; Bohte, Sander

2012-01-01

The arrival of graphics processing (GPU) cards suitable for massively parallel computing promises affordable large-scale neural network simulation previously only available at supercomputing facilities. While the raw numbers suggest that GPUs may outperform CPUs by at least an order of magnitude, the challenge is to develop fine-grained parallel algorithms to fully exploit the particulars of GPUs. Computation in a neural network is inherently parallel and thus a natural match for GPU architectures: given inputs, the internal state for each neuron can be updated in parallel. We show that for filter-based spiking neurons, like the Spike Response Model, the additive nature of membrane potential dynamics enables additional update parallelism. This also reduces the accumulation of numerical errors when using single precision computation, the native precision of GPUs. We further show that optimizing simulation algorithms and data structures to the GPU's architecture has a large pay-off: for example, matching iterative neural updating to the memory architecture of the GPU speeds up this simulation step by a factor of three to five. With such optimizations, we can simulate in better-than-realtime plausible spiking neural networks of up to 50 000 neurons, processing over 35 million spiking events per second.

Parallel computation for biological sequence comparison: comparing a portable model to the native model for the Intel Hypercube.

PubMed

Nadkarni, P M; Miller, P L

1991-01-01

A parallel program for inter-database sequence comparison was developed on the Intel Hypercube using two models of parallel programming. One version was built using machine-specific Hypercube parallel programming commands. The other version was built using Linda, a machine-independent parallel programming language. The two versions of the program provide a case study comparing these two approaches to parallelization in an important biological application area. Benchmark tests with both programs gave comparable results with a small number of processors. As the number of processors was increased, the Linda version was somewhat less efficient. The Linda version was also run without change on Network Linda, a virtual parallel machine running on a network of desktop workstations.

A sweep algorithm for massively parallel simulation of circuit-switched networks

NASA Technical Reports Server (NTRS)

Gaujal, Bruno; Greenberg, Albert G.; Nicol, David M.

1992-01-01

A new massively parallel algorithm is presented for simulating large asymmetric circuit-switched networks, controlled by a randomized-routing policy that includes trunk-reservation. A single instruction multiple data (SIMD) implementation is described, and corresponding experiments on a 16384 processor MasPar parallel computer are reported. A multiple instruction multiple data (MIMD) implementation is also described, and corresponding experiments on an Intel IPSC/860 parallel computer, using 16 processors, are reported. By exploiting parallelism, our algorithm increases the possible execution rate of such complex simulations by as much as an order of magnitude.

Hadoop neural network for parallel and distributed feature selection.

PubMed

Hodge, Victoria J; O'Keefe, Simon; Austin, Jim

2016-06-01

In this paper, we introduce a theoretical basis for a Hadoop-based neural network for parallel and distributed feature selection in Big Data sets. It is underpinned by an associative memory (binary) neural network which is highly amenable to parallel and distributed processing and fits with the Hadoop paradigm. There are many feature selectors described in the literature which all have various strengths and weaknesses. We present the implementation details of five feature selection algorithms constructed using our artificial neural network framework embedded in Hadoop YARN. Hadoop allows parallel and distributed processing. Each feature selector can be divided into subtasks and the subtasks can then be processed in parallel. Multiple feature selectors can also be processed simultaneously (in parallel) allowing multiple feature selectors to be compared. We identify commonalities among the five features selectors. All can be processed in the framework using a single representation and the overall processing can also be greatly reduced by only processing the common aspects of the feature selectors once and propagating these aspects across all five feature selectors as necessary. This allows the best feature selector and the actual features to select to be identified for large and high dimensional data sets through exploiting the efficiency and flexibility of embedding the binary associative-memory neural network in Hadoop. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Genetics Home Reference: medullary cystic kidney disease type 1

MedlinePlus

... They lead to the production of an altered protein. It is unclear how this change causes kidney disease. ... cystic kidney disease type 1 lie in a large VNTR in MUC1 missed by massively parallel sequencing. Nat Genet. 2013 Mar;45(3):299-303. ...

System providing limit switch function with simultaneous absolute position output

NASA Technical Reports Server (NTRS)

Alhorn, Dean C. (Inventor); Howard, David E. (Inventor); Smith, Dennis A. (Inventor)

2006-01-01

A limit and position sensing system includes a sensor assembly and an emitter. The sensor assembly includes first and second electrical conductors arranged in opposing parallel planes. The first electrical conductor is coiled outwardly from either end thereof in a clockwise fashion to form a first coil region and a second coil region. The second electrical conductor forms a single coil with portions of the single coil's rings lying between the first end and second end of the first electrical conductor being parallel to an axis of the first electrical conductor's plane. Ferromagnetic material is aligned with the first and second electrical conductors and spans beyond (a) the first and second ends of the first electrical conductor, and (b) the portions of the rings of the second electrical conductor's single coil that lie between the first end and second end of the first electrical conductor. The emitter is spaced apart from the sensor assembly and transmits a periodic electromagnetic wave towards the sensor assembly.

Machine-learning-based calving prediction from activity, lying, and ruminating behaviors in dairy cattle.

PubMed

Borchers, M R; Chang, Y M; Proudfoot, K L; Wadsworth, B A; Stone, A E; Bewley, J M

2017-07-01

The objective of this study was to use automated activity, lying, and rumination monitors to characterize prepartum behavior and predict calving in dairy cattle. Data were collected from 20 primiparous and 33 multiparous Holstein dairy cattle from September 2011 to May 2013 at the University of Kentucky Coldstream Dairy. The HR Tag (SCR Engineers Ltd., Netanya, Israel) automatically collected neck activity and rumination data in 2-h increments. The IceQube (IceRobotics Ltd., South Queensferry, United Kingdom) automatically collected number of steps, lying time, standing time, number of transitions from standing to lying (lying bouts), and total motion, summed in 15-min increments. IceQube data were summed in 2-h increments to match HR Tag data. All behavioral data were collected for 14 d before the predicted calving date. Retrospective data analysis was performed using mixed linear models to examine behavioral changes by day in the 14 d before calving. Bihourly behavioral differences from baseline values over the 14 d before calving were also evaluated using mixed linear models. Changes in daily rumination time, total motion, lying time, and lying bouts occurred in the 14 d before calving. In the bihourly analysis, extreme values for all behaviors occurred in the final 24 h, indicating that the monitored behaviors may be useful in calving prediction. To determine whether technologies were useful at predicting calving, random forest, linear discriminant analysis, and neural network machine-learning techniques were constructed and implemented using R version 3.1.0 (R Foundation for Statistical Computing, Vienna, Austria). These methods were used on variables from each technology and all combined variables from both technologies. A neural network analysis that combined variables from both technologies at the daily level yielded 100.0% sensitivity and 86.8% specificity. A neural network analysis that combined variables from both technologies in bihourly increments was used to identify 2-h periods in the 8 h before calving with 82.8% sensitivity and 80.4% specificity. Changes in behavior and machine-learning alerts indicate that commercially marketed behavioral monitors may have calving prediction potential. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Parallel discrete-event simulation of FCFS stochastic queueing networks

NASA Technical Reports Server (NTRS)

Nicol, David M.

1988-01-01

Physical systems are inherently parallel. Intuition suggests that simulations of these systems may be amenable to parallel execution. The parallel execution of a discrete-event simulation requires careful synchronization of processes in order to ensure the execution's correctness; this synchronization can degrade performance. Largely negative results were recently reported in a study which used a well-known synchronization method on queueing network simulations. Discussed here is a synchronization method (appointments), which has proven itself to be effective on simulations of FCFS queueing networks. The key concept behind appointments is the provision of lookahead. Lookahead is a prediction on a processor's future behavior, based on an analysis of the processor's simulation state. It is shown how lookahead can be computed for FCFS queueing network simulations, give performance data that demonstrates the method's effectiveness under moderate to heavy loads, and discuss performance tradeoffs between the quality of lookahead, and the cost of computing lookahead.

Multi-petascale highly efficient parallel supercomputer

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

Asaad, Sameh; Bellofatto, Ralph E.; Blocksome, Michael A.

A Multi-Petascale Highly Efficient Parallel Supercomputer of 100 petaflop-scale includes node architectures based upon System-On-a-Chip technology, where each processing node comprises a single Application Specific Integrated Circuit (ASIC). The ASIC nodes are interconnected by a five dimensional torus network that optimally maximize the throughput of packet communications between nodes and minimize latency. The network implements collective network and a global asynchronous network that provides global barrier and notification functions. Integrated in the node design include a list-based prefetcher. The memory system implements transaction memory, thread level speculation, and multiversioning cache that improves soft error rate at the same time andmore » supports DMA functionality allowing for parallel processing message-passing.« less

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

NASA Technical Reports Server (NTRS)

Janetzke, David C.; Murthy, Durbha V.

1991-01-01

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

Performing a local reduction operation on a parallel computer

DOEpatents

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

DOEpatents

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.

Sequential and parallel image restoration: neural network implementations.

PubMed

Figueiredo, M T; Leitao, J N

1994-01-01

Sequential and parallel image restoration algorithms and their implementations on neural networks are proposed. For images degraded by linear blur and contaminated by additive white Gaussian noise, maximum a posteriori (MAP) estimation and regularization theory lead to the same high dimension convex optimization problem. The commonly adopted strategy (in using neural networks for image restoration) is to map the objective function of the optimization problem into the energy of a predefined network, taking advantage of its energy minimization properties. Departing from this approach, we propose neural implementations of iterative minimization algorithms which are first proved to converge. The developed schemes are based on modified Hopfield (1985) networks of graded elements, with both sequential and parallel updating schedules. An algorithm supported on a fully standard Hopfield network (binary elements and zero autoconnections) is also considered. Robustness with respect to finite numerical precision is studied, and examples with real images are presented.

The method of parallel-hierarchical transformation for rapid recognition of dynamic images using GPGPU technology

NASA Astrophysics Data System (ADS)

Timchenko, Leonid; Yarovyi, Andrii; Kokriatskaya, Nataliya; Nakonechna, Svitlana; Abramenko, Ludmila; Ławicki, Tomasz; Popiel, Piotr; Yesmakhanova, Laura

2016-09-01

The paper presents a method of parallel-hierarchical transformations for rapid recognition of dynamic images using GPU technology. Direct parallel-hierarchical transformations based on cluster CPU-and GPU-oriented hardware platform. Mathematic models of training of the parallel hierarchical (PH) network for the transformation are developed, as well as a training method of the PH network for recognition of dynamic images. This research is most topical for problems on organizing high-performance computations of super large arrays of information designed to implement multi-stage sensing and processing as well as compaction and recognition of data in the informational structures and computer devices. This method has such advantages as high performance through the use of recent advances in parallelization, possibility to work with images of ultra dimension, ease of scaling in case of changing the number of nodes in the cluster, auto scan of local network to detect compute nodes.

An object-oriented approach to nested data parallelism

NASA Technical Reports Server (NTRS)

Sheffler, Thomas J.; Chatterjee, Siddhartha

1994-01-01

This paper describes an implementation technique for integrating nested data parallelism into an object-oriented language. Data-parallel programming employs sets of data called 'collections' and expresses parallelism as operations performed over the elements of a collection. When the elements of a collection are also collections, then there is the possibility for 'nested data parallelism.' Few current programming languages support nested data parallelism however. In an object-oriented framework, a collection is a single object. Its type defines the parallel operations that may be applied to it. Our goal is to design and build an object-oriented data-parallel programming environment supporting nested data parallelism. Our initial approach is built upon three fundamental additions to C++. We add new parallel base types by implementing them as classes, and add a new parallel collection type called a 'vector' that is implemented as a template. Only one new language feature is introduced: the 'foreach' construct, which is the basis for exploiting elementwise parallelism over collections. The strength of the method lies in the compilation strategy, which translates nested data-parallel C++ into ordinary C++. Extracting the potential parallelism in nested 'foreach' constructs is called 'flattening' nested parallelism. We show how to flatten 'foreach' constructs using a simple program transformation. Our prototype system produces vector code which has been successfully run on workstations, a CM-2, and a CM-5.

Parallel computation for biological sequence comparison: comparing a portable model to the native model for the Intel Hypercube.

PubMed Central

Nadkarni, P. M.; Miller, P. L.

1991-01-01

A parallel program for inter-database sequence comparison was developed on the Intel Hypercube using two models of parallel programming. One version was built using machine-specific Hypercube parallel programming commands. The other version was built using Linda, a machine-independent parallel programming language. The two versions of the program provide a case study comparing these two approaches to parallelization in an important biological application area. Benchmark tests with both programs gave comparable results with a small number of processors. As the number of processors was increased, the Linda version was somewhat less efficient. The Linda version was also run without change on Network Linda, a virtual parallel machine running on a network of desktop workstations. PMID:1807632

Can beneficial ends justify lying? Neural responses to the passive reception of lies and truth-telling with beneficial and harmful monetary outcomes.

PubMed

Yin, Lijun; Weber, Bernd

2016-03-01

Can beneficial ends justify morally questionable means? To investigate how monetary outcomes influence the neural responses to lying, we used a modified, cheap talk sender-receiver game in which participants were the direct recipients of lies and truthful statements resulting in either beneficial or harmful monetary outcomes. Both truth-telling (vs lying) as well as beneficial (vs harmful) outcomes elicited higher activity in the nucleus accumbens. Lying (vs truth-telling) elicited higher activity in the supplementary motor area, right inferior frontal gyrus, superior temporal sulcus and left anterior insula. Moreover, the significant interaction effect was found in the left amygdala, which showed that the monetary outcomes modulated the neural activity in the left amygdala only when truth-telling rather than lying. Our study identified a neural network associated with the reception of lies and truth, including the regions linked to the reward process, recognition and emotional experiences of being treated (dis)honestly. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Parallel discrete event simulation: A shared memory approach

NASA Technical Reports Server (NTRS)

Reed, Daniel A.; Malony, Allen D.; Mccredie, Bradley D.

1987-01-01

With traditional event list techniques, evaluating a detailed discrete event simulation model can often require hours or even days of computation time. Parallel simulation mimics the interacting servers and queues of a real system by assigning each simulated entity to a processor. By eliminating the event list and maintaining only sufficient synchronization to insure causality, parallel simulation can potentially provide speedups that are linear in the number of processors. A set of shared memory experiments is presented using the Chandy-Misra distributed simulation algorithm to simulate networks of queues. Parameters 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.

The Portals 4.0 network programming interface.

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

Barrett, Brian W.; Brightwell, Ronald Brian; Pedretti, Kevin

2012-11-01

This report presents a specification for the Portals 4.0 network programming interface. Portals 4.0 is intended to allow scalable, high-performance network communication between nodes of a parallel computing system. Portals 4.0 is well suited to massively parallel processing and embedded systems. Portals 4.0 represents an adaption of the data movement layer developed for massively parallel processing platforms, such as the 4500-node Intel TeraFLOPS machine. Sandias Cplant cluster project motivated the development of Version 3.0, which was later extended to Version 3.3 as part of the Cray Red Storm machine and XT line. Version 4.0 is targeted to the next generationmore » of machines employing advanced network interface architectures that support enhanced offload capabilities.« less

Learning To Be Heard: Organization, Power and Literacy.

ERIC Educational Resources Information Center

Heaney, Thomas W.

The principal failure of attempts to reduce illiteracy in the United States lies in the conceptualization of the problem to which literacy is the solution and in an underfinanced practice that parallels dominant educational institutions, emphasizing the service of individuals. Adult education plays a critical role in liberatory action. Although…

Floodplain restoration with flood control: fish habitat value of levee borrow pits

USDA-ARS?s Scientific Manuscript database

Earthen flood control levees are often built using soil excavated from borrow pits lying parallel to and riverward of the finished levee. After construction, these pits can provide valuable floodplain habitats, and their value is well established along corridors of larger rivers. However, levee bo...

A parallel implementation of the network identification by multiple regression (NIR) algorithm to reverse-engineer regulatory gene networks.

PubMed

Gregoretti, Francesco; Belcastro, Vincenzo; di Bernardo, Diego; Oliva, Gennaro

2010-04-21

The reverse engineering of gene regulatory networks using gene expression profile data has become crucial to gain novel biological knowledge. Large amounts of data that need to be analyzed are currently being produced due to advances in microarray technologies. Using current reverse engineering algorithms to analyze large data sets can be very computational-intensive. These emerging computational requirements can be met using parallel computing techniques. It has been shown that the Network Identification by multiple Regression (NIR) algorithm performs better than the other ready-to-use reverse engineering software. However it cannot be used with large networks with thousands of nodes--as is the case in biological networks--due to the high time and space complexity. In this work we overcome this limitation by designing and developing a parallel version of the NIR algorithm. The new implementation of the algorithm reaches a very good accuracy even for large gene networks, improving our understanding of the gene regulatory networks that is crucial for a wide range of biomedical applications.

Deep-learning networks and the functional architecture of executive control.

PubMed

Cooper, Richard P

2017-01-01

Lake et al. underrate both the promise and the limitations of contemporary deep learning techniques. The promise lies in combining those techniques with broad multisensory training as experienced by infants and children. The limitations lie in the need for such systems to possess functional subsystems that generate, monitor, and switch goals and strategies in the absence of human intervention.

A Systems Approach to Scalable Transportation Network Modeling

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

Perumalla, Kalyan S

2006-01-01

Emerging needs in transportation network modeling and simulation are raising new challenges with respect to scal-ability of network size and vehicular traffic intensity, speed of simulation for simulation-based optimization, and fidel-ity of vehicular behavior for accurate capture of event phe-nomena. Parallel execution is warranted to sustain the re-quired detail, size and speed. However, few parallel simulators exist for such applications, partly due to the challenges underlying their development. Moreover, many simulators are based on time-stepped models, which can be computationally inefficient for the purposes of modeling evacuation traffic. Here an approach is presented to de-signing a simulator with memory andmore » speed efficiency as the goals from the outset, and, specifically, scalability via parallel execution. The design makes use of discrete event modeling techniques as well as parallel simulation meth-ods. Our simulator, called SCATTER, is being developed, incorporating such design considerations. Preliminary per-formance results are presented on benchmark road net-works, showing scalability to one million vehicles simu-lated on one processor.« less

ANNarchy: a code generation approach to neural simulations on parallel hardware

PubMed Central

Vitay, Julien; Dinkelbach, Helge Ü.; Hamker, Fred H.

2015-01-01

Many modern neural simulators focus on the simulation of networks of spiking neurons on parallel hardware. Another important framework in computational neuroscience, rate-coded neural networks, is mostly difficult or impossible to implement using these simulators. We present here the ANNarchy (Artificial Neural Networks architect) neural simulator, which allows to easily define and simulate rate-coded and spiking networks, as well as combinations of both. The interface in Python has been designed to be close to the PyNN interface, while the definition of neuron and synapse models can be specified using an equation-oriented mathematical description similar to the Brian neural simulator. This information is used to generate C++ code that will efficiently perform the simulation on the chosen parallel hardware (multi-core system or graphical processing unit). Several numerical methods are available to transform ordinary differential equations into an efficient C++code. We compare the parallel performance of the simulator to existing solutions. PMID:26283957

IPv6 Tactical Network Management

DTIC Science & Technology

2009-09-01

is transitioning to IPv6 networks. While the benefits provided by IPv6 are numerous, its challenges lie in managing a network on the scale...operability, and usability in a tactical network is under way. New challenges are also presented by the need to integrate into the IPv6 segment new...Accessing this information also presents challenges . Feasibility studies are conducted to show that, for these devices, the IPv6 domain is at least

Real-world hydrologic assessment of a fully-distributed hydrological model in a parallel computing environment

NASA Astrophysics Data System (ADS)

Vivoni, Enrique R.; Mascaro, Giuseppe; Mniszewski, Susan; Fasel, Patricia; Springer, Everett P.; Ivanov, Valeriy Y.; Bras, Rafael L.

2011-10-01

SummaryA major challenge in the use of fully-distributed hydrologic models has been the lack of computational capabilities for high-resolution, long-term simulations in large river basins. In this study, we present the parallel model implementation and real-world hydrologic assessment of the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS). Our parallelization approach is based on the decomposition of a complex watershed using the channel network as a directed graph. The resulting sub-basin partitioning divides effort among processors and handles hydrologic exchanges across boundaries. Through numerical experiments in a set of nested basins, we quantify parallel performance relative to serial runs for a range of processors, simulation complexities and lengths, and sub-basin partitioning methods, while accounting for inter-run variability on a parallel computing system. In contrast to serial simulations, the parallel model speed-up depends on the variability of hydrologic processes. Load balancing significantly improves parallel speed-up with proportionally faster runs as simulation complexity (domain resolution and channel network extent) increases. The best strategy for large river basins is to combine a balanced partitioning with an extended channel network, with potential savings through a lower TIN resolution. Based on these advances, a wider range of applications for fully-distributed hydrologic models are now possible. This is illustrated through a set of ensemble forecasts that account for precipitation uncertainty derived from a statistical downscaling model.

Modeling of Arylamide Helix Mimetics in the p53 Peptide Binding Site of hDM2 Suggests Parallel and Anti-Parallel Conformations Are Both Stable

PubMed Central

Fuller, Jonathan C.; Jackson, Richard M.; Edwards, Thomas A.; Wilson, Andrew J.; Shirts, Michael R.

2012-01-01

The design of novel α-helix mimetic inhibitors of protein-protein interactions is of interest to pharmaceuticals and chemical genetics researchers as these inhibitors provide a chemical scaffold presenting side chains in the same geometry as an α-helix. This conformational arrangement allows the design of high affinity inhibitors mimicking known peptide sequences binding specific protein substrates. We show that GAFF and AutoDock potentials do not properly capture the conformational preferences of α-helix mimetics based on arylamide oligomers and identify alternate parameters matching solution NMR data and suitable for molecular dynamics simulation of arylamide compounds. Results from both docking and molecular dynamics simulations are consistent with the arylamides binding in the p53 peptide binding pocket. Simulations of arylamides in the p53 binding pocket of hDM2 are consistent with binding, exhibiting similar structural dynamics in the pocket as simulations of known hDM2 binders Nutlin-2 and a benzodiazepinedione compound. Arylamide conformations converge towards the same region of the binding pocket on the 20 ns time scale, and most, though not all dihedrals in the binding pocket are well sampled on this timescale. We show that there are two putative classes of binding modes for arylamide compounds supported equally by the modeling evidence. In the first, the arylamide compound lies parallel to the observed p53 helix. In the second class, not previously identified or proposed, the arylamide compound lies anti-parallel to the p53 helix. PMID:22916232

Topology-dependent density optima for efficient simultaneous network exploration

NASA Astrophysics Data System (ADS)

Wilson, Daniel B.; Baker, Ruth E.; Woodhouse, Francis G.

2018-06-01

A random search process in a networked environment is governed by the time it takes to visit every node, termed the cover time. Often, a networked process does not proceed in isolation but competes with many instances of itself within the same environment. A key unanswered question is how to optimize this process: How many concurrent searchers can a topology support before the benefits of parallelism are outweighed by competition for space? Here, we introduce the searcher-averaged parallel cover time (APCT) to quantify these economies of scale. We show that the APCT of the networked symmetric exclusion process is optimized at a searcher density that is well predicted by the spectral gap. Furthermore, we find that nonequilibrium processes, realized through the addition of bias, can support significantly increased density optima. Our results suggest alternative hybrid strategies of serial and parallel search for efficient information gathering in social interaction and biological transport networks.

Introduction to a system for implementing neural net connections on SIMD architectures

NASA Technical Reports Server (NTRS)

Tomboulian, Sherryl

1988-01-01

Neural networks have attracted much interest recently, and using parallel architectures to simulate neural networks is a natural and necessary application. The SIMD model of parallel computation is chosen, because systems of this type can be built with large numbers of processing elements. However, such systems are not naturally suited to generalized communication. A method is proposed that allows an implementation of neural network connections on massively parallel SIMD architectures. The key to this system is an algorithm permitting the formation of arbitrary connections between the neurons. A feature is the ability to add new connections quickly. It also has error recovery ability and is robust over a variety of network topologies. Simulations of the general connection system, and its implementation on the Connection Machine, indicate that the time and space requirements are proportional to the product of the average number of connections per neuron and the diameter of the interconnection network.

Introduction to a system for implementing neural net connections on SIMD architectures

NASA Technical Reports Server (NTRS)

Tomboulian, Sherryl

1988-01-01

Neural networks have attracted much interest recently, and using parallel architectures to simulate neural networks is a natural and necessary application. The SIMD model of parallel computation is chosen, because systems of this type can be built with large numbers of processing elements. However, such systems are not naturally suited to generalized elements. A method is proposed that allows an implementation of neural network connections on massively parallel SIMD architectures. The key to this system is an algorithm permitting the formation of arbitrary connections between the neurons. A feature is the ability to add new connections quickly. It also has error recovery ability and is robust over a variety of network topologies. Simulations of the general connection system, and its implementation on the Connection Machine, indicate that the time and space requirements are proportional to the product of the average number of connections per neuron and the diameter of the interconnection network.

Broadcasting collective operation contributions throughout a parallel computer

DOEpatents

Faraj, Ahmad [Rochester, MN

2012-02-21

Methods, systems, and products are disclosed for broadcasting collective operation contributions throughout a parallel computer. The parallel computer includes a plurality of compute nodes connected together through a data communications network. Each compute node has a plurality of processors for use in collective parallel operations on the parallel computer. Broadcasting collective operation contributions throughout a parallel computer according to embodiments of the present invention includes: transmitting, by each processor on each compute node, that processor's collective operation contribution to the other processors on that compute node using intra-node communications; and transmitting on a designated network link, by each processor on each compute node according to a serial processor transmission sequence, that processor's collective operation contribution to the other processors on the other compute nodes using inter-node communications.

Clustered Numerical Data Analysis Using Markov Lie Monoid Based Networks

NASA Astrophysics Data System (ADS)

Johnson, Joseph

2016-03-01

We have designed and build an optimal numerical standardization algorithm that links numerical values with their associated units, error level, and defining metadata thus supporting automated data exchange and new levels of artificial intelligence (AI). The software manages all dimensional and error analysis and computational tracing. Tables of entities verses properties of these generalized numbers (called ``metanumbers'') support a transformation of each table into a network among the entities and another network among their properties where the network connection matrix is based upon a proximity metric between the two items. We previously proved that every network is isomorphic to the Lie algebra that generates continuous Markov transformations. We have also shown that the eigenvectors of these Markov matrices provide an agnostic clustering of the underlying patterns. We will present this methodology and show how our new work on conversion of scientific numerical data through this process can reveal underlying information clusters ordered by the eigenvalues. We will also show how the linking of clusters from different tables can be used to form a ``supernet'' of all numerical information supporting new initiatives in AI.

Parallel replica dynamics method for bistable stochastic reaction networks: Simulation and sensitivity analysis

NASA Astrophysics Data System (ADS)

Wang, Ting; Plecháč, Petr

2017-12-01

Stochastic reaction networks that exhibit bistable behavior are common in systems biology, materials science, and catalysis. Sampling of stationary distributions is crucial for understanding and characterizing the long-time dynamics of bistable stochastic dynamical systems. However, simulations are often hindered by the insufficient sampling of rare transitions between the two metastable regions. In this paper, we apply the parallel replica method for a continuous time Markov chain in order to improve sampling of the stationary distribution in bistable stochastic reaction networks. The proposed method uses parallel computing to accelerate the sampling of rare transitions. Furthermore, it can be combined with the path-space information bounds for parametric sensitivity analysis. With the proposed methodology, we study three bistable biological networks: the Schlögl model, the genetic switch network, and the enzymatic futile cycle network. We demonstrate the algorithmic speedup achieved in these numerical benchmarks. More significant acceleration is expected when multi-core or graphics processing unit computer architectures and programming tools such as CUDA are employed.

Global interrupt and barrier networks

DOEpatents

Blumrich, Matthias A.; Chen, Dong; Coteus, Paul W.; Gara, Alan G.; Giampapa, Mark E; Heidelberger, Philip; Kopcsay, Gerard V.; Steinmacher-Burow, Burkhard D.; Takken, Todd E.

2008-10-28

A system and method for generating global asynchronous signals in a computing structure. Particularly, a global interrupt and barrier network is implemented that implements logic for generating global interrupt and barrier signals for controlling global asynchronous operations performed by processing elements at selected processing nodes of a computing structure in accordance with a processing algorithm; and includes the physical interconnecting of the processing nodes for communicating the global interrupt and barrier signals to the elements via low-latency paths. The global asynchronous signals respectively initiate interrupt and barrier operations at the processing nodes at times selected for optimizing performance of the processing algorithms. In one embodiment, the global interrupt and barrier network is implemented in a scalable, massively parallel supercomputing device structure comprising a plurality of processing nodes interconnected by multiple independent networks, with each node including one or more processing elements for performing computation or communication activity as required when performing parallel algorithm operations. One multiple independent network includes a global tree network for enabling high-speed global tree communications among global tree network nodes or sub-trees thereof. The global interrupt and barrier network may operate in parallel with the global tree network for providing global asynchronous sideband signals.

The portals 4.0.1 network programming interface.

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

Barrett, Brian W.; Brightwell, Ronald Brian; Pedretti, Kevin

2013-04-01

This report presents a specification for the Portals 4.0 network programming interface. Portals 4.0 is intended to allow scalable, high-performance network communication between nodes of a parallel computing system. Portals 4.0 is well suited to massively parallel processing and embedded systems. Portals 4.0 represents an adaption of the data movement layer developed for massively parallel processing platforms, such as the 4500-node Intel TeraFLOPS machine. Sandias Cplant cluster project motivated the development of Version 3.0, which was later extended to Version 3.3 as part of the Cray Red Storm machine and XT line. Version 4.0 is targeted to the next generationmore » of machines employing advanced network interface architectures that support enhanced offload capabilities. 3« less

Sentence alignment using feed forward neural network.

PubMed

Fattah, Mohamed Abdel; Ren, Fuji; Kuroiwa, Shingo

2006-12-01

Parallel corpora have become an essential resource for work in multi lingual natural language processing. However, sentence aligned parallel corpora are more efficient than non-aligned parallel corpora for cross language information retrieval and machine translation applications. In this paper, we present a new approach to align sentences in bilingual parallel corpora based on feed forward neural network classifier. A feature parameter vector is extracted from the text pair under consideration. This vector contains text features such as length, punctuate score, and cognate score values. A set of manually prepared training data has been assigned to train the feed forward neural network. Another set of data was used for testing. Using this new approach, we could achieve an error reduction of 60% over length based approach when applied on English-Arabic parallel documents. Moreover this new approach is valid for any language pair and it is quite flexible approach since the feature parameter vector may contain more/less or different features than that we used in our system such as lexical match feature.

Identifying messaging completion in a parallel computer by checking for change in message received and transmitted count at each node

DOEpatents

Archer, Charles J [Rochester, MN; Hardwick, Camesha R [Fayetteville, NC; McCarthy, Patrick J [Rochester, MN; Wallenfelt, Brian P [Eden Prairie, MN

2009-06-23

Methods, parallel computers, and products are provided for identifying messaging completion on a parallel computer. The parallel computer includes a plurality of compute nodes, the compute nodes coupled for data communications by at least two independent data communications networks including a binary tree data communications network optimal for collective operations that organizes the nodes as a tree and a torus data communications network optimal for point to point operations that organizes the nodes as a torus. Embodiments include reading all counters at each node of the torus data communications network; calculating at each node a current node value in dependence upon the values read from the counters at each node; and determining for all nodes whether the current node value for each node is the same as a previously calculated node value for each node. If the current node is the same as the previously calculated node value for all nodes of the torus data communications network, embodiments include determining that messaging is complete and if the current node is not the same as the previously calculated node value for all nodes of the torus data communications network, embodiments include determining that messaging is currently incomplete.

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.

Experimental implementation of array-compressed parallel transmission at 7 tesla.

PubMed

Yan, Xinqiang; Cao, Zhipeng; Grissom, William A

2016-06-01

To implement and validate a hardware-based array-compressed parallel transmission (acpTx) system. In array-compressed parallel transmission, a small number of transmit channels drive a larger number of transmit coils, which are connected via an array compression network that implements optimized coil-to-channel combinations. A two channel-to-eight coil array compression network was developed using power splitters, attenuators and phase shifters, and a simulation was performed to investigate the effects of coil coupling on power dissipation in a simplified network. An eight coil transmit array was constructed using induced current elimination decoupling, and the coil and network were validated in benchtop measurements, B1+ mapping scans, and an accelerated spiral excitation experiment. The developed attenuators came within 0.08 dB of the desired attenuations, and reflection coefficients were -22 dB or better. The simulation demonstrated that up to 3× more power was dissipated in the network when coils were poorly isolated (-9.6 dB), versus well-isolated (-31 dB). Compared to split circularly-polarized coil combinations, the additional degrees of freedom provided by the array compression network led to 54% lower squared excitation error in the spiral experiment. Array-compressed parallel transmission was successfully implemented in a hardware system. Further work is needed to develop remote network tuning and to minimize network power dissipation. Magn Reson Med 75:2545-2552, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Method and apparatus for routing data in an inter-nodal communications lattice of a massively parallel computer system by dynamic global mapping of contended links

DOEpatents

Archer, Charles Jens [Rochester, MN; Musselman, Roy Glenn [Rochester, MN; Peters, Amanda [Rochester, MN; Pinnow, Kurt Walter [Rochester, MN; Swartz, Brent Allen [Chippewa Falls, WI; Wallenfelt, Brian Paul [Eden Prairie, MN

2011-10-04

A massively parallel nodal computer system periodically collects and broadcasts usage data for an internal communications network. A node sending data over the network makes a global routing determination using the network usage data. Preferably, network usage data comprises an N-bit usage value for each output buffer associated with a network link. An optimum routing is determined by summing the N-bit values associated with each link through which a data packet must pass, and comparing the sums associated with different possible routes.

Method and apparatus for routing data in an inter-nodal communications lattice of a massively parallel computer system by dynamically adjusting local routing strategies

DOEpatents

Archer, Charles Jens; Musselman, Roy Glenn; Peters, Amanda; Pinnow, Kurt Walter; Swartz, Brent Allen; Wallenfelt, Brian Paul

2010-03-16

A massively parallel computer system contains an inter-nodal communications network of node-to-node links. Each node implements a respective routing strategy for routing data through the network, the routing strategies not necessarily being the same in every node. The routing strategies implemented in the nodes are dynamically adjusted during application execution to shift network workload as required. Preferably, adjustment of routing policies in selective nodes is performed at synchronization points. The network may be dynamically monitored, and routing strategies adjusted according to detected network conditions.

Visualizing Parallel Computer System Performance

NASA Technical Reports Server (NTRS)

Malony, Allen D.; Reed, Daniel A.

1988-01-01

Parallel computer systems are among the most complex of man's creations, making satisfactory performance characterization difficult. Despite this complexity, there are strong, indeed, almost irresistible, incentives to quantify parallel system performance using a single metric. The fallacy lies in succumbing to such temptations. A complete performance characterization requires not only an analysis of the system's constituent levels, it also requires both static and dynamic characterizations. Static or average behavior analysis may mask transients that dramatically alter system performance. Although the human visual system is remarkedly adept at interpreting and identifying anomalies in false color data, the importance of dynamic, visual scientific data presentation has only recently been recognized Large, complex parallel system pose equally vexing performance interpretation problems. Data from hardware and software performance monitors must be presented in ways that emphasize important events while eluding irrelevant details. Design approaches and tools for performance visualization are the subject of this paper.

A parallel adaptive quantum genetic algorithm for the controllability of arbitrary networks.

PubMed

Li, Yuhong; Gong, Guanghong; Li, Ni

2018-01-01

In this paper, we propose a novel algorithm-parallel adaptive quantum genetic algorithm-which can rapidly determine the minimum control nodes of arbitrary networks with both control nodes and state nodes. The corresponding network can be fully controlled with the obtained control scheme. We transformed the network controllability issue into a combinational optimization problem based on the Popov-Belevitch-Hautus rank condition. A set of canonical networks and a list of real-world networks were experimented. Comparison results demonstrated that the algorithm was more ideal to optimize the controllability of networks, especially those larger-size networks. We demonstrated subsequently that there were links between the optimal control nodes and some network statistical characteristics. The proposed algorithm provides an effective approach to improve the controllability optimization of large networks or even extra-large networks with hundreds of thousands nodes.

Towards an emergent model of solitonic particles from non-trivial vacuum structure

NASA Astrophysics Data System (ADS)

Gillard, Adam B.; Gresnigt, Niels G.

2017-12-01

We motivate and introduce what we refer to as the principles of Lie-stability and Hopf-stability and see what the physical theories must look like. Lie-stability is needed on the classical side and Hopf-stability is needed on the quantum side. We implement these two principles together with Lie-deformations consistent with basic constraints on the classical kinematical variables to arrive at the form of a theory that identifies standard model fermions with quantum solitonic trefoil knotted flux tubes which emerge from a flux tube vacuum network. Moreover, twisted unknot fluxtubes form natural dark matter candidates

Teaching Your Gymnasts to Swing. Biomechanics in Plain Talk for the Novice Coach.

ERIC Educational Resources Information Center

Sim, Laura J.

1985-01-01

The key to successful uneven parallel bar routines lies in the rhythm and continuity of movement which is ensured through the element of swing. Diagrams are offered to help illustrate how the biomechanical principles of torque and momentum are essential to learning and developing the mechanics of swing. (DF)

Concealed hinge permits flush mounting of doors and hatches

NASA Technical Reports Server (NTRS)

Holman, E. V.

1966-01-01

Hinge assembly permits flush mounting of doors and hatches of considerable thickness so that the axis of instant rotation, produced by the hinge, lies outside the panel surface and beyond the perimeter adjacent to the hinge. In operation, motion of the assembly is initially parallel, changing to angular after clearing the panel perimeter.

A Parallel Trade Study Architecture for Design Optimization of Complex Systems

NASA Technical Reports Server (NTRS)

Kim, Hongman; Mullins, James; Ragon, Scott; Soremekun, Grant; Sobieszczanski-Sobieski, Jaroslaw

2005-01-01

Design of a successful product requires evaluating many design alternatives in a limited design cycle time. This can be achieved through leveraging design space exploration tools and available computing resources on the network. This paper presents a parallel trade study architecture to integrate trade study clients and computing resources on a network using Web services. The parallel trade study solution is demonstrated to accelerate design of experiments, genetic algorithm optimization, and a cost as an independent variable (CAIV) study for a space system application.

A new transport phenomenon in nanostructures: a mesoscopic analog of the Braess paradox encountered in road networks

PubMed Central

2012-01-01

The Braess paradox, known for traffic and other classical networks, lies in the fact that adding a new route to a congested network in an attempt to relieve congestion can degrade counterintuitively the overall network performance. Recently, we have extended the concept of the Braess paradox to semiconductor mesoscopic networks, whose transport properties are governed by quantum physics. In this paper, we demonstrate theoretically that, alike in classical systems, congestion plays a key role in the occurrence of a Braess paradox in mesoscopic networks. PMID:22913510

The orientation of iron–sulphur clusters in membrane multilayers prepared from aerobically-grown Escherichia coli K12 and a cytochrome-deficient mutant

PubMed Central

Blum, Haywood; Poole, Robert K.; Ohnishi, Tomoko

1980-01-01

1. Membrane particles prepared from ultrasonically-disrupted, aerobically-grown Escherichia coli were centrifuged on to a plastic film that was supported perpendicular to the centrifugal field to yield oriented membrane multilayers. In such preparations, there is a high degree of orientation of the planes of the membranes such that they lie parallel to each other and to the supporting film. 2. When dithionite- or succinate-reduced multilayers are rotated in the magnetic field of an e.p.r. spectrometer, about an axis lying in the membrane plane, angular-dependent signals from an iron–sulphur cluster at gx=1.92, gy=1.93 and gz=2.02 are seen. The g=1.93 signal has maximal amplitude when the plane of the multilayer is perpendicular to the magnetic field. Conversely, the g=2.02 signal is maximal when the plane of the multilayer is parallel with the magnetic field. 3. Computer simulations of the experimental data show that the cluster lies in the cytoplasmic membrane with the gy axis perpendicular to the membrane plane and with the gx and gz axes lying in the membrane plane. 4. In partially-oxidized multilayers, a signal resembling the mitochondrial high-potential iron–sulphur protein (Hipip) is seen whose gz=2.02 axis may be deduced as lying perpendicular to the membrane plane. 5. Appropriate choice of sample temperature and receiver gain reveals two further signals in partially-reduced multilayers: a g=2.09 signal arises from a cluster with its gz axis in the membrane plane, whereas a g=2.04 signal is from a cluster with the gz axis lying along the membrane normal. 6. Membrane particles from a glucose-grown, haem-deficient mutant contain dramatically-lowered levels of cytochromes and exhibit, in addition to the iron–sulphur clusters seen in the parental strain, a major signal at g=1.90. 7. Only the latter may be demonstrated to be oriented in multilayer preparations from the mutant. 8. Comparisons are drawn between the orientations of the iron–sulphur proteins in the cytoplasmic membrane of E. coli and those in mitochondrial membranes. The effects of diminished cytochrome content on the properties of the iron–sulphur proteins are discussed. PMID:6258566

trans-Bis[4-amino-3,5-bis­(2-pyrid­yl)-4H-1,2,4-triazole-κN 3]diaqua­cobalt(II) bis­(3-carb­oxy-5-nitro­benzoate)

PubMed Central

Wang, Xi; Shao, Chun-Fu; Li, Cheng-Peng

2011-01-01

The title complex, [Co(C12H10N6)2(H2O)2](C8H4NO6)2, is composed of a mononuclear cobalt(II) cation and two 3-carb­oxy-5-nitro­benzoate anions for charge balance. In the cation, the CoII atom is six-coordinated in a distorted octa­hedral geometry. It bonds to two O atoms of two water mol­ecules, and two pairs of N atoms from two 4-amino-3,5-bis­(2-pyrid­yl)-4H-1,2,4-triazole mol­ecules, which behave as bidentate chelating ligands. There are intra­molecular N—H⋯N hydrogen bonds in the cation. In the crystal, there are a number of inter­molecular N—H⋯O and O—H⋯O hydrogen bonds, as well as inter­molecular π–π stacking inter­actions [centroid–centroid distances = 3.657 (2) and 3.847 (2) Å], that link the mol­ecules into two-dimensional networks lying parallel to the ab plane. The presence of C—H⋯O inter­actions leads to the formation of a three-dimensional network. PMID:22058688

Collective network for computer structures

DOEpatents

Blumrich, Matthias A; Coteus, Paul W; Chen, Dong; Gara, Alan; Giampapa, Mark E; Heidelberger, Philip; Hoenicke, Dirk; Takken, Todd E; Steinmacher-Burow, Burkhard D; Vranas, Pavlos M

2014-01-07

A system and method for enabling high-speed, low-latency global collective communications among interconnected processing nodes. The global collective network optimally enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices are included that interconnect the nodes of the network via links to facilitate performance of low-latency global processing operations at nodes of the virtual network. The global collective network may be configured to provide global barrier and interrupt functionality in asynchronous or synchronized manner. When implemented in a massively-parallel supercomputing structure, the global collective network is physically and logically partitionable according to the needs of a processing algorithm.

Collective network for computer structures

DOEpatents

Blumrich, Matthias A [Ridgefield, CT; Coteus, Paul W [Yorktown Heights, NY; Chen, Dong [Croton On Hudson, NY; Gara, Alan [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Hoenicke, Dirk [Ossining, NY; Takken, Todd E [Brewster, NY; Steinmacher-Burow, Burkhard D [Wernau, DE; Vranas, Pavlos M [Bedford Hills, NY

2011-08-16

A system and method for enabling high-speed, low-latency global collective communications among interconnected processing nodes. The global collective network optimally enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices ate included that interconnect the nodes of the network via links to facilitate performance of low-latency global processing operations at nodes of the virtual network and class structures. The global collective network may be configured to provide global barrier and interrupt functionality in asynchronous or synchronized manner. When implemented in a massively-parallel supercomputing structure, the global collective network is physically and logically partitionable according to needs of a processing algorithm.

Fencing network direct memory access data transfers in a parallel active messaging interface of a parallel computer

DOEpatents

Blocksome, Michael A.; Mamidala, Amith R.

2015-07-07

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 a deterministic data communications network 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 the deterministic data communications network; 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.

Fencing network direct memory access data transfers in a parallel active messaging interface of a parallel computer

DOEpatents

Blocksome, Michael A.; Mamidala, Amith R.

2015-07-14

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 a deterministic data communications network 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 the deterministic data communications network; 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.

Project CONVERGE: Impacts of local oceanographic processes on Adélie penguin foraging ecology

NASA Astrophysics Data System (ADS)

Kohut, J. T.; Bernard, K. S.; Fraser, W.; Oliver, M. J.; Statscewich, H.; Patterson-Fraser, D.; Winsor, P.; Cimino, M. A.; Miles, T. N.

2016-02-01

During the austral summer of 2014-2015, project CONVERGE deployed a multi-platform network to sample the Adélie penguin foraging hotspot associated with Palmer Deep Canyon along the Western Antarctic Peninsula. The focus of CONVERGE was to assess the impact of prey-concentrating ocean circulation dynamics on Adélie penguin foraging behavior. Food web links between phytoplankton and zooplankton abundance and penguin behavior were examined to better understand the within-season variability in Adélie foraging ecology. Since the High Frequency Radar (HFR) network installation in November 2014, the radial component current data from each of the three sites were combined to provide a high resolution (0.5 km) surface velocity maps. These hourly maps have revealed an incredibly dynamic system with strong fronts and frequent eddies extending across the Palmer Deep foraging area. A coordinated fleet of underwater gliders were used in concert with the HFR fields to sample the hydrography and phytoplankton distributions associated with convergent and divergent features. Three gliders mapped the along and across canyon variability of the hydrography, chlorophyll fluorescence and acoustic backscatter in the context of the observed surface currents and simultaneous penguin tracks. This presentation will highlight these synchronized measures of the food web in the context of the observed HFR fronts and eddies. The location and persistence of these features coupled with ecological sampling through the food web offer an unprecedented view of the Palmer Deep ecosystem. Specific examples will highlight how the vertical structure of the water column beneath the surface features stack the primary and secondary producers relative to observed penguin foraging behavior. The coupling from the physics through the food web as observed by our multi-platform network gives strong evidence for the critical role that distribution patterns of lower trophic levels have on Adélie foraging.

A Humanities Network Considers What Lies Beyond E-Mail.

ERIC Educational Resources Information Center

Guernsey, Lisa

1997-01-01

H-NET (Humanities and Social Sciences OnLine) is a new, rapidly expanding international online network of scholars that was established to increase electronic mail communication among individuals. Currently, the program is devoting more attention to World Wide Web-related projects providing information and reference sources. Internal conflict…

Resource Management in Tactical Military Networks

DTIC Science & Technology

2006-12-01

FGAN FORSCHUNGSINSTITUT FÜR KOMMUNIKATION, INFORMATIONSVERARBEITUNG UND ERGONOMIE KIEKOMMUNIKATION Resource Management in Tactical Military Networks...Martin Lies, Peter Sevenich, Christoph Karg, Christoph Barz Nr: 2 FGAN FORSCHUNGSINSTITUT FÜR KOMMUNIKATION, INFORMATIONSVERARBEITUNG UND ERGONOMIE ...Communication with IPSec in Tunnelmode Nr: 3 FGAN FORSCHUNGSINSTITUT FÜR KOMMUNIKATION, INFORMATIONSVERARBEITUNG UND ERGONOMIE KIEKOMMUNIKATION IPSec in

Uncertainty analysis of neural network based flood forecasting models: An ensemble based approach for constructing prediction interval

NASA Astrophysics Data System (ADS)

Kasiviswanathan, K.; Sudheer, K.

2013-05-01

Artificial neural network (ANN) based hydrologic models have gained lot of attention among water resources engineers and scientists, owing to their potential for accurate prediction of flood flows as compared to conceptual or physics based hydrologic models. The ANN approximates the non-linear functional relationship between the complex hydrologic variables in arriving at the river flow forecast values. Despite a large number of applications, there is still some criticism that ANN's point prediction lacks in reliability since the uncertainty of predictions are not quantified, and it limits its use in practical applications. A major concern in application of traditional uncertainty analysis techniques on neural network framework is its parallel computing architecture with large degrees of freedom, which makes the uncertainty assessment a challenging task. Very limited studies have considered assessment of predictive uncertainty of ANN based hydrologic models. In this study, a novel method is proposed that help construct the prediction interval of ANN flood forecasting model during calibration itself. The method is designed to have two stages of optimization during calibration: at stage 1, the ANN model is trained with genetic algorithm (GA) to obtain optimal set of weights and biases vector, and during stage 2, the optimal variability of ANN parameters (obtained in stage 1) is identified so as to create an ensemble of predictions. During the 2nd stage, the optimization is performed with multiple objectives, (i) minimum residual variance for the ensemble mean, (ii) maximum measured data points to fall within the estimated prediction interval and (iii) minimum width of prediction interval. The method is illustrated using a real world case study of an Indian basin. The method was able to produce an ensemble that has an average prediction interval width of 23.03 m3/s, with 97.17% of the total validation data points (measured) lying within the interval. The derived prediction interval for a selected hydrograph in the validation data set is presented in Fig 1. It is noted that most of the observed flows lie within the constructed prediction interval, and therefore provides information about the uncertainty of the prediction. One specific advantage of the method is that when ensemble mean value is considered as a forecast, the peak flows are predicted with improved accuracy by this method compared to traditional single point forecasted ANNs. Fig. 1 Prediction Interval for selected hydrograph

Sequence stratigraphic re-interpretation of [open quotes]stray[close quotes] sandstones in the Cretaceous Mancos Shale, Book Cliffs, Utah: Implications for exploration models

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

Hampson, G.J.; Howell, J.A.; Flint, S.S.

1996-01-01

The Mancos Shale, Book Cliffs, eastern Utah, represents the open marine mudstones of the Cretaceous Western Interior Seaway and contains a number of detached sandstone bodies ([open quotes]Mancos B[close quotes]) which are located 30-150 km down depositional dip from contemporaneous highstand shoreline deposits in the Blackhawk Formation. Examination of these [open quotes]stray[close quotes] sandstones reveals that they do not represent deep water deposition, as previously supposed, but instead comprise three shallow marine facies associations; (1) tidally-influenced fluvial channel fills, (2) fluvially-dominated delta front successions and (3) low-energy shorelines. Tidally-influenced fluvial channel fills are commonly stacked into multistorey bodies at discretemore » stratigraphic levels, thereby defining incised valley fill (IVF) networks. Fluvially-dominated deltas are eroded into by, and lie at the down-dip terminations of, IVFs and are therefore interpreted as falling stage and lowstand shorelines. Low-energy shorelines are inferred to lie along strike from these deltas. The above shallow marine deposits have been mapped at five discrete stratigraphic horizons, which can be either traced or projected up-dip to previously-documented IVFs in the Blackhawk Formation. Their paleocurrents imply that falling stage and lowstand shoreline trends were sub-parallel to mapped highstand shorelines, although there is evidence for a perpendicular lowstand shoreline trend in the east of the study area. This facies and sequence stratigraphic re-interpretation enables predictive exploration modelling of subsurface [open quotes]Mancos B[close quotes] gas reservoir sandstones.« less

Sequence stratigraphic re-interpretation of {open_quotes}stray{close_quotes} sandstones in the Cretaceous Mancos Shale, Book Cliffs, Utah: Implications for exploration models

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

Hampson, G.J.; Howell, J.A.; Flint, S.S.

1996-12-31

The Mancos Shale, Book Cliffs, eastern Utah, represents the open marine mudstones of the Cretaceous Western Interior Seaway and contains a number of detached sandstone bodies ({open_quotes}Mancos B{close_quotes}) which are located 30-150 km down depositional dip from contemporaneous highstand shoreline deposits in the Blackhawk Formation. Examination of these {open_quotes}stray{close_quotes} sandstones reveals that they do not represent deep water deposition, as previously supposed, but instead comprise three shallow marine facies associations; (1) tidally-influenced fluvial channel fills, (2) fluvially-dominated delta front successions and (3) low-energy shorelines. Tidally-influenced fluvial channel fills are commonly stacked into multistorey bodies at discrete stratigraphic levels, thereby definingmore » incised valley fill (IVF) networks. Fluvially-dominated deltas are eroded into by, and lie at the down-dip terminations of, IVFs and are therefore interpreted as falling stage and lowstand shorelines. Low-energy shorelines are inferred to lie along strike from these deltas. The above shallow marine deposits have been mapped at five discrete stratigraphic horizons, which can be either traced or projected up-dip to previously-documented IVFs in the Blackhawk Formation. Their paleocurrents imply that falling stage and lowstand shoreline trends were sub-parallel to mapped highstand shorelines, although there is evidence for a perpendicular lowstand shoreline trend in the east of the study area. This facies and sequence stratigraphic re-interpretation enables predictive exploration modelling of subsurface {open_quotes}Mancos B{close_quotes} gas reservoir sandstones.« less

Analysis of multigrid methods on massively parallel computers: Architectural implications

NASA Technical Reports Server (NTRS)

Matheson, Lesley R.; Tarjan, Robert E.

1993-01-01

We study the potential performance of multigrid algorithms running on massively parallel computers with the intent of discovering whether presently envisioned machines will provide an efficient platform for such algorithms. We consider the domain parallel version of the standard V cycle algorithm on model problems, discretized using finite difference techniques in two and three dimensions on block structured grids of size 10(exp 6) and 10(exp 9), respectively. Our models of parallel computation were developed to reflect the computing characteristics of the current generation of massively parallel multicomputers. These models are based on an interconnection network of 256 to 16,384 message passing, 'workstation size' processors executing in an SPMD mode. The first model accomplishes interprocessor communications through a multistage permutation network. The communication cost is a logarithmic function which is similar to the costs in a variety of different topologies. The second model allows single stage communication costs only. Both models were designed with information provided by machine developers and utilize implementation derived parameters. With the medium grain parallelism of the current generation and the high fixed cost of an interprocessor communication, our analysis suggests an efficient implementation requires the machine to support the efficient transmission of long messages, (up to 1000 words) or the high initiation cost of a communication must be significantly reduced through an alternative optimization technique. Furthermore, with variable length message capability, our analysis suggests the low diameter multistage networks provide little or no advantage over a simple single stage communications network.

Glove-talk II - a neural-network interface which maps gestures to parallel formant speech synthesizer controls.

PubMed

Fels, S S; Hinton, G E

1997-01-01

Glove-Talk II is a system which translates hand gestures to speech through an adaptive interface. Hand gestures are mapped continuously to ten control parameters of a parallel formant speech synthesizer. The mapping allows the hand to act as an artificial vocal tract that produces speech in real time. This gives an unlimited vocabulary in addition to direct control of fundamental frequency and volume. Currently, the best version of Glove-Talk II uses several input devices, a parallel formant speech synthesizer, and three neural networks. The gesture-to-speech task is divided into vowel and consonant production by using a gating network to weight the outputs of a vowel and a consonant neural network. The gating network and the consonant network are trained with examples from the user. The vowel network implements a fixed user-defined relationship between hand position and vowel sound and does not require any training examples from the user. Volume, fundamental frequency, and stop consonants are produced with a fixed mapping from the input devices. With Glove-Talk II, the subject can speak slowly but with far more natural sounding pitch variations than a text-to-speech synthesizer.

Parallel NGO networks for HIV control: risks and opportunities for NGO contracting.

PubMed

Zaidi, Shehla; Gul, Xaher; Nishtar, Noureen Aleem

2012-12-27

Policy measures for preventive and promotive services are increasingly reliant on contracting of NGOs. Contracting is a neo-liberal response relying on open market competition for service delivery tenders. In contracting of health services a common assumption is a monolithic NGO market. A case study of HIV control in Pakistan shows that in reality the NGO market comprises of parallel NGO networks having widely different service packages, approaches and agendas. These parallel networks had evolved over time due to vertical policy agendas. Contracting of NGOs for provision of HIV services was faced with uneven capacities and turf rivalries across both NGO networks. At the same time contracting helped NGO providers belonging to different clusters to move towards standardized service delivery for HIV prevention. Market based measures such as contracting need to be accompanied with wider policy measures that facilitate in bringing NGOs groups to a shared understanding of health issues and responses.

Providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer

DOEpatents

Archer, Charles J; Faraj, Ahmad A; Inglett, Todd A; Ratterman, Joseph D

2013-04-16

Methods, apparatus, and products are disclosed for providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer, each compute node connected to each adjacent compute node in the global combining network through a link, that include: receiving a network packet in a compute node, the network packet specifying a destination compute node; selecting, in dependence upon the destination compute node, at least one of the links for the compute node along which to forward the network packet toward the destination compute node; and forwarding the network packet along the selected link to the adjacent compute node connected to the compute node through the selected link.

Parallel Distributed Processing Theory in the Age of Deep Networks.

PubMed

Bowers, Jeffrey S

2017-12-01

Parallel distributed processing (PDP) models in psychology are the precursors of deep networks used in computer science. However, only PDP models are associated with two core psychological claims, namely that all knowledge is coded in a distributed format and cognition is mediated by non-symbolic computations. These claims have long been debated in cognitive science, and recent work with deep networks speaks to this debate. Specifically, single-unit recordings show that deep networks learn units that respond selectively to meaningful categories, and researchers are finding that deep networks need to be supplemented with symbolic systems to perform some tasks. Given the close links between PDP and deep networks, it is surprising that research with deep networks is challenging PDP theory. Copyright © 2017. Published by Elsevier Ltd.

Learning, memory, and the role of neural network architecture.

PubMed

Hermundstad, Ann M; Brown, Kevin S; Bassett, Danielle S; Carlson, Jean M

2011-06-01

The performance of information processing systems, from artificial neural networks to natural neuronal ensembles, depends heavily on the underlying system architecture. In this study, we compare the performance of parallel and layered network architectures during sequential tasks that require both acquisition and retention of information, thereby identifying tradeoffs between learning and memory processes. During the task of supervised, sequential function approximation, networks produce and adapt representations of external information. Performance is evaluated by statistically analyzing the error in these representations while varying the initial network state, the structure of the external information, and the time given to learn the information. We link performance to complexity in network architecture by characterizing local error landscape curvature. We find that variations in error landscape structure give rise to tradeoffs in performance; these include the ability of the network to maximize accuracy versus minimize inaccuracy and produce specific versus generalizable representations of information. Parallel networks generate smooth error landscapes with deep, narrow minima, enabling them to find highly specific representations given sufficient time. While accurate, however, these representations are difficult to generalize. In contrast, layered networks generate rough error landscapes with a variety of local minima, allowing them to quickly find coarse representations. Although less accurate, these representations are easily adaptable. The presence of measurable performance tradeoffs in both layered and parallel networks has implications for understanding the behavior of a wide variety of natural and artificial learning systems.

Parallel versus Serial Processing Dependencies in the Perisylvian Speech Network: A Granger Analysis of Intracranial EEG Data

ERIC Educational Resources Information Center

Gow, David W., Jr.; Keller, Corey J.; Eskandar, Emad; Meng, Nate; Cash, Sydney S.

2009-01-01

In this work, we apply Granger causality analysis to high spatiotemporal resolution intracranial EEG (iEEG) data to examine how different components of the left perisylvian language network interact during spoken language perception. The specific focus is on the characterization of serial versus parallel processing dependencies in the dominant…

Introduction to Neural Networks.

DTIC Science & Technology

1992-03-01

parallel processing of information that can greatly reduce the time required to perform operations which are needed in pattern recognition. Neural network, Artificial neural network , Neural net, ANN.

Interdisciplinary and physics challenges of network theory

NASA Astrophysics Data System (ADS)

Bianconi, Ginestra

2015-09-01

Network theory has unveiled the underlying structure of complex systems such as the Internet or the biological networks in the cell. It has identified universal properties of complex networks, and the interplay between their structure and dynamics. After almost twenty years of the field, new challenges lie ahead. These challenges concern the multilayer structure of most of the networks, the formulation of a network geometry and topology, and the development of a quantum theory of networks. Making progress on these aspects of network theory can open new venues to address interdisciplinary and physics challenges including progress on brain dynamics, new insights into quantum technologies, and quantum gravity.

The 2nd Symposium on the Frontiers of Massively Parallel Computations

NASA Technical Reports Server (NTRS)

Mills, Ronnie (Editor)

1988-01-01

Programming languages, computer graphics, neural networks, massively parallel computers, SIMD architecture, algorithms, digital terrain models, sort computation, simulation of charged particle transport on the massively parallel processor and image processing are among the topics discussed.

Performance Tradeoffs and Hierarchical Designs of Distributed Packet-Switching Communication Networks,

DTIC Science & Technology

1979-09-01

the traffic is ecenl\\ divided between groups. Gitman 1141 introduced Such a scheme and calculated the capaciy of two-level systems, lie assumed all...447-448. April 1976. 25 (141 Gitman , ., "On the Capacity of Slotted ALOH1A Networks and Sonic Design Problems," IEEE Transactions on Communicatons

[Doctors and the benefits and dangers of social networks].

PubMed

Tisseron, Serge

2015-05-13

Social networks have many different uses. Most young people use them for experimentation and innovation. Social networks help young people get familiar with the digital world, and develop themselves in interrelation with their peers. But social networks can also be used to avoid relationships in the real world, or to practice different forms of harassment. A specific danger lies in forgetting that a great number of people can have access to personal information posted online. Doctors should be particularly aware of this issue.

Resource Allocation and Cross Layer Control in Wireless Networks

DTIC Science & Technology

2006-08-25

arrival rates lies within the capacity region of the network. The notion of controlling the system to maximize its stability region and the following...optimization problem (4.5) that must be solved at the beginning of 48 Dynamic Control for Network Stability each time slot requires in general knowledge...Dynamic Control for Network Stability ~ (c) ab (t) those of any other feasible algorithm, then for any time t 0; X ic U (c) i (t) "X b ~ (c) ab (t) X

Class network routing

DOEpatents

Bhanot, Gyan [Princeton, NJ; 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; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Takken, Todd E [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY

2009-09-08

Class network routing is implemented in a network such as a computer network comprising a plurality of parallel compute processors at nodes thereof. Class network routing allows a compute processor to broadcast a message to a range (one or more) of other compute processors in the computer network, such as processors in a column or a row. Normally this type of operation requires a separate message to be sent to each processor. With class network routing pursuant to the invention, a single message is sufficient, which generally reduces the total number of messages in the network as well as the latency to do a broadcast. Class network routing is also applied to dense matrix inversion algorithms on distributed memory parallel supercomputers with hardware class function (multicast) capability. This is achieved by exploiting the fact that the communication patterns of dense matrix inversion can be served by hardware class functions, which results in faster execution times.

Scalable parallel communications

NASA Technical Reports Server (NTRS)

Maly, K.; Khanna, S.; Overstreet, C. M.; Mukkamala, R.; Zubair, M.; Sekhar, Y. S.; Foudriat, E. C.

1992-01-01

Coarse-grain parallelism in networking (that is, the use of multiple protocol processors running replicated software sending over several physical channels) can be used to provide gigabit communications for a single application. Since parallel network performance is highly dependent on real issues such as hardware properties (e.g., memory speeds and cache hit rates), operating system overhead (e.g., interrupt handling), and protocol performance (e.g., effect of timeouts), we have performed detailed simulations studies of both a bus-based multiprocessor workstation node (based on the Sun Galaxy MP multiprocessor) and a distributed-memory parallel computer node (based on the Touchstone DELTA) to evaluate the behavior of coarse-grain parallelism. Our results indicate: (1) coarse-grain parallelism can deliver multiple 100 Mbps with currently available hardware platforms and existing networking protocols (such as Transmission Control Protocol/Internet Protocol (TCP/IP) and parallel Fiber Distributed Data Interface (FDDI) rings); (2) scale-up is near linear in n, the number of protocol processors, and channels (for small n and up to a few hundred Mbps); and (3) since these results are based on existing hardware without specialized devices (except perhaps for some simple modifications of the FDDI boards), this is a low cost solution to providing multiple 100 Mbps on current machines. In addition, from both the performance analysis and the properties of these architectures, we conclude: (1) multiple processors providing identical services and the use of space division multiplexing for the physical channels can provide better reliability than monolithic approaches (it also provides graceful degradation and low-cost load balancing); (2) coarse-grain parallelism supports running several transport protocols in parallel to provide different types of service (for example, one TCP handles small messages for many users, other TCP's running in parallel provide high bandwidth service to a single application); and (3) coarse grain parallelism will be able to incorporate many future improvements from related work (e.g., reduced data movement, fast TCP, fine-grain parallelism) also with near linear speed-ups.

Cellular automata with object-oriented features for parallel molecular network modeling.

PubMed

Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan

2005-06-01

Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented.

Neural Correlates of Evaluations of Lying and Truth-Telling in Different Social Contexts

PubMed Central

Wu, Dingcheng; Loke, Ivy Chiu

2011-01-01

The present study examined the neural correlates of evaluations of both lying and truth-telling in different social contexts using fMRI methodology. The results demonstrated the differentiation between lying and truth-telling and between different types of lying in a network of brain regions. These regions included bilateral superior frontal gyrus (SFG), bilateral inferior parietal lobule (IPL), bilateral cuneus, right lingual gyrus (LG), right precuneus, and left postcentral gyrus (PoCG). Additionally, we found that activations in the right LG, the left IPL and the left PoCG were correlated with the off-line evaluations of truthful and untruthful communications about good and bad acts in different social contexts. These results suggest that the judgments of lying and truth-telling involving a third party might not be emotion-arousing but involve rational processing. This study is among the first to demonstrate that evaluations of truthful and untruthful communications in different social contexts can be differentiated in terms of brain BOLD (blood-oxygen-level dependent) activities. PMID:21382353

Enabling parallel simulation of large-scale HPC network systems

DOE PAGES

Mubarak, Misbah; Carothers, Christopher D.; Ross, Robert B.; ...

2016-04-07

Here, with the increasing complexity of today’s high-performance computing (HPC) architectures, simulation has become an indispensable tool for exploring the design space of HPC systems—in particular, networks. In order to make effective design decisions, simulations of these systems must possess the following properties: (1) have high accuracy and fidelity, (2) produce results in a timely manner, and (3) be able to analyze a broad range of network workloads. Most state-of-the-art HPC network simulation frameworks, however, are constrained in one or more of these areas. In this work, we present a simulation framework for modeling two important classes of networks usedmore » in today’s IBM and Cray supercomputers: torus and dragonfly networks. We use the Co-Design of Multi-layer Exascale Storage Architecture (CODES) simulation framework to simulate these network topologies at a flit-level detail using the Rensselaer Optimistic Simulation System (ROSS) for parallel discrete-event simulation. Our simulation framework meets all the requirements of a practical network simulation and can assist network designers in design space exploration. First, it uses validated and detailed flit-level network models to provide an accurate and high-fidelity network simulation. Second, instead of relying on serial time-stepped or traditional conservative discrete-event simulations that limit simulation scalability and efficiency, we use the optimistic event-scheduling capability of ROSS to achieve efficient and scalable HPC network simulations on today’s high-performance cluster systems. Third, our models give network designers a choice in simulating a broad range of network workloads, including HPC application workloads using detailed network traces, an ability that is rarely offered in parallel with high-fidelity network simulations« less

Enabling parallel simulation of large-scale HPC network systems

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

Mubarak, Misbah; Carothers, Christopher D.; Ross, Robert B.

Here, with the increasing complexity of today’s high-performance computing (HPC) architectures, simulation has become an indispensable tool for exploring the design space of HPC systems—in particular, networks. In order to make effective design decisions, simulations of these systems must possess the following properties: (1) have high accuracy and fidelity, (2) produce results in a timely manner, and (3) be able to analyze a broad range of network workloads. Most state-of-the-art HPC network simulation frameworks, however, are constrained in one or more of these areas. In this work, we present a simulation framework for modeling two important classes of networks usedmore » in today’s IBM and Cray supercomputers: torus and dragonfly networks. We use the Co-Design of Multi-layer Exascale Storage Architecture (CODES) simulation framework to simulate these network topologies at a flit-level detail using the Rensselaer Optimistic Simulation System (ROSS) for parallel discrete-event simulation. Our simulation framework meets all the requirements of a practical network simulation and can assist network designers in design space exploration. First, it uses validated and detailed flit-level network models to provide an accurate and high-fidelity network simulation. Second, instead of relying on serial time-stepped or traditional conservative discrete-event simulations that limit simulation scalability and efficiency, we use the optimistic event-scheduling capability of ROSS to achieve efficient and scalable HPC network simulations on today’s high-performance cluster systems. Third, our models give network designers a choice in simulating a broad range of network workloads, including HPC application workloads using detailed network traces, an ability that is rarely offered in parallel with high-fidelity network simulations« less

An annealed chaotic maximum neural network for bipartite subgraph problem.

PubMed

Wang, Jiahai; Tang, Zheng; Wang, Ronglong

2004-04-01

In this paper, based on maximum neural network, we propose a new parallel algorithm that can help the maximum neural network escape from local minima by including a transient chaotic neurodynamics for bipartite subgraph problem. The goal of the bipartite subgraph problem, which is an NP- complete problem, is to remove the minimum number of edges in a given graph such that the remaining graph is a bipartite graph. Lee et al. presented a parallel algorithm using the maximum neural model (winner-take-all neuron model) for this NP- complete problem. The maximum neural model always guarantees a valid solution and greatly reduces the search space without a burden on the parameter-tuning. However, the model has a tendency to converge to a local minimum easily because it is based on the steepest descent method. By adding a negative self-feedback to the maximum neural network, we proposed a new parallel algorithm that introduces richer and more flexible chaotic dynamics and can prevent the network from getting stuck at local minima. After the chaotic dynamics vanishes, the proposed algorithm is then fundamentally reined by the gradient descent dynamics and usually converges to a stable equilibrium point. The proposed algorithm has the advantages of both the maximum neural network and the chaotic neurodynamics. A large number of instances have been simulated to verify the proposed algorithm. The simulation results show that our algorithm finds the optimum or near-optimum solution for the bipartite subgraph problem superior to that of the best existing parallel algorithms.

Ballistic Deficits for Ionization Chamber Pulses in Pulse Shaping Amplifiers

NASA Astrophysics Data System (ADS)

Kumar, G. Anil; Sharma, S. L.; Choudhury, R. K.

2007-04-01

In order to understand the dependence of the ballistic deficit on the shape of rising portion of the voltage pulse at the input of a pulse shaping amplifier, we have estimated the ballistic deficits for the pulses from a two-electrode parallel plate ionization chamber as well as for the pulses from a gridded parallel plate ionization chamber. These estimations have been made using numerical integration method when the pulses are processed through the CR-RCn (n=1-6) shaping network as well as when the pulses are processed through the complex shaping network of the ORTEC Model 472 spectroscopic amplifier. Further, we have made simulations to see the effect of ballistic deficit on the pulse-height spectra under different conditions. We have also carried out measurements of the ballistic deficits for the pulses from a two-electrode parallel plate ionization chamber as well as for the pulses from a gridded parallel plate ionization chamber when these pulses are processed through the ORTEC 572 linear amplifier having a simple CR-RC shaping network. The reasonable matching of the simulated ballistic deficits with the experimental ballistic deficits for the CR-RC shaping network clearly establishes the validity of the simulation technique

A more secure parallel keyed hash function based on chaotic neural network

NASA Astrophysics Data System (ADS)

Huang, Zhongquan

2011-08-01

Although various hash functions based on chaos or chaotic neural network were proposed, most of them can not work efficiently in parallel computing environment. Recently, an algorithm for parallel keyed hash function construction based on chaotic neural network was proposed [13]. However, there is a strict limitation in this scheme that its secret keys must be nonce numbers. In other words, if the keys are used more than once in this scheme, there will be some potential security flaw. In this paper, we analyze the cause of vulnerability of the original one in detail, and then propose the corresponding enhancement measures, which can remove the limitation on the secret keys. Theoretical analysis and computer simulation indicate that the modified hash function is more secure and practical than the original one. At the same time, it can keep the parallel merit and satisfy the other performance requirements of hash function, such as good statistical properties, high message and key sensitivity, and strong collision resistance, etc.

Providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer

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

Archer, Charles J.; Faraj, Daniel A.; Inglett, Todd A.

Methods, apparatus, and products are disclosed for providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer, each compute node connected to each adjacent compute node in the global combining network through a link, that include: receiving a network packet in a compute node, the network packet specifying a destination compute node; selecting, in dependence upon the destination compute node, at least one of the links for the compute node along which to forward the network packet toward the destination compute node; and forwarding the network packet along the selectedmore » link to the adjacent compute node connected to the compute node through the selected link.« less

Oscillations and chaos in neural networks: an exactly solvable model.

PubMed Central

Wang, L P; Pichler, E E; Ross, J

1990-01-01

We consider a randomly diluted higher-order network with noise, consisting of McCulloch-Pitts neurons that interact by Hebbian-type connections. For this model, exact dynamical equations are derived and solved for both parallel and random sequential updating algorithms. For parallel dynamics, we find a rich spectrum of different behaviors including static retrieving and oscillatory and chaotic phenomena in different parts of the parameter space. The bifurcation parameters include first- and second-order neuronal interaction coefficients and a rescaled noise level, which represents the combined effects of the random synaptic dilution, interference between stored patterns, and additional background noise. We show that a marked difference in terms of the occurrence of oscillations or chaos exists between neural networks with parallel and random sequential dynamics. Images PMID:2251287

Exploiting parallel computing with limited program changes using a network of microcomputers

NASA Technical Reports Server (NTRS)

Rogers, J. L., Jr.; Sobieszczanski-Sobieski, J.

1985-01-01

Network computing and multiprocessor computers are two discernible trends in parallel processing. The computational behavior of an iterative distributed process in which some subtasks are completed later than others because of an imbalance in computational requirements is of significant interest. The effects of asynchronus processing was studied. A small existing program was converted to perform finite element analysis by distributing substructure analysis over a network of four Apple IIe microcomputers connected to a shared disk, simulating a parallel computer. The substructure analysis uses an iterative, fully stressed, structural resizing procedure. A framework of beams divided into three substructures is used as the finite element model. The effects of asynchronous processing on the convergence of the design variables are determined by not resizing particular substructures on various iterations.

1,1′-Bicyclo­propyl-1,1′-diyl 1,1′-biphenyl-2,2′-dicarboxyl­ate

PubMed Central

Fun, Hoong-Kun; Quah, Ching Kheng; Xu, Kai

2012-01-01

In the title compound, C20H16O4, the two benzene rings form a dihedral angle of 45.70 (4)°. In the crystal, mol­ecules are linked via C—H⋯O inter­actions into layers lying parallel to the bc plane. PMID:22719433

Forest resources in the Tennessee valley of north Alabama

Treesearch

James W. Cruikshank

1940-01-01

Forest survey Unit No. 6 in north Alabama embraces 10 counties that lie almost exclusively in the watershed of the Tennessee River (fig. 2). The unit, containing 4,595,900 acres, extends entirely across the northern part of the State, with its southern boundary roughly parallel to, and about 50 miles south of, the Tennessee State line. The Tennessee River, which enters...

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.

Big data driven cycle time parallel prediction for production planning in wafer manufacturing

NASA Astrophysics Data System (ADS)

Wang, Junliang; Yang, Jungang; Zhang, Jie; Wang, Xiaoxi; Zhang, Wenjun Chris

2018-07-01

Cycle time forecasting (CTF) is one of the most crucial issues for production planning to keep high delivery reliability in semiconductor wafer fabrication systems (SWFS). This paper proposes a novel data-intensive cycle time (CT) prediction system with parallel computing to rapidly forecast the CT of wafer lots with large datasets. First, a density peak based radial basis function network (DP-RBFN) is designed to forecast the CT with the diverse and agglomerative CT data. Second, the network learning method based on a clustering technique is proposed to determine the density peak. Third, a parallel computing approach for network training is proposed in order to speed up the training process with large scaled CT data. Finally, an experiment with respect to SWFS is presented, which demonstrates that the proposed CTF system can not only speed up the training process of the model but also outperform the radial basis function network, the back-propagation-network and multivariate regression methodology based CTF methods in terms of the mean absolute deviation and standard deviation.

A parallel algorithm for multi-level logic synthesis using the transduction method. M.S. Thesis

NASA Technical Reports Server (NTRS)

Lim, Chieng-Fai

1991-01-01

The Transduction Method has been shown to be a powerful tool in the optimization of multilevel networks. Many tools such as the SYLON synthesis system (X90), (CM89), (LM90) have been developed based on this method. A parallel implementation is presented of SYLON-XTRANS (XM89) on an eight processor Encore Multimax shared memory multiprocessor. It minimizes multilevel networks consisting of simple gates through parallel pruning, gate substitution, gate merging, generalized gate substitution, and gate input reduction. This implementation, called Parallel TRANSduction (PTRANS), also uses partitioning to break large circuits up and performs inter- and intra-partition dynamic load balancing. With this, good speedups and high processor efficiencies are achievable without sacrificing the resulting circuit quality.

Portable programming on parallel/networked computers using the Application Portable Parallel Library (APPL)

NASA Technical Reports Server (NTRS)

Quealy, Angela; Cole, Gary L.; Blech, Richard A.

1993-01-01

The Application Portable Parallel Library (APPL) is a subroutine-based library of communication primitives that is callable from applications written in FORTRAN or C. APPL provides a consistent programmer interface to a variety of distributed and shared-memory multiprocessor MIMD machines. The objective of APPL is to minimize the effort required to move parallel applications from one machine to another, or to a network of homogeneous machines. APPL encompasses many of the message-passing primitives that are currently available on commercial multiprocessor systems. This paper describes APPL (version 2.3.1) and its usage, reports the status of the APPL project, and indicates possible directions for the future. Several applications using APPL are discussed, as well as performance and overhead results.

Parallel computation with molecular-motor-propelled agents in nanofabricated networks.

PubMed

Nicolau, Dan V; Lard, Mercy; Korten, Till; van Delft, Falco C M J M; Persson, Malin; Bengtsson, Elina; Månsson, Alf; Diez, Stefan; Linke, Heiner; Nicolau, Dan V

2016-03-08

The combinatorial nature of many important mathematical problems, including nondeterministic-polynomial-time (NP)-complete problems, places a severe limitation on the problem size that can be solved with conventional, sequentially operating electronic computers. There have been significant efforts in conceiving parallel-computation approaches in the past, for example: DNA computation, quantum computation, and microfluidics-based computation. However, these approaches have not proven, so far, to be scalable and practical from a fabrication and operational perspective. Here, we report the foundations of an alternative parallel-computation system in which a given combinatorial problem is encoded into a graphical, modular network that is embedded in a nanofabricated planar device. Exploring the network in a parallel fashion using a large number of independent, molecular-motor-propelled agents then solves the mathematical problem. This approach uses orders of magnitude less energy than conventional computers, thus addressing issues related to power consumption and heat dissipation. We provide a proof-of-concept demonstration of such a device by solving, in a parallel fashion, the small instance {2, 5, 9} of the subset sum problem, which is a benchmark NP-complete problem. Finally, we discuss the technical advances necessary to make our system scalable with presently available technology.

Glove-TalkII--a neural-network interface which maps gestures to parallel formant speech synthesizer controls.

PubMed

Fels, S S; Hinton, G E

1998-01-01

Glove-TalkII is a system which translates hand gestures to speech through an adaptive interface. Hand gestures are mapped continuously to ten control parameters of a parallel formant speech synthesizer. The mapping allows the hand to act as an artificial vocal tract that produces speech in real time. This gives an unlimited vocabulary in addition to direct control of fundamental frequency and volume. Currently, the best version of Glove-TalkII uses several input devices (including a Cyberglove, a ContactGlove, a three-space tracker, and a foot pedal), a parallel formant speech synthesizer, and three neural networks. The gesture-to-speech task is divided into vowel and consonant production by using a gating network to weight the outputs of a vowel and a consonant neural network. The gating network and the consonant network are trained with examples from the user. The vowel network implements a fixed user-defined relationship between hand position and vowel sound and does not require any training examples from the user. Volume, fundamental frequency, and stop consonants are produced with a fixed mapping from the input devices. One subject has trained to speak intelligibly with Glove-TalkII. He speaks slowly but with far more natural sounding pitch variations than a text-to-speech synthesizer.

Reliability of a Parallel Pipe Network

NASA Technical Reports Server (NTRS)

Herrera, Edgar; Chamis, Christopher (Technical Monitor)

2001-01-01

The goal of this NASA-funded research is to advance research and education objectives in theoretical and computational probabilistic structural analysis, reliability, and life prediction methods for improved aerospace and aircraft propulsion system components. Reliability methods are used to quantify response uncertainties due to inherent uncertainties in design variables. In this report, several reliability methods are applied to a parallel pipe network. The observed responses are the head delivered by a main pump and the head values of two parallel lines at certain flow rates. The probability that the flow rates in the lines will be less than their specified minimums will be discussed.

Parallel and Distributed Systems for Probabilistic Reasoning

DTIC Science & Technology

2012-12-01

work at CMU I had the opportunity to work with Andreas Krause on Gaussian process models for signal quality estimation in wireless sensor networks ...we reviewed the natural parallelization of the belief propagation algorithm using the synchronous schedule and demonstrated both theoretically and...problem is that the power-law sparsity structure, commonly found in graphs derived from natural phenomena (e.g., social networks and the web

Programmed optoelectronic time-pulse coded relational processor as base element for sorting neural networks

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Bardachenko, Vitaliy F.; Nikolsky, Alexander I.; Lazarev, Alexander A.

2007-04-01

In the paper we show that the biologically motivated conception of the use of time-pulse encoding gives the row of advantages (single methodological basis, universality, simplicity of tuning, training and programming et al) at creation and designing of sensor systems with parallel input-output and processing, 2D-structures of hybrid and neuro-fuzzy neurocomputers of next generations. We show principles of construction of programmable relational optoelectronic time-pulse coded processors, continuous logic, order logic and temporal waves processes, that lie in basis of the creation. We consider structure that executes extraction of analog signal of the set grade (order), sorting of analog and time-pulse coded variables. We offer optoelectronic realization of such base relational elements of order logic, which consists of time-pulse coded phototransformers (pulse-width and pulse-phase modulators) with direct and complementary outputs, sorting network on logical elements and programmable commutations blocks. We make estimations of basic technical parameters of such base devices and processors on their basis by simulation and experimental research: power of optical input signals - 0.200-20 μW, processing time - microseconds, supply voltage - 1.5-10 V, consumption power - hundreds of microwatts per element, extended functional possibilities, training possibilities. We discuss some aspects of possible rules and principles of training and programmable tuning on the required function, relational operation and realization of hardware blocks for modifications of such processors. We show as on the basis of such quasiuniversal hardware simple block and flexible programmable tuning it is possible to create sorting machines, neural networks and hybrid data-processing systems with the untraditional numerical systems and pictures operands.

JPARSS: A Java Parallel Network Package for Grid Computing

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

Chen, Jie; Akers, Walter; Chen, Ying

2002-03-01

The emergence of high speed wide area networks makes grid computinga reality. However grid applications that need reliable data transfer still have difficulties to achieve optimal TCP performance due to network tuning of TCP window size to improve bandwidth and to reduce latency on a high speed wide area network. This paper presents a Java package called JPARSS (Java Parallel Secure Stream (Socket)) that divides data into partitions that are sent over several parallel Java streams simultaneously and allows Java or Web applications to achieve optimal TCP performance in a grid environment without the necessity of tuning TCP window size.more » This package enables single sign-on, certificate delegation and secure or plain-text data transfer using several security components based on X.509 certificate and SSL. Several experiments will be presented to show that using Java parallelstreams is more effective than tuning TCP window size. In addition a simple architecture using Web services« less

Parallel NGO Networks for HIV Control: Risks and Opportunities for NGO Contracting

PubMed Central

Zaidi, Shehla; Gul, Xaher; Nishtar, Noureen

2013-01-01

Policy measures for preventive and promotive services are increasingly reliant on contracting of NGOs. Contracting is a neo-liberal response relying on open market competition for service delivery tenders. In contracting of health services a common assumption is a monolithic NGO market. A case study of HIV control in Pakistan shows that in reality the NGO market comprises of parallel NGO networks having widely different service packages, approaches and agendas. These parallel networks had evolved over time due to vertical policy agendas. Contracting of NGOs for provision of HIV services was faced with uneven capacities and turf rivalries across both NGO networks. At the same time contracting helped NGO providers belonging to different clusters to move towards standardized service delivery for HIV prevention. Market based measures such as contracting need to be accompanied with wider policy and system measures that overcome silos in NGO working by facilitating a common construct on the health issue, cohesive priorities and integrated working. PMID:23445705

Parallelization of Nullspace Algorithm for the computation of metabolic pathways

PubMed Central

Jevremović, Dimitrije; Trinh, Cong T.; Srienc, Friedrich; Sosa, Carlos P.; Boley, Daniel

2011-01-01

Elementary mode analysis is a useful metabolic pathway analysis tool in understanding and analyzing cellular metabolism, since elementary modes can represent metabolic pathways with unique and minimal sets of enzyme-catalyzed reactions of a metabolic network under steady state conditions. However, computation of the elementary modes of a genome- scale metabolic network with 100–1000 reactions is very expensive and sometimes not feasible with the commonly used serial Nullspace Algorithm. In this work, we develop a distributed memory parallelization of the Nullspace Algorithm to handle efficiently the computation of the elementary modes of a large metabolic network. We give an implementation in C++ language with the support of MPI library functions for the parallel communication. Our proposed algorithm is accompanied with an analysis of the complexity and identification of major bottlenecks during computation of all possible pathways of a large metabolic network. The algorithm includes methods to achieve load balancing among the compute-nodes and specific communication patterns to reduce the communication overhead and improve efficiency. PMID:22058581

Evidence for a Functional Hierarchy of Association Networks.

PubMed

Choi, Eun Young; Drayna, Garrett K; Badre, David

2018-05-01

Patient lesion and neuroimaging studies have identified a rostral-to-caudal functional gradient in the lateral frontal cortex (LFC) corresponding to higher-order (complex or abstract) to lower-order (simple or concrete) cognitive control. At the same time, monkey anatomical and human functional connectivity studies show that frontal regions are reciprocally connected with parietal and temporal regions, forming parallel and distributed association networks. Here, we investigated the link between the functional gradient of LFC regions observed during control tasks and the parallel, distributed organization of association networks. Whole-brain fMRI task activity corresponding to four orders of hierarchical control [Badre, D., & D'Esposito, M. Functional magnetic resonance imaging evidence for a hierarchical organization of the prefrontal cortex. Journal of Cognitive Neuroscience, 19, 2082-2099, 2007] was compared with a resting-state functional connectivity MRI estimate of cortical networks [Yeo, B. T., Krienen, F. M., Sepulcre, J., Sabuncu, M. R., Lashkari, D., Hollinshead, M., et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. Journal of Neurophysiology, 106, 1125-1165, 2011]. Critically, at each order of control, activity in the LFC and parietal cortex overlapped onto a common association network that differed between orders. These results are consistent with a functional organization based on separable association networks that are recruited during hierarchical control. Furthermore, corticostriatal functional connectivity MRI showed that, consistent with their participation in functional networks, rostral-to-caudal LFC and caudal-to-rostral parietal regions had similar, order-specific corticostriatal connectivity that agreed with a striatal gating model of hierarchical rule use. Our results indicate that hierarchical cognitive control is subserved by parallel and distributed association networks, together forming multiple localized functional gradients in different parts of association cortex. As such, association networks, while connectionally organized in parallel, may be functionally organized in a hierarchy via dynamic interaction with the striatum.

Evaluating System Parameters on a Dragonfly using Simulation and Visualization

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

Bhatele, Abhinav; Jain, Nikhil; Livnat, Yarden

The dragon y topology is becoming a popular choice for build- ing high-radix, low-diameter networks with high-bandwidth links. Even with a powerful network, preliminary experi- ments on Edison at NERSC have shown that for communica- tion heavy applications, job interference and thus presumably job placement remains an important factor. In this paper, we explore the e ects of job placement, job sizes, parallel workloads and network con gurations on network through- put to better understand inter-job interference. We use a simulation tool called Damsel y to model the network be- havior of Edison and study the impact of various systemmore » parameters on network throughput. Parallel workloads based on ve representative communication patters are used and the simulation studies on up to 131,072 cores are aided by a new visualization of the dragon y network.« less

Deformation and Oil Migration Along the Active Newport-Inglewood Fault Zone, Southern California, USA

NASA Astrophysics Data System (ADS)

Sample, J. C.

2006-12-01

Deformation bands occur in an outcrop of a petroleum-bearing, sandstone-rich unit of the Monterey Formation along the active Newport-Inglewood fault zone (NIFZ), near Corona del Mar, California. The deformation bands likely developed in a damage zone associated with a strand of the NIFZ. The bands appear to have formed in poorly lithified sandstone. They are relatively oil-free whereas the matrix sandstone contains oil in pore space. The deformation bands acted as baffles to flow, but continuing deformation likely breached permeability barriers over time. Thus the bands did not completely isolate compartments from oil migration, but similar structures in the subsurface would likely slow the rate of production in reservoirs. The network of bands at Corona del Mar forms a mesh with band intersection lines lying parallel to the trend of the NIFZ (northwest). This geometry formed as continuing deformation in the NIFZ rotated early bands into unfavorable orientations for continuing deformation, and new bands formed at high angles to the first set. Permeability in this setting is likely to have been anisotropic, higher parallel to strike of the NIFZ and lower vertically and perpendicular to the strike of the fault zone. One unique type of deformation band found here formed by dilation and early oil migration along fractures, and consequent carbonate cementation along fracture margins. These are thin, planar zones of oil 1 - 2 mm thick sandwiched between parallel, carbonate-cemented, positively weathering ribs. These bands appear to represent early oil migration by hydrofracture. Based on crosscutting relationships between structures and cements, there are three distinct phases of oil migration: early migration along discrete hydrofractures; dominant pore migration associated with periodic breaching of deformation bands; and late migration along open fractures, some several centimeters in width. This sequence may be representative of migration histories along the NIFZ in the Los Angeles basin.

Automated target recognition and tracking using an optical pattern recognition neural network

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

1991-01-01

The on-going development of an automatic target recognition and tracking system at the Jet Propulsion Laboratory is presented. This system is an optical pattern recognition neural network (OPRNN) that is an integration of an innovative optical parallel processor and a feature extraction based neural net training algorithm. The parallel optical processor provides high speed and vast parallelism as well as full shift invariance. The neural network algorithm enables simultaneous discrimination of multiple noisy targets in spite of their scales, rotations, perspectives, and various deformations. This fully developed OPRNN system can be effectively utilized for the automated spacecraft recognition and tracking that will lead to success in the Automated Rendezvous and Capture (AR&C) of the unmanned Cargo Transfer Vehicle (CTV). One of the most powerful optical parallel processors for automatic target recognition is the multichannel correlator. With the inherent advantages of parallel processing capability and shift invariance, multiple objects can be simultaneously recognized and tracked using this multichannel correlator. This target tracking capability can be greatly enhanced by utilizing a powerful feature extraction based neural network training algorithm such as the neocognitron. The OPRNN, currently under investigation at JPL, is constructed with an optical multichannel correlator where holographic filters have been prepared using the neocognitron training algorithm. The computation speed of the neocognitron-type OPRNN is up to 10(exp 14) analog connections/sec that enabling the OPRNN to outperform its state-of-the-art electronics counterpart by at least two orders of magnitude.

Efficiently modeling neural networks on massively parallel computers

NASA Technical Reports Server (NTRS)

Farber, Robert M.

1993-01-01

Neural networks are a very useful tool for analyzing and modeling complex real world systems. Applying neural network simulations to real world problems generally involves large amounts of data and massive amounts of computation. To efficiently handle the computational requirements of large problems, we have implemented at Los Alamos a highly efficient neural network compiler for serial computers, vector computers, vector parallel computers, and fine grain SIMD computers such as the CM-2 connection machine. This paper describes the mapping used by the compiler to implement feed-forward backpropagation neural networks for a SIMD (Single Instruction Multiple Data) architecture parallel computer. Thinking Machines Corporation has benchmarked our code at 1.3 billion interconnects per second (approximately 3 gigaflops) on a 64,000 processor CM-2 connection machine (Singer 1990). This mapping is applicable to other SIMD computers and can be implemented on MIMD computers such as the CM-5 connection machine. Our mapping has virtually no communications overhead with the exception of the communications required for a global summation across the processors (which has a sub-linear runtime growth on the order of O(log(number of processors)). We can efficiently model very large neural networks which have many neurons and interconnects and our mapping can extend to arbitrarily large networks (within memory limitations) by merging the memory space of separate processors with fast adjacent processor interprocessor communications. This paper will consider the simulation of only feed forward neural network although this method is extendable to recurrent networks.

Multiprocessor architecture: Synthesis and evaluation

NASA Technical Reports Server (NTRS)

Standley, Hilda M.

1990-01-01

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

Upper mantle seismic anisotropy beneath Northern Peru from shear wave splitting analysis.

NASA Astrophysics Data System (ADS)

Franca, G. S.; Condori, C.; Tavera, H.; Eakin, C. M.; Beck, S. L.

2017-12-01

Beneath much of Peru lies the largest region of flat-slab subduction in the world today. The origins and dynamics of the Peruvian flat-slab however remain elusive, particularly in the north away from the Nazca Ridge. Studies of seismic anisotropy can potentially provide us with insight into the dynamics of recent and past deformational processes in the upper mantle. In this study, we conduct shear wave splitting to investigate seismic anisotropy across the northern extent of the Peruvian flat-slab for the first time. For the analysis, we used arrivals of SKS, SKKS and PKS phases from teleseismic events (88° > Δ < 150°) recorded at 30 broadband seismic stations from the Peruvian permanent and portable seismic networks, and international networks (CTBTO and RSBR-Brazil). The preliminary results reveal a complex anisotropy pattern with variations along strike. In the northernmost region, the average delay times range between 1.0 s and 1.2 s, with fast directions predominantly ENE-WSW oriented in a direction approximately perpendicular to the trench, parallel with subduction of the Nazca plate. Meanwhile towards the central region of Peru, the predominant fast direction changes to SE-NW oblique with the trench, but consistent with the pattern seen previously over the southern extent of the flat-slab by Eakin et al. (2013, 2015). These characteristics suggest a fundamental difference between the anisotropic structures, and therefore underlying mantle processes, beneath the northern and central portions of the Peruvian flat-slab.

Simulation Modeling and Analysis of Device-Aware Network Architectures

DTIC Science & Technology

2004-12-01

However, a potential issue lies in the location of the intermediate proxy with respect to the content servers; if the proxy is far away from the...to 11 guide the adaptation of content presented to that device [CC/PP, 2004]. The strength of CC/PP lies in its flexibility. CC/PP is based on RDF...from: http://ieeexplore.ieee.org/iel4/98/15881/00736473.pdf. Accessed October 2004. [Hu and Bagga, 2004] Jianying Hu and Amit Bagga, “Categorizing

Parallel architectures for iterative methods on adaptive, block structured grids

NASA Technical Reports Server (NTRS)

Gannon, D.; Vanrosendale, J.

1983-01-01

A parallel computer architecture well suited to the solution of partial differential equations in complicated geometries is proposed. Algorithms for partial differential equations contain a great deal of parallelism. But this parallelism can be difficult to exploit, particularly on complex problems. One approach to extraction of this parallelism is the use of special purpose architectures tuned to a given problem class. The architecture proposed here is tuned to boundary value problems on complex domains. An adaptive elliptic algorithm which maps effectively onto the proposed architecture is considered in detail. Two levels of parallelism are exploited by the proposed architecture. First, by making use of the freedom one has in grid generation, one can construct grids which are locally regular, permitting a one to one mapping of grids to systolic style processor arrays, at least over small regions. All local parallelism can be extracted by this approach. Second, though there may be a regular global structure to the grids constructed, there will be parallelism at this level. One approach to finding and exploiting this parallelism is to use an architecture having a number of processor clusters connected by a switching network. The use of such a network creates a highly flexible architecture which automatically configures to the problem being solved.

An Overview of High-performance Parallel Big Data transfers over multiple network channels with Transport Layer Security (TLS) and TLS plus Perfect Forward Secrecy (PFS)

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

Fang, Chin; Corttrell, R. A.

This Technical Note provides an overview of high-performance parallel Big Data transfers with and without encryption for data in-transit over multiple network channels. It shows that with the parallel approach, it is feasible to carry out high-performance parallel "encrypted" Big Data transfers without serious impact to throughput. But other impacts, e.g. the energy-consumption part should be investigated. It also explains our rationales of using a statistics-based approach for gaining understanding from test results and for improving the system. The presentation is of high-level nature. Nevertheless, at the end we will pose some questions and identify potentially fruitful directions for futuremore » work.« less

Massively-Parallel Architectures for Automatic Recognition of Visual Speech Signals

DTIC Science & Technology

1988-10-12

Secusrity Clamifieation, Nlassively-Parallel Architectures for Automa ic Recognitio of Visua, Speech Signals 12. PERSONAL AUTHOR(S) Terrence J...characteristics of speech from tJhe, visual speech signals. Neural networks have been trained on a database of vowels. The rqw images of faces , aligned and...images of faces , aligned and preprocessed, were used as input to these network which were trained to estimate the corresponding envelope of the

The Challenges Never Stop! Two Decades of Reaching for the Best in Clinical Practice

ERIC Educational Resources Information Center

Field, Bruce E.; Van Scoy, Irma J.

2014-01-01

The University of South Carolina Professional Development School (USC PDS) Network has been engaged in designing and redesigning school-university partnerships for more than 20 years with a focus on ensuring that school-based practice lies at the heart of candidate preparation. In 2012-2013, the USC PDS Network once again reexamined their program…

Parallel protein secondary structure prediction based on neural networks.

PubMed

Zhong, Wei; Altun, Gulsah; Tian, Xinmin; Harrison, Robert; Tai, Phang C; Pan, Yi

2004-01-01

Protein secondary structure prediction has a fundamental influence on today's bioinformatics research. In this work, binary and tertiary classifiers of protein secondary structure prediction are implemented on Denoeux belief neural network (DBNN) architecture. Hydrophobicity matrix, orthogonal matrix, BLOSUM62 and PSSM (position specific scoring matrix) are experimented separately as the encoding schemes for DBNN. The experimental results contribute to the design of new encoding schemes. New binary classifier for Helix versus not Helix ( approximately H) for DBNN produces prediction accuracy of 87% when PSSM is used for the input profile. The performance of DBNN binary classifier is comparable to other best prediction methods. The good test results for binary classifiers open a new approach for protein structure prediction with neural networks. Due to the time consuming task of training the neural networks, Pthread and OpenMP are employed to parallelize DBNN in the hyperthreading enabled Intel architecture. Speedup for 16 Pthreads is 4.9 and speedup for 16 OpenMP threads is 4 in the 4 processors shared memory architecture. Both speedup performance of OpenMP and Pthread is superior to that of other research. With the new parallel training algorithm, thousands of amino acids can be processed in reasonable amount of time. Our research also shows that hyperthreading technology for Intel architecture is efficient for parallel biological algorithms.

Antiparallel spin does not always contain more information

NASA Astrophysics Data System (ADS)

Ghosh, Sibasish; Roy, Anirban; Sen, Ujjwal

2001-01-01

We show that the Bloch vectors lying on any great circle comprise the largest set SL for which the parallel states \\|n-->,n-->> can always be exactly transformed into the antiparallel states \\|n-->,-n-->>. Thus more information about n--> is not extractable from \\|n-->,-n-->> than from \\|n-->,n-->> by any measuring strategy, for n-->∈SL. Surprisingly this most general transformation reduces to just a flip operation on the second particle. We also show here that a probabilistic exact parallel to antiparallel transformation is not possible if the corresponding antiparallel states span the whole Hilbert space of the two qubits. These considerations allow us to generalize a conjecture of Gisin and Popescu [Phys. Rev. Lett. 83, 432 (1999)].

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.

Reliability Analysis and Modeling of ZigBee Networks

NASA Astrophysics Data System (ADS)

Lin, Cheng-Min

The architecture of ZigBee networks focuses on developing low-cost, low-speed ubiquitous communication between devices. The ZigBee technique is based on IEEE 802.15.4, which specifies the physical layer and medium access control (MAC) for a low rate wireless personal area network (LR-WPAN). Currently, numerous wireless sensor networks have adapted the ZigBee open standard to develop various services to promote improved communication quality in our daily lives. The problem of system and network reliability in providing stable services has become more important because these services will be stopped if the system and network reliability is unstable. The ZigBee standard has three kinds of networks; star, tree and mesh. The paper models the ZigBee protocol stack from the physical layer to the application layer and analyzes these layer reliability and mean time to failure (MTTF). Channel resource usage, device role, network topology and application objects are used to evaluate reliability in the physical, medium access control, network, and application layers, respectively. In the star or tree networks, a series system and the reliability block diagram (RBD) technique can be used to solve their reliability problem. However, a division technology is applied here to overcome the problem because the network complexity is higher than that of the others. A mesh network using division technology is classified into several non-reducible series systems and edge parallel systems. Hence, the reliability of mesh networks is easily solved using series-parallel systems through our proposed scheme. The numerical results demonstrate that the reliability will increase for mesh networks when the number of edges in parallel systems increases while the reliability quickly drops when the number of edges and the number of nodes increase for all three networks. More use of resources is another factor impact on reliability decreasing. However, lower network reliability will occur due to network complexity, more resource usage and complex object relationship.

The sinuous ridge and channel network within Rahway Vallis and the wider contextual study of the surrounding Rahway Basin, Mars.

NASA Astrophysics Data System (ADS)

Ramsdale, Jason; Balme, Matthew; Conway, Susan; Gallagher, Colman

2014-05-01

Rahway Vallis is a previously identified shallow v-shaped valley network in the Mars Orbiter Laser Altimeter data, located at 10°N 175°E, within the Cerberus Plains in the Elysium Planitia region of Mars. Rahway Vallis is situated in low-lying terrain bounded to west, north and east by older highlands, and to the south by the flood-carved channel system Marte Vallis. Here we present a study of the low-lying area in which Rahway Vallis sits, which we refer to as the "Rahway basin". The floor of the Rahway basin is extremely flat (sloping at 0.02° south-east) and hosts a branching network of ridge and channel systems. The aim of this project is to determine the genesis of these branching forms, in particular to test the hypothesis that they are glaciofluvial in origin. Using topographic cross-profiles of the channels that are identifiable in CTX 6 m/pixel images, we have found that they are set within broader v-shaped valley that has almost no morphological expression. These valleys have a convex-up, shallow (around 15 metres vertically compared to several kilometres in the horizontal) V-shaped profiles that are consistent in form across the whole Rahway Basin. Long profiles show the channels to deepen with respect to the bank height downslope. Both channels and valley show a consistent downhill gradient from west to east. The channels typically widen down-slope and increase in width at confluences. If these are water-cut channels, they reach Strahler stream orders of 4, consistent with a contributory network with multiple sources. Associated with the channels are sinuous ridges, typically several kilometres long, 20 m across, with heights on the order of 10 m. They sometimes form branching networks leading into the channels but also form individually and parallel to the channels. Possible explanations for the sinuous ridges include inverted fluvial channels and eskers. However despite looking through ca. 250 CTX images across the Rahway basin, no other glacial landform was identified. This makes the esker hypothesis unlikely. We have found that the transition between the older heavily cratered highland terrain and the floor of the Rahway basin is often bounded by near-horizontal topographic terraces. These terraces appear continuous around the basin margin and are present in almost all locations where 6m/pixel resolution CTX images are available. These steps are at altitudes between -3108 m and -2620 m with a mean of -3000 m above the Mars datum and have a standard deviation of 68.7 metres. These properties suggest that the terraces could represent the palaeo-shorelines of a drained/evaporated standing body of water. A since drained standing body of water is consistent with the hypothesis that the channels and ridges are fluvial and inverted fluvial channels respectively.

Fabrication of micro- and nanometre-scale polymer structures in liquid crystal devices for next generation photonics applications

NASA Astrophysics Data System (ADS)

Tartan, Chloe C.; Salter, Patrick S.; Booth, Martin J.; Morris, Stephen M.; Elston, Steve J.

2016-09-01

Direct Laser Writing (DLW) by two-photon photopolymerization (TPP) enables the fabrication of micron-scale polymeric structures in soft matter systems. The technique has implications in a broad range of optics and photonics; in particular fast-switching liquid crystal (LC) modes for the development of next generation display technologies. In this paper, we report two different methodologies using our TPP-based fabrication technique. Two explicit examples are provided of voltage-dependent LC director profiles that are inherently unstable, but which appear to be promising candidates for fast-switching photonics applications. In the first instance, 1 μm-thick periodic walls of polymer network are written into a planar aligned (parallel rubbed) nematic pi-cell device containing a nematic LC-monomer mixture. The structures are fabricated when the device is electrically driven into a fast-switching nematic LC state and aberrations induced by the device substrates are corrected for by virtue of the adaptive optics elements included within the DLW setup. Optical polarizing microscopy images taken post-fabrication reveal that polymer walls oriented perpendicular to the rubbing direction promote the stability of the so-called optically compensated bend mode upon removal of the externally applied field. In the second case, polymer walls are written in a nematic LC-optically adhesive glue mixture. A polymer- LCs-polymer-slices or `POLICRYPS' template is formed by immersing the device in acetone post-fabrication to remove any remaining non-crosslinked material. Injecting the resultant series of polymer microchannels ( 1 μm-thick) with a short-pitch, chiral nematic LC mixture leads to the spontaneous alignment of a fast-switching chiral nematic mode, where the helical axis lies parallel to the glass substrates. Optimal contrast between the bright and dark states of the uniform lying helix alignment is achieved when the structures are spaced at the order of the device thickness, which was also found to be the case for the achiral system. The high resolution DLW technique limits structures to the focal spot size of the beam, 1 μm in diameter, such that the transmittance is expected to be significantly enhanced relative to other stabilization techniques. Moreover, both devices remain stable under electrical and thermal cycling.

Developmental time windows for axon growth influence neuronal network topology.

PubMed

Lim, Sol; Kaiser, Marcus

2015-04-01

Early brain connectivity development consists of multiple stages: birth of neurons, their migration and the subsequent growth of axons and dendrites. Each stage occurs within a certain period of time depending on types of neurons and cortical layers. Forming synapses between neurons either by growing axons starting at similar times for all neurons (much-overlapped time windows) or at different time points (less-overlapped) may affect the topological and spatial properties of neuronal networks. Here, we explore the extreme cases of axon formation during early development, either starting at the same time for all neurons (parallel, i.e., maximally overlapped time windows) or occurring for each neuron separately one neuron after another (serial, i.e., no overlaps in time windows). For both cases, the number of potential and established synapses remained comparable. Topological and spatial properties, however, differed: Neurons that started axon growth early on in serial growth achieved higher out-degrees, higher local efficiency and longer axon lengths while neurons demonstrated more homogeneous connectivity patterns for parallel growth. Second, connection probability decreased more rapidly with distance between neurons for parallel growth than for serial growth. Third, bidirectional connections were more numerous for parallel growth. Finally, we tested our predictions with C. elegans data. Together, this indicates that time windows for axon growth influence the topological and spatial properties of neuronal networks opening up the possibility to a posteriori estimate developmental mechanisms based on network properties of a developed network.

Parallel consensual neural networks.

PubMed

Benediktsson, J A; Sveinsson, J R; Ersoy, O K; Swain, P H

1997-01-01

A new type of a neural-network architecture, the parallel consensual neural network (PCNN), is introduced and applied in classification/data fusion of multisource remote sensing and geographic data. The PCNN architecture is based on statistical consensus theory and involves using stage neural networks with transformed input data. The input data are transformed several times and the different transformed data are used as if they were independent inputs. The independent inputs are first classified using the stage neural networks. The output responses from the stage networks are then weighted and combined to make a consensual decision. In this paper, optimization methods are used in order to weight the outputs from the stage networks. Two approaches are proposed to compute the data transforms for the PCNN, one for binary data and another for analog data. The analog approach uses wavelet packets. The experimental results obtained with the proposed approach show that the PCNN outperforms both a conjugate-gradient backpropagation neural network and conventional statistical methods in terms of overall classification accuracy of test data.

PREMER: a Tool to Infer Biological Networks.

PubMed

Villaverde, Alejandro F; Becker, Kolja; Banga, Julio R

2017-10-04

Inferring the structure of unknown cellular networks is a main challenge in computational biology. Data-driven approaches based on information theory can determine the existence of interactions among network nodes automatically. However, the elucidation of certain features - such as distinguishing between direct and indirect interactions or determining the direction of a causal link - requires estimating information-theoretic quantities in a multidimensional space. This can be a computationally demanding task, which acts as a bottleneck for the application of elaborate algorithms to large-scale network inference problems. The computational cost of such calculations can be alleviated by the use of compiled programs and parallelization. To this end we have developed PREMER (Parallel Reverse Engineering with Mutual information & Entropy Reduction), a software toolbox that can run in parallel and sequential environments. It uses information theoretic criteria to recover network topology and determine the strength and causality of interactions, and allows incorporating prior knowledge, imputing missing data, and correcting outliers. PREMER is a free, open source software tool that does not require any commercial software. Its core algorithms are programmed in FORTRAN 90 and implement OpenMP directives. It has user interfaces in Python and MATLAB/Octave, and runs on Windows, Linux and OSX (https://sites.google.com/site/premertoolbox/).

MapReduce Based Parallel Bayesian Network for Manufacturing Quality Control

NASA Astrophysics Data System (ADS)

Zheng, Mao-Kuan; Ming, Xin-Guo; Zhang, Xian-Yu; Li, Guo-Ming

2017-09-01

Increasing complexity of industrial products and manufacturing processes have challenged conventional statistics based quality management approaches in the circumstances of dynamic production. A Bayesian network and big data analytics integrated approach for manufacturing process quality analysis and control is proposed. Based on Hadoop distributed architecture and MapReduce parallel computing model, big volume and variety quality related data generated during the manufacturing process could be dealt with. Artificial intelligent algorithms, including Bayesian network learning, classification and reasoning, are embedded into the Reduce process. Relying on the ability of the Bayesian network in dealing with dynamic and uncertain problem and the parallel computing power of MapReduce, Bayesian network of impact factors on quality are built based on prior probability distribution and modified with posterior probability distribution. A case study on hull segment manufacturing precision management for ship and offshore platform building shows that computing speed accelerates almost directly proportionally to the increase of computing nodes. It is also proved that the proposed model is feasible for locating and reasoning of root causes, forecasting of manufacturing outcome, and intelligent decision for precision problem solving. The integration of bigdata analytics and BN method offers a whole new perspective in manufacturing quality control.

Microelectromechanical filter formed from parallel-connected lattice networks of contour-mode resonators

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

Wojciechowski, Kenneth E; Olsson, III, Roy H; Ziaei-Moayyed, Maryam

2013-07-30

A microelectromechanical (MEM) filter is disclosed which has a plurality of lattice networks formed on a substrate and electrically connected together in parallel. Each lattice network has a series resonant frequency and a shunt resonant frequency provided by one or more contour-mode resonators in the lattice network. Different types of contour-mode resonators including single input, single output resonators, differential resonators, balun resonators, and ring resonators can be used in MEM filter. The MEM filter can have a center frequency in the range of 10 MHz-10 GHz, with a filter bandwidth of up to about 1% when all of the latticemore » networks have the same series resonant frequency and the same shunt resonant frequency. The filter bandwidth can be increased up to about 5% by using unique series and shunt resonant frequencies for the lattice networks.« less

Embedding global and collective in a torus network with message class map based tree path selection

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

Chen, Dong; Coteus, Paul W.; Eisley, Noel A.

Embodiments of the invention provide a method, system and computer program product for embedding a global barrier and global interrupt network in a parallel computer system organized as a torus network. The computer system includes a multitude of nodes. In one embodiment, the method comprises taking inputs from a set of receivers of the nodes, dividing the inputs from the receivers into a plurality of classes, combining the inputs of each of the classes to obtain a result, and sending said result to a set of senders of the nodes. Embodiments of the invention provide a method, system and computermore » program product for embedding a collective network in a parallel computer system organized as a torus network. In one embodiment, the method comprises adding to a torus network a central collective logic to route messages among at least a group of nodes in a tree structure.« less

Dispatching packets on a global combining network of a parallel computer

DOEpatents

Almasi, Gheorghe [Ardsley, NY; Archer, Charles J [Rochester, MN

2011-07-19

Methods, apparatus, and products are disclosed for dispatching packets on a global combining network of a parallel computer comprising a plurality of nodes connected for data communications using the network capable of performing collective operations and point to point operations that include: receiving, by an origin system messaging module on an origin node from an origin application messaging module on the origin node, a storage identifier and an operation identifier, the storage identifier specifying storage containing an application message for transmission to a target node, and the operation identifier specifying a message passing operation; packetizing, by the origin system messaging module, the application message into network packets for transmission to the target node, each network packet specifying the operation identifier and an operation type for the message passing operation specified by the operation identifier; and transmitting, by the origin system messaging module, the network packets to the target node.

Coverage-Dependent Anchoring of 4,4'-Biphenyl Dicarboxylic Acid to CoO(111) Thin Films.

PubMed

Mohr, Susanne; Schmitt, Tobias; Döpper, Tibor; Xiang, Feifei; Schwarz, Matthias; Görling, Andreas; Schneider, M Alexander; Libuda, Jörg

2017-05-02

We investigated the adsorption behavior of 4,4'-biphenhyl dicarboxylic acid (BDA) on well-ordered CoO(111) films grown on Ir(100) as a function of coverage and temperature using time-resolved and temperature-programmed infrared reflection absorption spectroscopy (TR-IRAS, TP-IRAS) in combination with density functional theory (DFT) and scanning tunneling microscopy (STM) under ultrahigh vacuum (UHV) conditions. To compare the binding behavior of BDA as a function of the oxide film thickness, three different CoO(111) film thicknesses were explored: films of about 20 bilayers (BLs) (approximately 5 nm), 2 BLs, and 1 BL. The two carboxylic acid groups of BDA offer two potential anchoring points to the oxide surface. At 150 K, intact BDA adsorbs on 20 BL thick oxide films in planar geometry with the phenyl rings aligned parallel to the surface. With decreasing oxide film thickness, we observe an increasing tendency for deprotonation and the formation of flat-lying BDA molecules anchored as dicarboxylates. After saturation of the first monolayer, intact BDA multilayers grow with molecules aligned parallel to the surface. The BDA multilayer desorbs at around 360 K. Completely different growth behavior is observed if BDA is deposited above the multilayer desorption temperature. Initially, doubly deprotonated dicarboxylates are formed by adopting a flat-lying orientation. With increasing exposure, however, the adsorbate layer transforms into upright standing monocarboxylates. A sharp OH stretching band (3584 cm -1 ) and a blue-shifted CO stretching band (1759 cm -1 ) indicate weakly interacting apical carboxylic acid groups at the vacuum interface. The anchored monocarboxylate phase slowly desorbs in a temperature range of up to 470 K. At higher temperature, a flat-lying doubly deprotonated BDA is formed, which desorbs and decomposes in a temperature range of up to 600 K.

A Novel, Highly Stable Fold of the Immunoglobulin Binding Domain of Streptococcal Protein G

NASA Astrophysics Data System (ADS)

Gronenborn, Angela M.; Filpula, David R.; Essig, Nina Z.; Achari, Aniruddha; Whitlow, Marc; Wingfield, Paul T.; Marius Clore, G.

1991-08-01

The high-resolution three-dimensional structure of a single immunoglobulin binding domain (B1, which comprises 56 residues including the NH_2-terminal Met) of protein G from group G Streptococcus has been determined in solution by nuclear magnetic resonance spectroscopy on the basis of 1058 experimental restraints. The average atomic root-mean-square distribution about the mean coordinate positions is 0.27 angstrom (overset{circ}{mathrm A}) for the backbone atoms, 0.65 overset{circ}{mathrm A} for all atoms, and 0.39 overset{circ}{mathrm A} for atoms excluding disordered surface side chains. The structure has no disulfide bridges and is composed of a four-stranded β sheet, on top of which lies a long helix. The central two strands (β 1 and β 4), comprising the NH_2- and COOH-termini, are parallel, and the outer two strands (β 2 and β 3) are connected by the helix in a +3x crossover. This novel topology (-1, +3x, -1), coupled with an extensive hydrogen-bonding network and a tightly packed and buried hydrophobic core, is probably responsible for the extreme thermal stability of this small domain (reversible melting at 87^circC).

An Artificial Neural Networks Method for Solving Partial Differential Equations

NASA Astrophysics Data System (ADS)

Alharbi, Abir

2010-09-01

While there already exists many analytical and numerical techniques for solving PDEs, this paper introduces an approach using artificial neural networks. The approach consists of a technique developed by combining the standard numerical method, finite-difference, with the Hopfield neural network. The method is denoted Hopfield-finite-difference (HFD). The architecture of the nets, energy function, updating equations, and algorithms are developed for the method. The HFD method has been used successfully to approximate the solution of classical PDEs, such as the Wave, Heat, Poisson and the Diffusion equations, and on a system of PDEs. The software Matlab is used to obtain the results in both tabular and graphical form. The results are similar in terms of accuracy to those obtained by standard numerical methods. In terms of speed, the parallel nature of the Hopfield nets methods makes them easier to implement on fast parallel computers while some numerical methods need extra effort for parallelization.

Locating hardware faults in a parallel computer

DOEpatents

Archer, Charles J.; Megerian, Mark G.; Ratterman, Joseph D.; Smith, Brian E.

2010-04-13

Locating hardware faults in a parallel computer, including defining within a tree network of the parallel computer two or more sets of non-overlapping test levels of compute nodes of the network that together include all the data communications links of the network, each non-overlapping test level comprising two or more adjacent tiers of the tree; defining test cells within each non-overlapping test level, each test cell comprising a subtree of the tree including a subtree root compute node and all descendant compute nodes of the subtree root compute node within a non-overlapping test level; performing, separately on each set of non-overlapping test levels, an uplink test on all test cells in a set of non-overlapping test levels; and performing, separately from the uplink tests and separately on each set of non-overlapping test levels, a downlink test on all test cells in a set of non-overlapping test levels.

Locating hardware faults in a data communications network of a parallel computer

DOEpatents

Archer, Charles J.; Megerian, Mark G.; Ratterman, Joseph D.; Smith, Brian E.

2010-01-12

Hardware faults location in a data communications network of a parallel computer. Such a parallel computer includes a plurality of compute nodes and a data communications network that couples the compute nodes for data communications and organizes the compute node as a tree. Locating hardware faults includes identifying a next compute node as a parent node and a root of a parent test tree, identifying for each child compute node of the parent node a child test tree having the child compute node as root, running a same test suite on the parent test tree and each child test tree, and identifying the parent compute node as having a defective link connected from the parent compute node to a child compute node if the test suite fails on the parent test tree and succeeds on all the child test trees.

A Short-Circuit Method for Networks.

ERIC Educational Resources Information Center

Ong, P. P.

1983-01-01

Describes a method of network analysis that allows avoidance of Kirchoff's Laws (providing the network is symmetrical) by reduction to simple series/parallel resistances. The method can be extended to symmetrical alternating current, capacitance or inductance if corresponding theorems are used. Symmetric cubic network serves as an example. (JM)

Discontinuous solutions of Hamilton-Jacobi equations on networks

NASA Astrophysics Data System (ADS)

Graber, P. J.; Hermosilla, C.; Zidani, H.

2017-12-01

This paper studies optimal control problems on networks without controllability assumptions at the junctions. The Value Function associated with the control problem is characterized as the solution to a system of Hamilton-Jacobi equations with appropriate junction conditions. The novel feature of the result lies in that the controllability conditions are not needed and the characterization remains valid even when the Value Function is not continuous.

Configuring compute nodes of a parallel computer in an operational group into a plurality of independent non-overlapping collective networks

DOEpatents

Archer, Charles J.; Inglett, Todd A.; Ratterman, Joseph D.; Smith, Brian E.

2010-03-02

Methods, apparatus, and products are disclosed for configuring compute nodes of a parallel computer in an operational group into a plurality of independent non-overlapping collective networks, the compute nodes in the operational group connected together for data communications through a global combining network, that include: partitioning the compute nodes in the operational group into a plurality of non-overlapping subgroups; designating one compute node from each of the non-overlapping subgroups as a master node; and assigning, to the compute nodes in each of the non-overlapping subgroups, class routing instructions that organize the compute nodes in that non-overlapping subgroup as a collective network such that the master node is a physical root.

Multirate parallel distributed compensation of a cluster in wireless sensor and actor networks

NASA Astrophysics Data System (ADS)

Yang, Chun-xi; Huang, Ling-yun; Zhang, Hao; Hua, Wang

2016-01-01

The stabilisation problem for one of the clusters with bounded multiple random time delays and packet dropouts in wireless sensor and actor networks is investigated in this paper. A new multirate switching model is constructed to describe the feature of this single input multiple output linear system. According to the difficulty of controller design under multi-constraints in multirate switching model, this model can be converted to a Takagi-Sugeno fuzzy model. By designing a multirate parallel distributed compensation, a sufficient condition is established to ensure this closed-loop fuzzy control system to be globally exponentially stable. The solution of the multirate parallel distributed compensation gains can be obtained by solving an auxiliary convex optimisation problem. Finally, two numerical examples are given to show, compared with solving switching controller, multirate parallel distributed compensation can be obtained easily. Furthermore, it has stronger robust stability than arbitrary switching controller and single-rate parallel distributed compensation under the same conditions.

Distributed computing methodology for training neural networks in an image-guided diagnostic application.

PubMed

Plagianakos, V P; Magoulas, G D; Vrahatis, M N

2006-03-01

Distributed computing is a process through which a set of computers connected by a network is used collectively to solve a single problem. In this paper, we propose a distributed computing methodology for training neural networks for the detection of lesions in colonoscopy. Our approach is based on partitioning the training set across multiple processors using a parallel virtual machine. In this way, interconnected computers of varied architectures can be used for the distributed evaluation of the error function and gradient values, and, thus, training neural networks utilizing various learning methods. The proposed methodology has large granularity and low synchronization, and has been implemented and tested. Our results indicate that the parallel virtual machine implementation of the training algorithms developed leads to considerable speedup, especially when large network architectures and training sets are used.

6-(4-Nitro­phen­oxy)hexa­nol

PubMed Central

Saif Ullah Khan, Muhammad; Akhter, Zareen; Bolte, Michael; Cheema, Sajjad A.; Siddiqi, Humaira M.

2009-01-01

The title compound, C12H17NO4, features an almost planar mol­ecule (r.m.s. deviation for all non-H atoms = 0.070 Å). All methyl­ene C—C bonds adopt an anti­periplanar conformation. In the crystal structure the mol­ecules lie in planes parallel to (12) and the packing is stabilized by O—H⋯O hydrogen bonds. PMID:21583147

dfnWorks: A discrete fracture network framework for modeling subsurface flow and transport

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

Hyman, Jeffrey D.; Karra, Satish; Makedonska, Nataliia

DFNWORKS is a parallelized computational suite to generate three-dimensional discrete fracture networks (DFN) and simulate flow and transport. Developed at Los Alamos National Laboratory over the past five years, it has been used to study flow and transport in fractured media at scales ranging from millimeters to kilometers. The networks are created and meshed using DFNGEN, which combines FRAM (the feature rejection algorithm for meshing) methodology to stochastically generate three-dimensional DFNs with the LaGriT meshing toolbox to create a high-quality computational mesh representation. The representation produces a conforming Delaunay triangulation suitable for high performance computing finite volume solvers in anmore » intrinsically parallel fashion. Flow through the network is simulated in dfnFlow, which utilizes the massively parallel subsurface flow and reactive transport finite volume code PFLOTRAN. A Lagrangian approach to simulating transport through the DFN is adopted within DFNTRANS to determine pathlines and solute transport through the DFN. Example applications of this suite in the areas of nuclear waste repository science, hydraulic fracturing and CO 2 sequestration are also included.« less

dfnWorks: A discrete fracture network framework for modeling subsurface flow and transport

DOE PAGES

Hyman, Jeffrey D.; Karra, Satish; Makedonska, Nataliia; ...

2015-11-01

DFNWORKS is a parallelized computational suite to generate three-dimensional discrete fracture networks (DFN) and simulate flow and transport. Developed at Los Alamos National Laboratory over the past five years, it has been used to study flow and transport in fractured media at scales ranging from millimeters to kilometers. The networks are created and meshed using DFNGEN, which combines FRAM (the feature rejection algorithm for meshing) methodology to stochastically generate three-dimensional DFNs with the LaGriT meshing toolbox to create a high-quality computational mesh representation. The representation produces a conforming Delaunay triangulation suitable for high performance computing finite volume solvers in anmore » intrinsically parallel fashion. Flow through the network is simulated in dfnFlow, which utilizes the massively parallel subsurface flow and reactive transport finite volume code PFLOTRAN. A Lagrangian approach to simulating transport through the DFN is adopted within DFNTRANS to determine pathlines and solute transport through the DFN. Example applications of this suite in the areas of nuclear waste repository science, hydraulic fracturing and CO 2 sequestration are also included.« less

Photochemical numerics for global-scale modeling: Fidelity and GCM testing

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

Elliott, S.; Jim Kao, Chih-Yue; Zhao, X.

1995-03-01

Atmospheric photochemistry lies at the heart of global-scale pollution problems, but it is a nonlinear system embedded in nonlinear transport and so must be modeled in three dimensions. Total earth grids are massive and kinetics require dozens of interacting tracers, taxing supercomputers to their limits in global calculations. A matrix-free and noniterative family scheme is described that permits chemical step sizes an order of magnitude or more larger than time constants for molecular groupings, in the 1-h range used for transport. Families are partitioned through linearized implicit integrations that produce stabilizing species concentrations for a mass-conserving forward solver. The kineticsmore » are also parallelized by moving geographic loops innermost and changes in the continuity equations are automated through list reading. The combination of speed, parallelization and automation renders the programs naturally modular. Accuracy lies within 1% for all species in week-long fidelity tests. A 50-species, 150-reaction stratospheric module tested in a spectral GCM benchmarks at 10 min CPU time per day and agrees with lower-dimensionality simulations. Tropospheric nonmethane hydrocarbon chemistry will soon be added, and inherently three-dimensional phenomena will be investigated both decoupled from dynamics and in a complete chemical GCM. 225 refs., 11 figs., 2 tabs.« less

Numerical Experiments on Advective Transport in Large Three-Dimensional Discrete Fracture Networks

NASA Astrophysics Data System (ADS)

Makedonska, N.; Painter, S. L.; Karra, S.; Gable, C. W.

2013-12-01

Modeling of flow and solute transport in discrete fracture networks is an important approach for understanding the migration of contaminants in impermeable hard rocks such as granite, where fractures provide dominant flow and transport pathways. The discrete fracture network (DFN) model attempts to mimic discrete pathways for fluid flow through a fractured low-permeable rock mass, and may be combined with particle tracking simulations to address solute transport. However, experience has shown that it is challenging to obtain accurate transport results in three-dimensional DFNs because of the high computational burden and difficulty in constructing a high-quality unstructured computational mesh on simulated fractures. An integrated DFN meshing [1], flow, and particle tracking [2] simulation capability that enables accurate flow and particle tracking simulation on large DFNs has recently been developed. The new capability has been used in numerical experiments on advective transport in large DFNs with tens of thousands of fractures and millions of computational cells. The modeling procedure starts from the fracture network generation using a stochastic model derived from site data. A high-quality computational mesh is then generated [1]. Flow is then solved using the highly parallel PFLOTRAN [3] code. PFLOTRAN uses the finite volume approach, which is locally mass conserving and thus eliminates mass balance problems during particle tracking. The flow solver provides the scalar fluxes on each control volume face. From the obtained fluxes the Darcy velocity is reconstructed for each node in the network [4]. Velocities can then be continuously interpolated to any point in the domain of interest, thus enabling random walk particle tracking. In order to describe the flow field on fractures intersections, the control volume cells on intersections are split into four planar polygons, where each polygon corresponds to a piece of a fracture near the intersection line. Thus, computational nodes lying on fracture intersections have four associated velocities, one on each side of the intersection in each fracture plane [2]. This information is used to route particles arriving at the fracture intersection to the appropriate downstream fracture segment. Verified for small DFNs, the new simulation capability allows accurate particle tracking on more realistic representations of fractured rock sites. In the current work we focus on travel time statistics and spatial dispersion and show numerical results in DFNs of different sizes, fracture densities, and transmissivity distributions. [1] Hyman J.D., Gable C.W., Painter S.L., Automated meshing of stochastically generated discrete fracture networks, Abstract H33G-1403, 2011 AGU, San Francisco, CA, 5-9 Dec. [2] N. Makedonska, S. L. Painter, T.-L. Hsieh, Q.M. Bui, and C. W. Gable., Development and verification of a new particle tracking capability for modeling radionuclide transport in discrete fracture networks, Abstract, 2013 IHLRWM, Albuquerque, NM, Apr. 28 - May 3. [3] Lichtner, P.C., Hammond, G.E., Bisht, G., Karra, S., Mills, R.T., and Kumar, J. (2013) PFLOTRAN User's Manual: A Massively Parallel Reactive Flow Code. [4] Painter S.L., Gable C.W., Kelkar S., Pathline tracing on fully unstructured control-volume grids, Computational Geosciences, 16 (4), 2012, 1125-1134.

Changes in collagen fibril network organization and proteoglycan distribution in equine articular cartilage during maturation and growth

PubMed Central

Hyttinen, Mika M; Holopainen, Jaakko; René van Weeren, P; Firth, Elwyn C; Helminen, Heikki J; Brama, Pieter A J

2009-01-01

The aim of this study was to record growth-related changes in collagen network organization and proteoglycan distribution in intermittently peak-loaded and continuously lower-level-loaded articular cartilage. Cartilage from the proximal phalangeal bone of the equine metacarpophalangeal joint at birth, at 5, 11 and 18 months, and at 6–10 years of age was collected from two sites. Site 1, at the joint margin, is unloaded at slow gaits but is subjected to high-intensity loading during athletic activity; site 2 is a continuously but less intensively loaded site in the centre of the joint. The degree of collagen parallelism was determined with quantitative polarized light microscopy and the parallelism index for collagen fibrils was computed from the cartilage surface to the osteochondral junction. Concurrent changes in the proteoglycan distribution were quantified with digital densitometry. We found that the parallelism index increased significantly with age (up to 90%). At birth, site 2 exhibited a more organized collagen network than site 1. In adult horses this situation was reversed. The superficial and intermediate zones exhibited the greatest reorganization of collagen. Site 1 had a higher proteoglycan content than site 2 at birth but here too the situation was reversed in adult horses. We conclude that large changes in joint loading during growth and maturation in the period from birth to adulthood profoundly affect the architecture of the collagen network in equine cartilage. In addition, the distribution and content of proteoglycans are modified significantly by altered joint use. Intermittent peak-loading with shear seems to induce higher collagen parallelism and a lower proteoglycan content in cartilage than more constant weight-bearing. Therefore, we hypothesize that the formation of mature articular cartilage with a highly parallel collagen network and relatively low proteoglycan content in the peak-loaded area of a joint is needed to withstand intermittent stress and shear, whereas a constantly weight-bearing joint area benefits from lower collagen parallelism and a higher proteoglycan content. PMID:19732210

Multiprocessor graphics computation and display using transputers

NASA Technical Reports Server (NTRS)

Ellis, Graham K.

1988-01-01

A package of two-dimensional graphics routines was developed to run on a transputer-based parallel processing system. These routines were designed to enable applications programmers to easily generate and display results from the transputer network in a graphic format. The graphics procedures were designed for the lowest possible network communication overhead for increased performance. The routines were designed for ease of use and to present an intuitive approach to generating graphics on the transputer parallel processing system.

Mechanical Behavior of Collagen-Fibrin Co-Gels Reflects Transition From Series to Parallel Interactions With Increasing Collagen Content

PubMed Central

Lai, Victor K.; Lake, Spencer P.; Frey, Christina R.; Tranquillo, Robert T.; Barocas, Victor H.

2012-01-01

Fibrin and collagen, biopolymers occurring naturally in the body, are biomaterials commonly-used as scaffolds for tissue engineering. How collagen and fibrin interact to confer macroscopic mechanical properties in collagen-fibrin composite systems remains poorly understood. In this study, we formulated collagen-fibrin co-gels at different collagen-tofibrin ratios to observe changes in the overall mechanical behavior and microstructure. A modeling framework of a two-network system was developed by modifying our micro-scale model, considering two forms of interaction between the networks: (a) two interpenetrating but noninteracting networks (“parallel”), and (b) a single network consisting of randomly alternating collagen and fibrin fibrils (“series”). Mechanical testing of our gels show that collagen-fibrin co-gels exhibit intermediate properties (UTS, strain at failure, tangent modulus) compared to those of pure collagen and fibrin. The comparison with model predictions show that the parallel and series model cases provide upper and lower bounds, respectively, for the experimental data, suggesting that a combination of such interactions exists between the collagen and fibrin in co-gels. A transition from the series model to the parallel model occurs with increasing collagen content, with the series model best describing predominantly fibrin co-gels, and the parallel model best describing predominantly collagen co-gels. PMID:22482659

Methods for design and evaluation of parallel computating systems (The PISCES project)

NASA Technical Reports Server (NTRS)

Pratt, Terrence W.; Wise, Robert; Haught, Mary JO

1989-01-01

The PISCES project started in 1984 under the sponsorship of the NASA Computational Structural Mechanics (CSM) program. A PISCES 1 programming environment and parallel FORTRAN were implemented in 1984 for the DEC VAX (using UNIX processes to simulate parallel processes). This system was used for experimentation with parallel programs for scientific applications and AI (dynamic scene analysis) applications. PISCES 1 was ported to a network of Apollo workstations by N. Fitzgerald.

Parallel Simulation of Subsonic Fluid Dynamics on a Cluster of Workstations.

DTIC Science & Technology

1994-11-01

inside wind musical instruments. Typical simulations achieve $80\\%$ parallel efficiency (speedup/processors) using 20 HP-Apollo workstations. Detailed...TERMS AI, MIT, Artificial Intelligence, Distributed Computing, Workstation Cluster, Network, Fluid Dynamics, Musical Instruments 17. SECURITY...for example, the flow of air inside wind musical instruments. Typical simulations achieve 80% parallel efficiency (speedup/processors) using 20 HP

The Brain's Router: A Cortical Network Model of Serial Processing in the Primate Brain

PubMed Central

Zylberberg, Ariel; Fernández Slezak, Diego; Roelfsema, Pieter R.; Dehaene, Stanislas; Sigman, Mariano

2010-01-01

The human brain efficiently solves certain operations such as object recognition and categorization through a massively parallel network of dedicated processors. However, human cognition also relies on the ability to perform an arbitrarily large set of tasks by flexibly recombining different processors into a novel chain. This flexibility comes at the cost of a severe slowing down and a seriality of operations (100–500 ms per step). A limit on parallel processing is demonstrated in experimental setups such as the psychological refractory period (PRP) and the attentional blink (AB) in which the processing of an element either significantly delays (PRP) or impedes conscious access (AB) of a second, rapidly presented element. Here we present a spiking-neuron implementation of a cognitive architecture where a large number of local parallel processors assemble together to produce goal-driven behavior. The precise mapping of incoming sensory stimuli onto motor representations relies on a “router” network capable of flexibly interconnecting processors and rapidly changing its configuration from one task to another. Simulations show that, when presented with dual-task stimuli, the network exhibits parallel processing at peripheral sensory levels, a memory buffer capable of keeping the result of sensory processing on hold, and a slow serial performance at the router stage, resulting in a performance bottleneck. The network captures the detailed dynamics of human behavior during dual-task-performance, including both mean RTs and RT distributions, and establishes concrete predictions on neuronal dynamics during dual-task experiments in humans and non-human primates. PMID:20442869

Elastic relaxation of a truncated circular cylinder with uniform dilatational eigenstrain in a half space

NASA Astrophysics Data System (ADS)

Glas, Frank

2003-06-01

We give a fully analytical solution for the displacement and strain fields generated by the coherent elastic relaxation of a type of misfitting inclusions with uniform dilatational eigenstrain lying in a half space, assuming linear isotropic elasticity. The inclusion considered is an infinitely long circular cylinder having an axis parallel to the free surface and truncated by two arbitrarily positioned planes parallel to this surface. These calculations apply in particular to strained semiconductor quantum wires. The calculations are illustrated by examples showing quantitatively that, depending on the depth of the wire under the free surface, the latter may significantly affect the magnitude and the distribution of the various strain components inside the inclusion as well as in the surrounding matrix.

Engineering of Sensor Network Structure for Dependable Fusion

DTIC Science & Technology

2014-08-15

Lossy Wireless Sensor Networks , IEEE/ACM Transactions on Networking , (04 2013): 0. doi: 10.1109/TNET.2013.2256795 Soumik Sarkar, Kushal Mukherjee...Phoha, Bharat B. Madan, Asok Ray. Distributed Network Control for Mobile Multi-Modal Wireless Sensor Networks , Journal of Parallel and Distributed...Deadline Constraints, IEEE Transactions on Automatic Control special issue on Wireless Sensor and Actuator Networks , (01 2011): 1. doi: Eric Keller

A queueing network model to analyze the impact of parallelization of care on patient cycle time.

PubMed

Jiang, Lixiang; Giachetti, Ronald E

2008-09-01

The total time a patient spends in an outpatient facility, called the patient cycle time, is a major contributor to overall patient satisfaction. A frequently recommended strategy to reduce the total time is to perform some activities in parallel thereby shortening patient cycle time. To analyze patient cycle time this paper extends and improves upon existing multi-class open queueing network model (MOQN) so that the patient flow in an urgent care center can be modeled. Results of the model are analyzed using data from an urgent care center contemplating greater parallelization of patient care activities. The results indicate that parallelization can reduce the cycle time for those patient classes which require more than one diagnostic and/ or treatment intervention. However, for many patient classes there would be little if any improvement, indicating the importance of tools to analyze business process reengineering rules. The paper makes contributions by implementing an approximation for fork/join queues in the network and by improving the approximation for multiple server queues in both low traffic and high traffic conditions. We demonstrate the accuracy of the MOQN results through comparisons to simulation results.

Extensions to the Parallel Real-Time Artificial Intelligence System (PRAIS) for fault-tolerant heterogeneous cycle-stealing reasoning

NASA Technical Reports Server (NTRS)

Goldstein, David

1991-01-01

Extensions to an architecture for real-time, distributed (parallel) knowledge-based systems called the Parallel Real-time Artificial Intelligence System (PRAIS) are discussed. PRAIS strives for transparently parallelizing production (rule-based) systems, even under real-time constraints. PRAIS accomplished these goals (presented at the first annual C Language Integrated Production System (CLIPS) conference) by incorporating a dynamic task scheduler, operating system extensions for fact handling, and message-passing among multiple copies of CLIPS executing on a virtual blackboard. This distributed knowledge-based system tool uses the portability of CLIPS and common message-passing protocols to operate over a heterogeneous network of processors. Results using the original PRAIS architecture over a network of Sun 3's, Sun 4's and VAX's are presented. Mechanisms using the producer-consumer model to extend the architecture for fault-tolerance and distributed truth maintenance initiation are also discussed.

Accurate prediction of protein–protein interactions from sequence alignments using a Bayesian method

PubMed Central

Burger, Lukas; van Nimwegen, Erik

2008-01-01

Accurate and large-scale prediction of protein–protein interactions directly from amino-acid sequences is one of the great challenges in computational biology. Here we present a new Bayesian network method that predicts interaction partners using only multiple alignments of amino-acid sequences of interacting protein domains, without tunable parameters, and without the need for any training examples. We first apply the method to bacterial two-component systems and comprehensively reconstruct two-component signaling networks across all sequenced bacteria. Comparisons of our predictions with known interactions show that our method infers interaction partners genome-wide with high accuracy. To demonstrate the general applicability of our method we show that it also accurately predicts interaction partners in a recent dataset of polyketide synthases. Analysis of the predicted genome-wide two-component signaling networks shows that cognates (interacting kinase/regulator pairs, which lie adjacent on the genome) and orphans (which lie isolated) form two relatively independent components of the signaling network in each genome. In addition, while most genes are predicted to have only a small number of interaction partners, we find that 10% of orphans form a separate class of ‘hub' nodes that distribute and integrate signals to and from up to tens of different interaction partners. PMID:18277381

Parallel Computing for Probabilistic Response Analysis of High Temperature Composites

NASA Technical Reports Server (NTRS)

Sues, R. H.; Lua, Y. J.; Smith, M. D.

1994-01-01

The objective of this Phase I research was to establish the required software and hardware strategies to achieve large scale parallelism in solving PCM problems. To meet this objective, several investigations were conducted. First, we identified the multiple levels of parallelism in PCM and the computational strategies to exploit these parallelisms. Next, several software and hardware efficiency investigations were conducted. These involved the use of three different parallel programming paradigms and solution of two example problems on both a shared-memory multiprocessor and a distributed-memory network of workstations.

Application Portable Parallel Library

NASA Technical Reports Server (NTRS)

Cole, Gary L.; Blech, Richard A.; Quealy, Angela; Townsend, Scott

1995-01-01

Application Portable Parallel Library (APPL) computer program is subroutine-based message-passing software library intended to provide consistent interface to variety of multiprocessor computers on market today. Minimizes effort needed to move application program from one computer to another. User develops application program once and then easily moves application program from parallel computer on which created to another parallel computer. ("Parallel computer" also include heterogeneous collection of networked computers). Written in C language with one FORTRAN 77 subroutine for UNIX-based computers and callable from application programs written in C language or FORTRAN 77.

An executable specification for the message processor in a simple combining network

NASA Technical Reports Server (NTRS)

Middleton, David

1995-01-01

While the primary function of the network in a parallel computer is to communicate data between processors, it is often useful if the network can also perform rudimentary calculations. That is, some simple processing ability in the network itself, particularly for performing parallel prefix computations, can reduce both the volume of data being communicated and the computational load on the processors proper. Unfortunately, typical implementations of such networks require a large fraction of the hardware budget, and so combining networks are viewed as being impractical. The FFP Machine has such a combining network, and various characteristics of the machine allow a good deal of simplification in the network design. Despite being simple in construction however, the network relies on many subtle details to work correctly. This paper describes an executable model of the network which will serve several purposes. It provides a complete and detailed description of the network which can substantiate its ability to support necessary functions. It provides an environment in which algorithms to be run on the network can be designed and debugged more easily than they would on physical hardware. Finally, it provides the foundation for exploring the design of the message receiving facility which connects the network to the individual processors.

The ARPANET after twenty years

NASA Technical Reports Server (NTRS)

Denning, Peter J.

1989-01-01

The ARPANET began operations in 1969 with four nodes as an experiment in resource sharing among computers. It has evolved into a worldwide research network of over 60,000 nodes, influencing the design of other networks in business, education, and government. It demonstrated the speed and reliability of packet-switching networks. Its protocols have served as the models for international standards. And yet the significance of the ARPANET lies not in its technology, but in the profound alterations networking has produced in human practices. Network designers must now turn their attention to the discourses of scientific technology, business, education, and government that are being mixed together in the milieux of networking, and in particular the conflicts and misunderstandings that arise from the different world views of these discourses.

Load Forecasting Based Distribution System Network Reconfiguration -- A Distributed Data-Driven Approach

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

Jiang, Huaiguang; Zhang, Yingchen; Muljadi, Eduard

In this paper, a short-term load forecasting approach based network reconfiguration is proposed in a parallel manner. Specifically, a support vector regression (SVR) based short-term load forecasting approach is designed to provide an accurate load prediction and benefit the network reconfiguration. Because of the nonconvexity of the three-phase balanced optimal power flow, a second-order cone program (SOCP) based approach is used to relax the optimal power flow problem. Then, the alternating direction method of multipliers (ADMM) is used to compute the optimal power flow in distributed manner. Considering the limited number of the switches and the increasing computation capability, themore » proposed network reconfiguration is solved in a parallel way. The numerical results demonstrate the feasible and effectiveness of the proposed approach.« less

Analysis of 100Mb/s Ethernet for the Whitney Commodity Computing Testbed

NASA Technical Reports Server (NTRS)

Fineberg, Samuel A.; Pedretti, Kevin T.; Kutler, Paul (Technical Monitor)

1997-01-01

We evaluate the performance of a Fast Ethernet network configured with a single large switch, a single hub, and a 4x4 2D torus topology in a testbed cluster of "commodity" Pentium Pro PCs. We also evaluated a mixed network composed of ethernet hubs and switches. An MPI collective communication benchmark, and the NAS Parallel Benchmarks version 2.2 (NPB2) show that the torus network performs best for all sizes that we were able to test (up to 16 nodes). For larger networks the ethernet switch outperforms the hub, though its performance is far less than peak. The hub/switch combination tests indicate that the NAS parallel benchmarks are relatively insensitive to hub densities of less than 7 nodes per hub.

Graphics Processing Unit–Enhanced Genetic Algorithms for Solving the Temporal Dynamics of Gene Regulatory Networks

PubMed Central

García-Calvo, Raúl; Guisado, JL; Diaz-del-Rio, Fernando; Córdoba, Antonio; Jiménez-Morales, Francisco

2018-01-01

Understanding the regulation of gene expression is one of the key problems in current biology. A promising method for that purpose is the determination of the temporal dynamics between known initial and ending network states, by using simple acting rules. The huge amount of rule combinations and the nonlinear inherent nature of the problem make genetic algorithms an excellent candidate for finding optimal solutions. As this is a computationally intensive problem that needs long runtimes in conventional architectures for realistic network sizes, it is fundamental to accelerate this task. In this article, we study how to develop efficient parallel implementations of this method for the fine-grained parallel architecture of graphics processing units (GPUs) using the compute unified device architecture (CUDA) platform. An exhaustive and methodical study of various parallel genetic algorithm schemes—master-slave, island, cellular, and hybrid models, and various individual selection methods (roulette, elitist)—is carried out for this problem. Several procedures that optimize the use of the GPU’s resources are presented. We conclude that the implementation that produces better results (both from the performance and the genetic algorithm fitness perspectives) is simulating a few thousands of individuals grouped in a few islands using elitist selection. This model comprises 2 mighty factors for discovering the best solutions: finding good individuals in a short number of generations, and introducing genetic diversity via a relatively frequent and numerous migration. As a result, we have even found the optimal solution for the analyzed gene regulatory network (GRN). In addition, a comparative study of the performance obtained by the different parallel implementations on GPU versus a sequential application on CPU is carried out. In our tests, a multifold speedup was obtained for our optimized parallel implementation of the method on medium class GPU over an equivalent sequential single-core implementation running on a recent Intel i7 CPU. This work can provide useful guidance to researchers in biology, medicine, or bioinformatics in how to take advantage of the parallelization on massively parallel devices and GPUs to apply novel metaheuristic algorithms powered by nature for real-world applications (like the method to solve the temporal dynamics of GRNs). PMID:29662297

Graphics Processing Unit-Enhanced Genetic Algorithms for Solving the Temporal Dynamics of Gene Regulatory Networks.

PubMed

García-Calvo, Raúl; Guisado, J L; Diaz-Del-Rio, Fernando; Córdoba, Antonio; Jiménez-Morales, Francisco

2018-01-01

Understanding the regulation of gene expression is one of the key problems in current biology. A promising method for that purpose is the determination of the temporal dynamics between known initial and ending network states, by using simple acting rules. The huge amount of rule combinations and the nonlinear inherent nature of the problem make genetic algorithms an excellent candidate for finding optimal solutions. As this is a computationally intensive problem that needs long runtimes in conventional architectures for realistic network sizes, it is fundamental to accelerate this task. In this article, we study how to develop efficient parallel implementations of this method for the fine-grained parallel architecture of graphics processing units (GPUs) using the compute unified device architecture (CUDA) platform. An exhaustive and methodical study of various parallel genetic algorithm schemes-master-slave, island, cellular, and hybrid models, and various individual selection methods (roulette, elitist)-is carried out for this problem. Several procedures that optimize the use of the GPU's resources are presented. We conclude that the implementation that produces better results (both from the performance and the genetic algorithm fitness perspectives) is simulating a few thousands of individuals grouped in a few islands using elitist selection. This model comprises 2 mighty factors for discovering the best solutions: finding good individuals in a short number of generations, and introducing genetic diversity via a relatively frequent and numerous migration. As a result, we have even found the optimal solution for the analyzed gene regulatory network (GRN). In addition, a comparative study of the performance obtained by the different parallel implementations on GPU versus a sequential application on CPU is carried out. In our tests, a multifold speedup was obtained for our optimized parallel implementation of the method on medium class GPU over an equivalent sequential single-core implementation running on a recent Intel i7 CPU. This work can provide useful guidance to researchers in biology, medicine, or bioinformatics in how to take advantage of the parallelization on massively parallel devices and GPUs to apply novel metaheuristic algorithms powered by nature for real-world applications (like the method to solve the temporal dynamics of GRNs).

Computer model of a reverberant and parallel circuit coupling

NASA Astrophysics Data System (ADS)

Kalil, Camila de Andrade; de Castro, Maria Clícia Stelling; Cortez, Célia Martins

2017-11-01

The objective of the present study was to deepen the knowledge about the functioning of the neural circuits by implementing a signal transmission model using the Graph Theory in a small network of neurons composed of an interconnected reverberant and parallel circuit, in order to investigate the processing of the signals in each of them and the effects on the output of the network. For this, a program was developed in C language and simulations were done using neurophysiological data obtained in the literature.

Network support for system initiated checkpoints

DOEpatents

Chen, Dong; Heidelberger, Philip

2013-01-29

A system, method and computer program product for supporting system initiated checkpoints in parallel computing systems. The system and method generates selective control signals to perform checkpointing of system related data in presence of messaging activity associated with a user application running at the node. The checkpointing is initiated by the system such that checkpoint data of a plurality of network nodes may be obtained even in the presence of user applications running on highly parallel computers that include ongoing user messaging activity.

Queueing Network Models for Parallel Processing of Task Systems: an Operational Approach

NASA Technical Reports Server (NTRS)

Mak, Victor W. K.

1986-01-01

Computer performance modeling of possibly complex computations running on highly concurrent systems is considered. Earlier works in this area either dealt with a very simple program structure or resulted in methods with exponential complexity. An efficient procedure is developed to compute the performance measures for series-parallel-reducible task systems using queueing network models. The procedure is based on the concept of hierarchical decomposition and a new operational approach. Numerical results for three test cases are presented and compared to those of simulations.

Parallel computing on Unix workstation arrays

NASA Astrophysics Data System (ADS)

Reale, F.; Bocchino, F.; Sciortino, S.

1994-12-01

We have tested arrays of general-purpose Unix workstations used as MIMD systems for massive parallel computations. In particular we have solved numerically a demanding test problem with a 2D hydrodynamic code, generally developed to study astrophysical flows, by exucuting it on arrays either of DECstations 5000/200 on Ethernet LAN, or of DECstations 3000/400, equipped with powerful Alpha processors, on FDDI LAN. The code is appropriate for data-domain decomposition, and we have used a library for parallelization previously developed in our Institute, and easily extended to work on Unix workstation arrays by using the PVM software toolset. We have compared the parallel efficiencies obtained on arrays of several processors to those obtained on a dedicated MIMD parallel system, namely a Meiko Computing Surface (CS-1), equipped with Intel i860 processors. We discuss the feasibility of using non-dedicated parallel systems and conclude that the convenience depends essentially on the size of the computational domain as compared to the relative processor power and network bandwidth. We point out that for future perspectives a parallel development of processor and network technology is important, and that the software still offers great opportunities of improvement, especially in terms of latency times in the message-passing protocols. In conditions of significant gain in terms of speedup, such workstation arrays represent a cost-effective approach to massive parallel computations.

Subglacial Depositional Processes in the Port Askaig Formation (Neoproterozoic) of Ireland

NASA Astrophysics Data System (ADS)

Knight, J.

2004-12-01

The Port Askaig Formation was deposited during the Vendian glaciation (c. 650 Ma) and is a range of tillites that outcrop discontinuously from Banffshire (Scotland) to Connemara (Ireland). Sedimentary structures commonly observed include dropstones and sediment drapes, interpreted as deposition from a floating glacial ice shelf in a shallow marginal sea. Other structures, such as intersecting clastic dikes, have been interpreted as evidence for subaerial exposure of the tillite surface. Exposures of the Port Askaig Formation were examined at its Irish type area at Kiltyfanned Lough, County Donegal. Here, homogeneous sandy beds with internal planar bedding structures are separated by laminated fine sand beds which have erosional upper surfaces. The laminated beds are clast-free and individual laminae are laterally continuous and undisturbed. Larger clasts lie bed-parallel and are draped by overlying beds. Occasionally drapes are asymmetric with a thickened sediment prow, suggestive of flow direction. The clastic dikes are polygonal in plan view, may be isolated or interconnected, and are often arranged in parallel sheets which pinch out laterally. Internally, the clastic dikes are infilled with coarse sand to gravel. Infills are often aligned parallel to dike margins. The presence of draped and deformed sediments suggest a subglacial environment with free water availability. The flat-lying morphology of clasts also favours a subglacial rather than a full marine environment. The morphology and disposition of clastic dikes is interpreted as due to subglacial hydrofracturing of a till sheet and upward passage of sediment-charged water through the fracture zone, which is known from late Pleistocene and Precambrian tillites elsewhere. Variations in water availability can be reconciled by a sub-ice shelf depositional model with spatial and temporal changes in tidally-induced ice-bed coupling.

Functional Alignment of Metabolic Networks.

PubMed

Mazza, Arnon; Wagner, Allon; Ruppin, Eytan; Sharan, Roded

2016-05-01

Network alignment has become a standard tool in comparative biology, allowing the inference of protein function, interaction, and orthology. However, current alignment techniques are based on topological properties of networks and do not take into account their functional implications. Here we propose, for the first time, an algorithm to align two metabolic networks by taking advantage of their coupled metabolic models. These models allow us to assess the functional implications of genes or reactions, captured by the metabolic fluxes that are altered following their deletion from the network. Such implications may spread far beyond the region of the network where the gene or reaction lies. We apply our algorithm to align metabolic networks from various organisms, ranging from bacteria to humans, showing that our alignment can reveal functional orthology relations that are missed by conventional topological alignments.

Epidemiology, the humanities, and public health.

PubMed Central

Weed, D L

1995-01-01

Epidemiologists may benefit from the disciplines of history, philosophy of science, ethics, literature, and art. Within these disciplines lie answers to the questions of who we are, what is right, how to think, and when to act. Studying and participating in the humanities may also help epidemiologists focus their professional concerns on the humanity their methods serve. A parallel phenomenon in the clinical sciences--medical humanities--provides support for the approach (and some lessons). PMID:7604912

Epitaxially Grown Films of Standing and Lying Pentacene Molecules on Cu(110) Surfaces

PubMed Central

2011-01-01

Here, it is shown that pentacene thin films (30 nm) with distinctively different crystallographic structures and molecular orientations can be grown under essentially identical growth conditions in UHV on clean Cu(110) surfaces. By X-ray diffraction, we show that the epitaxially oriented pentacene films crystallize either in the “thin film” phase with standing molecules or in the “single crystal” structure with molecules lying with their long axes parallel to the substrate. The morphology of the samples observed by atomic force microscopy shows an epitaxial alignment of pentacene crystallites, which corroborates the molecular orientation observed by X-ray diffraction pole figures. Low energy electron diffraction measurements reveal that these dissimilar growth behaviors are induced by subtle differences in the monolayer structures formed by slightly different preparation procedures. PMID:21479111

Embedding global barrier and collective in torus network with each node combining input from receivers according to class map for output to senders

DOEpatents

Chen, Dong; Coteus, Paul W; Eisley, Noel A; Gara, Alan; Heidelberger, Philip; Senger, Robert M; Salapura, Valentina; Steinmacher-Burow, Burkhard; Sugawara, Yutaka; Takken, Todd E

2013-08-27

Embodiments of the invention provide a method, system and computer program product for embedding a global barrier and global interrupt network in a parallel computer system organized as a torus network. The computer system includes a multitude of nodes. In one embodiment, the method comprises taking inputs from a set of receivers of the nodes, dividing the inputs from the receivers into a plurality of classes, combining the inputs of each of the classes to obtain a result, and sending said result to a set of senders of the nodes. Embodiments of the invention provide a method, system and computer program product for embedding a collective network in a parallel computer system organized as a torus network. In one embodiment, the method comprises adding to a torus network a central collective logic to route messages among at least a group of nodes in a tree structure.

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

Barrett, Brian; Brightwell, Ronald B.; Grant, Ryan

This report presents a specification for the Portals 4 networ k programming interface. Portals 4 is intended to allow scalable, high-performance network communication betwee n nodes of a parallel computing system. Portals 4 is well suited to massively parallel processing and embedded syste ms. Portals 4 represents an adaption of the data movement layer developed for massively parallel processing platfor ms, such as the 4500-node Intel TeraFLOPS machine. Sandia's Cplant cluster project motivated the development of Version 3.0, which was later extended to Version 3.3 as part of the Cray Red Storm machine and XT line. Version 4 is tarmore » geted to the next generation of machines employing advanced network interface architectures that support enh anced offload capabilities.« less

IQ imbalance tolerable parallel-channel DMT transmission for coherent optical OFDMA access network

NASA Astrophysics Data System (ADS)

Jung, Sang-Min; Mun, Kyoung-Hak; Jung, Sun-Young; Han, Sang-Kook

2016-12-01

Phase diversity of coherent optical communication provides spectrally efficient higher-order modulation for optical communications. However, in-phase/quadrature (IQ) imbalance in coherent optical communication degrades transmission performance by introducing unwanted signal distortions. In a coherent optical orthogonal frequency division multiple access (OFDMA) passive optical network (PON), IQ imbalance-induced signal distortions degrade transmission performance by interferences of mirror subcarriers, inter-symbol interference (ISI), and inter-channel interference (ICI). We propose parallel-channel discrete multitone (DMT) transmission to mitigate transceiver IQ imbalance-induced signal distortions in coherent orthogonal frequency division multiplexing (OFDM) transmissions. We experimentally demonstrate the effectiveness of parallel-channel DMT transmission compared with that of OFDM transmission in the presence of IQ imbalance.

Relationships among classes of self-oscillating transistor parallel inverters. [for power conditioning applications

NASA Technical Reports Server (NTRS)

Wilson, T. G.; Lee, F. C. Y.; Burns, W. W., III; Owen, H. A., Jr.

1975-01-01

It recently has been shown in the literature that many dc-to-square-wave parallel inverters which are widely used in power-conditioning applications can be grouped into one of two families. Each family is characterized by an equivalent RLC network. Based on this approach, a classification procedure is presented for self-oscillating parallel inverters which makes evident natural relationships which exist between various inverter configurations. By utilizing concepts from the basic theory of negative resistance oscillators and the principle of duality as applied to nonlinear networks, a chain of relationships is established which enables a methodical transfer of knowledge gained about one family of inverters to any of the other families in the classification array.

Parallel and orthogonal stimulus in ultradiluted neural networks

NASA Astrophysics Data System (ADS)

Sobral, G. A., Jr.; Vieira, V. M.; Lyra, M. L.; da Silva, C. R.

2006-10-01

Extending a model due to Derrida, Gardner, and Zippelius, we have studied the recognition ability of an extreme and asymmetrically diluted version of the Hopfield model for associative memory by including the effect of a stimulus in the dynamics of the system. We obtain exact results for the dynamic evolution of the average network superposition. The stimulus field was considered as proportional to the overlapping of the state of the system with a particular stimulated pattern. Two situations were analyzed, namely, the external stimulus acting on the initialization pattern (parallel stimulus) and the external stimulus acting on a pattern orthogonal to the initialization one (orthogonal stimulus). In both cases, we obtained the complete phase diagram in the parameter space composed of the stimulus field, thermal noise, and network capacity. Our results show that the system improves its recognition ability for parallel stimulus. For orthogonal stimulus two recognition phases emerge with the system locking at the initialization or stimulated pattern. We confront our analytical results with numerical simulations for the noiseless case T=0 .

Parallel changes of taxonomic interaction networks in lacustrine bacterial communities induced by a polymetallic perturbation

PubMed Central

Laplante, Karine; Sébastien, Boutin; Derome, Nicolas

2013-01-01

Heavy metals released by anthropogenic activities such as mining trigger profound changes to bacterial communities. In this study we used 16S SSU rRNA gene high-throughput sequencing to characterize the impact of a polymetallic perturbation and other environmental parameters on taxonomic networks within five lacustrine bacterial communities from sites located near Rouyn-Noranda, Quebec, Canada. The results showed that community equilibrium was disturbed in terms of both diversity and structure. Moreover, heavy metals, especially cadmium combined with water acidity, induced parallel changes among sites via the selection of resistant OTUs (Operational Taxonomic Unit) and taxonomic dominance perturbations favoring the Alphaproteobacteria. Furthermore, under a similar selective pressure, covariation trends between phyla revealed conservation and parallelism within interphylum interactions. Our study sheds light on the importance of analyzing communities not only from a phylogenetic perspective but also including a quantitative approach to provide significant insights into the evolutionary forces that shape the dynamic of the taxonomic interaction networks in bacterial communities. PMID:23789031

The Software Correlator of the Chinese VLBI Network

NASA Technical Reports Server (NTRS)

Zheng, Weimin; Quan, Ying; Shu, Fengchun; Chen, Zhong; Chen, Shanshan; Wang, Weihua; Wang, Guangli

2010-01-01

The software correlator of the Chinese VLBI Network (CVN) has played an irreplaceable role in the CVN routine data processing, e.g., in the Chinese lunar exploration project. This correlator will be upgraded to process geodetic and astronomical observation data. In the future, with several new stations joining the network, CVN will carry out crustal movement observations, quick UT1 measurements, astrophysical observations, and deep space exploration activities. For the geodetic or astronomical observations, we need a wide-band 10-station correlator. For spacecraft tracking, a realtime and highly reliable correlator is essential. To meet the scientific and navigation requirements of CVN, two parallel software correlators in the multiprocessor environments are under development. A high speed, 10-station prototype correlator using the mixed Pthreads and MPI (Massage Passing Interface) parallel algorithm on a computer cluster platform is being developed. Another real-time software correlator for spacecraft tracking adopts the thread-parallel technology, and it runs on the SMP (Symmetric Multiple Processor) servers. Both correlators have the characteristic of flexible structure and scalability.

Report of the Geological Exploration of the Fortieth Parallel, Volume V: Botany

USGS Publications Warehouse

King, Clarence; Watson, Sereno; Eaton, Daniel C.

1871-01-01

The territory within which botanical collections have been nmade in connection with the United States Geological Survey of the 40th Parallel lies wholly within the limits of Northern Nevada and Utah. It forms a narrow tract at no point exceeding seventy miles in width, between the meridians of 111° and 120°, and extending frorn the parallel of 39° at the southwestern limit to that of 42° at the northeastern. This region constitutes the northern portion of what was at first designated as the "Great Basin" the high plateau, without outlet for its waters, separated on the north by low divides from the valley of the Snake River and continuing southward until it merges into the desert of the Lower Colorado. Geologically considered, however, as well as botanically, the term is now properly made to include the whole similar arid stretch of country northward to the plains of the Columbia in latitude 48°.

Seven-core multicore fiber transmissions for passive optical network.

PubMed

Zhu, B; Taunay, T F; Yan, M F; Fini, J M; Fishteyn, M; Monberg, E M; Dimarcello, F V

2010-05-24

We design and fabricate a novel multicore fiber (MCF), with seven cores arranged in a hexagonal array. The fiber properties of MCF including low crosstalk, attenuation and splice loss are described. A new tapered MCF connector (TMC), showing ultra-low crosstalk and losses, is also designed and fabricated for coupling the individual signals in-and-out of the MCF. We further propose a novel network configuration using parallel transmissions with the MCF and TMC for passive optical network (PON). To the best of our knowledge, we demonstrate the first bi-directional parallel transmissions of 1310 nm and 1490 nm signals over 11.3-km of seven-core MCF with 64-way splitter for PON.

The language parallel Pascal and other aspects of the massively parallel processor

NASA Technical Reports Server (NTRS)

Reeves, A. P.; Bruner, J. D.

1982-01-01

A high level language for the Massively Parallel Processor (MPP) was designed. This language, called Parallel Pascal, is described in detail. A description of the language design, a description of the intermediate language, Parallel P-Code, and details for the MPP implementation are included. Formal descriptions of Parallel Pascal and Parallel P-Code are given. A compiler was developed which converts programs in Parallel Pascal into the intermediate Parallel P-Code language. The code generator to complete the compiler for the MPP is being developed independently. A Parallel Pascal to Pascal translator was also developed. The architecture design for a VLSI version of the MPP was completed with a description of fault tolerant interconnection networks. The memory arrangement aspects of the MPP are discussed and a survey of other high level languages is given.

Multiradio Resource Management: Parallel Transmission for Higher Throughput?

NASA Astrophysics Data System (ADS)

Bazzi, Alessandro; Pasolini, Gianni; Andrisano, Oreste

2008-12-01

Mobile communication systems beyond the third generation will see the interconnection of heterogeneous radio access networks (UMTS, WiMax, wireless local area networks, etc.) in order to always provide the best quality of service (QoS) to users with multimode terminals. This scenario poses a number of critical issues, which have to be faced in order to get the best from the integrated access network. In this paper, we will investigate the issue of parallel transmission over multiple radio access technologies (RATs), focusing the attention on the QoS perceived by final users. We will show that the achievement of a real benefit from parallel transmission over multiple RATs is conditioned to the fulfilment of some requirements related to the kind of RATs, the multiradio resource management (MRRM) strategy, and the transport-level protocol behaviour. All these aspects will be carefully considered in our investigation, which will be carried out partly adopting an analytical approach and partly by means of simulations. In this paper, in particular, we will propose a simple but effective MRRM algorithm, whose performance will be investigated in IEEE802.11a-UMTS and IEEE802.11a-IEEE802.16e heterogeneous networks (adopted as case studies).

Parallel multi-join query optimization algorithm for distributed sensor network in the internet of things

NASA Astrophysics Data System (ADS)

Zheng, Yan

2015-03-01

Internet of things (IoT), focusing on providing users with information exchange and intelligent control, attracts a lot of attention of researchers from all over the world since the beginning of this century. IoT is consisted of large scale of sensor nodes and data processing units, and the most important features of IoT can be illustrated as energy confinement, efficient communication and high redundancy. With the sensor nodes increment, the communication efficiency and the available communication band width become bottle necks. Many research work is based on the instance which the number of joins is less. However, it is not proper to the increasing multi-join query in whole internet of things. To improve the communication efficiency between parallel units in the distributed sensor network, this paper proposed parallel query optimization algorithm based on distribution attributes cost graph. The storage information relations and the network communication cost are considered in this algorithm, and an optimized information changing rule is established. The experimental result shows that the algorithm has good performance, and it would effectively use the resource of each node in the distributed sensor network. Therefore, executive efficiency of multi-join query between different nodes could be improved.

Advantages of Parallel Processing and the Effects of Communications Time

NASA Technical Reports Server (NTRS)

Eddy, Wesley M.; Allman, Mark

2000-01-01

Many computing tasks involve heavy mathematical calculations, or analyzing large amounts of data. These operations can take a long time to complete using only one computer. Networks such as the Internet provide many computers with the ability to communicate with each other. Parallel or distributed computing takes advantage of these networked computers by arranging them to work together on a problem, thereby reducing the time needed to obtain the solution. The drawback to using a network of computers to solve a problem is the time wasted in communicating between the various hosts. The application of distributed computing techniques to a space environment or to use over a satellite network would therefore be limited by the amount of time needed to send data across the network, which would typically take much longer than on a terrestrial network. This experiment shows how much faster a large job can be performed by adding more computers to the task, what role communications time plays in the total execution time, and the impact a long-delay network has on a distributed computing system.

Models and algorithm of optimization launch and deployment of virtual network functions in the virtual data center

NASA Astrophysics Data System (ADS)

Bolodurina, I. P.; Parfenov, D. I.

2017-10-01

The goal of our investigation is optimization of network work in virtual data center. The advantage of modern infrastructure virtualization lies in the possibility to use software-defined networks. However, the existing optimization of algorithmic solutions does not take into account specific features working with multiple classes of virtual network functions. The current paper describes models characterizing the basic structures of object of virtual data center. They including: a level distribution model of software-defined infrastructure virtual data center, a generalized model of a virtual network function, a neural network model of the identification of virtual network functions. We also developed an efficient algorithm for the optimization technology of containerization of virtual network functions in virtual data center. We propose an efficient algorithm for placing virtual network functions. In our investigation we also generalize the well renowned heuristic and deterministic algorithms of Karmakar-Karp.

Medical Remote Sensors in Tactical Networks

DTIC Science & Technology

2015-03-01

increased efficiency and patient survivability? We say yes and propose that the answers may lie in recent advancements in wireless sensor technology...subject to poor documentation, errors in transcription, illegible handwriting , and possible loss of the TCCC card during patient transit. Leveraging

The HOX genes are expressed, in vivo, in human tooth germs: in vitro cAMP exposure of dental pulp cells results in parallel HOX network activation and neuronal differentiation.

PubMed

D'Antò, Vincenzo; Cantile, Monica; D'Armiento, Maria; Schiavo, Giulia; Spagnuolo, Gianrico; Terracciano, Luigi; Vecchione, Raffaela; Cillo, Clemente

2006-03-01

Homeobox-containing genes play a crucial role in odontogenesis. After the detection of Dlx and Msx genes in overlapping domains along maxillary and mandibular processes, a homeobox odontogenic code has been proposed to explain the interaction between different homeobox genes during dental lamina patterning. No role has so far been assigned to the Hox gene network in the homeobox odontogenic code due to studies on specific Hox genes and evolutionary considerations. Despite its involvement in early patterning during embryonal development, the HOX gene network, the most repeat-poor regions of the human genome, controls the phenotype identity of adult eukaryotic cells. Here, according to our results, the HOX gene network appears to be active in human tooth germs between 18 and 24 weeks of development. The immunohistochemical localization of specific HOX proteins mostly concerns the epithelial tooth germ compartment. Furthermore, only a few genes of the network are active in embryonal retromolar tissues, as well as in ectomesenchymal dental pulp cells (DPC) grown in vitro from adult human molar. Exposure of DPCs to cAMP induces the expression of from three to nine total HOX genes of the network in parallel with phenotype modifications with traits of neuronal differentiation. Our observations suggest that: (i) by combining its component genes, the HOX gene network determines the phenotype identity of epithelial and ectomesenchymal cells interacting in the generation of human tooth germ; (ii) cAMP treatment activates the HOX network and induces, in parallel, a neuronal-like phenotype in human primary ectomesenchymal dental pulp cells. 2005 Wiley-Liss, Inc.

Generating Billion-Edge Scale-Free Networks in Seconds: Performance Study of a Novel GPU-based Preferential Attachment Model

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

Perumalla, Kalyan S.; Alam, Maksudul

A novel parallel algorithm is presented for generating random scale-free networks using the preferential-attachment model. The algorithm, named cuPPA, is custom-designed for single instruction multiple data (SIMD) style of parallel processing supported by modern processors such as graphical processing units (GPUs). To the best of our knowledge, our algorithm is the first to exploit GPUs, and also the fastest implementation available today, to generate scale free networks using the preferential attachment model. A detailed performance study is presented to understand the scalability and runtime characteristics of the cuPPA algorithm. In one of the best cases, when executed on an NVidiamore » GeForce 1080 GPU, cuPPA generates a scale free network of a billion edges in less than 2 seconds.« less

An Electroencephalography Network and Connectivity Analysis for Deception in Instructed Lying Tasks

PubMed Central

Wang, Yue; Ng, Wu Chun; Ng, Khoon Siong; Yu, Ke; Wu, Tiecheng; Li, Xiaoping

2015-01-01

Deception is an impactful social event that has been the focus of an abundance of researches over recent decades. In this paper, an electroencephalography (EEG) study is presented regarding the cognitive processes of an instructed liar/truth-teller during the time window of stimulus (question) delivery period (SDP) prior to their deceptive/truthful responses towards questions related to authentic (WE: with prior experience) and fictional experience (NE: no prior experience). To investigate deception in non-experienced events, the subjects were given stimuli in a mock interview scenario that induced them to fabricate lies. To analyze the data, frequency domain network and connectivity analysis was performed in the source space in order to provide a more systematic level understanding of deception during SDP. This study reveals several groups of neuronal generators underlying both the instructed lying (IL) and the instructed truth-telling (IT) conditions for both tasks during the SDP. Despite the similarities existed in these group components, significant differences were found in the intra- and inter-group connectivity between the IL and IT conditions in either task. Additionally, the response time was found to be positively correlated with the clustering coefficient of the inferior frontal gyrus (44R) in the WE-IL condition and positively correlated with the clustering coefficient of the precuneus (7L) and the angular gyrus (39R) in the WE-IT condition. However, the response time was found to be marginally negatively correlated with the clustering coefficient of the secondary auditory cortex (42L) in the NE-IL condition and negatively correlated with the clustering coefficient of the somatosensory association cortex (5L, R) in the NE-IT condition. Therefore, these results provide complementary and intuitive evidence for the differences between the IL and IT conditions in SDP for two types of deception tasks, thus elucidating the electrophysiological mechanisms underlying SDP of deception from regional, inter-regional, network, and inter-network scale analyses. PMID:25679784

Electronic Neural Networks

NASA Technical Reports Server (NTRS)

Thakoor, Anil

1990-01-01

Viewgraphs on electronic neural networks for space station are presented. Topics covered include: electronic neural networks; electronic implementations; VLSI/thin film hybrid hardware for neurocomputing; computations with analog parallel processing; features of neuroprocessors; applications of neuroprocessors; neural network hardware for terrain trafficability determination; a dedicated processor for path planning; neural network system interface; neural network for robotic control; error backpropagation algorithm for learning; resource allocation matrix; global optimization neuroprocessor; and electrically programmable read only thin-film synaptic array.

Neural network applications in telecommunications

NASA Technical Reports Server (NTRS)

Alspector, Joshua

1994-01-01

Neural network capabilities include automatic and organized handling of complex information, quick adaptation to continuously changing environments, nonlinear modeling, and parallel implementation. This viewgraph presentation presents Bellcore work on applications, learning chip computational function, learning system block diagram, neural network equalization, broadband access control, calling-card fraud detection, software reliability prediction, and conclusions.

Killing and Noether Symmetries of Plane Symmetric Spacetime

NASA Astrophysics Data System (ADS)

Shamir, M. Farasat; Jhangeer, Adil; Bhatti, Akhlaq Ahmad

2013-09-01

This paper is devoted to investigate the Killing and Noether symmetries of static plane symmetric spacetime. For this purpose, five different cases have been discussed. The Killing and Noether symmetries of Minkowski spacetime in cartesian coordinates are calculated as a special case and it is found that Lie algebra of the Lagrangian is 10 and 17 dimensional respectively. The symmetries of Taub's universe, anti-deSitter universe, self similar solutions of infinite kind for parallel perfect fluid case and self similar solutions of infinite kind for parallel dust case are also explored. In all the cases, the Noether generators are calculated in the presence of gauge term. All these examples justify the conjecture that Killing symmetries form a subalgebra of Noether symmetries (Bokhari et al. in Int. J. Theor. Phys. 45:1063, 2006).

5-Methylpyrazine-2-carboxamide

DOE PAGES

Rillema, D. Paul; Senaratne, Nilmini K.; Moore, Curtis; ...

2017-07-28

The title compound, C 6H 7N 3O, is nearly planar, with a dihedral angle of 2.14 (11)° between the pyrazine ring and the mean plane of the carboxamide group [C—C(=O)—N]. In the crystal, molecules are linked via pairs of N—H...O hydrogen bonds forming inversion dimers with an R 2 2 (8) ring motif. These dimers are further linked by a pair of N—H...N hydrogen bonds, enclosing an R 2 2 (10) ring motif, and C—H...O hydrogen bonds, forming ribbons lying parallel to the ab plane. The ribbons are linked by offset π–π interactions [intercentroid distance = 3.759(1)Å], forming two setsmore » of mutually perpendicular slabs parallel to planes (110) and (1-10).« less

7-Meth­oxy­indan-1-one

PubMed Central

Chang, Yuan Jay; Chen, Kew-Yu

2012-01-01

In the title compound, C10H10O2, the 1-indanone unit is essentially planar (r.m.s. deviation = 0.028 Å). In the crystal, molecules are linked via C—H⋯O hydrogen bonds, forming layers lying parallel to the ab plane. This two-dimensional structure is stabilized by a weak C—H⋯π inter­action. A second weak C—H⋯π inter­action links the layers, forming a three-dimensional structure. PMID:23284398

Performance verification of network function virtualization in software defined optical transport networks

NASA Astrophysics Data System (ADS)

Zhao, Yongli; Hu, Liyazhou; Wang, Wei; Li, Yajie; Zhang, Jie

2017-01-01

With the continuous opening of resource acquisition and application, there are a large variety of network hardware appliances deployed as the communication infrastructure. To lunch a new network application always implies to replace the obsolete devices and needs the related space and power to accommodate it, which will increase the energy and capital investment. Network function virtualization1 (NFV) aims to address these problems by consolidating many network equipment onto industry standard elements such as servers, switches and storage. Many types of IT resources have been deployed to run Virtual Network Functions (vNFs), such as virtual switches and routers. Then how to deploy NFV in optical transport networks is a of great importance problem. This paper focuses on this problem, and gives an implementation architecture of NFV-enabled optical transport networks based on Software Defined Optical Networking (SDON) with the procedure of vNFs call and return. Especially, an implementation solution of NFV-enabled optical transport node is designed, and a parallel processing method for NFV-enabled OTN nodes is proposed. To verify the performance of NFV-enabled SDON, the protocol interaction procedures of control function virtualization and node function virtualization are demonstrated on SDON testbed. Finally, the benefits and challenges of the parallel processing method for NFV-enabled OTN nodes are simulated and analyzed.

Energy efficiency analysis of two-sided feed scheme of DC traction network with high asymmetry of feeders parameters

NASA Astrophysics Data System (ADS)

Abramov, E. Y.; Sopov, V. I.

2017-10-01

In a given research using the example of traction network area with high asymmetry of power supply parameters, the sequence of comparative assessment of power losses in DC traction network with parallel and traditional separated operating modes of traction substation feeders was shown. Experimental measurements were carried out under these modes of operation. The calculation data results based on statistic processing showed the power losses decrease in contact network and the increase in feeders. The changes proved to be critical ones and this demonstrates the significance of potential effects when converting traction network areas into parallel feeder operation. An analytical method of calculation the average power losses for different feed schemes of the traction network was developed. On its basis, the dependences of the relative losses were obtained by varying the difference in feeder voltages. The calculation results showed unreasonableness transition to a two-sided feed scheme for the considered traction network area. A larger reduction in the total power loss can be obtained with a smaller difference of the feeders’ resistance and / or a more symmetrical sectioning scheme of contact network.

Cooperative UAV-Based Communications Backbone for Sensor Networks

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

Roberts, R S

2001-10-07

The objective of this project is to investigate the use of unmanned air vehicles (UAVs) as mobile, adaptive communications backbones for ground-based sensor networks. In this type of network, the UAVs provide communication connectivity to sensors that cannot communicate with each other because of terrain, distance, or other geographical constraints. In these situations, UAVs provide a vertical communication path for the sensors, thereby mitigating geographic obstacles often imposed on networks. With the proper use of UAVs, connectivity to a widely disbursed sensor network in rugged terrain is readily achieved. Our investigation has focused on networks where multiple cooperating UAVs aremore » used to form a network backbone. The advantage of using multiple UAVs to form the network backbone is parallelization of sensor connectivity. Many widely spaced or isolated sensors can be connected to the network at once using this approach. In these networks, the UAVs logically partition the sensor network into sub-networks (subnets), with one UAV assigned per subnet. Partitioning the network into subnets allows the UAVs to service sensors in parallel thereby decreasing the sensor-to-network connectivity. A UAV services sensors in its subnet by flying a route (path) through the subnet, uplinking data collected by the sensors, and forwarding the data to a ground station. An additional advantage of using multiple UAVs in the network is that they provide redundancy in the communications backbone, so that the failure of a single UAV does not necessarily imply the loss of the network.« less

Merlin - Massively parallel heterogeneous computing

NASA Technical Reports Server (NTRS)

Wittie, Larry; Maples, Creve

1989-01-01

Hardware and software for Merlin, a new kind of massively parallel computing system, are described. Eight computers are linked as a 300-MIPS prototype to develop system software for a larger Merlin network with 16 to 64 nodes, totaling 600 to 3000 MIPS. These working prototypes help refine a mapped reflective memory technique that offers a new, very general way of linking many types of computer to form supercomputers. Processors share data selectively and rapidly on a word-by-word basis. Fast firmware virtual circuits are reconfigured to match topological needs of individual application programs. Merlin's low-latency memory-sharing interfaces solve many problems in the design of high-performance computing systems. The Merlin prototypes are intended to run parallel programs for scientific applications and to determine hardware and software needs for a future Teraflops Merlin network.

Buffered coscheduling for parallel programming and enhanced fault tolerance

DOEpatents

Petrini, Fabrizio [Los Alamos, NM; Feng, Wu-chun [Los Alamos, NM

2006-01-31

A computer implemented method schedules processor jobs on a network of parallel machine processors or distributed system processors. Control information communications generated by each process performed by each processor during a defined time interval is accumulated in buffers, where adjacent time intervals are separated by strobe intervals for a global exchange of control information. A global exchange of the control information communications at the end of each defined time interval is performed during an intervening strobe interval so that each processor is informed by all of the other processors of the number of incoming jobs to be received by each processor in a subsequent time interval. The buffered coscheduling method of this invention also enhances the fault tolerance of a network of parallel machine processors or distributed system processors

Dynamic stability analysis of fractional order leaky integrator echo state neural networks

NASA Astrophysics Data System (ADS)

Pahnehkolaei, Seyed Mehdi Abedi; Alfi, Alireza; Tenreiro Machado, J. A.

2017-06-01

The Leaky integrator echo state neural network (Leaky-ESN) is an improved model of the recurrent neural network (RNN) and adopts an interconnected recurrent grid of processing neurons. This paper presents a new proof for the convergence of a Lyapunov candidate function to zero when time tends to infinity by means of the Caputo fractional derivative with order lying in the range (0, 1). The stability of Fractional-Order Leaky-ESN (FO Leaky-ESN) is then analyzed, and the existence, uniqueness and stability of the equilibrium point are provided. A numerical example demonstrates the feasibility of the proposed method.

Hyperbolic geometry of Kuramoto oscillator networks

NASA Astrophysics Data System (ADS)

Chen, Bolun; Engelbrecht, Jan R.; Mirollo, Renato

2017-09-01

Kuramoto oscillator networks have the special property that their trajectories are constrained to lie on the (at most) 3D orbits of the Möbius group acting on the state space T N (the N-fold torus). This result has been used to explain the existence of the N-3 constants of motion discovered by Watanabe and Strogatz for Kuramoto oscillator networks. In this work we investigate geometric consequences of this Möbius group action. The dynamics of Kuramoto phase models can be further reduced to 2D reduced group orbits, which have a natural geometry equivalent to the unit disk \

Characterizing information propagation through inter-vehicle communication on a simple network of two parallel roads

DOT National Transportation Integrated Search

2010-10-01

In this report, we study information propagation via inter-vehicle communication along two parallel : roads. By identifying an inherent Bernoulli process, we are able to derive the mean and variance of : propagation distance. A road separation distan...

An approach to enhance pnetCDF performance in environmental modeling applications

EPA Science Inventory

Data intensive simulations are often limited by their I/O (input/output) performance, and "novel" techniques need to be developed in order to overcome this limitation. The software package pnetCDF (parallel network Common Data Form), which works with parallel file syste...

Metallization of ultra-thin, non-thiol SAMs with flat-lying molecular units: Pd on 1, 4-dicyanobenzene.

PubMed

Eberle, Felix; Metzler, Martin; Kolb, Dieter M; Saitner, Marc; Wagner, Patrick; Boyen, Hans-Gerd

2010-09-10

Self-assembled monolayers of 1,4-dicyanobenzene on Au(111) electrodes are studied by cyclic voltammetry, in-situ STM and ex-situ XPS. High-resolution STM images reveal a long-range order of propeller-like assemblies each of which consists of three molecules, all lying flat on the gold substrate with the cyano groups oriented parallel to the metal surface. It is demonstrated that both functional groups can act as complexation sites for metal ions from solution. Surprisingly, such arrangements still allow the metal to be deposited on top of the molecules by electrochemical reduction despite the close vicinity to the Au surface. The latter is demonstrated by angle-resolved XPS which unequivocally shows that the metal indeed resides on top of the organic layer rather than underneath, despite the flat arrangement of the molecules.

Conformal superalgebras via tractor calculus

NASA Astrophysics Data System (ADS)

Lischewski, Andree

2015-01-01

We use the manifestly conformally invariant description of a Lorentzian conformal structure in terms of a parabolic Cartan geometry in order to introduce a superalgebra structure on the space of twistor spinors and normal conformal vector fields formulated in purely algebraic terms on parallel sections in tractor bundles. Via a fixed metric in the conformal class, one reproduces a conformal superalgebra structure that has been considered in the literature before. The tractor approach, however, makes clear that the failure of this object to be a Lie superalgebra in certain cases is due to purely algebraic identities on the spinor module and to special properties of the conformal holonomy representation. Moreover, it naturally generalizes to higher signatures. This yields new formulas for constructing new twistor spinors and higher order normal conformal Killing forms out of existing ones, generalizing the well-known spinorial Lie derivative. Moreover, we derive restrictions on the possible dimension of the space of twistor spinors in any metric signature.

Processing large remote sensing image data sets on Beowulf clusters

USGS Publications Warehouse

Steinwand, Daniel R.; Maddox, Brian; Beckmann, Tim; Schmidt, Gail

2003-01-01

High-performance computing is often concerned with the speed at which floating- point calculations can be performed. The architectures of many parallel computers and/or their network topologies are based on these investigations. Often, benchmarks resulting from these investigations are compiled with little regard to how a large dataset would move about in these systems. This part of the Beowulf study addresses that concern by looking at specific applications software and system-level modifications. Applications include an implementation of a smoothing filter for time-series data, a parallel implementation of the decision tree algorithm used in the Landcover Characterization project, a parallel Kriging algorithm used to fit point data collected in the field on invasive species to a regular grid, and modifications to the Beowulf project's resampling algorithm to handle larger, higher resolution datasets at a national scale. Systems-level investigations include a feasibility study on Flat Neighborhood Networks and modifications of that concept with Parallel File Systems.

Design Sketches For Optical Crossbar Switches Intended For Large-Scale Parallel Processing Applications

NASA Astrophysics Data System (ADS)

Hartmann, Alfred; Redfield, Steve

1989-04-01

This paper discusses design of large-scale (1000x 1000) optical crossbar switching networks for use in parallel processing supercom-puters. Alternative design sketches for an optical crossbar switching network are presented using free-space optical transmission with either a beam spreading/masking model or a beam steering model for internodal communications. The performances of alternative multiple access channel communications protocol-unslotted and slotted ALOHA and carrier sense multiple access (CSMA)-are compared with the performance of the classic arbitrated bus crossbar of conventional electronic parallel computing. These comparisons indicate an almost inverse relationship between ease of implementation and speed of operation. Practical issues of optical system design are addressed, and an optically addressed, composite spatial light modulator design is presented for fabrication to arbitrarily large scale. The wide range of switch architecture, communications protocol, optical systems design, device fabrication, and system performance problems presented by these design sketches poses a serious challenge to practical exploitation of highly parallel optical interconnects in advanced computer designs.

Strategies for Transporting Data Between Classified and Unclassified Networks

DTIC Science & Technology

2016-03-01

datagram protocol (UDP) must be used. The UDP is typically used when speed is a higher priority than data integrity, such as in music or video streaming ...and the exit point of data are separate and can be tightly controlled. This does effectively prevent the comingling of data and is used in industry to...perform functions such as streaming video and audio from secure to insecure networks (ref. 1). A second disadvantage lies in the fact that the

Computer architecture evaluation for structural dynamics computations: Project summary

NASA Technical Reports Server (NTRS)

Standley, Hilda M.

1989-01-01

The intent of the proposed effort is the examination of the impact of the elements of parallel architectures on the performance realized in a parallel computation. To this end, three major projects are developed: a language for the expression of high level parallelism, a statistical technique for the synthesis of multicomputer interconnection networks based upon performance prediction, and a queueing model for the analysis of shared memory hierarchies.

Efficient partitioning and assignment on programs for multiprocessor execution

NASA Technical Reports Server (NTRS)

Standley, Hilda M.

1993-01-01

The general problem studied is that of segmenting or partitioning programs for distribution across a multiprocessor system. Efficient partitioning and the assignment of program elements are of great importance since the time consumed in this overhead activity may easily dominate the computation, effectively eliminating any gains made by the use of the parallelism. In this study, the partitioning of sequentially structured programs (written in FORTRAN) is evaluated. Heuristics, developed for similar applications are examined. Finally, a model for queueing networks with finite queues is developed which may be used to analyze multiprocessor system architectures with a shared memory approach to the problem of partitioning. The properties of sequentially written programs form obstacles to large scale (at the procedure or subroutine level) parallelization. Data dependencies of even the minutest nature, reflecting the sequential development of the program, severely limit parallelism. The design of heuristic algorithms is tied to the experience gained in the parallel splitting. Parallelism obtained through the physical separation of data has seen some success, especially at the data element level. Data parallelism on a grander scale requires models that accurately reflect the effects of blocking caused by finite queues. A model for the approximation of the performance of finite queueing networks is developed. This model makes use of the decomposition approach combined with the efficiency of product form solutions.

An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions

USGS Publications Warehouse

Stanislawski, Larry V.; Survila, Kornelijus; Wendel, Jeffrey; Liu, Yan; Buttenfield, Barbara P.

2018-01-01

This paper describes a workflow for automating the extraction of elevation-derived stream lines using open source tools with parallel computing support and testing the effectiveness of procedures in various terrain conditions within the conterminous United States. Drainage networks are extracted from the US Geological Survey 1/3 arc-second 3D Elevation Program elevation data having a nominal cell size of 10 m. This research demonstrates the utility of open source tools with parallel computing support for extracting connected drainage network patterns and handling depressions in 30 subbasins distributed across humid, dry, and transitional climate regions and in terrain conditions exhibiting a range of slopes. Special attention is given to low-slope terrain, where network connectivity is preserved by generating synthetic stream channels through lake and waterbody polygons. Conflation analysis compares the extracted streams with a 1:24,000-scale National Hydrography Dataset flowline network and shows that similarities are greatest for second- and higher-order tributaries.

Providing nearest neighbor point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer

DOEpatents

Archer, Charles J.; Faraj, Ahmad A.; Inglett, Todd A.; Ratterman, Joseph D.

2012-10-23

Methods, apparatus, and products are disclosed for providing nearest neighbor point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer, each compute node connected to each adjacent compute node in the global combining network through a link, that include: identifying each link in the global combining network for each compute node of the operational group; designating one of a plurality of point-to-point class routing identifiers for each link such that no compute node in the operational group is connected to two adjacent compute nodes in the operational group with links designated for the same class routing identifiers; and configuring each compute node of the operational group for point-to-point communications with each adjacent compute node in the global combining network through the link between that compute node and that adjacent compute node using that link's designated class routing identifier.

Nanotomography and Micromagnetic Modelling of Remanence Carriers in the Semarkona LL3.0 Chondrite: A New View of the Vortex State

NASA Astrophysics Data System (ADS)

Harrison, R. J.; Einsle, J. F.; Williams, W.; Ó Conbhuí, P.; Fu, R. R.; Weiss, B. P.; Kasama, T.

2015-12-01

Dusty-olivine chondrules are carriers of stable pre-accretionary remanence, and have recently been used to obtain the first reliable estimate of the magnetic field of the early solar nebula. Here we show how the magnetic architecture of a single dusty olivine grain from the Semarkona LL3.0 ordinary chondrite meteorite can be fully characterised in three-dimensions, using a combination of Focussed-Ion-Beam nanotomography (FIB-nt), electron tomography and finite-element micromagnetic modelling. We present a 3D volume reconstruction of a dusty olivine grain, obtained by selective milling through a region of interest in a series of sequential 20 nm slices, which are then imaged using scanning electron microscopy. The data provide a quantitative description of the iron particle ensemble, including the distribution of particle sizes, shapes, interparticle spacings and preferred orientations. Iron particles are predominantly oblate ellipoids. Particles nucleate on dislocation networks and are loosely arranged in a series of parallel sheets with their shortest dimension oriented normal to the sheets and their longest dimensions preferentially aligned within the sheets. Individual particle geometries are converted to a finite-element mesh and used to perform micromagnetic simulations. The majority of particles adopt a single vortex state, with 'bulk' spins that rotate around a central vortex core. The results challenge pre-conceived ideas about the remanence carrying properties of vortex states. We find that remanence is carried by bulk spins rather than the vortex core. Although the orientation of the core is determined by the ellipsoidal geometry (parallel to the major axis for prolate ellipsoids; parallel to the minor axis for oblate ellipsoids), the remanence vectors generally lie at large angles (and in many cases antiparallel) to the core magnetisation. Even in the case of prolate particles, the resulting remanence vector can make a large angle of ~50° to the expected easy axis. The results reconcile the predicted and observed directions of remanence anisotropy, and demonstrate how this combination of nanotomography and micromagnetics will become an essential component of future single-crystal paleomagnetic studies.

Electron Microscopy Characterization of Vanadium Dioxide Thin Films and Nanoparticles

NASA Astrophysics Data System (ADS)

Rivera, Felipe

Vanadium dioxide (VO_2) is a material of particular interest due to its exhibited metal to insulator phase transition at 68°C that is accompanied by an abrupt and significant change in its electronic and optical properties. Since this material can exhibit a reversible drop in resistivity of up to five orders of magnitude and a reversible drop in infrared optical transmission of up to 80%, this material holds promise in several technological applications. Solid phase crystallization of VO_2 thin films was obtained by a post-deposition annealing process of a VO_{x,x approx 2} amorphous film sputtered on an amorphous silicon dioxide (SiO_2) layer. Scanning electron microscopy (SEM) and electron-backscattered diffraction (EBSD) were utilized to study the morphology of the solid phase crystallization that resulted from this post-deposition annealing process. The annealing parameters ranged in temperature from 300°C up to 1000°C and in time from 5 minutes up to 12 hours. Depending on the annealing parameters, EBSD showed that this process yielded polycrystalline vanadium dioxide thin films, semi-continuous thin films, and films of isolated single-crystal particles. In addition to these films on SiO_2, other VO_2 thin films were deposited onto a-, c-, and r-cuts of sapphire and on TiO_2(001) heated single-crystal substrates by pulsed-laser deposition (PLD). The temperature of the substrates was kept at ˜500°C during deposition. EBSD maps and orientation imaging microscopy were used to study the epitaxy and orientation of the VO_2 grains deposited on the single crystal substrates, as well as on the amorphous SiO_2 layer. The EBSD/OIM results showed that: 1) For all the sapphire substrates analyzed, there is a predominant family of crystallographic relationships wherein the rutile VO_2{001} planes tend to lie parallel to the sapphire's {10-10} and the rutile VO_2{100} planes lie parallel to the sapphire's {1-210} and {0001}. Furthermore, while this family of relationships accounts for the majority of the VO_2 grains observed, due to the sapphire substrate's geometry there were variations within these rules that changed the orientation of VO_2 grains with respect to the substrate's normal direction. 2) For the TiO_2, a substrate with a lower lattice mismatch, we observe the expected relationship where the rutile VO_2 [100], [110], and [001] crystal directions lie parallel to the TiO_2 substrate's [100], [110], and [001] crystal directions respectively. 3) For the amorphous SiO_2 layer, all VO_2 crystals that were measurable (those that grew to the thickness of the deposited film) had a preferred orientation with the the rutile VO_2[001] crystal direction tending to lie parallel to the plane of the specimen. The use of transmission electron microscopy (TEM) is presented as a tool for further characterization studies of this material and its applications. In this work TEM diffraction patterns taken from cross-sections of particles of the a- and r-cut sapphire substrates not only solidified the predominant family mentioned, but also helped lift the ambiguity present in the rutile VO_2{100} axes. Finally, a focused-ion beam technique for preparation of cross-sectional TEM samples of metallic thin films deposited on polymer substrates is demonstrated.

Massive parallelization of a 3D finite difference electromagnetic forward solution using domain decomposition methods on multiple CUDA enabled GPUs

NASA Astrophysics Data System (ADS)

Schultz, A.

2010-12-01

3D forward solvers lie at the core of inverse formulations used to image the variation of electrical conductivity within the Earth's interior. This property is associated with variations in temperature, composition, phase, presence of volatiles, and in specific settings, the presence of groundwater, geothermal resources, oil/gas or minerals. The high cost of 3D solutions has been a stumbling block to wider adoption of 3D methods. Parallel algorithms for modeling frequency domain 3D EM problems have not achieved wide scale adoption, with emphasis on fairly coarse grained parallelism using MPI and similar approaches. The communications bandwidth as well as the latency required to send and receive network communication packets is a limiting factor in implementing fine grained parallel strategies, inhibiting wide adoption of these algorithms. Leading Graphics Processor Unit (GPU) companies now produce GPUs with hundreds of GPU processor cores per die. The footprint, in silicon, of the GPU's restricted instruction set is much smaller than the general purpose instruction set required of a CPU. Consequently, the density of processor cores on a GPU can be much greater than on a CPU. GPUs also have local memory, registers and high speed communication with host CPUs, usually through PCIe type interconnects. The extremely low cost and high computational power of GPUs provides the EM geophysics community with an opportunity to achieve fine grained (i.e. massive) parallelization of codes on low cost hardware. The current generation of GPUs (e.g. NVidia Fermi) provides 3 billion transistors per chip die, with nearly 500 processor cores and up to 6 GB of fast (DDR5) GPU memory. This latest generation of GPU supports fast hardware double precision (64 bit) floating point operations of the type required for frequency domain EM forward solutions. Each Fermi GPU board can sustain nearly 1 TFLOP in double precision, and multiple boards can be installed in the host computer system. We describe our ongoing efforts to achieve massive parallelization on a novel hybrid GPU testbed machine currently configured with 12 Intel Westmere Xeon CPU cores (or 24 parallel computational threads) with 96 GB DDR3 system memory, 4 GPU subsystems which in aggregate contain 960 NVidia Tesla GPU cores with 16 GB dedicated DDR3 GPU memory, and a second interleved bank of 4 GPU subsystems containing in aggregate 1792 NVidia Fermi GPU cores with 12 GB dedicated DDR5 GPU memory. We are applying domain decomposition methods to a modified version of Weiss' (2001) 3D frequency domain full physics EM finite difference code, an open source GPL licensed f90 code available for download from www.OpenEM.org. This will be the core of a new hybrid 3D inversion that parallelizes frequencies across CPUs and individual forward solutions across GPUs. We describe progress made in modifying the code to use direct solvers in GPU cores dedicated to each small subdomain, iteratively improving the solution by matching adjacent subdomain boundary solutions, rather than iterative Krylov space sparse solvers as currently applied to the whole domain.

Animal origins of SARS coronavirus: possible links with the international trade in small carnivores.

PubMed Central

Bell, Diana; Roberton, Scott; Hunter, Paul R

2004-01-01

The search for animal host origins of severe acute respiratory syndrome (SARS) coronavirus has so far remained focused on wildlife markets, restaurants and farms within China. A significant proportion of this wildlife enters China through an expanding regional network of illegal, international wildlife trade. We present the case for extending the search for ancestral coronaviruses and their hosts across international borders into countries such as Vietnam and Lao People's Democratic Republic, where the same guilds of species are found on sale in similar wildlife markets or food outlets. The three species that have so far been implicated, a viverrid, a mustelid and a canid, are part of a large suite of small carnivores distributed across this region currently overexploited by this international wildlife trade. A major lesson from SARS is that the underlying roots of newly emergent zoonotic diseases may lie in the parallel biodiversity crisis of massive species loss as a result of overexploitation of wild animal populations and the destruction of their natural habitats by increasing human populations. To address these dual threats to the long-term future of biodiversity, including man, requires a less anthropocentric and more interdisciplinary approach to problems that require the combined research expertise of ecologists, conservation biologists, veterinarians, epidemiologists, virologists, as well as human health professionals. PMID:15306396

Animal origins of SARS coronavirus: possible links with the international trade in small carnivores.

PubMed

Bell, Diana; Roberton, Scott; Hunter, Paul R

2004-07-29

The search for animal host origins of severe acute respiratory syndrome (SARS) coronavirus has so far remained focused on wildlife markets, restaurants and farms within China. A significant proportion of this wildlife enters China through an expanding regional network of illegal, international wildlife trade. We present the case for extending the search for ancestral coronaviruses and their hosts across international borders into countries such as Vietnam and Lao People's Democratic Republic, where the same guilds of species are found on sale in similar wildlife markets or food outlets. The three species that have so far been implicated, a viverrid, a mustelid and a canid, are part of a large suite of small carnivores distributed across this region currently overexploited by this international wildlife trade. A major lesson from SARS is that the underlying roots of newly emergent zoonotic diseases may lie in the parallel biodiversity crisis of massive species loss as a result of overexploitation of wild animal populations and the destruction of their natural habitats by increasing human populations. To address these dual threats to the long-term future of biodiversity, including man, requires a less anthropocentric and more interdisciplinary approach to problems that require the combined research expertise of ecologists, conservation biologists, veterinarians, epidemiologists, virologists, as well as human health professionals.

Parallel network simulations with NEURON.

PubMed

Migliore, M; Cannia, C; Lytton, W W; Markram, Henry; Hines, M L

2006-10-01

The NEURON simulation environment has been extended to support parallel network simulations. Each processor integrates the equations for its subnet over an interval equal to the minimum (interprocessor) presynaptic spike generation to postsynaptic spike delivery connection delay. The performance of three published network models with very different spike patterns exhibits superlinear speedup on Beowulf clusters and demonstrates that spike communication overhead is often less than the benefit of an increased fraction of the entire problem fitting into high speed cache. On the EPFL IBM Blue Gene, almost linear speedup was obtained up to 100 processors. Increasing one model from 500 to 40,000 realistic cells exhibited almost linear speedup on 2,000 processors, with an integration time of 9.8 seconds and communication time of 1.3 seconds. The potential for speed-ups of several orders of magnitude makes practical the running of large network simulations that could otherwise not be explored.

Parallel Network Simulations with NEURON

PubMed Central

Migliore, M.; Cannia, C.; Lytton, W.W; Markram, Henry; Hines, M. L.

2009-01-01

The NEURON simulation environment has been extended to support parallel network simulations. Each processor integrates the equations for its subnet over an interval equal to the minimum (interprocessor) presynaptic spike generation to postsynaptic spike delivery connection delay. The performance of three published network models with very different spike patterns exhibits superlinear speedup on Beowulf clusters and demonstrates that spike communication overhead is often less than the benefit of an increased fraction of the entire problem fitting into high speed cache. On the EPFL IBM Blue Gene, almost linear speedup was obtained up to 100 processors. Increasing one model from 500 to 40,000 realistic cells exhibited almost linear speedup on 2000 processors, with an integration time of 9.8 seconds and communication time of 1.3 seconds. The potential for speed-ups of several orders of magnitude makes practical the running of large network simulations that could otherwise not be explored. PMID:16732488

Introduction to Parallel Computing

DTIC Science & Technology

1992-05-01

Instruction Stream, Multiple Data Stream Machines .................... 19 2.4 Networks of M achines...independent memory units and connecting them to the processors by an interconnection network . Many different interconnection schemes have been considered, and...connected to the same processor at the same time. Crossbar switching networks are still too expensive to be practical for connecting large numbers of

RAMA: A file system for massively parallel computers

NASA Technical Reports Server (NTRS)

Miller, Ethan L.; Katz, Randy H.

1993-01-01

This paper describes a file system design for massively parallel computers which makes very efficient use of a few disks per processor. This overcomes the traditional I/O bottleneck of massively parallel machines by storing the data on disks within the high-speed interconnection network. In addition, the file system, called RAMA, requires little inter-node synchronization, removing another common bottleneck in parallel processor file systems. Support for a large tertiary storage system can easily be integrated in lo the file system; in fact, RAMA runs most efficiently when tertiary storage is used.

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

PubMed Central

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

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

DOE PAGES

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

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

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

What Lies Beyond the Online Catalog?

ERIC Educational Resources Information Center

Matthews, Joseph R.; And Others

1985-01-01

Five prominent consultants project technological advancements that, in some cases, will enhance current library systems, and in many cases will cause them to become obsolete. Major trends include advances in mainframe and microcomputing technology, development of inexpensive local area networks and telecommunications gateways, and the advent of…

Synthesis of Efficient Structures for Concurrent Computation.

DTIC Science & Technology

1983-10-01

formal presentation of these techniques, called virtualisation and aggregation, can be found n [King-83$. 113.2 Census Functions Trees perform broadcast... Functions .. .. .. .. ... .... ... ... .... ... ... ....... 6 4 User-Assisted Aggregation .. .. .. .. ... ... ... .... ... .. .......... 6 5 Parallel...6. Simple Parallel Structure for Broadcasting .. .. .. .. .. . ... .. . .. . .... 4 Figure 7. Internal Structure of a Prefix Computation Network

An appraisal of biological responses and network of environmental interactions in non-mining and mining impacted coastal waters.

PubMed

Fernandes, Christabelle E G; Malik, Ashish; Jineesh, V K; Fernandes, Sheryl O; Das, Anindita; Pandey, Sunita S; Kanolkar, Geeta; Sujith, P P; Velip, Dhillan M; Shaikh, Shagufta; Helekar, Samita; Gonsalves, Maria Judith; Nair, Shanta; LokaBharathi, P A

2015-08-01

The coastal waters of Goa and Ratnagiri lying on the West coast of India are influenced by terrestrial influx. However, Goa is influenced anthropogenically by iron-ore mining, while Ratnagiri is influenced by deposition of heavy minerals containing iron brought from the hinterlands. We hypothesize that there could be a shift in biological response along with changes in network of interactions between environmental and biological variables in these mining and non-mining impacted regions, lying 160 nmi apart. Biological and environmental parameters were analyzed during pre-monsoon season. Except silicates, the measured parameters were higher at Goa and related significantly, suggesting bacteria centric, detritus-driven region. At Ratnagiri, phytoplankton biomass related positively with silicate suggesting a region dominated by primary producers. This dominance perhaps got reflected as a higher tertiary yield. Thus, even though the regions are geographically proximate, the different biological response could be attributed to the differences in the web of interactions between the measured variables.

Limits to high-speed simulations of spiking neural networks using general-purpose computers.

PubMed

Zenke, Friedemann; Gerstner, Wulfram

2014-01-01

To understand how the central nervous system performs computations using recurrent neuronal circuitry, simulations have become an indispensable tool for theoretical neuroscience. To study neuronal circuits and their ability to self-organize, increasing attention has been directed toward synaptic plasticity. In particular spike-timing-dependent plasticity (STDP) creates specific demands for simulations of spiking neural networks. On the one hand a high temporal resolution is required to capture the millisecond timescale of typical STDP windows. On the other hand network simulations have to evolve over hours up to days, to capture the timescale of long-term plasticity. To do this efficiently, fast simulation speed is the crucial ingredient rather than large neuron numbers. Using different medium-sized network models consisting of several thousands of neurons and off-the-shelf hardware, we compare the simulation speed of the simulators: Brian, NEST and Neuron as well as our own simulator Auryn. Our results show that real-time simulations of different plastic network models are possible in parallel simulations in which numerical precision is not a primary concern. Even so, the speed-up margin of parallelism is limited and boosting simulation speeds beyond one tenth of real-time is difficult. By profiling simulation code we show that the run times of typical plastic network simulations encounter a hard boundary. This limit is partly due to latencies in the inter-process communications and thus cannot be overcome by increased parallelism. Overall, these results show that to study plasticity in medium-sized spiking neural networks, adequate simulation tools are readily available which run efficiently on small clusters. However, to run simulations substantially faster than real-time, special hardware is a prerequisite.

Preliminary bedrock and surficial geologic map of the west half of the Sanders 30' x 60' quadrangle, Navajo and Apache Counties, northern Arizona

USGS Publications Warehouse

Amoroso, Lee; Priest, Susan S.; Hiza-Redsteer, Margaret

2014-01-01

The bedrock and surficial geologic map of the west half of the Sanders 30' x 60' quadrangle was completed in a cooperative effort of the U.S. Geological Survey (USGS) and the Navajo Nation to provide regional geologic information for management and planning officials. This report provides baseline geologic information that will be useful in future studies of groundwater and surface water resources, geologic hazards, and the distribution of soils and plants. The west half of the Sanders quadrangle encompasses approximately 2,509 km2 (980 mi2) within Navajo and Apache Counties of northern Arizona and is bounded by lat 35°30' to 35° N., long 109°30' to 110° W. The majority of the land within the map area lies within the Navajo Nation. South of the Navajo Nation, private and State lands form a checkerboard pattern east and west of Petrified Forest National Park. In the west half of the Sanders quadrangle, Mesozoic bedrock is nearly flat lying except near folds. A shallow Cenozoic erosional basin that developed about 20 Ma in the western part of the map area cut across late Paleozoic and Mesozoic rocks that were subsequently filled with flat-lying Miocene and Pliocene mudstone and argillaceous sandstone and fluvial sediments of the Bidahochi Formation and associated volcanic rocks of the Hopi Buttes volcanic field. The Bidahochi rocks are capped by Pliocene(?) and Pleistocene fluvial sediments and Quaternary eolian and alluvial deposits. Erosion along northeast-southwest-oriented drainages have exposed elongated ridges of Bidahochi Formation and basin-fill deposits that are exposed through shallow eolian cover of similarly oriented longitudinal dunes. Stokes (1964) concluded that the accumulation of longitudinal sand bodies and the development of confined parallel drainages are simultaneous processes resulting in parallel sets of drainages and ridges oriented along the prevailing southwest wind direction on the southern Colorado Plateau.

3-DIMENSIONAL Optoelectronic

NASA Astrophysics Data System (ADS)

Krishnamoorthy, Ashok Venketaraman

This thesis covers the design, analysis, optimization, and implementation of optoelectronic (N,M,F) networks. (N,M,F) networks are generic space-division networks that are well suited to implementation using optoelectronic integrated circuits and free-space optical interconnects. An (N,M,F) networks consists of N input channels each having a fanout F_{rm o}, M output channels each having a fanin F_{rm i}, and Log_{rm K}(N/F) stages of K x K switches. The functionality of the fanout, switching, and fanin stages depends on the specific application. Three applications of optoelectronic (N,M,F) networks are considered. The first is an optoelectronic (N,1,1) content -addressable memory system that achieves associative recall on two-dimensional images retrieved from a parallel-access optical memory. The design and simulation of the associative memory are discussed, and an experimental emulation of a prototype system using images from a parallel-readout optical disk is presented. The system design provides superior performance to existing electronic content-addressable memory chips in terms of capacity and search rate, and uses readily available optical disk and VLSI technologies. Next, a scalable optoelectronic (N,M,F) neural network that uses free-space holographic optical interconnects is presented. The neural architecture minimizes the number of optical transmitters needed, and provides accurate electronic fanin with low signal skew, and dendritic-type fan-in processing capability in a compact layout. Optimal data-encoding methods and circuit techniques are discussed. The implementation of an prototype optoelectronic neural system, and its application to a simple recognition task is demonstrated. Finally, the design, analysis, and optimization of a (N,N,F) self-routing, packet-switched multistage interconnection network is described. The network is suitable for parallel computing and broadband switching applications. The tradeoff between optical and electronic interconnects is examined quantitatively by varying the electronic switch size K. The performance of the (N,N,F) network versus the fanning parameter F, is also analyzed. It is shown that the optoelectronic (N,N,F) networks provide a range of performance-cost alternatives, and offer superior performance-per-cost to fully electronic switching networks and to previous networks designs.

Dense wavelength division multiplexing devices for metropolitan-area datacom and telecom networks

NASA Astrophysics Data System (ADS)

DeCusatis, Casimer M.; Priest, David G.

2000-12-01

Large data processing environments in use today can require multi-gigabyte or terabyte capacity in the data communication infrastructure; these requirements are being driven by storage area networks with access to petabyte data bases, new architecture for parallel processing which require high bandwidth optical links, and rapidly growing network applications such as electronic commerce over the Internet or virtual private networks. These datacom applications require high availability, fault tolerance, security, and the capacity to recover from any single point of failure without relying on traditional SONET-based networking. These requirements, coupled with fiber exhaust in metropolitan areas, are driving the introduction of dense optical wavelength division multiplexing (DWDM) in data communication systems, particularly for large enterprise servers or mainframes. In this paper, we examine the technical requirements for emerging nextgeneration DWDM systems. Protocols for storage area networks and computer architectures such as Parallel Sysplex are presented, including their fiber bandwidth requirements. We then describe two commercially available DWDM solutions, a first generation 10 channel system and a recently announced next generation 32 channel system. Technical requirements, network management and security, fault tolerant network designs, new network topologies enabled by DWDM, and the role of time division multiplexing in the network are all discussed. Finally, we present a description of testing conducted on these networks and future directions for this technology.

Proteus: a reconfigurable computational network for computer vision

NASA Astrophysics Data System (ADS)

Haralick, Robert M.; Somani, Arun K.; Wittenbrink, Craig M.; Johnson, Robert; Cooper, Kenneth; Shapiro, Linda G.; Phillips, Ihsin T.; Hwang, Jenq N.; Cheung, William; Yao, Yung H.; Chen, Chung-Ho; Yang, Larry; Daugherty, Brian; Lorbeski, Bob; Loving, Kent; Miller, Tom; Parkins, Larye; Soos, Steven L.

1992-04-01

The Proteus architecture is a highly parallel MIMD, multiple instruction, multiple-data machine, optimized for large granularity tasks such as machine vision and image processing The system can achieve 20 Giga-flops (80 Giga-flops peak). It accepts data via multiple serial links at a rate of up to 640 megabytes/second. The system employs a hierarchical reconfigurable interconnection network with the highest level being a circuit switched Enhanced Hypercube serial interconnection network for internal data transfers. The system is designed to use 256 to 1,024 RISC processors. The processors use one megabyte external Read/Write Allocating Caches for reduced multiprocessor contention. The system detects, locates, and replaces faulty subsystems using redundant hardware to facilitate fault tolerance. The parallelism is directly controllable through an advanced software system for partitioning, scheduling, and development. System software includes a translator for the INSIGHT language, a parallel debugger, low and high level simulators, and a message passing system for all control needs. Image processing application software includes a variety of point operators neighborhood, operators, convolution, and the mathematical morphology operations of binary and gray scale dilation, erosion, opening, and closing.

Characterization of robotics parallel algorithms and mapping onto a reconfigurable SIMD machine

NASA Technical Reports Server (NTRS)

Lee, C. S. G.; Lin, C. T.

1989-01-01

The kinematics, dynamics, Jacobian, and their corresponding inverse computations are six essential problems in the control of robot manipulators. Efficient parallel algorithms for these computations are discussed and analyzed. Their characteristics are identified and a scheme on the mapping of these algorithms to a reconfigurable parallel architecture is presented. Based on the characteristics including type of parallelism, degree of parallelism, uniformity of the operations, fundamental operations, data dependencies, and communication requirement, it is shown that most of the algorithms for robotic computations possess highly regular properties and some common structures, especially the linear recursive structure. Moreover, they are well-suited to be implemented on a single-instruction-stream multiple-data-stream (SIMD) computer with reconfigurable interconnection network. The model of a reconfigurable dual network SIMD machine with internal direct feedback is introduced. A systematic procedure internal direct feedback is introduced. A systematic procedure to map these computations to the proposed machine is presented. A new scheduling problem for SIMD machines is investigated and a heuristic algorithm, called neighborhood scheduling, that reorders the processing sequence of subtasks to reduce the communication time is described. Mapping results of a benchmark algorithm are illustrated and discussed.

Energy-efficient STDP-based learning circuits with memristor synapses

NASA Astrophysics Data System (ADS)

Wu, Xinyu; Saxena, Vishal; Campbell, Kristy A.

2014-05-01

It is now accepted that the traditional von Neumann architecture, with processor and memory separation, is ill suited to process parallel data streams which a mammalian brain can efficiently handle. Moreover, researchers now envision computing architectures which enable cognitive processing of massive amounts of data by identifying spatio-temporal relationships in real-time and solving complex pattern recognition problems. Memristor cross-point arrays, integrated with standard CMOS technology, are expected to result in massively parallel and low-power Neuromorphic computing architectures. Recently, significant progress has been made in spiking neural networks (SNN) which emulate data processing in the cortical brain. These architectures comprise of a dense network of neurons and the synapses formed between the axons and dendrites. Further, unsupervised or supervised competitive learning schemes are being investigated for global training of the network. In contrast to a software implementation, hardware realization of these networks requires massive circuit overhead for addressing and individually updating network weights. Instead, we employ bio-inspired learning rules such as the spike-timing-dependent plasticity (STDP) to efficiently update the network weights locally. To realize SNNs on a chip, we propose to use densely integrating mixed-signal integrate-andfire neurons (IFNs) and cross-point arrays of memristors in back-end-of-the-line (BEOL) of CMOS chips. Novel IFN circuits have been designed to drive memristive synapses in parallel while maintaining overall power efficiency (<1 pJ/spike/synapse), even at spike rate greater than 10 MHz. We present circuit design details and simulation results of the IFN with memristor synapses, its response to incoming spike trains and STDP learning characterization.

Photonic reservoir computing: a new approach to optical information processing

NASA Astrophysics Data System (ADS)

Vandoorne, Kristof; Fiers, Martin; Verstraeten, David; Schrauwen, Benjamin; Dambre, Joni; Bienstman, Peter

2010-06-01

Despite ever increasing computational power, recognition and classification problems remain challenging to solve. Recently, advances have been made by the introduction of the new concept of reservoir computing. This is a methodology coming from the field of machine learning and neural networks that has been successfully used in several pattern classification problems, like speech and image recognition. Thus far, most implementations have been in software, limiting their speed and power efficiency. Photonics could be an excellent platform for a hardware implementation of this concept because of its inherent parallelism and unique nonlinear behaviour. Moreover, a photonic implementation offers the promise of massively parallel information processing with low power and high speed. We propose using a network of coupled Semiconductor Optical Amplifiers (SOA) and show in simulation that it could be used as a reservoir by comparing it to conventional software implementations using a benchmark speech recognition task. In spite of the differences with classical reservoir models, the performance of our photonic reservoir is comparable to that of conventional implementations and sometimes slightly better. As our implementation uses coherent light for information processing, we find that phase tuning is crucial to obtain high performance. In parallel we investigate the use of a network of photonic crystal cavities. The coupled mode theory (CMT) is used to investigate these resonators. A new framework is designed to model networks of resonators and SOAs. The same network topologies are used, but feedback is added to control the internal dynamics of the system. By adjusting the readout weights of the network in a controlled manner, we can generate arbitrary periodic patterns.

Intervality and coherence in complex networks

NASA Astrophysics Data System (ADS)

Domínguez-García, Virginia; Johnson, Samuel; Muñoz, Miguel A.

2016-06-01

Food webs—networks of predators and prey—have long been known to exhibit "intervality": species can generally be ordered along a single axis in such a way that the prey of any given predator tend to lie on unbroken compact intervals. Although the meaning of this axis—usually identified with a "niche" dimension—has remained a mystery, it is assumed to lie at the basis of the highly non-trivial structure of food webs. With this in mind, most trophic network modelling has for decades been based on assigning species a niche value by hand. However, we argue here that intervality should not be considered the cause but rather a consequence of food-web structure. First, analysing a set of 46 empirical food webs, we find that they also exhibit predator intervality: the predators of any given species are as likely to be contiguous as the prey are, but in a different ordering. Furthermore, this property is not exclusive of trophic networks: several networks of genes, neurons, metabolites, cellular machines, airports, and words are found to be approximately as interval as food webs. We go on to show that a simple model of food-web assembly which does not make use of a niche axis can nevertheless generate significant intervality. Therefore, the niche dimension (in the sense used for food-web modelling) could in fact be the consequence of other, more fundamental structural traits. We conclude that a new approach to food-web modelling is required for a deeper understanding of ecosystem assembly, structure, and function, and propose that certain topological features thought to be specific of food webs are in fact common to many complex networks.

A new method for constructing networks from binary data

NASA Astrophysics Data System (ADS)

van Borkulo, Claudia D.; Borsboom, Denny; Epskamp, Sacha; Blanken, Tessa F.; Boschloo, Lynn; Schoevers, Robert A.; Waldorp, Lourens J.

2014-08-01

Network analysis is entering fields where network structures are unknown, such as psychology and the educational sciences. A crucial step in the application of network models lies in the assessment of network structure. Current methods either have serious drawbacks or are only suitable for Gaussian data. In the present paper, we present a method for assessing network structures from binary data. Although models for binary data are infamous for their computational intractability, we present a computationally efficient model for estimating network structures. The approach, which is based on Ising models as used in physics, combines logistic regression with model selection based on a Goodness-of-Fit measure to identify relevant relationships between variables that define connections in a network. A validation study shows that this method succeeds in revealing the most relevant features of a network for realistic sample sizes. We apply our proposed method to estimate the network of depression and anxiety symptoms from symptom scores of 1108 subjects. Possible extensions of the model are discussed.

Comparison of Two Windstorm Events During the Sierra Rotors Project and Terrain-Induced Rotor Experiment

DTIC Science & Technology

2010-06-01

photograph of Owens Valley during the event. There is an isolated cloud with a leading edge over the center of the valley, consistent with a lenticular ...tom) Lenticular cloud over Owens Valley at 2100 UTC looking SE (photo by Alex Reinecke). vations and there is no separation of the surface wester- lies...southwestern US. On the other hand, satellite also shows clouds organized in bands parallel to the mountains and lenticular clouds were present over Owens

Finite lateral compression of an elastic plasticfibre-reinforced tube : loading solutions

NASA Astrophysics Data System (ADS)

England, A. H.; Gregory, P. W.

1999-02-01

This paper considers the finite plane-strain deformations of an elastic-plastic tubecompressed between two rigid smooth parallel plates. The tube is composed of an elastic-plasticfibre-reinforced material in which the fibres lie in planes perpendicular to the axis of the tube andreinforce the tube in the circumferential direction. The composite is assumed to be an idealmaterial which is inextensible in the fibre-direction and is incompressible. The unloading of theelastic-plastic tube will be considered in a subsequent paper.

Evaluation of fracture toughness of human dentin using elastic-plastic fracture mechanics.

PubMed

Yan, Jiahau; Taskonak, Burak; Platt, Jeffrey A; Mecholsky, John J

2008-01-01

Dentin, the mineralized tissue forming the bulk of the tooth, lies between the enamel and the pulp chamber. It is a rich source of inspiration for designing novel synthetic materials due to its unique microstructure. Most of the previous studies investigating the fracture toughness of dentin have used linear-elastic fracture mechanics (LEFM) that ignores plastic deformation and could underestimate the toughness of dentin. With the presence of collagen (approximately 30% by volume) aiding the toughening mechanisms in dentin, we hypothesize that there is a significant difference between the fracture toughness estimated using LEFM (Kc) and elastic-plastic fracture mechanics (EPFM) (KJc). Single-edge notched beam specimens with in-plane (n=10) and anti-plane (n=10) parallel fractures were prepared following ASTM standard E1820 and tested in three-point flexure. KJc of the in-plane parallel and anti-plane parallel specimens were found to be 3.1 and 3.4 MPa m 1/2 and Kc were 2.4 and 2.5 MPa m 1/2, respectively. The fracture toughness estimated based on KJc is significantly greater than that estimated based on Kc (32.5% on average; p<0.001). In addition, KJc of anti-plane parallel specimens is significantly greater than that of in-plane parallel specimens. We suggest that, in order to critically evaluate the fracture toughness of human dentin, EPFM should be employed.

Optical interconnection networks for high-performance computing systems

NASA Astrophysics Data System (ADS)

Biberman, Aleksandr; Bergman, Keren

2012-04-01

Enabled by silicon photonic technology, optical interconnection networks have the potential to be a key disruptive technology in computing and communication industries. The enduring pursuit of performance gains in computing, combined with stringent power constraints, has fostered the ever-growing computational parallelism associated with chip multiprocessors, memory systems, high-performance computing systems and data centers. Sustaining these parallelism growths introduces unique challenges for on- and off-chip communications, shifting the focus toward novel and fundamentally different communication approaches. Chip-scale photonic interconnection networks, enabled by high-performance silicon photonic devices, offer unprecedented bandwidth scalability with reduced power consumption. We demonstrate that the silicon photonic platforms have already produced all the high-performance photonic devices required to realize these types of networks. Through extensive empirical characterization in much of our work, we demonstrate such feasibility of waveguides, modulators, switches and photodetectors. We also demonstrate systems that simultaneously combine many functionalities to achieve more complex building blocks. We propose novel silicon photonic devices, subsystems, network topologies and architectures to enable unprecedented performance of these photonic interconnection networks. Furthermore, the advantages of photonic interconnection networks extend far beyond the chip, offering advanced communication environments for memory systems, high-performance computing systems, and data centers.

Modern temporal network theory: a colloquium

NASA Astrophysics Data System (ADS)

Holme, Petter

2015-09-01

The power of any kind of network approach lies in the ability to simplify a complex system so that one can better understand its function as a whole. Sometimes it is beneficial, however, to include more information than in a simple graph of only nodes and links. Adding information about times of interactions can make predictions and mechanistic understanding more accurate. The drawback, however, is that there are not so many methods available, partly because temporal networks is a relatively young field, partly because it is more difficult to develop such methods compared to for static networks. In this colloquium, we review the methods to analyze and model temporal networks and processes taking place on them, focusing mainly on the last three years. This includes the spreading of infectious disease, opinions, rumors, in social networks; information packets in computer networks; various types of signaling in biology, and more. We also discuss future directions.

Broadband Optical Access Technologies to Converge towards a Broadband Society in Europe

NASA Astrophysics Data System (ADS)

Coudreuse, Jean-Pierre; Pautonnier, Sophie; Lavillonnière, Eric; Didierjean, Sylvain; Hilt, Benoît; Kida, Toshimichi; Oshima, Kazuyoshi

This paper provides insights on the status of broadband optical access market and technologies in Europe and on the expected trends for the next generation optical access networks. The final target for most operators, cities or any other player is of course FTTH (Fibre To The Home) deployment although we can expect intermediate steps with copper or wireless technologies. Among the two candidate architectures for FTTH, PON (Passive Optical Network) is by far the most attractive and cost effective solution. We also demonstrate that Ethernet based optical access network is very adequate to all-IP networks without any incidence on the level of quality of service. Finally, we provide feedback from a FTTH pilot network in Colmar (France) based on Gigabit Ethernet PON technology. The interest of this pilot lies on the level of functionality required for broadband optical access networks but also on the development of new home network configurations.

Cell Migration in 1D and 2D Nanofiber Microenvironments.

PubMed

Estabridis, Horacio M; Jana, Aniket; Nain, Amrinder; Odde, David J

2018-03-01

Understanding how cells migrate in fibrous environments is important in wound healing, immune function, and cancer progression. A key question is how fiber orientation and network geometry influence cell movement. Here we describe a quantitative, modeling-based approach toward identifying the mechanisms by which cells migrate in fibrous geometries having well controlled orientation. Specifically, U251 glioblastoma cells were seeded onto non-electrospinning Spinneret based tunable engineering parameters fiber substrates that consist of networks of suspended 400 nm diameter nanofibers. Cells were classified based on the local fiber geometry and cell migration dynamics observed by light microscopy. Cells were found in three distinct geometries: adhering two a single fiber, adhering to two parallel fibers, and adhering to a network of orthogonal fibers. Cells adhering to a single fiber or two parallel fibers can only move in one dimension along the fiber axis, whereas cells on a network of orthogonal fibers can move in two dimensions. We found that cells move faster and more persistently in 1D geometries than in 2D, with cell migration being faster on parallel fibers than on single fibers. To explain these behaviors mechanistically, we simulated cell migration in the three different geometries using a motor-clutch based model for cell traction forces. Using nearly identical parameter sets for each of the three cases, we found that the simulated cells naturally replicated the reduced migration in 2D relative to 1D geometries. In addition, the modestly faster 1D migration on parallel fibers relative to single fibers was captured using a correspondingly modest increase in the number of clutches to reflect increased surface area of adhesion on parallel fibers. Overall, the integrated modeling and experimental analysis shows that cell migration in response to varying fibrous geometries can be explained by a simple mechanical readout of geometry via a motor-clutch mechanism.

Using Motivational Interviewing Techniques to Address Parallel Process in Supervision

ERIC Educational Resources Information Center

Giordano, Amanda; Clarke, Philip; Borders, L. DiAnne

2013-01-01

Supervision offers a distinct opportunity to experience the interconnection of counselor-client and counselor-supervisor interactions. One product of this network of interactions is parallel process, a phenomenon by which counselors unconsciously identify with their clients and subsequently present to their supervisors in a similar fashion…

Hardware packet pacing using a DMA in a parallel computer

DOEpatents

Chen, Dong; Heidelberger, Phillip; Vranas, Pavlos

2013-08-13

Method and system for hardware packet pacing using a direct memory access controller in a parallel computer which, in one aspect, keeps track of a total number of bytes put on the network as a result of a remote get operation, using a hardware token counter.

What's in a Name?

ERIC Educational Resources Information Center

Petersen, Rodney

2004-01-01

The evolution of terms, such as computer security, network security, information security, and information assurance, appears to reflect a changing landscape, largely influenced by rapid developments in technology and the maturity of a relatively young profession and an emerging academic discipline. What lies behind the evolution of these terms?…

Optical Interconnection Via Computer-Generated Holograms

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang; Zhou, Shaomin

1995-01-01

Method of free-space optical interconnection developed for data-processing applications like parallel optical computing, neural-network computing, and switching in optical communication networks. In method, multiple optical connections between multiple sources of light in one array and multiple photodetectors in another array made via computer-generated holograms in electrically addressed spatial light modulators (ESLMs). Offers potential advantages of massive parallelism, high space-bandwidth product, high time-bandwidth product, low power consumption, low cross talk, and low time skew. Also offers advantage of programmability with flexibility of reconfiguration, including variation of strengths of optical connections in real time.

High Performance Computing and Visualization Infrastructure for Simultaneous Parallel Computing and Parallel Visualization Research

DTIC Science & Technology

2016-11-09

Total Number: Sub Contractors (DD882) Names of Personnel receiving masters degrees Names of personnel receiving PHDs Names of other research staff...Broadcom 5720 QP 1Gb Network Daughter Card (2) Intel Xeon E5-2680 v3 2.5GHz, 30M Cache, 9.60GT/s QPI, Turbo, HT , 12C/24T (120W...Broadcom 5720 QP 1Gb Network Daughter Card (2) Intel Xeon E5-2680 v3 2.5GHz, 30M Cache, 9.60GT/s QPI, Turbo, HT , 12C/24T (120W

Parallelized direct execution simulation of message-passing parallel programs

NASA Technical Reports Server (NTRS)

Dickens, Phillip M.; Heidelberger, Philip; Nicol, David M.

1994-01-01

As massively parallel computers proliferate, there is growing interest in findings ways by which performance of massively parallel codes can be efficiently predicted. This problem arises in diverse contexts such as parallelizing computers, parallel performance monitoring, and parallel algorithm development. In this paper we describe one solution where one directly executes the application code, but uses a discrete-event simulator to model details of the presumed parallel machine such as operating system and communication network behavior. Because this approach is computationally expensive, we are interested in its own parallelization specifically the parallelization of the discrete-event simulator. We describe methods suitable for parallelized direct execution simulation of message-passing parallel programs, and report on the performance of such a system, Large Application Parallel Simulation Environment (LAPSE), we have built on the Intel Paragon. On all codes measured to date, LAPSE predicts performance well typically within 10 percent relative error. Depending on the nature of the application code, we have observed low slowdowns (relative to natively executing code) and high relative speedups using up to 64 processors.

A general purpose wideband optical spatial frequency spectrum analyzer

NASA Technical Reports Server (NTRS)

Ballard, G. S.; Mellor, F. A.

1972-01-01

The light scattered at various angles by a transparent media is studied. An example of these applications is the optical Fourier spectrum measurement resulting from various spatial frequencies which were recorded on a photographic emulsion. A method for obtaining these measurements consists of illuminating the test object with parallel monochromatic light. A stationary lens, placed in the resulting wavefield at a distance of one focal length from the object, will focus parallel waves emanating from the test object at a point lying in the focal plane of the lens. A light detector with a small filtering aperture is then used to measure the intensity variation of the light in the focal or transform plane of the lens. Such measurements require the use of a lens which is highly corrected for all of the common aberrations except chromatic aberration.

Evaluating local indirect addressing in SIMD proc essors

NASA Technical Reports Server (NTRS)

Middleton, David; Tomboulian, Sherryl

1989-01-01

In the design of parallel computers, there exists a tradeoff between the number and power of individual processors. The single instruction stream, multiple data stream (SIMD) model of parallel computers lies at one extreme of the resulting spectrum. The available hardware resources are devoted to creating the largest possible number of processors, and consequently each individual processor must use the fewest possible resources. Disagreement exists as to whether SIMD processors should be able to generate addresses individually into their local data memory, or all processors should access the same address. The tradeoff is examined between the increased capability and the reduced number of processors that occurs in this single instruction stream, multiple, locally addressed, data (SIMLAD) model. Factors are assembled that affect this design choice, and the SIMLAD model is compared with the bare SIMD and the MIMD models.

Projective flatness in the quantisation of bosons and fermions

NASA Astrophysics Data System (ADS)

Wu, Siye

2015-07-01

We compare the quantisation of linear systems of bosons and fermions. We recall the appearance of projectively flat connection and results on parallel transport in the quantisation of bosons. We then discuss pre-quantisation and quantisation of fermions using the calculus of fermionic variables. We define a natural connection on the bundle of Hilbert spaces and show that it is projectively flat. This identifies, up to a phase, equivalent spinor representations constructed by various polarisations. We introduce the concept of metaplectic correction for fermions and show that the bundle of corrected Hilbert spaces is naturally flat. We then show that the parallel transport in the bundle of Hilbert spaces along a geodesic is a rescaled projection provided that the geodesic lies within the complement of a cut locus. Finally, we study the bundle of Hilbert spaces when there is a symmetry.

Switch for serial or parallel communication networks

DOEpatents

Crosette, D.B.

1994-07-19

A communication switch apparatus and a method for use in a geographically extensive serial, parallel or hybrid communication network linking a multi-processor or parallel processing system has a very low software processing overhead in order to accommodate random burst of high density data. Associated with each processor is a communication switch. A data source and a data destination, a sensor suite or robot for example, may also be associated with a switch. The configuration of the switches in the network are coordinated through a master processor node and depends on the operational phase of the multi-processor network: data acquisition, data processing, and data exchange. The master processor node passes information on the state to be assumed by each switch to the processor node associated with the switch. The processor node then operates a series of multi-state switches internal to each communication switch. The communication switch does not parse and interpret communication protocol and message routing information. During a data acquisition phase, the communication switch couples sensors producing data to the processor node associated with the switch, to a downlink destination on the communications network, or to both. It also may couple an uplink data source to its processor node. During the data exchange phase, the switch couples its processor node or an uplink data source to a downlink destination (which may include a processor node or a robot), or couples an uplink source to its processor node and its processor node to a downlink destination. 9 figs.

Switch for serial or parallel communication networks

DOEpatents

Crosette, Dario B.

1994-01-01

A communication switch apparatus and a method for use in a geographically extensive serial, parallel or hybrid communication network linking a multi-processor or parallel processing system has a very low software processing overhead in order to accommodate random burst of high density data. Associated with each processor is a communication switch. A data source and a data destination, a sensor suite or robot for example, may also be associated with a switch. The configuration of the switches in the network are coordinated through a master processor node and depends on the operational phase of the multi-processor network: data acquisition, data processing, and data exchange. The master processor node passes information on the state to be assumed by each switch to the processor node associated with the switch. The processor node then operates a series of multi-state switches internal to each communication switch. The communication switch does not parse and interpret communication protocol and message routing information. During a data acquisition phase, the communication switch couples sensors producing data to the processor node associated with the switch, to a downlink destination on the communications network, or to both. It also may couple an uplink data source to its processor node. During the data exchange phase, the switch couples its processor node or an uplink data source to a downlink destination (which may include a processor node or a robot), or couples an uplink source to its processor node and its processor node to a downlink destination.

A General Connectionist Model of Attitude Structure and Change: The ACS (Attitudes as Constraint Satisfaction) Model

ERIC Educational Resources Information Center

Monroe, Brian M.; Read, Stephen J.

2008-01-01

A localist, parallel constraint satisfaction, artificial neural network model is presented that accounts for a broad collection of attitude and attitude-change phenomena. The network represents the attitude object and cognitions and beliefs related to the attitude, as well as how to integrate a persuasive message into this network. Short-term…

Game Theoretic Models of Competition and Upgrade Investments in Communication Networks

ERIC Educational Resources Information Center

Wu, Shuang

2010-01-01

In the first part of this dissertation, we study the competition among network service providers in a parallel-link network with the presence of elastic user demand that diminishes both with higher prices and congestion. First we analyze a game where providers strategically price their service for single class of traffic. Later we analyze a game…

Analog Processor To Solve Optimization Problems

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Eberhardt, Silvio P.; Thakoor, Anil P.

1993-01-01

Proposed analog processor solves "traveling-salesman" problem, considered paradigm of global-optimization problems involving routing or allocation of resources. Includes electronic neural network and auxiliary circuitry based partly on concepts described in "Neural-Network Processor Would Allocate Resources" (NPO-17781) and "Neural Network Solves 'Traveling-Salesman' Problem" (NPO-17807). Processor based on highly parallel computing solves problem in significantly less time.

Design and Evaluation of a Widget-Based Dashboard for Awareness Support in Research Networks

ERIC Educational Resources Information Center

Reinhardt, Wolfgang; Mletzko, Christian; Drachsler, Hendrik; Sloep, Peter B.

2014-01-01

In this article, we describe the rationale, design and evaluation of a widget-based dashboard to support scholars' awareness of their Research Networks. We introduce the concept of a Research Network and discuss Personal Research Environments that are built of as a development parallel to Personal Learning Environments. Based on the results…

Method and apparatus for routing data in an inter-nodal communications lattice of a massively parallel computer system by semi-randomly varying routing policies for different packets

DOEpatents

Archer, Charles Jens; Musselman, Roy Glenn; Peters, Amanda; Pinnow, Kurt Walter; Swartz, Brent Allen; Wallenfelt, Brian Paul

2010-11-23

A massively parallel computer system contains an inter-nodal communications network of node-to-node links. Nodes vary a choice of routing policy for routing data in the network in a semi-random manner, so that similarly situated packets are not always routed along the same path. Semi-random variation of the routing policy tends to avoid certain local hot spots of network activity, which might otherwise arise using more consistent routing determinations. Preferably, the originating node chooses a routing policy for a packet, and all intermediate nodes in the path route the packet according to that policy. Policies may be rotated on a round-robin basis, selected by generating a random number, or otherwise varied.

Predicting Cost/Performance Trade-Offs for Whitney: A Commodity Computing Cluster

NASA Technical Reports Server (NTRS)

Becker, Jeffrey C.; Nitzberg, Bill; VanderWijngaart, Rob F.; Kutler, Paul (Technical Monitor)

1997-01-01

Recent advances in low-end processor and network technology have made it possible to build a "supercomputer" out of commodity components. We develop simple models of the NAS Parallel Benchmarks version 2 (NPB 2) to explore the cost/performance trade-offs involved in building a balanced parallel computer supporting a scientific workload. We develop closed form expressions detailing the number and size of messages sent by each benchmark. Coupling these with measured single processor performance, network latency, and network bandwidth, our models predict benchmark performance to within 30%. A comparison based on total system cost reveals that current commodity technology (200 MHz Pentium Pros with 100baseT Ethernet) is well balanced for the NPBs up to a total system cost of around $1,000,000.

DMA shared byte counters in a parallel computer

DOEpatents

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.

Reverse engineering and analysis of large genome-scale gene networks

PubMed Central

Aluru, Maneesha; Zola, Jaroslaw; Nettleton, Dan; Aluru, Srinivas

2013-01-01

Reverse engineering the whole-genome networks of complex multicellular organisms continues to remain a challenge. While simpler models easily scale to large number of genes and gene expression datasets, more accurate models are compute intensive limiting their scale of applicability. To enable fast and accurate reconstruction of large networks, we developed Tool for Inferring Network of Genes (TINGe), a parallel mutual information (MI)-based program. The novel features of our approach include: (i) B-spline-based formulation for linear-time computation of MI, (ii) a novel algorithm for direct permutation testing and (iii) development of parallel algorithms to reduce run-time and facilitate construction of large networks. We assess the quality of our method by comparison with ARACNe (Algorithm for the Reconstruction of Accurate Cellular Networks) and GeneNet and demonstrate its unique capability by reverse engineering the whole-genome network of Arabidopsis thaliana from 3137 Affymetrix ATH1 GeneChips in just 9 min on a 1024-core cluster. We further report on the development of a new software Gene Network Analyzer (GeNA) for extracting context-specific subnetworks from a given set of seed genes. Using TINGe and GeNA, we performed analysis of 241 Arabidopsis AraCyc 8.0 pathways, and the results are made available through the web. PMID:23042249

Phonon coupling to dynamic short-range polar order in a relaxor ferroelectric near the morphotropic phase boundary

DOE PAGES

John A. Schneeloch; Xu, Zhijun; Winn, B.; ...

2015-12-28

We report neutron inelastic scattering experiments on single-crystal PbMg 1/3Nb 2/3O 3 doped with 32% PbTiO 3, a relaxor ferroelectric that lies close to the morphotropic phase boundary. When cooled under an electric field E∥ [001] into tetragonal and monoclinic phases, the scattering cross section from transverse acoustic (TA) phonons polarized parallel to E weakens and shifts to higher energy relative to that under zero-field-cooled conditions. Likewise, the scattering cross section from transverse optic (TO) phonons polarized parallel to E weakens for energy transfers 4 ≤ ℏω ≤ 9 meV. However, TA and TO phonons polarized perpendicular to E showmore » no change. This anisotropic field response is similar to that of the diffuse scattering cross section, which, as previously reported, is suppressed when polarized parallel to E but not when polarized perpendicular to E. Lastly, our findings suggest that the lattice dynamics and dynamic short-range polar correlations that give rise to the diffuse scattering are coupled.« less

A distributed parallel storage architecture and its potential application within EOSDIS

NASA Technical Reports Server (NTRS)

Johnston, William E.; Tierney, Brian; Feuquay, Jay; Butzer, Tony

1994-01-01

We describe the architecture, implementation, use of a scalable, high performance, distributed-parallel data storage system developed in the ARPA funded MAGIC gigabit testbed. A collection of wide area distributed disk servers operate in parallel to provide logical block level access to large data sets. Operated primarily as a network-based cache, the architecture supports cooperation among independently owned resources to provide fast, large-scale, on-demand storage to support data handling, simulation, and computation.

Synchronization Of Parallel Discrete Event Simulations

NASA Technical Reports Server (NTRS)

Steinman, Jeffrey S.

1992-01-01

Adaptive, parallel, discrete-event-simulation-synchronization algorithm, Breathing Time Buckets, developed in Synchronous Parallel Environment for Emulation and Discrete Event Simulation (SPEEDES) operating system. Algorithm allows parallel simulations to process events optimistically in fluctuating time cycles that naturally adapt while simulation in progress. Combines best of optimistic and conservative synchronization strategies while avoiding major disadvantages. Algorithm processes events optimistically in time cycles adapting while simulation in progress. Well suited for modeling communication networks, for large-scale war games, for simulated flights of aircraft, for simulations of computer equipment, for mathematical modeling, for interactive engineering simulations, and for depictions of flows of information.

Parallel Signal Processing and System Simulation using aCe

NASA Technical Reports Server (NTRS)

Dorband, John E.; Aburdene, Maurice F.

2003-01-01

Recently, networked and cluster computation have become very popular for both signal processing and system simulation. A new language is ideally suited for parallel signal processing applications and system simulation since it allows the programmer to explicitly express the computations that can be performed concurrently. In addition, the new C based parallel language (ace C) for architecture-adaptive programming allows programmers to implement algorithms and system simulation applications on parallel architectures by providing them with the assurance that future parallel architectures will be able to run their applications with a minimum of modification. In this paper, we will focus on some fundamental features of ace C and present a signal processing application (FFT).

Turbomachinery CFD on parallel computers

NASA Technical Reports Server (NTRS)

Blech, Richard A.; Milner, Edward J.; Quealy, Angela; Townsend, Scott E.

1992-01-01

The role of multistage turbomachinery simulation in the development of propulsion system models is discussed. Particularly, the need for simulations with higher fidelity and faster turnaround time is highlighted. It is shown how such fast simulations can be used in engineering-oriented environments. The use of parallel processing to achieve the required turnaround times is discussed. Current work by several researchers in this area is summarized. Parallel turbomachinery CFD research at the NASA Lewis Research Center is then highlighted. These efforts are focused on implementing the average-passage turbomachinery model on MIMD, distributed memory parallel computers. Performance results are given for inviscid, single blade row and viscous, multistage applications on several parallel computers, including networked workstations.

Connecticut's Evolving Interactive Distance Learning Network in the Cable and Telecommunications Industries.

ERIC Educational Resources Information Center

Pietras, Jesse John

This paper describes the state of interactive distance learning in Connecticut, particularly the current and future provision of these services by the telecommunications and cable television industries. The overview examines questions of where obligation and responsibility lie (with schools, local exchange companies, cable franchises, etc.) in…

QR-decomposition based SENSE reconstruction using parallel architecture.

PubMed

Ullah, Irfan; Nisar, Habab; Raza, Haseeb; Qasim, Malik; Inam, Omair; Omer, Hammad

2018-04-01

Magnetic Resonance Imaging (MRI) is a powerful medical imaging technique that provides essential clinical information about the human body. One major limitation of MRI is its long scan time. Implementation of advance MRI algorithms on a parallel architecture (to exploit inherent parallelism) has a great potential to reduce the scan time. Sensitivity Encoding (SENSE) is a Parallel Magnetic Resonance Imaging (pMRI) algorithm that utilizes receiver coil sensitivities to reconstruct MR images from the acquired under-sampled k-space data. At the heart of SENSE lies inversion of a rectangular encoding matrix. This work presents a novel implementation of GPU based SENSE algorithm, which employs QR decomposition for the inversion of the rectangular encoding matrix. For a fair comparison, the performance of the proposed GPU based SENSE reconstruction is evaluated against single and multicore CPU using openMP. Several experiments against various acceleration factors (AFs) are performed using multichannel (8, 12 and 30) phantom and in-vivo human head and cardiac datasets. Experimental results show that GPU significantly reduces the computation time of SENSE reconstruction as compared to multi-core CPU (approximately 12x speedup) and single-core CPU (approximately 53x speedup) without any degradation in the quality of the reconstructed images. Copyright © 2018 Elsevier Ltd. All rights reserved.

TRANSMISSION NETWORK PLANNING METHOD FOR COMPARATIVE STUDIES (JOURNAL VERSION)

EPA Science Inventory

An automated transmission network planning method for comparative studies is presented. This method employs logical steps that may closely parallel those taken in practice by the planning engineers. Use is made of a sensitivity matrix to simulate the engineers' experience in sele...

Architecture of interstitial nodal spaces in the rodent renal inner medulla.

PubMed

Gilbert, Rebecca L; Pannabecker, Thomas L

2013-09-01

Every collecting duct (CD) of the rat inner medulla is uniformly surrounded by about four abutting ascending vasa recta (AVR) running parallel to it. One or two ascending thin limbs (ATLs) lie between and parallel to each abutting AVR pair, opposite the CD. These structures form boundaries of axially running interstitial compartments. Viewed in transverse sections, these compartments appear as four interstitial nodal spaces (INSs) positioned symmetrically around each CD. The axially running compartments are segmented by interstitial cells spaced at regular intervals. The pairing of ATLs and CDs bounded by an abundant supply of AVR carrying reabsorbed water, NaCl, and urea make a strong argument that the mixing of NaCl and urea within the INSs and countercurrent flows play a critical role in generating the inner medullary osmotic gradient. The results of this study fully support that hypothesis. We quantified interactions of all structures comprising INSs along the corticopapillary axis for two rodent species, the Munich-Wistar rat and the kangaroo rat. The results showed remarkable similarities in the configurations of INSs, suggesting that the structural arrangement of INSs is a highly conserved architecture that plays a fundamental role in renal function. The number density of INSs along the corticopapillary axis directly correlated with a loop population that declines exponentially with distance below the outer medullary-inner medullary boundary. The axial configurations were consistent with discrete association between near-bend loop segments and INSs and with upper loop segments lying distant from INSs.

Architecture of interstitial nodal spaces in the rodent renal inner medulla

PubMed Central

Gilbert, Rebecca L.

2013-01-01

Every collecting duct (CD) of the rat inner medulla is uniformly surrounded by about four abutting ascending vasa recta (AVR) running parallel to it. One or two ascending thin limbs (ATLs) lie between and parallel to each abutting AVR pair, opposite the CD. These structures form boundaries of axially running interstitial compartments. Viewed in transverse sections, these compartments appear as four interstitial nodal spaces (INSs) positioned symmetrically around each CD. The axially running compartments are segmented by interstitial cells spaced at regular intervals. The pairing of ATLs and CDs bounded by an abundant supply of AVR carrying reabsorbed water, NaCl, and urea make a strong argument that the mixing of NaCl and urea within the INSs and countercurrent flows play a critical role in generating the inner medullary osmotic gradient. The results of this study fully support that hypothesis. We quantified interactions of all structures comprising INSs along the corticopapillary axis for two rodent species, the Munich-Wistar rat and the kangaroo rat. The results showed remarkable similarities in the configurations of INSs, suggesting that the structural arrangement of INSs is a highly conserved architecture that plays a fundamental role in renal function. The number density of INSs along the corticopapillary axis directly correlated with a loop population that declines exponentially with distance below the outer medullary-inner medullary boundary. The axial configurations were consistent with discrete association between near-bend loop segments and INSs and with upper loop segments lying distant from INSs. PMID:23825077

Assignment Of Finite Elements To Parallel Processors

NASA Technical Reports Server (NTRS)

Salama, Moktar A.; Flower, Jon W.; Otto, Steve W.

1990-01-01

Elements assigned approximately optimally to subdomains. Mapping algorithm based on simulated-annealing concept used to minimize approximate time required to perform finite-element computation on hypercube computer or other network of parallel data processors. Mapping algorithm needed when shape of domain complicated or otherwise not obvious what allocation of elements to subdomains minimizes cost of computation.

Parallel Distributed Processing at 25: Further Explorations in the Microstructure of Cognition

ERIC Educational Resources Information Center

Rogers, Timothy T.; McClelland, James L.

2014-01-01

This paper introduces a special issue of "Cognitive Science" initiated on the 25th anniversary of the publication of "Parallel Distributed Processing" (PDP), a two-volume work that introduced the use of neural network models as vehicles for understanding cognition. The collection surveys the core commitments of the PDP…

Scalable Static and Dynamic Community Detection Using Grappolo

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

Halappanavar, Mahantesh; Lu, Hao; Kalyanaraman, Anantharaman

Graph clustering, popularly known as community detection, is a fundamental kernel for several applications of relevance to the Defense Advanced Research Projects Agency’s (DARPA) Hierarchical Identify Verify Exploit (HIVE) Pro- gram. Clusters or communities represent natural divisions within a network that are densely connected within a cluster and sparsely connected to the rest of the network. The need to compute clustering on large scale data necessitates the development of efficient algorithms that can exploit modern architectures that are fundamentally parallel in nature. How- ever, due to their irregular and inherently sequential nature, many of the current algorithms for community detectionmore » are challenging to parallelize. In response to the HIVE Graph Challenge, we present several parallelization heuristics for fast community detection using the Louvain method as the serial template. We implement all the heuristics in a software library called Grappolo. Using the inputs from the HIVE Challenge, we demonstrate superior performance and high quality solutions based on four parallelization heuristics. We use Grappolo on static graphs as the first step towards community detection on streaming graphs.« less

An eight-channel T/R head coil for parallel transmit MRI at 3T using ultra-low output impedance amplifiers

PubMed Central

Moody, Katherine Lynn; Hollingsworth, Neal A.; Zhao, Feng; Nielsen, Jon-Fredrik; Noll, Douglas C.; Wright, Steven M.; McDougall, Mary Preston

2014-01-01

Parallel transmit is an emerging technology to address the technical challenges associated with MR imaging at high field strengths. When developing arrays for parallel transmit systems, one of the primary factors to be considered is the mechanism to manage coupling and create independently operating channels. Recent work has demonstrated the use of amplifiers to provide some or all of the channel-to-channel isolation, reducing the need for on-coil decoupling networks in a manner analogous to the use of isolation preamplifiers with receive coils. This paper discusses an eight-channel transmit/receive head array for use with an ultra-low output impedance (ULOI) parallel transmit system. The ULOI amplifiers eliminated the need for a complex lumped element network to decouple the eight rung array. The design and construction details of the array are discussed in addition to the measurement considerations required for appropriately characterizing an array when using ULOI amplifiers. B1 maps and coupling matrices are used to verify the performance of the system. PMID:25072190

Electromagnetic Design of a Magnetically-Coupled Spatial Power Combiner

NASA Technical Reports Server (NTRS)

Bulcha, B.; Cataldo, G.; Stevenson, T. R.; U-Yen, K.; Moseley, S. H.; Wollack, E. J.

2017-01-01

The design of a two-dimensional beam-combining network employing a parallel-plate superconducting waveguide with a mono-crystalline silicon dielectric is presented. This novel beam-combining network structure employs an array of magnetically coupled antenna elements to achieve high coupling efficiency and full sampling of the intensity distribution while avoiding diffractive losses in the multi-mode region defined by the parallel-plate waveguide. These attributes enable the structures use in realizing compact far-infrared spectrometers for astrophysical and instrumentation applications. When configured with a suitable corporate-feed power-combiner, this fully sampled array can be used to realize a low-sidelobe apodized response without incurring a reduction in coupling efficiency. To control undesired reflections over a wide range of angles in the finite-sized parallel-plate waveguide region, a wideband meta-material electromagnetic absorber structure is implemented. This adiabatic structure absorbs greater than 99 of the power over the 1.7:1 operational band at angles ranging from normal (0 degree) to near parallel (180 degree) incidence. Design, simulations, and application of the device will be presented.

Decentralized diagnostics based on a distributed micro-genetic algorithm for transducer networks monitoring large experimental systems.

PubMed

Arpaia, P; Cimmino, P; Girone, M; La Commara, G; Maisto, D; Manna, C; Pezzetti, M

2014-09-01

Evolutionary approach to centralized multiple-faults diagnostics is extended to distributed transducer networks monitoring large experimental systems. Given a set of anomalies detected by the transducers, each instance of the multiple-fault problem is formulated as several parallel communicating sub-tasks running on different transducers, and thus solved one-by-one on spatially separated parallel processes. A micro-genetic algorithm merges evaluation time efficiency, arising from a small-size population distributed on parallel-synchronized processors, with the effectiveness of centralized evolutionary techniques due to optimal mix of exploitation and exploration. In this way, holistic view and effectiveness advantages of evolutionary global diagnostics are combined with reliability and efficiency benefits of distributed parallel architectures. The proposed approach was validated both (i) by simulation at CERN, on a case study of a cold box for enhancing the cryogeny diagnostics of the Large Hadron Collider, and (ii) by experiments, under the framework of the industrial research project MONDIEVOB (Building Remote Monitoring and Evolutionary Diagnostics), co-funded by EU and the company Del Bo srl, Napoli, Italy.

An eight-channel T/R head coil for parallel transmit MRI at 3T using ultra-low output impedance amplifiers

NASA Astrophysics Data System (ADS)

Moody, Katherine Lynn; Hollingsworth, Neal A.; Zhao, Feng; Nielsen, Jon-Fredrik; Noll, Douglas C.; Wright, Steven M.; McDougall, Mary Preston

2014-09-01

Parallel transmit is an emerging technology to address the technical challenges associated with MR imaging at high field strengths. When developing arrays for parallel transmit systems, one of the primary factors to be considered is the mechanism to manage coupling and create independently operating channels. Recent work has demonstrated the use of amplifiers to provide some or all of the channel-to-channel isolation, reducing the need for on-coil decoupling networks in a manner analogous to the use of isolation preamplifiers with receive coils. This paper discusses an eight-channel transmit/receive head array for use with an ultra-low output impedance (ULOI) parallel transmit system. The ULOI amplifiers eliminated the need for a complex lumped element network to decouple the eight-rung array. The design and construction details of the array are discussed in addition to the measurement considerations required for appropriately characterizing an array when using ULOI amplifiers. B1 maps and coupling matrices are used to verify the performance of the system.

Flow distribution in parallel microfluidic networks and its effect on concentration gradient

PubMed Central

Guermonprez, Cyprien; Michelin, Sébastien; Baroud, Charles N.

2015-01-01

The architecture of microfluidic networks can significantly impact the flow distribution within its different branches and thereby influence tracer transport within the network. In this paper, we study the flow rate distribution within a network of parallel microfluidic channels with a single input and single output, using a combination of theoretical modeling and microfluidic experiments. Within the ladder network, the flow rate distribution follows a U-shaped profile, with the highest flow rate occurring in the initial and final branches. The contrast with the central branches is controlled by a single dimensionless parameter, namely, the ratio of hydrodynamic resistance between the distribution channel and the side branches. This contrast in flow rates decreases when the resistance of the side branches increases relative to the resistance of the distribution channel. When the inlet flow is composed of two parallel streams, one of which transporting a diffusing species, a concentration variation is produced within the side branches of the network. The shape of this concentration gradient is fully determined by two dimensionless parameters: the ratio of resistances, which determines the flow rate distribution, and the Péclet number, which characterizes the relative speed of diffusion and advection. Depending on the values of these two control parameters, different distribution profiles can be obtained ranging from a flat profile to a step distribution of solute, with well-distributed gradients between these two limits. Our experimental results are in agreement with our numerical model predictions, based on a simplified 2D advection-diffusion problem. Finally, two possible applications of this work are presented: the first one combines the present design with self-digitization principle to encapsulate the controlled concentration in nanoliter chambers, while the second one extends the present design to create a continuous concentration gradient within an open flow chamber. PMID:26487905

Real-time simulation of a spiking neural network model of the basal ganglia circuitry using general purpose computing on graphics processing units.

PubMed

Igarashi, Jun; Shouno, Osamu; Fukai, Tomoki; Tsujino, Hiroshi

2011-11-01

Real-time simulation of a biologically realistic spiking neural network is necessary for evaluation of its capacity to interact with real environments. However, the real-time simulation of such a neural network is difficult due to its high computational costs that arise from two factors: (1) vast network size and (2) the complicated dynamics of biologically realistic neurons. In order to address these problems, mainly the latter, we chose to use general purpose computing on graphics processing units (GPGPUs) for simulation of such a neural network, taking advantage of the powerful computational capability of a graphics processing unit (GPU). As a target for real-time simulation, we used a model of the basal ganglia that has been developed according to electrophysiological and anatomical knowledge. The model consists of heterogeneous populations of 370 spiking model neurons, including computationally heavy conductance-based models, connected by 11,002 synapses. Simulation of the model has not yet been performed in real-time using a general computing server. By parallelization of the model on the NVIDIA Geforce GTX 280 GPU in data-parallel and task-parallel fashion, faster-than-real-time simulation was robustly realized with only one-third of the GPU's total computational resources. Furthermore, we used the GPU's full computational resources to perform faster-than-real-time simulation of three instances of the basal ganglia model; these instances consisted of 1100 neurons and 33,006 synapses and were synchronized at each calculation step. Finally, we developed software for simultaneous visualization of faster-than-real-time simulation output. These results suggest the potential power of GPGPU techniques in real-time simulation of realistic neural networks. Copyright © 2011 Elsevier Ltd. All rights reserved.

Electrooptical adaptive switching network for the hypercube computer

NASA Technical Reports Server (NTRS)

Chow, E.; Peterson, J.

1988-01-01

An all-optical network design for the hyperswitch network using regular free-space interconnects between electronic processor nodes is presented. The adaptive routing model used is described, and an adaptive routing control example is presented. The design demonstrates that existing electrooptical techniques are sufficient for implementing efficient parallel architectures without the need for more complex means of implementing arbitrary interconnection schemes. The electrooptical hyperswitch network significantly improves the communication performance of the hypercube computer.

Joint Services Electronics Program

DTIC Science & Technology

1992-03-05

Packaging Considerations M. T. Raghunath (Professor Abhiram Ranade) A central issue in massively parallel computation is the design of the interconnection...programs on promising network architectures. Publications: [1] M. T. Raghunath and A. G. Ranade, A Simulation-Based Compari- son of Interconnection Networks...more difficult analog function approximation task. Network Design Issues for Fast Global Communication Professor A. Ranade with M.T. Raghunath A

Naval Surface Warfare Center Carderock Division, Technical Digest

DTIC Science & Technology

2001-12-01

Survivability Systems: An Overview Fred J. Fisch 139 Modeling and Simulation of Weapons Effects on Ships Robert R. Wunderlick 143 Intelligent Networks ...communications capability of forces afloat to support emerging network -centric warfare doc- trines. Stealth, for our next generation of warships...fully-inte- grated, fully- networked electronic countermeasures system, developed in parallel and in close coordination with sister systems. An

The Roles of Religious Culture and Moral Knowledge Teachers in Organizing Their Students Relationships with Social Networks

ERIC Educational Resources Information Center

Turan, Emine Zehra; Isçitürk, Gökçe Becit

2017-01-01

In parallel to the improvements experienced in information and communication systems in recent years, any use of Internet, especially the social networks by children and adolescents has been noticed to be increasing gradually. Use of social networks that starts at early ages has exposed children to some dangers. For that reason, the responsibility…

How to cluster in parallel with neural networks

NASA Technical Reports Server (NTRS)

Kamgar-Parsi, Behzad; Gualtieri, J. A.; Devaney, Judy E.; Kamgar-Parsi, Behrooz

1988-01-01

Partitioning a set of N patterns in a d-dimensional metric space into K clusters - in a way that those in a given cluster are more similar to each other than the rest - is a problem of interest in astrophysics, image analysis and other fields. As there are approximately K(N)/K (factorial) possible ways of partitioning the patterns among K clusters, finding the best solution is beyond exhaustive search when N is large. Researchers show that this problem can be formulated as an optimization problem for which very good, but not necessarily optimal solutions can be found by using a neural network. To do this the network must start from many randomly selected initial states. The network is simulated on the MPP (a 128 x 128 SIMD array machine), where researchers use the massive parallelism not only in solving the differential equations that govern the evolution of the network, but also by starting the network from many initial states at once, thus obtaining many solutions in one run. Researchers obtain speedups of two to three orders of magnitude over serial implementations and the promise through Analog VLSI implementations of speedups comensurate with human perceptual abilities.

Performance of multi-hop parallel free-space optical communication over gamma-gamma fading channel with pointing errors.

PubMed

Gao, Zhengguang; Liu, Hongzhan; Ma, Xiaoping; Lu, Wei

2016-11-10

Multi-hop parallel relaying is considered in a free-space optical (FSO) communication system deploying binary phase-shift keying (BPSK) modulation under the combined effects of a gamma-gamma (GG) distribution and misalignment fading. Based on the best path selection criterion, the cumulative distribution function (CDF) of this cooperative random variable is derived. Then the performance of this optical mesh network is analyzed in detail. A Monte Carlo simulation is also conducted to demonstrate the effectiveness of the results for the average bit error rate (ABER) and outage probability. The numerical result proves that it needs a smaller average transmitted optical power to achieve the same ABER and outage probability when using the multi-hop parallel network in FSO links. Furthermore, the system use of more number of hops and cooperative paths can improve the quality of the communication.

Parallel Evolutionary Optimization for Neuromorphic Network Training

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

Schuman, Catherine D; Disney, Adam; Singh, Susheela

One of the key impediments to the success of current neuromorphic computing architectures is the issue of how best to program them. Evolutionary optimization (EO) is one promising programming technique; in particular, its wide applicability makes it especially attractive for neuromorphic architectures, which can have many different characteristics. In this paper, we explore different facets of EO on a spiking neuromorphic computing model called DANNA. We focus on the performance of EO in the design of our DANNA simulator, and on how to structure EO on both multicore and massively parallel computing systems. We evaluate how our parallel methods impactmore » the performance of EO on Titan, the U.S.'s largest open science supercomputer, and BOB, a Beowulf-style cluster of Raspberry Pi's. We also focus on how to improve the EO by evaluating commonality in higher performing neural networks, and present the result of a study that evaluates the EO performed by Titan.« less

The control of a parallel hybrid-electric propulsion system for a small unmanned aerial vehicle using a CMAC neural network.

PubMed

Harmon, Frederick G; Frank, Andrew A; Joshi, Sanjay S

2005-01-01

A Simulink model, a propulsion energy optimization algorithm, and a CMAC controller were developed for a small parallel hybrid-electric unmanned aerial vehicle (UAV). The hybrid-electric UAV is intended for military, homeland security, and disaster-monitoring missions involving intelligence, surveillance, and reconnaissance (ISR). The Simulink model is a forward-facing simulation program used to test different control strategies. The flexible energy optimization algorithm for the propulsion system allows relative importance to be assigned between the use of gasoline, electricity, and recharging. A cerebellar model arithmetic computer (CMAC) neural network approximates the energy optimization results and is used to control the parallel hybrid-electric propulsion system. The hybrid-electric UAV with the CMAC controller uses 67.3% less energy than a two-stroke gasoline-powered UAV during a 1-h ISR mission and 37.8% less energy during a longer 3-h ISR mission.

Rapid automated classification of anesthetic depth levels using GPU based parallelization of neural networks.

PubMed

Peker, Musa; Şen, Baha; Gürüler, Hüseyin

2015-02-01

The effect of anesthesia on the patient is referred to as depth of anesthesia. Rapid classification of appropriate depth level of anesthesia is a matter of great importance in surgical operations. Similarly, accelerating classification algorithms is important for the rapid solution of problems in the field of biomedical signal processing. However numerous, time-consuming mathematical operations are required when training and testing stages of the classification algorithms, especially in neural networks. In this study, to accelerate the process, parallel programming and computing platform (Nvidia CUDA) facilitates dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU) was utilized. The system was employed to detect anesthetic depth level on related electroencephalogram (EEG) data set. This dataset is rather complex and large. Moreover, the achieving more anesthetic levels with rapid response is critical in anesthesia. The proposed parallelization method yielded high accurate classification results in a faster time.

Collective dynamics of 'small-world' networks.

PubMed

Watts, D J; Strogatz, S H

1998-06-04

Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks 'rewired' to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them 'small-world' networks, by analogy with the small-world phenomenon (popularly known as six degrees of separation. The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices.

Survey of methods for secure connection to the internet

NASA Astrophysics Data System (ADS)

Matsui, Shouichi

1994-04-01

This paper describes a study of a security method of protecting inside network computers against outside miscreants and unwelcome visitors and a control method when these computers are connected with the Internet. In the present Internet, a method to encipher all data cannot be used, so that it is necessary to utilize PEM (Privacy Enhanced Mail) capable of the encipherment and conversion of secret information. For preventing miscreant access by eavesdropping password, one-time password is effective. The most cost-effective method is a firewall system. This system lies between the outside and inside network. By limiting computers that directly communicate with the Internet, control is centralized and inside network security is protected. If the security of firewall systems is strictly controlled under correct setting, security within the network can be secured even in open networks such as the Internet.

Research in Parallel Algorithms and Software for Computational Aerosciences

NASA Technical Reports Server (NTRS)

Domel, Neal D.

1996-01-01

Phase I is complete for the development of a Computational Fluid Dynamics parallel code with automatic grid generation and adaptation for the Euler analysis of flow over complex geometries. SPLITFLOW, an unstructured Cartesian grid code developed at Lockheed Martin Tactical Aircraft Systems, has been modified for a distributed memory/massively parallel computing environment. The parallel code is operational on an SGI network, Cray J90 and C90 vector machines, SGI Power Challenge, and Cray T3D and IBM SP2 massively parallel machines. Parallel Virtual Machine (PVM) is the message passing protocol for portability to various architectures. A domain decomposition technique was developed which enforces dynamic load balancing to improve solution speed and memory requirements. A host/node algorithm distributes the tasks. The solver parallelizes very well, and scales with the number of processors. Partially parallelized and non-parallelized tasks consume most of the wall clock time in a very fine grain environment. Timing comparisons on a Cray C90 demonstrate that Parallel SPLITFLOW runs 2.4 times faster on 8 processors than its non-parallel counterpart autotasked over 8 processors.

Research in Parallel Algorithms and Software for Computational Aerosciences

NASA Technical Reports Server (NTRS)

Domel, Neal D.

1996-01-01

Phase 1 is complete for the development of a computational fluid dynamics CFD) parallel code with automatic grid generation and adaptation for the Euler analysis of flow over complex geometries. SPLITFLOW, an unstructured Cartesian grid code developed at Lockheed Martin Tactical Aircraft Systems, has been modified for a distributed memory/massively parallel computing environment. The parallel code is operational on an SGI network, Cray J90 and C90 vector machines, SGI Power Challenge, and Cray T3D and IBM SP2 massively parallel machines. Parallel Virtual Machine (PVM) is the message passing protocol for portability to various architectures. A domain decomposition technique was developed which enforces dynamic load balancing to improve solution speed and memory requirements. A host/node algorithm distributes the tasks. The solver parallelizes very well, and scales with the number of processors. Partially parallelized and non-parallelized tasks consume most of the wall clock time in a very fine grain environment. Timing comparisons on a Cray C90 demonstrate that Parallel SPLITFLOW runs 2.4 times faster on 8 processors than its non-parallel counterpart autotasked over 8 processors.

Functional networks in parallel with cortical development associate with executive functions in children.

PubMed

Zhong, Jidan; Rifkin-Graboi, Anne; Ta, Anh Tuan; Yap, Kar Lai; Chuang, Kai-Hsiang; Meaney, Michael J; Qiu, Anqi

2014-07-01

Children begin performing similarly to adults on tasks requiring executive functions in late childhood, a transition that is probably due to neuroanatomical fine-tuning processes, including myelination and synaptic pruning. In parallel to such structural changes in neuroanatomical organization, development of functional organization may also be associated with cognitive behaviors in children. We examined 6- to 10-year-old children's cortical thickness, functional organization, and cognitive performance. We used structural magnetic resonance imaging (MRI) to identify areas with cortical thinning, resting-state fMRI to identify functional organization in parallel to cortical development, and working memory/response inhibition tasks to assess executive functioning. We found that neuroanatomical changes in the form of cortical thinning spread over bilateral frontal, parietal, and occipital regions. These regions were engaged in 3 functional networks: sensorimotor and auditory, executive control, and default mode network. Furthermore, we found that working memory and response inhibition only associated with regional functional connectivity, but not topological organization (i.e., local and global efficiency of information transfer) of these functional networks. Interestingly, functional connections associated with "bottom-up" as opposed to "top-down" processing were more clearly related to children's performance on working memory and response inhibition, implying an important role for brain systems involved in late childhood. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Low-Lying Energy Isomers and Global Minima of Aqueous Nanoclusters: Structures and Spectroscopic Features of the Pentagonal Dodecahedron (H2O)20 and (H3O)+(H2O)20

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

Xantheas, Sotiris S.

We rely on a hierarchy of methods to identify the low-lying isomers for the pentagonal dodecahedron (H2O)20 and the H3O+(H2O)20 clusters. Initial screening of isomers was performed with classical potentials [TIP4P, TTM2-F, TTM2.1-F for (H2O)20 and ASP for H3O+(H2O)20] and the networks obtained with those potentials were subsequently reoptimized at the DFT (B3LYP) and MP2 levels of theory. For the pentagonal dodecahedron (H2O)20 it was found that DFT (B3LYP) and MP2 produced the same global minimum. However, this was not the case for the H3O+(H2O)20 cluster, for which MP2 produced a different network for the global minimum when compared tomore » DFT (B3LYP). All low-lying minima of H3O+(H2O)20 correspond to hydrogen bonding networks having 9 ''free'' OH bonds and the hydronium ion on the surface of the cluster. The fact that DFT (B3LYP) and MP2 produce different results and issues related to the use of a smaller basis set, explains the discrepancy between the current results and the structure previously suggested [Science 304, 1137 (2004)] for the global minimum of the H3O+(H2O)20 cluster. Additionally, the IR spectra of the MP2 global minimum are closer to the experimentally measured ones than the spectra of the previously suggested DFT global minimum. The latter exhibit additional bands in the most red-shifted region of the OH stretching vibrations (corresponding to the ''fingerprint'' of the underlying hydrogen bonding network), which are absent from both the experimental as well as the spectra of the new structure suggested for the global minimum of this cluster.« less

System-wide power management control via clock distribution network

DOEpatents

Coteus, Paul W.; Gara, Alan; Gooding, Thomas M.; Haring, Rudolf A.; Kopcsay, Gerard V.; Liebsch, Thomas A.; Reed, Don D.

2015-05-19

An apparatus, method and computer program product for automatically controlling power dissipation of a parallel computing system that includes a plurality of processors. A computing device issues a command to the parallel computing system. A clock pulse-width modulator encodes the command in a system clock signal to be distributed to the plurality of processors. The plurality of processors in the parallel computing system receive the system clock signal including the encoded command, and adjusts power dissipation according to the encoded command.

Joint Services Electronics Program

DTIC Science & Technology

1991-03-05

Parallel Computing Network and Program Professor Abhiram Ranade with M.T. Raghunath and Robert Boothe The goal of our research is to develop high...References/Publications [1] M. T. Raghunath and A. 0. Ranade. "A Simulation-Based Comparison of Interconnection Networks," Proceedings of the 2nd IEEE

Parallel or convergent evolution in human population genomic data revealed by genotype networks.

PubMed

R Vahdati, Ali; Wagner, Andreas

2016-08-02

Genotype networks are representations of genetic variation data that are complementary to phylogenetic trees. A genotype network is a graph whose nodes are genotypes (DNA sequences) with the same broadly defined phenotype. Two nodes are connected if they differ in some minimal way, e.g., in a single nucleotide. We analyze human genome variation data from the 1,000 genomes project, and construct haploid genotype (haplotype) networks for 12,235 protein coding genes. The structure of these networks varies widely among genes, indicating different patterns of variation despite a shared evolutionary history. We focus on those genes whose genotype networks show many cycles, which can indicate homoplasy, i.e., parallel or convergent evolution, on the sequence level. For 42 genes, the observed number of cycles is so large that it cannot be explained by either chance homoplasy or recombination. When analyzing possible explanations, we discovered evidence for positive selection in 21 of these genes and, in addition, a potential role for constrained variation and purifying selection. Balancing selection plays at most a small role. The 42 genes with excess cycles are enriched in functions related to immunity and response to pathogens. Genotype networks are representations of genetic variation data that can help understand unusual patterns of genomic variation.

Reconfigurable microfluidic hanging drop network for multi-tissue interaction and analysis.

PubMed

Frey, Olivier; Misun, Patrick M; Fluri, David A; Hengstler, Jan G; Hierlemann, Andreas

2014-06-30

Integration of multiple three-dimensional microtissues into microfluidic networks enables new insights in how different organs or tissues of an organism interact. Here, we present a platform that extends the hanging-drop technology, used for multi-cellular spheroid formation, to multifunctional complex microfluidic networks. Engineered as completely open, 'hanging' microfluidic system at the bottom of a substrate, the platform features high flexibility in microtissue arrangements and interconnections, while fabrication is simple and operation robust. Multiple spheroids of different cell types are formed in parallel on the same platform; the different tissues are then connected in physiological order for multi-tissue experiments through reconfiguration of the fluidic network. Liquid flow is precisely controlled through the hanging drops, which enable nutrient supply, substance dosage and inter-organ metabolic communication. The possibility to perform parallelized microtissue formation on the same chip that is subsequently used for complex multi-tissue experiments renders the developed platform a promising technology for 'body-on-a-chip'-related research.

MPIGeneNet: Parallel Calculation of Gene Co-Expression Networks on Multicore Clusters.

PubMed

Gonzalez-Dominguez, Jorge; Martin, Maria J

2017-10-10

In this work we present MPIGeneNet, a parallel tool that applies Pearson's correlation and Random Matrix Theory to construct gene co-expression networks. It is based on the state-of-the-art sequential tool RMTGeneNet, which provides networks with high robustness and sensitivity at the expenses of relatively long runtimes for large scale input datasets. MPIGeneNet returns the same results as RMTGeneNet but improves the memory management, reduces the I/O cost, and accelerates the two most computationally demanding steps of co-expression network construction by exploiting the compute capabilities of common multicore CPU clusters. Our performance evaluation on two different systems using three typical input datasets shows that MPIGeneNet is significantly faster than RMTGeneNet. As an example, our tool is up to 175.41 times faster on a cluster with eight nodes, each one containing two 12-core Intel Haswell processors. Source code of MPIGeneNet, as well as a reference manual, are available at https://sourceforge.net/projects/mpigenenet/.

A solution to neural field equations by a recurrent neural network method

NASA Astrophysics Data System (ADS)

Alharbi, Abir

2012-09-01

Neural field equations (NFE) are used to model the activity of neurons in the brain, it is introduced from a single neuron 'integrate-and-fire model' starting point. The neural continuum is spatially discretized for numerical studies, and the governing equations are modeled as a system of ordinary differential equations. In this article the recurrent neural network approach is used to solve this system of ODEs. This consists of a technique developed by combining the standard numerical method of finite-differences with the Hopfield neural network. The architecture of the net, energy function, updating equations, and algorithms are developed for the NFE model. A Hopfield Neural Network is then designed to minimize the energy function modeling the NFE. Results obtained from the Hopfield-finite-differences net show excellent performance in terms of accuracy and speed. The parallelism nature of the Hopfield approaches may make them easier to implement on fast parallel computers and give them the speed advantage over the traditional methods.

3DScapeCS: application of three dimensional, parallel, dynamic network visualization in Cytoscape

PubMed Central

2013-01-01

Background The exponential growth of gigantic biological data from various sources, such as protein-protein interaction (PPI), genome sequences scaffolding, Mass spectrometry (MS) molecular networking and metabolic flux, demands an efficient way for better visualization and interpretation beyond the conventional, two-dimensional visualization tools. Results We developed a 3D Cytoscape Client/Server (3DScapeCS) plugin, which adopted Cytoscape in interpreting different types of data, and UbiGraph for three-dimensional visualization. The extra dimension is useful in accommodating, visualizing, and distinguishing large-scale networks with multiple crossed connections in five case studies. Conclusions Evaluation on several experimental data using 3DScapeCS and its special features, including multilevel graph layout, time-course data animation, and parallel visualization has proven its usefulness in visualizing complex data and help to make insightful conclusions. PMID:24225050

Engineering rules for evaluating the efficiency of multiplexing traffic streams

NASA Astrophysics Data System (ADS)

Klincewicz, John G.

2004-09-01

It is common, either for a telecommunications service provider or for a corporate enterprise, to have multiple data networks. For example, both an IP network and an ATM or Frame Relay network could be in operation to serve different applications. This can result in parallel transport links between the same two locations, each carrying data traffic under a different protocol. In this paper, we consider some practical engineering rules, for particular situations, to evaluate whether or not it is advantageous to combine these parallel traffic streams onto a single transport link. Combining the streams requires additional overhead (a so-called "cell tax" ) but, in at least some situations, can result in more efficient use of modular transport capacity. Simple graphs can be used to summarize the analysis. Some interesting, and perhaps unexpected, observations can be made.

Planning in subsumption architectures

NASA Technical Reports Server (NTRS)

Chalfant, Eugene C.

1994-01-01

A subsumption planner using a parallel distributed computational paradigm based on the subsumption architecture for control of real-world capable robots is described. Virtual sensor state space is used as a planning tool to visualize the robot's anticipated effect on its environment. Decision sequences are generated based on the environmental situation expected at the time the robot must commit to a decision. Between decision points, the robot performs in a preprogrammed manner. A rudimentary, domain-specific partial world model contains enough information to extrapolate the end results of the rote behavior between decision points. A collective network of predictors operates in parallel with the reactive network forming a recurrrent network which generates plans as a hierarchy. Details of a plan segment are generated only when its execution is imminent. The use of the subsumption planner is demonstrated by a simple maze navigation problem.

Parallel Fixed Point Implementation of a Radial Basis Function Network in an FPGA

PubMed Central

de Souza, Alisson C. D.; Fernandes, Marcelo A. C.

2014-01-01

This paper proposes a parallel fixed point radial basis function (RBF) artificial neural network (ANN), implemented in a field programmable gate array (FPGA) trained online with a least mean square (LMS) algorithm. The processing time and occupied area were analyzed for various fixed point formats. The problems of precision of the ANN response for nonlinear classification using the XOR gate and interpolation using the sine function were also analyzed in a hardware implementation. The entire project was developed using the System Generator platform (Xilinx), with a Virtex-6 xc6vcx240t-1ff1156 as the target FPGA. PMID:25268918

Method and apparatus for routing data in an inter-nodal communications lattice of a massively parallel computer system by employing bandwidth shells at areas of overutilization

DOEpatents

Archer, Charles Jens; Musselman, Roy Glenn; Peters, Amanda; Pinnow, Kurt Walter; Swartz, Brent Allen; Wallenfelt, Brian Paul

2010-04-27

A massively parallel computer system contains an inter-nodal communications network of node-to-node links. An automated routing strategy routes packets through one or more intermediate nodes of the network to reach a final destination. The default routing strategy is altered responsive to detection of overutilization of a particular path of one or more links, and at least some traffic is re-routed by distributing the traffic among multiple paths (which may include the default path). An alternative path may require a greater number of link traversals to reach the destination node.

A parallel input composite transimpedance amplifier.

PubMed

Kim, D J; Kim, C

2018-01-01

A new approach to high performance current to voltage preamplifier design is presented. The design using multiple operational amplifiers (op-amps) has a parasitic capacitance compensation network and a composite amplifier topology for fast, precision, and low noise performance. The input stage consisting of a parallel linked JFET op-amps and a high-speed bipolar junction transistor (BJT) gain stage driving the output in the composite amplifier topology, cooperating with the capacitance compensation feedback network, ensures wide bandwidth stability in the presence of input capacitance above 40 nF. The design is ideal for any two-probe measurement, including high impedance transport and scanning tunneling microscopy measurements.

A parallel input composite transimpedance amplifier

NASA Astrophysics Data System (ADS)

Kim, D. J.; Kim, C.

2018-01-01

A new approach to high performance current to voltage preamplifier design is presented. The design using multiple operational amplifiers (op-amps) has a parasitic capacitance compensation network and a composite amplifier topology for fast, precision, and low noise performance. The input stage consisting of a parallel linked JFET op-amps and a high-speed bipolar junction transistor (BJT) gain stage driving the output in the composite amplifier topology, cooperating with the capacitance compensation feedback network, ensures wide bandwidth stability in the presence of input capacitance above 40 nF. The design is ideal for any two-probe measurement, including high impedance transport and scanning tunneling microscopy measurements.

Resource Management for Distributed Parallel Systems

NASA Technical Reports Server (NTRS)

Neuman, B. Clifford; Rao, Santosh

1993-01-01

Multiprocessor systems should exist in the the larger context of distributed systems, allowing multiprocessor resources to be shared by those that need them. Unfortunately, typical multiprocessor resource management techniques do not scale to large networks. The Prospero Resource Manager (PRM) is a scalable resource allocation system that supports the allocation of processing resources in large networks and multiprocessor systems. To manage resources in such distributed parallel systems, PRM employs three types of managers: system managers, job managers, and node managers. There exist multiple independent instances of each type of manager, reducing bottlenecks. The complexity of each manager is further reduced because each is designed to utilize information at an appropriate level of abstraction.

SiGN-SSM: open source parallel software for estimating gene networks with state space models.

PubMed

Tamada, Yoshinori; Yamaguchi, Rui; Imoto, Seiya; Hirose, Osamu; Yoshida, Ryo; Nagasaki, Masao; Miyano, Satoru

2011-04-15

SiGN-SSM is an open-source gene network estimation software able to run in parallel on PCs and massively parallel supercomputers. The software estimates a state space model (SSM), that is a statistical dynamic model suitable for analyzing short time and/or replicated time series gene expression profiles. SiGN-SSM implements a novel parameter constraint effective to stabilize the estimated models. Also, by using a supercomputer, it is able to determine the gene network structure by a statistical permutation test in a practical time. SiGN-SSM is applicable not only to analyzing temporal regulatory dependencies between genes, but also to extracting the differentially regulated genes from time series expression profiles. SiGN-SSM is distributed under GNU Affero General Public Licence (GNU AGPL) version 3 and can be downloaded at http://sign.hgc.jp/signssm/. The pre-compiled binaries for some architectures are available in addition to the source code. The pre-installed binaries are also available on the Human Genome Center supercomputer system. The online manual and the supplementary information of SiGN-SSM is available on our web site. tamada@ims.u-tokyo.ac.jp.

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.

Enhancing PC Cluster-Based Parallel Branch-and-Bound Algorithms for the Graph Coloring Problem

NASA Astrophysics Data System (ADS)

Taoka, Satoshi; Takafuji, Daisuke; Watanabe, Toshimasa

A branch-and-bound algorithm (BB for short) is the most general technique to deal with various combinatorial optimization problems. Even if it is used, computation time is likely to increase exponentially. So we consider its parallelization to reduce it. It has been reported that the computation time of a parallel BB heavily depends upon node-variable selection strategies. And, in case of a parallel BB, it is also necessary to prevent increase in communication time. So, it is important to pay attention to how many and what kind of nodes are to be transferred (called sending-node selection strategy). In this paper, for the graph coloring problem, we propose some sending-node selection strategies for a parallel BB algorithm by adopting MPI for parallelization and experimentally evaluate how these strategies affect computation time of a parallel BB on a PC cluster network.

CMIP: a software package capable of reconstructing genome-wide regulatory networks using gene expression data.

PubMed

Zheng, Guangyong; Xu, Yaochen; Zhang, Xiujun; Liu, Zhi-Ping; Wang, Zhuo; Chen, Luonan; Zhu, Xin-Guang

2016-12-23

A gene regulatory network (GRN) represents interactions of genes inside a cell or tissue, in which vertexes and edges stand for genes and their regulatory interactions respectively. Reconstruction of gene regulatory networks, in particular, genome-scale networks, is essential for comparative exploration of different species and mechanistic investigation of biological processes. Currently, most of network inference methods are computationally intensive, which are usually effective for small-scale tasks (e.g., networks with a few hundred genes), but are difficult to construct GRNs at genome-scale. Here, we present a software package for gene regulatory network reconstruction at a genomic level, in which gene interaction is measured by the conditional mutual information measurement using a parallel computing framework (so the package is named CMIP). The package is a greatly improved implementation of our previous PCA-CMI algorithm. In CMIP, we provide not only an automatic threshold determination method but also an effective parallel computing framework for network inference. Performance tests on benchmark datasets show that the accuracy of CMIP is comparable to most current network inference methods. Moreover, running tests on synthetic datasets demonstrate that CMIP can handle large datasets especially genome-wide datasets within an acceptable time period. In addition, successful application on a real genomic dataset confirms its practical applicability of the package. This new software package provides a powerful tool for genomic network reconstruction to biological community. The software can be accessed at http://www.picb.ac.cn/CMIP/ .

Research on two-port network of wavelet transform processor using surface acoustic wavelet devices and its application.

PubMed

Liu, Shoubing; Lu, Wenke; Zhu, Changchun

2017-11-01

The goal of this research is to study two-port network of wavelet transform processor (WTP) using surface acoustic wave (SAW) devices and its application. The motive was prompted by the inconvenience of the long research and design cycle and the huge research funding involved with traditional method in this field, which were caused by the lack of the simulation and emulation method of WTP using SAW devices. For this reason, we introduce the two-port network analysis tool, which has been widely used in the design and analysis of SAW devices with uniform interdigital transducers (IDTs). Because the admittance parameters calculation formula of the two-port network can only be used for the SAW devices with uniform IDTs, this analysis tool cannot be directly applied into the design and analysis of the processor using SAW devices, whose input interdigital transducer (IDT) is apodized weighting. Therefore, in this paper, we propose the channel segmentation method, which can convert the WTP using SAW devices into parallel channels, and also provide with the calculation formula of the number of channels, the number of finger pairs and the static capacitance of an interdigital period in each parallel channel firstly. From the parameters given above, we can calculate the admittance parameters of the two port network for each channel, so that we can obtain the admittance parameter of the two-port network of the WTP using SAW devices on the basis of the simplification rule of parallel two-port network. Through this analysis tool, not only can we get the impulse response function of the WTP using SAW devices but we can also get the matching circuit of it. Large numbers of studies show that the parameters of the two-port network obtained by this paper are consistent with those measured by network analyzer E5061A, and the impulse response function obtained by the two-port network analysis tool is also consistent with that measured by network analyzer E5061A, which can meet the accuracy requirements of the analysis of the WTP using SAW devices. Therefore the two-port network analysis tool discussed in this paper has comparatively higher theoretical and practical value. Copyright © 2017 Elsevier B.V. All rights reserved.

Nongyrotropic Electrons in Guide Field Reconnection

NASA Technical Reports Server (NTRS)

Wendel, D. E.; Hesse, M.; Bessho, N.; Adrian, M. L.; Kuznetsova, M.

2016-01-01

We apply a scalar measure of nongyrotropy to the electron pressure tensor in a 2D particle-in-cell simulation of guide field reconnection and assess the corresponding electron distributions and the forces that account for the nongyrotropy. The scalar measure reveals that the nongyrotropy lies in bands that straddle the electron diffusion region and the separatrices, in the same regions where there are parallel electric fields. Analysis of electron distributions and fields shows that the nongyrotropy along the inflow and outflow separatrices emerges as a result of multiple populations of electrons influenced differently by large and small-scale parallel electric fields and by gradients in the electric field. The relevant parallel electric fields include large-scale potential ramps emanating from the x-line and sub-ion inertial scale bipolar electron holes. Gradients in the perpendicular electric field modify electrons differently depending on their phase, thus producing nongyrotropy. Magnetic flux violation occurs along portions of the separatrices that coincide with the parallel electric fields. An inductive electric field in the electron EB drift frame thus develops, which has the effect of enhancing nongyrotropies already produced by other mechanisms and under certain conditions producing their own nongyrotropy. Particle tracing of electrons from nongyrotropic populations along the inflows and outflows shows that the striated structure of nongyrotropy corresponds to electrons arriving from different source regions. We also show that the relevant parallel electric fields receive important contributions not only from the nongyrotropic portion of the electron pressure tensor but from electron spatial and temporal inertial terms as well.

Chiral magnetoresistance in the Weyl semimetal NbP

NASA Astrophysics Data System (ADS)

Niemann, Anna Corinna; Gooth, Johannes; Wu, Shu-Chun; Bäßler, Svenja; Sergelius, Philip; Hühne, Ruben; Rellinghaus, Bernd; Shekhar, Chandra; Süß, Vicky; Schmidt, Marcus; Felser, Claudia; Yan, Binghai; Nielsch, Kornelius

2017-03-01

NbP is a recently realized Weyl semimetal (WSM), hosting Weyl points through which conduction and valence bands cross linearly in the bulk and exotic Fermi arcs appear. The most intriguing transport phenomenon of a WSM is the chiral anomaly-induced negative magnetoresistance (NMR) in parallel electric and magnetic fields. In intrinsic NbP the Weyl points lie far from the Fermi energy, making chiral magneto-transport elusive. Here, we use Ga-doping to relocate the Fermi energy in NbP sufficiently close to the W2 Weyl points, for which the different Fermi surfaces are verified by resultant quantum oscillations. Consequently, we observe a NMR for parallel electric and magnetic fields, which is considered as a signature of the chiral anomaly in condensed-matter physics. The NMR survives up to room temperature, making NbP a versatile material platform for the development of Weyltronic applications.

Labeled trees and the efficient computation of derivations

NASA Technical Reports Server (NTRS)

Grossman, Robert; Larson, Richard G.

1989-01-01

The effective parallel symbolic computation of operators under composition is discussed. Examples include differential operators under composition and vector fields under the Lie bracket. Data structures consisting of formal linear combinations of rooted labeled trees are discussed. A multiplication on rooted labeled trees is defined, thereby making the set of these data structures into an associative algebra. An algebra homomorphism is defined from the original algebra of operators into this algebra of trees. An algebra homomorphism from the algebra of trees into the algebra of differential operators is then described. The cancellation which occurs when noncommuting operators are expressed in terms of commuting ones occurs naturally when the operators are represented using this data structure. This leads to an algorithm which, for operators which are derivations, speeds up the computation exponentially in the degree of the operator. It is shown that the algebra of trees leads naturally to a parallel version of the algorithm.

Neural network based speech synthesizer: A preliminary report

NASA Technical Reports Server (NTRS)

Villarreal, James A.; Mcintire, Gary

1987-01-01

A neural net based speech synthesis project is discussed. The novelty is that the reproduced speech was extracted from actual voice recordings. In essence, the neural network learns the timing, pitch fluctuations, connectivity between individual sounds, and speaking habits unique to that individual person. The parallel distributed processing network used for this project is the generalized backward propagation network which has been modified to also learn sequences of actions or states given in a particular plan.

Wavelet Transforms in Parallel Image Processing

DTIC Science & Technology

1994-01-27

NUMBER OF PAGES Object Segmentation, Texture Segmentation, Image Compression, Image 137 Halftoning , Neural Network, Parallel Algorithms, 2D and 3D...Vector Quantization of Wavelet Transform Coefficients ........ ............................. 57 B.1.f Adaptive Image Halftoning based on Wavelet...application has been directed to the adaptive image halftoning . The gray information at a pixel, including its gray value and gradient, is represented by

CMOS VLSI Layout and Verification of a SIMD Computer

NASA Technical Reports Server (NTRS)

Zheng, Jianqing

1996-01-01

A CMOS VLSI layout and verification of a 3 x 3 processor parallel computer has been completed. The layout was done using the MAGIC tool and the verification using HSPICE. Suggestions for expanding the computer into a million processor network are presented. Many problems that might be encountered when implementing a massively parallel computer are discussed.

Low-frequency sine wave hard-limiting technique

NASA Technical Reports Server (NTRS)

Anderson, T. O.

1977-01-01

Circuit includes serial-in/parallel-out shift register and weighting network that are used to eliminate effects of noise and other nonrepetitive circuit transients. Register and weighting network average decisions from section of signal where decisions are more dependable or where differences between two consecutive samples are larger.

Medical applications for high-performance computers in SKIF-GRID network.

PubMed

Zhuchkov, Alexey; Tverdokhlebov, Nikolay

2009-01-01

The paper presents a set of software services for massive mammography image processing by using high-performance parallel computers of SKIF-family which are linked into a service-oriented grid-network. An experience of a prototype system implementation in two medical institutions is also described.

Integrated Business Process Adaptation towards Friction-Free Business-to-Business Collaboration

ERIC Educational Resources Information Center

Shan, Zhe

2011-01-01

One key issue in process-aware E-commerce collaboration is the orchestration of business processes of multiple business partners throughout a supply chain network in an automated and seamless way. Since each partner has its own internal processes with different control flow structures and message interfaces, the real challenge lies in verifying…

The Use of Twitter for Professional Growth and Development

ERIC Educational Resources Information Center

Gerstein, Jackie

2011-01-01

Twitter, the micro blogging tool, has seen unprecedented growth in the past year and is expected to continue into the future. Twitter's power, engagement, and popularity lie in its endless networking opportunities. Its potential as a venue for professional growth and development needs to be explored, discussed, and ultimately used as such. A brief…

Enabling Leadership: Just Cycling Along. CRLRA Discussion Paper.

ERIC Educational Resources Information Center

Falk, Ian

Conventional notions of leadership have focused on the leader alone rather than on the situation that leaders must enable. The common threads to successful rural community development in Australia over the last few decades lie in the way the community develops its stores of social capital, which is based on trust, shared values, networks, and…

75 FR 36071 - Framework for Broadband Internet Service

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-24

... contractor, Best Copy and Printing, Inc. (BCPI), Portals II, 445 12th Street, SW., Room CY-B402, Washington...-leading high-speed broadband networks--both wired and wireless--lies at the very core of the FCC's mission... subscribers with high-speed Internet access, as well as many applications or functions that can be used with...

A Novel Approach for Lie Detection Based on F-Score and Extreme Learning Machine

PubMed Central

Gao, Junfeng; Wang, Zhao; Yang, Yong; Zhang, Wenjia; Tao, Chunyi; Guan, Jinan; Rao, Nini

2013-01-01

A new machine learning method referred to as F-score_ELM was proposed to classify the lying and truth-telling using the electroencephalogram (EEG) signals from 28 guilty and innocent subjects. Thirty-one features were extracted from the probe responses from these subjects. Then, a recently-developed classifier called extreme learning machine (ELM) was combined with F-score, a simple but effective feature selection method, to jointly optimize the number of the hidden nodes of ELM and the feature subset by a grid-searching training procedure. The method was compared to two classification models combining principal component analysis with back-propagation network and support vector machine classifiers. We thoroughly assessed the performance of these classification models including the training and testing time, sensitivity and specificity from the training and testing sets, as well as network size. The experimental results showed that the number of the hidden nodes can be effectively optimized by the proposed method. Also, F-score_ELM obtained the best classification accuracy and required the shortest training and testing time. PMID:23755136

A Multimetric Approach for Handoff Decision in Heterogeneous Wireless Networks

NASA Astrophysics Data System (ADS)

Kustiawan, I.; Purnama, W.

2018-02-01

Seamless mobility and service continuity anywhere at any time are an important issue in the wireless Internet. This research proposes a scheme to make handoff decisions effectively in heterogeneous wireless networks using a fuzzy system. Our design lies in an inference engine which takes RSS (received signal strength), data rate, network latency, and user preference as strategic determinants. The logic of our engine is realized on a UE (user equipment) side in faster reaction to network dynamics while roaming across different radio access technologies. The fuzzy system handles four metrics jointly to deduce a moderate decision about when to initiate handoff. The performance of our design is evaluated by simulating move-out mobility scenarios. Simulation results show that our scheme outperforms other approaches in terms of reducing unnecessary handoff.

Shor's quantum factoring algorithm on a photonic chip.

PubMed

Politi, Alberto; Matthews, Jonathan C F; O'Brien, Jeremy L

2009-09-04

Shor's quantum factoring algorithm finds the prime factors of a large number exponentially faster than any other known method, a task that lies at the heart of modern information security, particularly on the Internet. This algorithm requires a quantum computer, a device that harnesses the massive parallelism afforded by quantum superposition and entanglement of quantum bits (or qubits). We report the demonstration of a compiled version of Shor's algorithm on an integrated waveguide silica-on-silicon chip that guides four single-photon qubits through the computation to factor 15.

Receptivity and Bypass Dynamics

NASA Technical Reports Server (NTRS)

Lasseigne, D. G.; Criminale, W. O.; Joslin, R. D.; Jackson, T. L.

1999-01-01

Problems concerning laminar-turbulent transition are addressed by solving a series of initial value problems. Solutions to the temporal, initial-value problem .with an inhomogeneous forcing term imposed upon the flow are sought. It is shown that: (1) A transient disturbance lying located outside of the boundary layer can lead to the growth of an unstable Tollmein-Schlicting wave; (2) A resonance with the continuous spectrum may provide a mechanism for bypass transition; and (3) The continuum modes of a disturbance feed directly into the Tollmein-Schlicting wave downstream through non-parallel effects.

1-Azaniumylcyclobutane-1-carboxylate monohydrate

NASA Technical Reports Server (NTRS)

Butcher, Ray J.; Brewer, Greg; Burton, Aaron S.; Dworkin, Jason

2014-01-01

In the title compound, C5H9NO2H2O, the amino acid is in the usual zwitterionic form involving the carboxylate group. The cyclobutane backbone of the amino acid is disordered over two conformations, with occupancies of 0.882 (7) and0.118 (7). In the crystal, NH O and OH O hydrogen bonds link the zwitterions [with the water molecule involved as both acceptor (with the NH3+) and donor (through a single carboxylate O from two different aminocyclobutane carboxylatemoities)], resulting in a two-dimensional layered structure lying parallel to (100).

Towards an M5-brane model I: A 6d superconformal field theory

NASA Astrophysics Data System (ADS)

Sämann, Christian; Schmidt, Lennart

2018-04-01

We present an action for a six-dimensional superconformal field theory containing a non-abelian tensor multiplet. All of the ingredients of this action have been available in the literature. We bring these pieces together by choosing the string Lie 2-algebra as a gauge structure, which we motivated in previous work. The kinematical data contains a connection on a categorified principal bundle, which is the appropriate mathematical description of the parallel transport of self-dual strings. Our action can be written down for each of the simply laced Dynkin diagrams, and each case reduces to a four-dimensional supersymmetric Yang-Mills theory with corresponding gauge Lie algebra. Our action also reduces nicely to an M2-brane model which is a deformation of the Aharony-Bergman-Jafferis-Maldacena (ABJM) model. While this action is certainly not the desired M5-brane model, we regard it as a key stepping stone towards a potential construction of the (2, 0)-theory.

A highly efficient multi-core algorithm for clustering extremely large datasets

PubMed Central

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

A neural-network approach to robotic control

NASA Technical Reports Server (NTRS)

Graham, D. P. W.; Deleuterio, G. M. T.

1993-01-01

An artificial neural-network paradigm for the control of robotic systems is presented. The approach is based on the Cerebellar Model Articulation Controller created by James Albus and incorporates several extensions. First, recognizing the essential structure of multibody equations of motion, two parallel modules are used that directly reflect the dynamical characteristics of multibody systems. Second, the architecture of the proposed network is imbued with a self-organizational capability which improves efficiency and accuracy. Also, the networks can be arranged in hierarchical fashion with each subsequent network providing finer and finer resolution.

Implementation of logic functions and computations by chemical kinetics

NASA Astrophysics Data System (ADS)

Hjelmfelt, A.; Ross, J.

We review our work on the computational functions of the kinetics of chemical networks. We examine spatially homogeneous networks which are based on prototypical reactions occurring in living cells and show the construction of logic gates and sequential and parallel networks. This work motivates the study of an important biochemical pathway, glycolysis, and we demonstrate that the switch that controls the flux in the direction of glycolysis or gluconeogenesis may be described as a fuzzy AND operator. We also study a spatially inhomogeneous network which shares features of theoretical and biological neural networks.

Towards green high capacity optical networks

NASA Astrophysics Data System (ADS)

Glesk, I.; Mohd Warip, M. N.; Idris, S. K.; Osadola, T. B.; Andonovic, I.

2011-09-01

The demand for fast, secure, energy efficient high capacity networks is growing. It is fuelled by transmission bandwidth needs which will support among other things the rapid penetration of multimedia applications empowering smart consumer electronics and E-businesses. All the above trigger unparallel needs for networking solutions which must offer not only high-speed low-cost "on demand" mobile connectivity but should be ecologically friendly and have low carbon footprint. The first answer to address the bandwidth needs was deployment of fibre optic technologies into transport networks. After this it became quickly obvious that the inferior electronic bandwidth (if compared to optical fiber) will further keep its upper hand on maximum implementable serial data rates. A new solution was found by introducing parallelism into data transport in the form of Wavelength Division Multiplexing (WDM) which has helped dramatically to improve aggregate throughput of optical networks. However with these advancements a new bottleneck has emerged at fibre endpoints where data routers must process the incoming and outgoing traffic. Here, even with the massive and power hungry electronic parallelism routers today (still relying upon bandwidth limiting electronics) do not offer needed processing speeds networks demands. In this paper we will discuss some novel unconventional approaches to address network scalability leading to energy savings via advance optical signal processing. We will also investigate energy savings based on advanced network management through nodes hibernation proposed for Optical IP networks. The hibernation reduces the network overall power consumption by forming virtual network reconfigurations through selective nodes groupings and by links segmentations and partitionings.

Modeling evolution of crosstalk in noisy signal transduction networks

NASA Astrophysics Data System (ADS)

Tareen, Ammar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

2018-02-01

Signal transduction networks can form highly interconnected systems within cells due to crosstalk between constituent pathways. To better understand the evolutionary design principles underlying such networks, we study the evolution of crosstalk for two parallel signaling pathways that arise via gene duplication. We use a sequence-based evolutionary algorithm and evolve the network based on two physically motivated fitness functions related to information transmission. We find that one fitness function leads to a high degree of crosstalk while the other leads to pathway specificity. Our results offer insights on the relationship between network architecture and information transmission for noisy biomolecular networks.

A Scalable Approach for Discovering Conserved Active Subnetworks across Species

PubMed Central

Verfaillie, Catherine M.; Hu, Wei-Shou; Myers, Chad L.

2010-01-01

Overlaying differential changes in gene expression on protein interaction networks has proven to be a useful approach to interpreting the cell's dynamic response to a changing environment. Despite successes in finding active subnetworks in the context of a single species, the idea of overlaying lists of differentially expressed genes on networks has not yet been extended to support the analysis of multiple species' interaction networks. To address this problem, we designed a scalable, cross-species network search algorithm, neXus (Network - cross(X)-species - Search), that discovers conserved, active subnetworks based on parallel differential expression studies in multiple species. Our approach leverages functional linkage networks, which provide more comprehensive coverage of functional relationships than physical interaction networks by combining heterogeneous types of genomic data. We applied our cross-species approach to identify conserved modules that are differentially active in stem cells relative to differentiated cells based on parallel gene expression studies and functional linkage networks from mouse and human. We find hundreds of conserved active subnetworks enriched for stem cell-associated functions such as cell cycle, DNA repair, and chromatin modification processes. Using a variation of this approach, we also find a number of species-specific networks, which likely reflect mechanisms of stem cell function that have diverged between mouse and human. We assess the statistical significance of the subnetworks by comparing them with subnetworks discovered on random permutations of the differential expression data. We also describe several case examples that illustrate the utility of comparative analysis of active subnetworks. PMID:21170309

Experimental Evidence of Low Density Liquid Water under Decompression

NASA Astrophysics Data System (ADS)

Shen, G.; Lin, C.; Sinogeikin, S. V.; Smith, J.

2017-12-01

Water is not only the most important substance for life, but also plays important roles in liquid science for its anomalous properties. It has been widely accepted that water's anomalies are not a result of simple thermal fluctuation, but are connected to the formation of various structural aggregates in the hydrogen bonding network. Among several proposed scenarios, one model of fluctuations between two different liquids has gradually gained traction. These two liquids are referred to as a low-density liquid (LDL) and a high-density liquid (HDL) with a coexistence line in the deeply supercooled regime at elevated pressure. The LDL-HDL transition ends with decreasing pressure at a liquid-liquid critical point (LLCP) with its Widom line extending to low pressures. Above the Widom line lies mostly HDL which is favored by entropy, while LDL, mostly lying below the Widom line, is favored by enthalpy in the tetrahedral hydrogen bonding network. The origin of water's anomalies can then be explained by the increase in structural fluctuations, as water is cooled down to deeply supercooled temperatures approaching the Widom line. Because both the LLCP and the LDL-HDL transition line lie in water's "no man's land" between the homogeneous nucleation temperature (TH, 232 K) and the crystallization temperature (TX, 150 K), the success of experiments exploring this region has been limited thus far. Using a rapid decompression technique integrated with in situ x-ray diffraction, we observe that a high-pressure ice phase transforms to a low-density noncrystalline (LDN) form upon rapid release of pressure at temperatures of 140-165K. The LDN subsequently crystallizes into ice-Ic through a diffusion-controlled process. The change in crystallization rate with temperature indicates that the LDN is a LDL with its tetrahedrally-coordinated network fully developed and clearly linked to low-density amorphous ices. The observation of the tetrahedral LDL supports the two-liquid model for water including the existence of a LLCP.

Repeated Stimulation of Cultured Networks of Rat Cortical Neurons Induces Parallel Memory Traces

ERIC Educational Resources Information Center

le Feber, Joost; Witteveen, Tim; van Veenendaal, Tamar M.; Dijkstra, Jelle

2015-01-01

During systems consolidation, memories are spontaneously replayed favoring information transfer from hippocampus to neocortex. However, at present no empirically supported mechanism to accomplish a transfer of memory from hippocampal to extra-hippocampal sites has been offered. We used cultured neuronal networks on multielectrode arrays and…

Temporal interactions facilitate endemicity in the susceptible-infected-susceptible epidemic model

NASA Astrophysics Data System (ADS)

Speidel, Leo; Klemm, Konstantin; Eguíluz, Víctor M.; Masuda, Naoki

2016-07-01

Data of physical contacts and face-to-face communications suggest temporally varying networks as the media on which infections take place among humans and animals. Epidemic processes on temporal networks are complicated by complexity of both network structure and temporal dimensions. Theoretical approaches are much needed for identifying key factors that affect dynamics of epidemics. In particular, what factors make some temporal networks stronger media of infection than other temporal networks is under debate. We develop a theory to understand the susceptible-infected-susceptible epidemic model on arbitrary temporal networks, where each contact is used for a finite duration. We show that temporality of networks lessens the epidemic threshold such that infections persist more easily in temporal networks than in their static counterparts. We further show that the Lie commutator bracket of the adjacency matrices at different times is a key determinant of the epidemic threshold in temporal networks. The effect of temporality on the epidemic threshold, which depends on a data set, is approximately predicted by the magnitude of a commutator norm.

A Survey of Middleware for Sensor and Network Virtualization

PubMed Central

Khalid, Zubair; Fisal, Norsheila; Rozaini, Mohd.

2014-01-01

Wireless Sensor Network (WSN) is leading to a new paradigm of Internet of Everything (IoE). WSNs have a wide range of applications but are usually deployed in a particular application. However, the future of WSNs lies in the aggregation and allocation of resources, serving diverse applications. WSN virtualization by the middleware is an emerging concept that enables aggregation of multiple independent heterogeneous devices, networks, radios and software platforms; and enhancing application development. WSN virtualization, middleware can further be categorized into sensor virtualization and network virtualization. Middleware for WSN virtualization poses several challenges like efficient decoupling of networks, devices and software. In this paper efforts have been put forward to bring an overview of the previous and current middleware designs for WSN virtualization, the design goals, software architectures, abstracted services, testbeds and programming techniques. Furthermore, the paper also presents the proposed model, challenges and future opportunities for further research in the middleware designs for WSN virtualization. PMID:25615737

Joint Optimization of Receiver Placement and Illuminator Selection for a Multiband Passive Radar Network.

PubMed

Xie, Rui; Wan, Xianrong; Hong, Sheng; Yi, Jianxin

2017-06-14

The performance of a passive radar network can be greatly improved by an optimal radar network structure. Generally, radar network structure optimization consists of two aspects, namely the placement of receivers in suitable places and selection of appropriate illuminators. The present study investigates issues concerning the joint optimization of receiver placement and illuminator selection for a passive radar network. Firstly, the required radar cross section (RCS) for target detection is chosen as the performance metric, and the joint optimization model boils down to the partition p -center problem (PPCP). The PPCP is then solved by a proposed bisection algorithm. The key of the bisection algorithm lies in solving the partition set covering problem (PSCP), which can be solved by a hybrid algorithm developed by coupling the convex optimization with the greedy dropping algorithm. In the end, the performance of the proposed algorithm is validated via numerical simulations.

A survey of middleware for sensor and network virtualization.

PubMed

Khalid, Zubair; Fisal, Norsheila; Rozaini, Mohd

2014-12-12

Wireless Sensor Network (WSN) is leading to a new paradigm of Internet of Everything (IoE). WSNs have a wide range of applications but are usually deployed in a particular application. However, the future of WSNs lies in the aggregation and allocation of resources, serving diverse applications. WSN virtualization by the middleware is an emerging concept that enables aggregation of multiple independent heterogeneous devices, networks, radios and software platforms; and enhancing application development. WSN virtualization, middleware can further be categorized into sensor virtualization and network virtualization. Middleware for WSN virtualization poses several challenges like efficient decoupling of networks, devices and software. In this paper efforts have been put forward to bring an overview of the previous and current middleware designs for WSN virtualization, the design goals, software architectures, abstracted services, testbeds and programming techniques. Furthermore, the paper also presents the proposed model, challenges and future opportunities for further research in the middleware designs for WSN virtualization.

Building a Community of Practice for Researchers: The International Network for Simulation-Based Pediatric Innovation, Research and Education.

PubMed

Cheng, Adam; Auerbach, Marc; Calhoun, Aaron; Mackinnon, Ralph; Chang, Todd P; Nadkarni, Vinay; Hunt, Elizabeth A; Duval-Arnould, Jordan; Peiris, Nicola; Kessler, David

2018-06-01

The scope and breadth of simulation-based research is growing rapidly; however, few mechanisms exist for conducting multicenter, collaborative research. Failure to foster collaborative research efforts is a critical gap that lies in the path of advancing healthcare simulation. The 2017 Research Summit hosted by the Society for Simulation in Healthcare highlighted how simulation-based research networks can produce studies that positively impact the delivery of healthcare. In 2011, the International Network for Simulation-based Pediatric Innovation, Research and Education (INSPIRE) was formed to facilitate multicenter, collaborative simulation-based research with the aim of developing a community of practice for simulation researchers. Since its formation, the network has successfully completed and published numerous collaborative research projects. In this article, we describe INSPIRE's history, structure, and internal processes with the goal of highlighting the community of practice model for other groups seeking to form a simulation-based research network.

Link failure detection in a parallel computer

DOEpatents

Archer, Charles J.; Blocksome, Michael A.; Megerian, Mark G.; Smith, Brian E.

2010-11-09

Methods, apparatus, and products are disclosed for link failure detection in a parallel computer including compute nodes connected in a rectangular mesh network, each pair of adjacent compute nodes in the rectangular mesh network connected together using a pair of links, that includes: assigning each compute node to either a first group or a second group such that adjacent compute nodes in the rectangular mesh network are assigned to different groups; sending, by each of the compute nodes assigned to the first group, a first test message to each adjacent compute node assigned to the second group; determining, by each of the compute nodes assigned to the second group, whether the first test message was received from each adjacent compute node assigned to the first group; and notifying a user, by each of the compute nodes assigned to the second group, whether the first test message was received.

Parallel multipoint recording of aligned and cultured neurons on corresponding Micro Channel Array toward on-chip cell analysis.

PubMed

Tonomura, W; Moriguchi, H; Jimbo, Y; Konishi, S

2008-01-01

This paper describes an advanced Micro Channel Array (MCA) so as to record neuronal network at multiple points simultaneously. Developed MCA is designed for neuronal network analysis which has been studied by co-authors using MEA (Micro Electrode Arrays) system. The MCA employs the principle of the extracellular recording. Presented MCA has the following advantages. First of all, the electrodes integrated around individual micro channels are electrically isolated for parallel multipoint recording. Sucking and clamping of cells through micro channels is expected to improve the cellular selectivity and S/N ratio. In this study, hippocampal neurons were cultured on the developed MCA. As a result, the spontaneous and evoked spike potential could be recorded by sucking and clamping the cells at multiple points. Herein, we describe the successful experimental results together with the design and fabrication of the advanced MCA toward on-chip analysis of neuronal network.

Dielectric monitoring of carbon nanotube network formation in curing thermosetting nanocomposites

NASA Astrophysics Data System (ADS)

Battisti, A.; Skordos, A. A.; Partridge, I. K.

2009-08-01

This paper focuses on monitoring of carbon nanotube (CNT) network development during the cure of unsaturated polyester nanocomposites by means of electrical impedance spectroscopy. A phenomenological model of the dielectric response is developed using equivalent circuit analysis. The model comprises two parallel RC elements connected in series, each of them giving rise to a semicircular arc in impedance complex plane plots. An established inverse modelling methodology is utilized for the estimation of the parameters of the corresponding equivalent circuit. This allows a quantification of the evolution of two separate processes corresponding to the two parallel RC elements. The high frequency process, which is attributed to CNT aggregates, shows a monotonic decrease in characteristic time during the cure. In contrast, the low frequency process, which corresponds to inter-aggregate phenomena, shows a more complex behaviour explained by the interplay between conductive network development and the cross-linking of the polymer.

Conservative parallel simulation of priority class queueing networks

NASA Technical Reports Server (NTRS)

Nicol, David

1992-01-01

A conservative synchronization protocol is described for the parallel simulation of queueing networks having C job priority classes, where a job's class is fixed. This problem has long vexed designers of conservative synchronization protocols because of its seemingly poor ability to compute lookahead: the time of the next departure. For, a job in service having low priority can be preempted at any time by an arrival having higher priority and an arbitrarily small service time. The solution is to skew the event generation activity so that the events for higher priority jobs are generated farther ahead in simulated time than lower priority jobs. Thus, when a lower priority job enters service for the first time, all the higher priority jobs that may preempt it are already known and the job's departure time can be exactly predicted. Finally, the protocol was analyzed and it was demonstrated that good performance can be expected on the simulation of large queueing networks.

Conservative parallel simulation of priority class queueing networks

NASA Technical Reports Server (NTRS)

Nicol, David M.

1990-01-01

A conservative synchronization protocol is described for the parallel simulation of queueing networks having C job priority classes, where a job's class is fixed. This problem has long vexed designers of conservative synchronization protocols because of its seemingly poor ability to compute lookahead: the time of the next departure. For, a job in service having low priority can be preempted at any time by an arrival having higher priority and an arbitrarily small service time. The solution is to skew the event generation activity so that the events for higher priority jobs are generated farther ahead in simulated time than lower priority jobs. Thus, when a lower priority job enters service for the first time, all the higher priority jobs that may preempt it are already known and the job's departure time can be exactly predicted. Finally, the protocol was analyzed and it was demonstrated that good performance can be expected on the simulation of large queueing networks.

Integrated Network Decompositions and Dynamic Programming for Graph Optimization (INDDGO)

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

The INDDGO software package offers a set of tools for finding exact solutions to graph optimization problems via tree decompositions and dynamic programming algorithms. Currently the framework offers serial and parallel (distributed memory) algorithms for finding tree decompositions and solving the maximum weighted independent set problem. The parallel dynamic programming algorithm is implemented on top of the MADNESS task-based runtime.

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

Koniges, A.E.

The author describes the new T3D parallel computer at NERSC. The adaptive mesh ICF3D code is one of the current applications being ported and developed for use on the T3D. It has been stressed in other papers in this proceedings that the development environment and tools available on the parallel computer is similar to any planned for the future including networks of workstations.

Long-range interactions and parallel scalability in molecular simulations

NASA Astrophysics Data System (ADS)

Patra, Michael; Hyvönen, Marja T.; Falck, Emma; Sabouri-Ghomi, Mohsen; Vattulainen, Ilpo; Karttunen, Mikko

2007-01-01

Typical biomolecular systems such as cellular membranes, DNA, and protein complexes are highly charged. Thus, efficient and accurate treatment of electrostatic interactions is of great importance in computational modeling of such systems. We have employed the GROMACS simulation package to perform extensive benchmarking of different commonly used electrostatic schemes on a range of computer architectures (Pentium-4, IBM Power 4, and Apple/IBM G5) for single processor and parallel performance up to 8 nodes—we have also tested the scalability on four different networks, namely Infiniband, GigaBit Ethernet, Fast Ethernet, and nearly uniform memory architecture, i.e. communication between CPUs is possible by directly reading from or writing to other CPUs' local memory. It turns out that the particle-mesh Ewald method (PME) performs surprisingly well and offers competitive performance unless parallel runs on PC hardware with older network infrastructure are needed. Lipid bilayers of sizes 128, 512 and 2048 lipid molecules were used as the test systems representing typical cases encountered in biomolecular simulations. Our results enable an accurate prediction of computational speed on most current computing systems, both for serial and parallel runs. These results should be helpful in, for example, choosing the most suitable configuration for a small departmental computer cluster.

Identifying failure in a tree network of a parallel computer

DOEpatents

Archer, Charles J.; Pinnow, Kurt W.; Wallenfelt, Brian P.

2010-08-24

Methods, parallel computers, and products are provided for identifying failure in a tree network of a parallel computer. The parallel computer includes one or more processing sets including an I/O node and a plurality of compute nodes. For each processing set embodiments include selecting a set of test compute nodes, the test compute nodes being a subset of the compute nodes of the processing set; measuring the performance of the I/O node of the processing set; measuring the performance of the selected set of test compute nodes; calculating a current test value in dependence upon the measured performance of the I/O node of the processing set, the measured performance of the set of test compute nodes, and a predetermined value for I/O node performance; and comparing the current test value with a predetermined tree performance threshold. If the current test value is below the predetermined tree performance threshold, embodiments include selecting another set of test compute nodes. If the current test value is not below the predetermined tree performance threshold, embodiments include selecting from the test compute nodes one or more potential problem nodes and testing individually potential problem nodes and links to potential problem nodes.

ISDN Application in the Army Environment

DTIC Science & Technology

1992-02-01

Signalling System Number 7 ( SS7 ). SS7 is a packet switched signalling network operating in parallel with the traffic bearing network. The current, in...for example, require SS7 . Further into the future, broadband ISDN (B-ISDN) is expected to provide high-quality, full-motion video, High Definition...smaller business offices, ISDN could be a viable alternative to private networks, especially when switches are connected through SS7 . ISDN, in combination

Controls on the spacing and geometry of rill networks on hillslopes: Rainsplash detachment, initial hillslope roughness, and the competition between fluvial and colluvial transport

USDA-ARS?s Scientific Manuscript database

Rill networks have been a focus of study for many decades but we still lack a complete understanding of what variables control the spacing of rills and the geometry of rill networks (e.g. parallel or dendritic) on hillslopes. In this paper we investigate the controls on the spacing and geometry of ...

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

Bonachea, Dan; Hargrove, P.

GASNet is a language-independent, low-level networking layer that provides network-independent, high-performance communication primitives tailored for implementing parallel global address space SPMD languages and libraries such as UPC, UPC++, Co-Array Fortran, Legion, Chapel, and many others. The interface is primarily intended as a compilation target and for use by runtime library writers (as opposed to end users), and the primary goals are high performance, interface portability, and expressiveness. GASNet stands for "Global-Address Space Networking".

Slow Computing Simulation of Bio-plausible Control

DTIC Science & Technology

2012-03-01

information networks, neuromorphic chips would become necessary. Small unstable flying platforms currently require RTK, GPS, or Vicon closed-circuit...Visual, and IR Sensing FPGA ASIC Neuromorphic Chip Simulation Quad Rotor Robotic Insect Uniform Independent Network Single Modality Neural Network... neuromorphic Processing across parallel computational elements =0.54 N u m b e r o f c o m p u ta tio n s - No info 14 integrated circuit

PRAIS: Distributed, real-time knowledge-based systems made easy

NASA Technical Reports Server (NTRS)

Goldstein, David G.

1990-01-01

This paper discusses an architecture for real-time, distributed (parallel) knowledge-based systems called the Parallel Real-time Artificial Intelligence System (PRAIS). PRAIS strives for transparently parallelizing production (rule-based) systems, even when under real-time constraints. PRAIS accomplishes these goals by incorporating a dynamic task scheduler, operating system extensions for fact handling, and message-passing among multiple copies of CLIPS executing on a virtual blackboard. This distributed knowledge-based system tool uses the portability of CLIPS and common message-passing protocols to operate over a heterogeneous network of processors.

Trace-Driven Debugging of Message Passing Programs

NASA Technical Reports Server (NTRS)

Frumkin, Michael; Hood, Robert; Lopez, Louis; Bailey, David (Technical Monitor)

1998-01-01

In this paper we report on features added to a parallel debugger to simplify the debugging of parallel message passing programs. These features include replay, setting consistent breakpoints based on interprocess event causality, a parallel undo operation, and communication supervision. These features all use trace information collected during the execution of the program being debugged. We used a number of different instrumentation techniques to collect traces. We also implemented trace displays using two different trace visualization systems. The implementation was tested on an SGI Power Challenge cluster and a network of SGI workstations.

Tectono-magmatic relationships along an obliquely convergent plate boundary: Sumatra, Indonesia.

NASA Astrophysics Data System (ADS)

Acocella, Valerio; Bellier, Olivier

2017-04-01

The tectono-magmatic relationships along divergent and orthogonally convergent plate boundaries have been defined in several aspects. However, much less is known along obliquely convergent plate boundaries, where the strain partitioning promotes strike-slip structures along the volcanic arc. Here it is unclear if and, in case, how strike-slip structures may control arc volcanism, in terms of processes, distribution and size. To better define these features, we review the available tectonic, structural and volcanological data on Sumatra (Indonesia), which provides the ideal case study. The Sumatra volcanic arc consists of 48 major active volcanoes. Of these, 46% lie within 10 km from the dextral Great Sumatra Fault (GSF), which carries most of the strike-slip displacement on the overriding plate, whereas 27% of the volcanoes lie at >20 km from the GSF. Considering the volcanoes lying within 10 km from GSF, 76% show some possible structural relation to the GSF, whereas only 28% (7 volcanoes) show a clear structural relation to the GSF, being located in pull-apart or releasing bends between dextral segments. However, these localized areas of extension do not seem to promote the development of magmatic segments, similarly to orthogonally convergent plate boundaries. Many volcanoes lie to the west of the GSF, largely following the shallower portions of the slab, which reaches its average partial melting depth (130±30 km) more westward. There is a preferred volcano alignment and elongation along the N30-N40°E trend, almost parallel to the convergence vector; this trend coincides with the direction of the extensional structures found along the arc. Other volcanoes are elongated parallel to the GSF, possibly resulting from the co- and post-seismic across-arc extension, as observed during the 2004 mega-earthquake. Finally, there is no relationship between the slip rate along GSF and the erupted volumes along the arc: the highest productivity of Toba caldera may be explained by a slab tear. Overall, these data highlight a limited control of the geometry and kinematics of the GSF on the arc volcanism of Sumatra. This control is mostly confined to the: a) suitable depth for partial melting of the slab; b) structural configuration of the GSF, promoting localized extension. Otherwise, magma may rise far from the GSF, where the direction of the feeder dikes may be controlled by the inter-seismic extension (perpendicular to the convergence vector) or by the arc normal co- and post-seismic extension.

Connectopathy in Autism Spectrum Disorders: A Review of Evidence from Visual Evoked Potentials and Diffusion Magnetic Resonance Imaging

PubMed Central

Yamasaki, Takao; Maekawa, Toshihiko; Fujita, Takako; Tobimatsu, Shozo

2017-01-01

Individuals with autism spectrum disorder (ASD) show superior performance in processing fine details; however, they often exhibit impairments of gestalt face, global motion perception, and visual attention as well as core social deficits. Increasing evidence has suggested that social deficits in ASD arise from abnormal functional and structural connectivities between and within distributed cortical networks that are recruited during social information processing. Because the human visual system is characterized by a set of parallel, hierarchical, multistage network systems, we hypothesized that the altered connectivity of visual networks contributes to social cognition impairment in ASD. In the present review, we focused on studies of altered connectivity of visual and attention networks in ASD using visual evoked potentials (VEPs), event-related potentials (ERPs), and diffusion tensor imaging (DTI). A series of VEP, ERP, and DTI studies conducted in our laboratory have demonstrated complex alterations (impairment and enhancement) of visual and attention networks in ASD. Recent data have suggested that the atypical visual perception observed in ASD is caused by altered connectivity within parallel visual pathways and attention networks, thereby contributing to the impaired social communication observed in ASD. Therefore, we conclude that the underlying pathophysiological mechanism of ASD constitutes a “connectopathy.” PMID:29170625

Quantitative Analysis of Filament Branch Orientation in Listeria Actin Comet Tails.

PubMed

Jasnin, Marion; Crevenna, Alvaro H

2016-02-23

Several bacterial and viral pathogens hijack the host actin cytoskeleton machinery to facilitate spread and infection. In particular, Listeria uses Arp2/3-mediated actin filament nucleation at the bacterial surface to generate a branched network that will help propel the bacteria. However, the mechanism of force generation remains elusive due to the lack of high-resolution three-dimensional structural data on the spatial organization of the actin mother and daughter (i.e., branch) filaments within this network. Here, we have explored the three-dimensional structure of Listeria actin tails in Xenopus laevis egg extracts using cryo-electron tomography. We found that the architecture of Listeria actin tails is shared between those formed in cells and in cell extracts. Both contained nanoscopic bundles along the plane of the substrate, where the bacterium lies, and upright filaments (also called Z filaments), both oriented tangentially to the bacterial cell wall. Here, we were able to identify actin filament intersections, which likely correspond to branches, within the tails. A quantitative analysis of putative Arp2/3-mediated branches in the actin network showed that mother filaments lie on the plane of the substrate, whereas daughter filaments have random deviations out of this plane. Moreover, the analysis revealed that branches are randomly oriented with respect to the bacterial surface. Therefore, the actin filament network does not push directly toward the surface but rather accumulates, building up stress around the Listeria surface. Our results favor a mechanism of force generation for Listeria movement where the stress is released into propulsive motion. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Design and implementation of a high performance network security processor

NASA Astrophysics Data System (ADS)

Wang, Haixin; Bai, Guoqiang; Chen, Hongyi

2010-03-01

The last few years have seen many significant progresses in the field of application-specific processors. One example is network security processors (NSPs) that perform various cryptographic operations specified by network security protocols and help to offload the computation intensive burdens from network processors (NPs). This article presents a high performance NSP system architecture implementation intended for both internet protocol security (IPSec) and secure socket layer (SSL) protocol acceleration, which are widely employed in virtual private network (VPN) and e-commerce applications. The efficient dual one-way pipelined data transfer skeleton and optimised integration scheme of the heterogenous parallel crypto engine arrays lead to a Gbps rate NSP, which is programmable with domain specific descriptor-based instructions. The descriptor-based control flow fragments large data packets and distributes them to the crypto engine arrays, which fully utilises the parallel computation resources and improves the overall system data throughput. A prototyping platform for this NSP design is implemented with a Xilinx XC3S5000 based FPGA chip set. Results show that the design gives a peak throughput for the IPSec ESP tunnel mode of 2.85 Gbps with over 2100 full SSL handshakes per second at a clock rate of 95 MHz.

Automation of multi-agent control for complex dynamic systems in heterogeneous computational network

NASA Astrophysics Data System (ADS)

Oparin, Gennady; Feoktistov, Alexander; Bogdanova, Vera; Sidorov, Ivan

2017-01-01

The rapid progress of high-performance computing entails new challenges related to solving large scientific problems for various subject domains in a heterogeneous distributed computing environment (e.g., a network, Grid system, or Cloud infrastructure). The specialists in the field of parallel and distributed computing give the special attention to a scalability of applications for problem solving. An effective management of the scalable application in the heterogeneous distributed computing environment is still a non-trivial issue. Control systems that operate in networks, especially relate to this issue. We propose a new approach to the multi-agent management for the scalable applications in the heterogeneous computational network. The fundamentals of our approach are the integrated use of conceptual programming, simulation modeling, network monitoring, multi-agent management, and service-oriented programming. We developed a special framework for an automation of the problem solving. Advantages of the proposed approach are demonstrated on the parametric synthesis example of the static linear regulator for complex dynamic systems. Benefits of the scalable application for solving this problem include automation of the multi-agent control for the systems in a parallel mode with various degrees of its detailed elaboration.

Artificially modified magnetic anisotropy in interconnected nanowire networks.

PubMed

Araujo, Elsie; Encinas, Armando; Velázquez-Galván, Yenni; Martínez-Huerta, Juan Manuel; Hamoir, Gaël; Ferain, Etienne; Piraux, Luc

2015-01-28

Interconnected or crossed magnetic nanowire networks have been fabricated by electrodeposition into a polycarbonate template with crossed cylindrical nanopores oriented ±30° with respect to the surface normal. Tailor-made nanoporous polymer membranes have been designed by performing a double energetic heavy ion irradiation with fixed incidence angles. The Ni and Ni/NiFe nanowire networks have been characterized by magnetometry as well as ferromagnetic resonance and compared with parallel nanowire arrays of the same diameter and density. The most interesting feature of these nanostructured materials is a significant reduction of the magnetic anisotropy when the external field is applied perpendicular and parallel to the plane of the sample. This effect is attributed to the relative orientation of the nanowire axes with the applied field. Moreover, the microwave transmission spectra of these nanowire networks display an asymmetric linewidth broadening, which may be interesting for the development of low-pass filters. Nanoporous templates made of well-defined nanochannel network constitute an interesting approach to fabricate materials with controlled anisotropy and microwave absorption properties that can be easily modified by adjusting the relative orientation of the nanochannels, pore sizes and material composition along the length of the nanowire.

Parallel processor-based raster graphics system architecture

DOEpatents

Littlefield, Richard J.

1990-01-01

An apparatus for generating raster graphics images from the graphics command stream includes a plurality of graphics processors connected in parallel, each adapted to receive any part of the graphics command stream for processing the command stream part into pixel data. The apparatus also includes a frame buffer for mapping the pixel data to pixel locations and an interconnection network for interconnecting the graphics processors to the frame buffer. Through the interconnection network, each graphics processor may access any part of the frame buffer concurrently with another graphics processor accessing any other part of the frame buffer. The plurality of graphics processors can thereby transmit concurrently pixel data to pixel locations in the frame buffer.

Roles of epsilon-near-zero (ENZ) and mu-near-zero (MNZ) materials in optical metatronic circuit networks.

PubMed

Abbasi, Fereshteh; Engheta, Nader

2014-10-20

The concept of metamaterial-inspired nanocircuits, dubbed metatronics, was introduced in [Science 317, 1698 (2007); Phys. Rev. Lett. 95, 095504 (2005)]. It was suggested how optical lumped elements (nanoelements) can be made using subwavelength plasmonic or non-plasmonic particles. As a result, the optical metatronic equivalents of a number of electronic circuits, such as frequency mixers and filters, were suggested. In this work we further expand the concept of electronic lumped element networks into optical metatronic circuits and suggest a conceptual model applicable to various metatronic passive networks. In particular, we differentiate between the series and parallel networks using epsilon-near-zero (ENZ) and mu-near-zero (MNZ) materials. We employ layered structures with subwavelength thicknesses for the nanoelements as the building blocks of collections of metatronic networks. Furthermore, we explore how by choosing the non-zero constitutive parameters of the materials with specific dispersions, either Drude or Lorentzian dispersion with suitable parameters, capacitive and inductive responses can be achieved in both series and parallel networks. Next, we proceed with the one-to-one analogy between electronic circuits and optical metatronic filter layered networks and justify our analogies by comparing the frequency response of the two paradigms. Finally, we examine the material dispersion of near-zero relative permittivity as well as other physically important material considerations such as losses.

Template based parallel checkpointing in a massively parallel computer system

DOEpatents

Archer, Charles Jens [Rochester, MN; Inglett, Todd Alan [Rochester, MN

2009-01-13

A method and apparatus for a template based parallel checkpoint save for a massively parallel super computer system using a parallel variation of the rsync protocol, and network broadcast. In preferred embodiments, the checkpoint data for each node is compared to a template checkpoint file that resides in the storage and that was previously produced. Embodiments herein greatly decrease the amount of data that must be transmitted and stored for faster checkpointing and increased efficiency of the computer system. Embodiments are directed to a parallel computer system with nodes arranged in a cluster with a high speed interconnect that can perform broadcast communication. The checkpoint contains a set of actual small data blocks with their corresponding checksums from all nodes in the system. The data blocks may be compressed using conventional non-lossy data compression algorithms to further reduce the overall checkpoint size.

Distributed and parallel Ada and the Ada 9X recommendations

NASA Technical Reports Server (NTRS)

Volz, Richard A.; Goldsack, Stephen J.; Theriault, R.; Waldrop, Raymond S.; Holzbacher-Valero, A. A.

1992-01-01

Recently, the DoD has sponsored work towards a new version of Ada, intended to support the construction of distributed systems. The revised version, often called Ada 9X, will become the new standard sometimes in the 1990s. It is intended that Ada 9X should provide language features giving limited support for distributed system construction. The requirements for such features are given. Many of the most advanced computer applications involve embedded systems that are comprised of parallel processors or networks of distributed computers. If Ada is to become the widely adopted language envisioned by many, it is essential that suitable compilers and tools be available to facilitate the creation of distributed and parallel Ada programs for these applications. The major languages issues impacting distributed and parallel programming are reviewed, and some principles upon which distributed/parallel language systems should be built are suggested. Based upon these, alternative language concepts for distributed/parallel programming are analyzed.

Smoldyn on graphics processing units: massively parallel Brownian dynamics simulations.

PubMed

Dematté, Lorenzo

2012-01-01

Space is a very important aspect in the simulation of biochemical systems; recently, the need for simulation algorithms able to cope with space is becoming more and more compelling. Complex and detailed models of biochemical systems need to deal with the movement of single molecules and particles, taking into consideration localized fluctuations, transportation phenomena, and diffusion. A common drawback of spatial models lies in their complexity: models can become very large, and their simulation could be time consuming, especially if we want to capture the systems behavior in a reliable way using stochastic methods in conjunction with a high spatial resolution. In order to deliver the promise done by systems biology to be able to understand a system as whole, we need to scale up the size of models we are able to simulate, moving from sequential to parallel simulation algorithms. In this paper, we analyze Smoldyn, a widely diffused algorithm for stochastic simulation of chemical reactions with spatial resolution and single molecule detail, and we propose an alternative, innovative implementation that exploits the parallelism of Graphics Processing Units (GPUs). The implementation executes the most computational demanding steps (computation of diffusion, unimolecular, and bimolecular reaction, as well as the most common cases of molecule-surface interaction) on the GPU, computing them in parallel on each molecule of the system. The implementation offers good speed-ups and real time, high quality graphics output

Localization of multilayer networks by optimized single-layer rewiring.

PubMed

Jalan, Sarika; Pradhan, Priodyuti

2018-04-01

We study localization properties of principal eigenvectors (PEVs) of multilayer networks (MNs). Starting with a multilayer network corresponding to a delocalized PEV, we rewire the network edges using an optimization technique such that the PEV of the rewired multilayer network becomes more localized. The framework allows us to scrutinize structural and spectral properties of the networks at various localization points during the rewiring process. We show that rewiring only one layer is enough to attain a MN having a highly localized PEV. Our investigation reveals that a single edge rewiring of the optimized MN can lead to the complete delocalization of a highly localized PEV. This sensitivity in the localization behavior of PEVs is accompanied with the second largest eigenvalue lying very close to the largest one. This observation opens an avenue to gain a deeper insight into the origin of PEV localization of networks. Furthermore, analysis of multilayer networks constructed using real-world social and biological data shows that the localization properties of these real-world multilayer networks are in good agreement with the simulation results for the model multilayer network. This paper is relevant to applications that require understanding propagation of perturbation in multilayer networks.

Thermalnet: a Deep Convolutional Network for Synthetic Thermal Image Generation

NASA Astrophysics Data System (ADS)

Kniaz, V. V.; Gorbatsevich, V. S.; Mizginov, V. A.

2017-05-01

Deep convolutional neural networks have dramatically changed the landscape of the modern computer vision. Nowadays methods based on deep neural networks show the best performance among image recognition and object detection algorithms. While polishing of network architectures received a lot of scholar attention, from the practical point of view the preparation of a large image dataset for a successful training of a neural network became one of major challenges. This challenge is particularly profound for image recognition in wavelengths lying outside the visible spectrum. For example no infrared or radar image datasets large enough for successful training of a deep neural network are available to date in public domain. Recent advances of deep neural networks prove that they are also capable to do arbitrary image transformations such as super-resolution image generation, grayscale image colorisation and imitation of style of a given artist. Thus a natural question arise: how could be deep neural networks used for augmentation of existing large image datasets? This paper is focused on the development of the Thermalnet deep convolutional neural network for augmentation of existing large visible image datasets with synthetic thermal images. The Thermalnet network architecture is inspired by colorisation deep neural networks.

Localization of multilayer networks by optimized single-layer rewiring

NASA Astrophysics Data System (ADS)

Jalan, Sarika; Pradhan, Priodyuti

2018-04-01

We study localization properties of principal eigenvectors (PEVs) of multilayer networks (MNs). Starting with a multilayer network corresponding to a delocalized PEV, we rewire the network edges using an optimization technique such that the PEV of the rewired multilayer network becomes more localized. The framework allows us to scrutinize structural and spectral properties of the networks at various localization points during the rewiring process. We show that rewiring only one layer is enough to attain a MN having a highly localized PEV. Our investigation reveals that a single edge rewiring of the optimized MN can lead to the complete delocalization of a highly localized PEV. This sensitivity in the localization behavior of PEVs is accompanied with the second largest eigenvalue lying very close to the largest one. This observation opens an avenue to gain a deeper insight into the origin of PEV localization of networks. Furthermore, analysis of multilayer networks constructed using real-world social and biological data shows that the localization properties of these real-world multilayer networks are in good agreement with the simulation results for the model multilayer network. This paper is relevant to applications that require understanding propagation of perturbation in multilayer networks.

Study of Two Successive Three-ribbon Solar Flares on 2012 July 6

NASA Astrophysics Data System (ADS)

Wang, Haimin; Liu, Chang; Deng, Na; Zeng, Zhicheng; Xu, Yan; Jing, Ju; Cao, Wenda

2014-01-01

This Letter reports two rarely observed three-ribbon flares (M1.9 and C9.2) on 2012 July 6 in NOAA AR 11515, which we found using Hα observations of 0.''1 resolution from the New Solar Telescope and Ca II H images from Hinode. The flaring site is characterized by an intriguing "fish-bone-like" morphology evidenced by both Hα images and a nonlinear force-free field (NLFFF) extrapolation, where two semi-parallel rows of low-lying, sheared loops connect an elongated, parasitic negative field with the sandwiching positive fields. The NLFFF model also shows that the two rows of loops are asymmetric in height and have opposite twists, and are enveloped by large-scale field lines including open fields. The two flares occurred in succession within half an hour and are located at the two ends of the flaring region. The three ribbons of each flare run parallel to the magnetic polarity inversion line, with the outer two lying in the positive field and the central one in the negative field. Both flares show surge-like flows in Hα apparently toward the remote region, while the C9.2 flare is also accompanied by EUV jets possibly along the open field lines. Interestingly, the 12-25 keV hard X-ray sources of the C9.2 flare first line up with the central ribbon then shift to concentrate on the top of the higher branch of loops. These results are discussed in favor of reconnection along the coronal null line, producing the three flare ribbons and the associated ejections.

Study of Two Successive Three-ribbon Solar Flares Using BBSO/NST Observations

NASA Astrophysics Data System (ADS)

Wang, Haimin; Liu, Chang; Deng, Na; Zeng, Zhicheng; Xu, Yan; Jing, Ju; Cao, Wenda

2014-06-01

We studied two rarely observed three-ribbon flares (M1.9 and C9.2) on 2012 July 6 in NOAA AR 11515, which we found using Hα observations of 0.1 arcsec resolution from the New Solar Telescope and Ca II H images from Hinode. The flaring site is characterized by an intriguing "fish-bone-like" morphology evidenced by both Halpha images and a nonlinear force-free field (NLFFF) extrapolation, where two semi-parallel rows of low-lying, sheared loops connect an elongated, parasitic negative field with the sandwiching positive fields. The NLFFF model also shows that the two rows of loops are asymmetric in height and have opposite twists, and are enveloped by large-scale field lines including open fields. The two flares occurred in succession within half an hour and are located at the two ends of the flaring region. The three ribbons of each flare run parallel to the magnetic polarity inversion line, with the outer two lying in the positive field and the central one in the negative field. Both flares show surge-like flows in Halpha apparently toward the remote region, while the C9.2 flare is also accompanied by EUV jets possibly along the open field lines. Interestingly, the 12-25 keV hard X-ray sources of the C9.2 flare first line up with the central ribbon then shift to concentrate on the top of the higher branch of loops. These results are discussed in favor of reconnection along the coronal null line, producing the three flare ribbons and the associated ejections.

Comparing the OpenMP, MPI, and Hybrid Programming Paradigm on an SMP Cluster

NASA Technical Reports Server (NTRS)

Jost, Gabriele; Jin, Hao-Qiang; anMey, Dieter; Hatay, Ferhat F.

2003-01-01

Clusters of SMP (Symmetric Multi-Processors) nodes provide support for a wide range of parallel programming paradigms. The shared address space within each node is suitable for OpenMP parallelization. Message passing can be employed within and across the nodes of a cluster. Multiple levels of parallelism can be achieved by combining message passing and OpenMP parallelization. Which programming paradigm is the best will depend on the nature of the given problem, the hardware components of the cluster, the network, and the available software. In this study we compare the performance of different implementations of the same CFD benchmark application, using the same numerical algorithm but employing different programming paradigms.

Situated Knowledge and Visual Education: Patrick Geddes and Reclus's Geography (1886-1932)

ERIC Educational Resources Information Center

Ferretti, Federico

2017-01-01

This article addresses Patrick Geddes's relationship with geography and visual education by focusing on his collaboration with the network of the anarchist geographers Élie, Élisée, and Paul Reclus. Drawing on empirical archival research, it contributes to the current debates on geographies of anarchist education and on geographic teaching. The…

Signal or noise: brain network interactions underlying the experience and training of mindfulness.

PubMed

Mooneyham, Benjamin W; Mrazek, Michael D; Mrazek, Alissa J; Schooler, Jonathan W

2016-04-01

A broad set of brain regions has been associated with the experience and training of mindfulness. Many of these regions lie within key intrinsic brain networks, including the executive control, salience, and default networks. In this paper, we review the existing literature on the cognitive neuroscience of mindfulness through the lens of network science. We describe the characteristics of the intrinsic brain networks implicated in mindfulness and summarize the relevant findings pertaining to changes in functional connectivity (FC) within and between these networks. Convergence across these findings suggests that mindfulness may be associated with increased FC between two regions within the default network: the posterior cingulate cortex and the ventromedial prefrontal cortex. Additionally, extensive meditation experience may be associated with increased FC between the insula and the dorsolateral prefrontal cortex. However, little consensus has emerged within the existing literature owing to the diversity of operational definitions of mindfulness, neuroimaging methods, and network characterizations. We describe several challenges to develop a coherent cognitive neuroscience of mindfulness and to provide detailed recommendations for future research. © 2016 New York Academy of Sciences.

Array processor architecture

NASA Technical Reports Server (NTRS)

Barnes, George H. (Inventor); Lundstrom, Stephen F. (Inventor); Shafer, Philip E. (Inventor)

1983-01-01

A high speed parallel array data processing architecture fashioned under a computational envelope approach includes a data base memory for secondary storage of programs and data, and a plurality of memory modules interconnected to a plurality of processing modules by a connection network of the Omega gender. Programs and data are fed from the data base memory to the plurality of memory modules and from hence the programs are fed through the connection network to the array of processors (one copy of each program for each processor). Execution of the programs occur with the processors operating normally quite independently of each other in a multiprocessing fashion. For data dependent operations and other suitable operations, all processors are instructed to finish one given task or program branch before all are instructed to proceed in parallel processing fashion on the next instruction. Even when functioning in the parallel processing mode however, the processors are not locked-step but execute their own copy of the program individually unless or until another overall processor array synchronization instruction is issued.

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.

Neural networks: Alternatives to conventional techniques for automatic docking

NASA Technical Reports Server (NTRS)

Vinz, Bradley L.

1994-01-01

Automatic docking of orbiting spacecraft is a crucial operation involving the identification of vehicle orientation as well as complex approach dynamics. The chaser spacecraft must be able to recognize the target spacecraft within a scene and achieve accurate closing maneuvers. In a video-based system, a target scene must be captured and transformed into a pattern of pixels. Successful recognition lies in the interpretation of this pattern. Due to their powerful pattern recognition capabilities, artificial neural networks offer a potential role in interpretation and automatic docking processes. Neural networks can reduce the computational time required by existing image processing and control software. In addition, neural networks are capable of recognizing and adapting to changes in their dynamic environment, enabling enhanced performance, redundancy, and fault tolerance. Most neural networks are robust to failure, capable of continued operation with a slight degradation in performance after minor failures. This paper discusses the particular automatic docking tasks neural networks can perform as viable alternatives to conventional techniques.

Improving the scalability of hyperspectral imaging applications on heterogeneous platforms using adaptive run-time data compression

NASA Astrophysics Data System (ADS)

Plaza, Antonio; Plaza, Javier; Paz, Abel

2010-10-01

Latest generation remote sensing instruments (called hyperspectral imagers) are now able to generate hundreds of images, corresponding to different wavelength channels, for the same area on the surface of the Earth. In previous work, we have reported that the scalability of parallel processing algorithms dealing with these high-dimensional data volumes is affected by the amount of data to be exchanged through the communication network of the system. However, large messages are common in hyperspectral imaging applications since processing algorithms are pixel-based, and each pixel vector to be exchanged through the communication network is made up of hundreds of spectral values. Thus, decreasing the amount of data to be exchanged could improve the scalability and parallel performance. In this paper, we propose a new framework based on intelligent utilization of wavelet-based data compression techniques for improving the scalability of a standard hyperspectral image processing chain on heterogeneous networks of workstations. This type of parallel platform is quickly becoming a standard in hyperspectral image processing due to the distributed nature of collected hyperspectral data as well as its flexibility and low cost. Our experimental results indicate that adaptive lossy compression can lead to improvements in the scalability of the hyperspectral processing chain without sacrificing analysis accuracy, even at sub-pixel precision levels.

Adding the 'heart' to hanging drop networks for microphysiological multi-tissue experiments.

PubMed

Rismani Yazdi, Saeed; Shadmani, Amir; Bürgel, Sebastian C; Misun, Patrick M; Hierlemann, Andreas; Frey, Olivier

2015-11-07

Microfluidic hanging-drop networks enable culturing and analysis of 3D microtissue spheroids derived from different cell types under controlled perfusion and investigating inter-tissue communication in multi-tissue formats. In this paper we introduce a compact on-chip pumping approach for flow control in hanging-drop networks. The pump includes one pneumatic chamber located directly above one of the hanging drops and uses the surface tension at the liquid-air-interface for flow actuation. Control of the pneumatic protocol provides a wide range of unidirectional pulsatile and continuous flow profiles. With the proposed concept several independent hanging-drop networks can be operated in parallel with only one single pneumatic actuation line at high fidelity. Closed-loop medium circulation between different organ models for multi-tissue formats and multiple simultaneous assays in parallel are possible. Finally, we implemented a real-time feedback control-loop of the pump actuation based on the beating of a human iPS-derived cardiac microtissue cultured in the same system. This configuration allows for simulating physiological effects on the heart and their impact on flow circulation between the organ models on chip.

Parallel multipoint recording of aligned and cultured neurons on micro channel array toward cellular network analysis.

PubMed

Tonomura, Wataru; Moriguchi, Hiroyuki; Jimbo, Yasuhiko; Konishi, Satoshi

2010-08-01

This paper describes an advanced Micro Channel Array (MCA) for recording electrophysiological signals of neuronal networks at multiple points simultaneously. The developed MCA is designed for neuronal network analysis which has been studied by the co-authors using the Micro Electrode Arrays (MEA) system, and employs the principles of extracellular recordings. A prerequisite for extracellular recordings with good signal-to-noise ratio is a tight contact between cells and electrodes. The MCA described herein has the following advantages. The electrodes integrated around individual micro channels are electrically isolated to enable parallel multipoint recording. Reliable clamping of a targeted cell through micro channels is expected to improve the cellular selectivity and the attachment between the cell and the electrode toward steady electrophysiological recordings. We cultured hippocampal neurons on the developed MCA. As a result, the spontaneous and evoked spike potentials could be recorded by sucking and clamping the cells at multiple points. In this paper, we describe the design and fabrication of the MCA and the successful electrophysiological recordings leading to the development of an effective cellular network analysis device.

Koszul information geometry and Souriau Lie group thermodynamics

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

Barbaresco, Frédéric, E-mail: frederic.barbaresco@thalesgroup.com

The François Massieu 1869 idea to derive some mechanical and thermal properties of physical systems from 'Characteristic Functions', was developed by Gibbs and Duhem in thermodynamics with the concept of potentials, and introduced by Poincaré in probability. This paper deals with generalization of this Characteristic Function concept by Jean-Louis Koszul in Mathematics and by Jean-Marie Souriau in Statistical Physics. The Koszul-Vinberg Characteristic Function (KVCF) on convex cones will be presented as cornerstone of 'Information Geometry' theory, defining Koszul Entropy as Legendre transform of minus the logarithm of KVCF, and Fisher Information Metrics as hessian of these dual functions, invariant bymore » their automorphisms. In parallel, Souriau has extended the Characteristic Function in Statistical Physics looking for other kinds of invariances through co-adjoint action of a group on its momentum space, defining physical observables like energy, heat and momentum as pure geometrical objects. In covariant Souriau model, Gibbs equilibriums states are indexed by a geometric parameter, the Geometric (Planck) Temperature, with values in the Lie algebra of the dynamical Galileo/Poincaré groups, interpreted as a space-time vector, giving to the metric tensor a null Lie derivative. Fisher Information metric appears as the opposite of the derivative of Mean 'Moment map' by geometric temperature, equivalent to a Geometric Capacity or Specific Heat. These elements has been developed by author in [10][11].« less

Face specificity and the role of metal adatoms in molecular reorientation at surfaces

NASA Astrophysics Data System (ADS)

Perry, C. C.; Haq, S.; Frederick, B. G.; Richardson, N. V.

1998-07-01

Using reflection absorption infrared spectroscopy (RAIRS), the coverage-dependent reorientation of the benzoate species on the (110) and (111) faces of copper is compared and contrasted. Whereas on Cu(110) benzoate reorients from a flat-lying to an upright orientation with increasing coverage, on Cu(111), at all coverages, benzoate is aligned normal to the surface. The formation of periodic, flat-lying copper-benzoate structures has been attributed to the availability of metal adatoms, which differs dramatically between the (111) and (110) faces. We discuss the face specificity of molecular orientation by comparing calculated formation energies of adatom vacancies from ledges and kink sites on (100), (110) and (111) faces. Further support for this model is given by the evaporation of sodium, either by pre- or post-dosing, onto low-coverage benzoate/Cu(111), which induces benzoate to convert from a perpendicular to a parallel orientation. Likewise, coevaporation of Cu while dosing benzoic acid onto the Cu(111) surface also results in a majority of flat-lying benzoate species. Finally, for adsorption on the p(2×1)O/Cu(110) reconstruction, benzoate occurs only as the upright species, which is consistent with reducing the copper mobility and availability on the (110) face. We therefore suggest the possible role of metal adatoms as a new mechanism in controlling adsorbate orientation and therefore face specificity in surface reactions.

Analysis of Compound Water Hazard in Coastal Urbanized Areas under the Future Climate

NASA Astrophysics Data System (ADS)

Shibuo, Y.; Taniguchi, K.; Sanuki, H.; Yoshimura, K.; Lee, S.; Tajima, Y.; Koike, T.; Furumai, H.; Sato, S.

2017-12-01

Several studies indicate the increased frequency and magnitude of heavy rainfalls as well as the sea level rise under the future climate, which implies that coastal low-lying urbanized areas may experience increased risk against flooding. In such areas, where river discharge, tidal fluctuation, and city drainage networks altogether influence urban inundation, it is necessary to consider their potential interference to understand the effect of compound water hazard. For instance, pump stations cannot pump out storm water when the river water level is high, and in the meantime the river water level shall increase when it receives pumped water from cities. At the further downstream, as the tidal fluctuation regulates the water levels in the river, it will also affect the functionality of pump stations and possible inundation from rivers. In this study, we estimate compound water hazard in the coastal low-lying urbanized areas of the Tsurumi river basin under the future climate. We developed the seamlessly integrated river, sewerage, and coastal hydraulic model that can simulate river water levels, water flow in sewerage network, and inundation from the rivers and/or the coast to address the potential interference issue. As a forcing, the pseudo global warming method, which applies the changes in GCM anomaly to re-analysis data, is employed to produce ensemble typhoons to drive the seamlessly integrated model. The results show that heavy rainfalls caused by the observed typhoon generally become stronger under the pseudo global climate condition. It also suggests that the coastal low-lying areas become extensively inundated if the onset of river flooding and storm surge coincides.

Cellular automata simulation of topological effects on the dynamics of feed-forward motifs

PubMed Central

Apte, Advait A; Cain, John W; Bonchev, Danail G; Fong, Stephen S

2008-01-01

Background Feed-forward motifs are important functional modules in biological and other complex networks. The functionality of feed-forward motifs and other network motifs is largely dictated by the connectivity of the individual network components. While studies on the dynamics of motifs and networks are usually devoted to the temporal or spatial description of processes, this study focuses on the relationship between the specific architecture and the overall rate of the processes of the feed-forward family of motifs, including double and triple feed-forward loops. The search for the most efficient network architecture could be of particular interest for regulatory or signaling pathways in biology, as well as in computational and communication systems. Results Feed-forward motif dynamics were studied using cellular automata and compared with differential equation modeling. The number of cellular automata iterations needed for a 100% conversion of a substrate into a target product was used as an inverse measure of the transformation rate. Several basic topological patterns were identified that order the specific feed-forward constructions according to the rate of dynamics they enable. At the same number of network nodes and constant other parameters, the bi-parallel and tri-parallel motifs provide higher network efficacy than single feed-forward motifs. Additionally, a topological property of isodynamicity was identified for feed-forward motifs where different network architectures resulted in the same overall rate of the target production. Conclusion It was shown for classes of structural motifs with feed-forward architecture that network topology affects the overall rate of a process in a quantitatively predictable manner. These fundamental results can be used as a basis for simulating larger networks as combinations of smaller network modules with implications on studying synthetic gene circuits, small regulatory systems, and eventually dynamic whole-cell models. PMID:18304325

Using algebra for massively parallel processor design and utilization

NASA Technical Reports Server (NTRS)

Campbell, Lowell; Fellows, Michael R.

1990-01-01

This paper summarizes the author's advances in the design of dense processor networks. Within is reported a collection of recent constructions of dense symmetric networks that provide the largest know values for the number of nodes that can be placed in a network of a given degree and diameter. The constructions are in the range of current potential engineering significance and are based on groups of automorphisms of finite-dimensional vector spaces.

Lambda network having 2.sup.m-1 nodes in each of m stages with each node coupled to four other nodes for bidirectional routing of data packets between nodes

DOEpatents

Napolitano, Jr., Leonard M.

1995-01-01

The Lambda network is a single stage, packet-switched interprocessor communication network for a distributed memory, parallel processor computer. Its design arises from the desired network characteristics of minimizing mean and maximum packet transfer time, local routing, expandability, deadlock avoidance, and fault tolerance. The network is based on fixed degree nodes and has mean and maximum packet transfer distances where n is the number of processors. The routing method is detailed, as are methods for expandability, deadlock avoidance, and fault tolerance.

Effective contaminant detection networks in uncertain groundwater flow fields.

PubMed

Hudak, P F

2001-01-01

A mass transport simulation model tested seven contaminant detection-monitoring networks under a 40 degrees range of groundwater flow directions. Each monitoring network contained five wells located 40 m from a rectangular landfill. The 40-m distance (lag) was measured in different directions, depending upon the strategy used to design a particular monitoring network. Lagging the wells parallel to the central flow path was more effective than alternative design strategies. Other strategies allowed higher percentages of leaks to migrate between monitoring wells. Results of this study suggest that centrally lagged groundwater monitoring networks perform most effectively in uncertain groundwater-flow fields.

Optical-Correlator Neural Network Based On Neocognitron

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Stoner, William W.

1994-01-01

Multichannel optical correlator implements shift-invariant, high-discrimination pattern-recognizing neural network based on paradigm of neocognitron. Selected as basic building block of this neural network because invariance under shifts is inherent advantage of Fourier optics included in optical correlators in general. Neocognitron is conceptual electronic neural-network model for recognition of visual patterns. Multilayer processing achieved by iteratively feeding back output of feature correlator to input spatial light modulator and updating Fourier filters. Neural network trained by use of characteristic features extracted from target images. Multichannel implementation enables parallel processing of large number of selected features.

Compiler and Runtime Support for Programming in Adaptive Parallel Environments

DTIC Science & Technology

1998-10-15

noother job is waiting for resources, and use a smaller number of processors when other jobs needresources. Setia et al. [15, 20] have shown that such...15] Vijay K. Naik, Sanjeev Setia , and Mark Squillante. Performance analysis of job scheduling policiesin parallel supercomputing environments. In...on networks ofheterogeneous workstations. Technical Report CSE-94-012, Oregon Graduate Institute of Scienceand Technology, 1994.[20] Sanjeev Setia

Vision-Based Navigation and Parallel Computing

DTIC Science & Technology

1990-08-01

33 5.8. Behizad Kamgar-Parsi and Behrooz Karngar-Parsi,"On Problem 5- lving with Hopfield Neural Networks", CAR-TR-462, CS-TR...Second. the hypercube connections support logarithmic implementations of fundamental parallel algorithms. such as grid permutations and scan...the pose space. It also uses a set of virtual processors to represent an orthogonal projection grid , and projections of the six dimensional pose space

Automatic Adaptation of Tunable Distributed Applications

DTIC Science & Technology

2001-01-01

size, weight, and battery life, with a single CPU, less memory, smaller hard disk, and lower bandwidth network connectivity. The power of PDAs is...wireless, and bluetooth [32] facilities; thus achieving different rates of data transmission. 1 With the trend of “write once, run everywhere...applications, a single component can execute on multiple processors (or machines) in parallel. These parallel applications, written in a specialized language

Perception of straightness and parallelism with minimal distance information.

PubMed

Rogers, Brian; Naumenko, Olga

2016-07-01

The ability of human observers to judge the straightness and parallelism of extended lines has been a neglected topic of study since von Helmholtz's initial observations 150 years ago. He showed that there were significant misperceptions of the straightness of extended lines seen in the peripheral visual field. The present study focused on the perception of extended lines (spanning 90° visual angle) that were directly fixated in the visual environment of a planetarium where there was only minimal information about the distance to the lines. Observers were asked to vary the curvature of 1 or more lines until they appeared to be straight and/or parallel, ignoring any perceived curvature in depth. When the horizon between the ground and the sky was visible, the results showed that observers' judgements of the straightness of a single line were significantly biased away from the veridical, great circle locations, and towards equal elevation settings. Similar biases can be seen in the jet trails of aircraft flying across the sky and in Rogers and Anstis's new moon illusion (Perception, 42(Abstract supplement) 18, 2013, 2016). The biasing effect of the horizon was much smaller when observers were asked to judge the straightness and parallelism of 2 or more extended lines. We interpret the results as showing that, in the absence of adequate distance information, observers tend to perceive the projected lines as lying on an approximately equidistant, hemispherical surface and that their judgements of straightness and parallelism are based on the perceived separation of the lines superimposed on that surface.

Parallel pumping for magnon spintronics: Amplification and manipulation of magnon spin currents on the micron-scale

NASA Astrophysics Data System (ADS)

Brächer, T.; Pirro, P.; Hillebrands, B.

2017-06-01

Magnonics and magnon spintronics aim at the utilization of spin waves and magnons, their quanta, for the construction of wave-based logic networks via the generation of pure all-magnon spin currents and their interfacing with electric charge transport. The promise of efficient parallel data processing and low power consumption renders this field one of the most promising research areas in spintronics. In this context, the process of parallel parametric amplification, i.e., the conversion of microwave photons into magnons at one half of the microwave frequency, has proven to be a versatile tool to excite and to manipulate spin waves. Its beneficial and unique properties such as frequency and mode-selectivity, the possibility to excite spin waves in a wide wavevector range and the creation of phase-correlated wave pairs, have enabled the achievement of important milestones like the magnon Bose-Einstein condensation and the cloning and trapping of spin-wave packets. Parallel parametric amplification, which allows for the selective amplification of magnons while conserving their phase is, thus, one of the key methods of spin-wave generation and amplification. The application of parallel parametric amplification to CMOS-compatible micro- and nano-structures is an important step towards the realization of magnonic networks. This is motivated not only by the fact that amplifiers are an important tool for the construction of any extended logic network but also by the unique properties of parallel parametric amplification. In particular, the creation of phase-correlated wave pairs allows for rewarding alternative logic operations such as a phase-dependent amplification of the incident waves. Recently, the successful application of parallel parametric amplification to metallic microstructures has been reported which constitutes an important milestone for the application of magnonics in practical devices. It has been demonstrated that parametric amplification provides an excellent tool to generate and to amplify spin waves in these systems in a wide wavevector range. In particular, the amplification greatly benefits from the discreteness of the spin-wave spectra since the size of the microstructures is comparable to the spin-wave wavelength. This opens up new, interesting routes of spin-wave amplification and manipulation. In this review, we will give an overview over the recent developments and achievements in this field.

Suppressing epidemics on networks by exploiting observer nodes.

PubMed

Takaguchi, Taro; Hasegawa, Takehisa; Yoshida, Yuichi

2014-07-01

To control infection spreading on networks, we investigate the effect of observer nodes that recognize infection in a neighboring node and make the rest of the neighbor nodes immune. We numerically show that random placement of observer nodes works better on networks with clustering than on locally treelike networks, implying that our model is promising for realistic social networks. The efficiency of several heuristic schemes for observer placement is also examined for synthetic and empirical networks. In parallel with numerical simulations of epidemic dynamics, we also show that the effect of observer placement can be assessed by the size of the largest connected component of networks remaining after removing observer nodes and links between their neighboring nodes.

Suppressing epidemics on networks by exploiting observer nodes

NASA Astrophysics Data System (ADS)

Takaguchi, Taro; Hasegawa, Takehisa; Yoshida, Yuichi

2014-07-01

To control infection spreading on networks, we investigate the effect of observer nodes that recognize infection in a neighboring node and make the rest of the neighbor nodes immune. We numerically show that random placement of observer nodes works better on networks with clustering than on locally treelike networks, implying that our model is promising for realistic social networks. The efficiency of several heuristic schemes for observer placement is also examined for synthetic and empirical networks. In parallel with numerical simulations of epidemic dynamics, we also show that the effect of observer placement can be assessed by the size of the largest connected component of networks remaining after removing observer nodes and links between their neighboring nodes.

fastBMA: scalable network inference and transitive reduction.

PubMed

Hung, Ling-Hong; Shi, Kaiyuan; Wu, Migao; Young, William Chad; Raftery, Adrian E; Yeung, Ka Yee

2017-10-01

Inferring genetic networks from genome-wide expression data is extremely demanding computationally. We have developed fastBMA, a distributed, parallel, and scalable implementation of Bayesian model averaging (BMA) for this purpose. fastBMA also includes a computationally efficient module for eliminating redundant indirect edges in the network by mapping the transitive reduction to an easily solved shortest-path problem. We evaluated the performance of fastBMA on synthetic data and experimental genome-wide time series yeast and human datasets. When using a single CPU core, fastBMA is up to 100 times faster than the next fastest method, LASSO, with increased accuracy. It is a memory-efficient, parallel, and distributed application that scales to human genome-wide expression data. A 10 000-gene regulation network can be obtained in a matter of hours using a 32-core cloud cluster (2 nodes of 16 cores). fastBMA is a significant improvement over its predecessor ScanBMA. It is more accurate and orders of magnitude faster than other fast network inference methods such as the 1 based on LASSO. The improved scalability allows it to calculate networks from genome scale data in a reasonable time frame. The transitive reduction method can improve accuracy in denser networks. fastBMA is available as code (M.I.T. license) from GitHub (https://github.com/lhhunghimself/fastBMA), as part of the updated networkBMA Bioconductor package (https://www.bioconductor.org/packages/release/bioc/html/networkBMA.html) and as ready-to-deploy Docker images (https://hub.docker.com/r/biodepot/fastbma/). © The Authors 2017. Published by Oxford University Press.

Mechanisms mediating parallel action monitoring in fronto-striatal circuits.

PubMed

Beste, Christian; Ness, Vanessa; Lukas, Carsten; Hoffmann, Rainer; Stüwe, Sven; Falkenstein, Michael; Saft, Carsten

2012-08-01

Flexible response adaptation and the control of conflicting information play a pivotal role in daily life. Yet, little is known about the neuronal mechanisms mediating parallel control of these processes. We examined these mechanisms using a multi-methodological approach that integrated data from event-related potentials (ERPs) with structural MRI data and source localisation using sLORETA. Moreover, we calculated evoked wavelet oscillations. We applied this multi-methodological approach in healthy subjects and patients in a prodromal phase of a major basal ganglia disorder (i.e., Huntington's disease), to directly focus on fronto-striatal networks. Behavioural data indicated, especially the parallel execution of conflict monitoring and flexible response adaptation was modulated across the examined cohorts. When both processes do not co-incide a high integrity of fronto-striatal loops seems to be dispensable. The neurophysiological data suggests that conflict monitoring (reflected by the N2 ERP) and working memory processes (reflected by the P3 ERP) differentially contribute to this pattern of results. Flexible response adaptation under the constraint of high conflict processing affected the N2 and P3 ERP, as well as their delta frequency band oscillations. Yet, modulatory effects were strongest for the N2 ERP and evoked wavelet oscillations in this time range. The N2 ERPs were localized in the anterior cingulate cortex (BA32, BA24). Modulations of the P3 ERP were localized in parietal areas (BA7). In addition, MRI-determined caudate head volume predicted modulations in conflict monitoring, but not working memory processes. The results show how parallel conflict monitoring and flexible adaptation of action is mediated via fronto-striatal networks. While both, response monitoring and working memory processes seem to play a role, especially response selection processes and ACC-basal ganglia networks seem to be the driving force in mediating parallel conflict monitoring and flexible adaptation of actions. Copyright © 2012 Elsevier Inc. All rights reserved.

GSHR-Tree: a spatial index tree based on dynamic spatial slot and hash table in grid environments

NASA Astrophysics Data System (ADS)

Chen, Zhanlong; Wu, Xin-cai; Wu, Liang

2008-12-01

Computation Grids enable the coordinated sharing of large-scale distributed heterogeneous computing resources that can be used to solve computationally intensive problems in science, engineering, and commerce. Grid spatial applications are made possible by high-speed networks and a new generation of Grid middleware that resides between networks and traditional GIS applications. The integration of the multi-sources and heterogeneous spatial information and the management of the distributed spatial resources and the sharing and cooperative of the spatial data and Grid services are the key problems to resolve in the development of the Grid GIS. The performance of the spatial index mechanism is the key technology of the Grid GIS and spatial database affects the holistic performance of the GIS in Grid Environments. In order to improve the efficiency of parallel processing of a spatial mass data under the distributed parallel computing grid environment, this paper presents a new grid slot hash parallel spatial index GSHR-Tree structure established in the parallel spatial indexing mechanism. Based on the hash table and dynamic spatial slot, this paper has improved the structure of the classical parallel R tree index. The GSHR-Tree index makes full use of the good qualities of R-Tree and hash data structure. This paper has constructed a new parallel spatial index that can meet the needs of parallel grid computing about the magnanimous spatial data in the distributed network. This arithmetic splits space in to multi-slots by multiplying and reverting and maps these slots to sites in distributed and parallel system. Each sites constructs the spatial objects in its spatial slot into an R tree. On the basis of this tree structure, the index data was distributed among multiple nodes in the grid networks by using large node R-tree method. The unbalance during process can be quickly adjusted by means of a dynamical adjusting algorithm. This tree structure has considered the distributed operation, reduplication operation transfer operation of spatial index in the grid environment. The design of GSHR-Tree has ensured the performance of the load balance in the parallel computation. This tree structure is fit for the parallel process of the spatial information in the distributed network environments. Instead of spatial object's recursive comparison where original R tree has been used, the algorithm builds the spatial index by applying binary code operation in which computer runs more efficiently, and extended dynamic hash code for bit comparison. In GSHR-Tree, a new server is assigned to the network whenever a split of a full node is required. We describe a more flexible allocation protocol which copes with a temporary shortage of storage resources. It uses a distributed balanced binary spatial tree that scales with insertions to potentially any number of storage servers through splits of the overloaded ones. The application manipulates the GSHR-Tree structure from a node in the grid environment. The node addresses the tree through its image that the splits can make outdated. This may generate addressing errors, solved by the forwarding among the servers. In this paper, a spatial index data distribution algorithm that limits the number of servers has been proposed. We improve the storage utilization at the cost of additional messages. The structure of GSHR-Tree is believed that the scheme of this grid spatial index should fit the needs of new applications using endlessly larger sets of spatial data. Our proposal constitutes a flexible storage allocation method for a distributed spatial index. The insertion policy can be tuned dynamically to cope with periods of storage shortage. In such cases storage balancing should be favored for better space utilization, at the price of extra message exchanges between servers. This structure makes a compromise in the updating of the duplicated index and the transformation of the spatial index data. Meeting the needs of the grid computing, GSHRTree has a flexible structure in order to satisfy new needs in the future. The GSHR-Tree provides the R-tree capabilities for large spatial datasets stored over interconnected servers. The analysis, including the experiments, confirmed the efficiency of our design choices. The scheme should fit the needs of new applications of spatial data, using endlessly larger datasets. Using the system response time of the parallel processing of spatial scope query algorithm as the performance evaluation factor, According to the result of the simulated the experiments, GSHR-Tree is performed to prove the reasonable design and the high performance of the indexing structure that the paper presented.

Almucantar radio telescope report 1: A preliminary study of the capabilities of large partially steerable paraboloidal antennas

NASA Technical Reports Server (NTRS)

Usher, P. D.

1971-01-01

The almucantar radio telescope development and characteristics are presented. The radio telescope consists of a paraboloidal reflector free to rotate in azimuth but limited in altitude between two fixed angles from the zenith. The fixed angles are designed to provide the capability where sources lying between two small circles parallel with the horizon (almucantars) are accessible at any one instant. Basic geometrical considerations in the almucantar design are presented. The capabilities of the almucantar telescope for source counting and for monitoring which are essential to a resolution of the cosmological problem are described.

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

Akatsu, T.; Bourdelle, K.K.; Richtarch, C.

Extended defects formed after hydrogen implantation into Si and Ge (100) substrates and subsequent thermal anneals were investigated by transmission electron microscopy. The majority of the extended defects formed in both materials were platelet-like structures lying on {l_brace}100{r_brace} and {l_brace}111{r_brace} planes. We found {l_brace}100{r_brace} platelets not only parallel but also perpendicular to the surface. In Ge wafers, high density of {l_brace}311{r_brace} defects and nanobubbles with the average size of 2 nm were observed. The difference between two materials can be attributed to the weaker strength of Ge-H bond.

Sinai peninsula taken by the STS-112 crew

NASA Image and Video Library

2002-10-08

STS112-702-002 (7-18 October 2002) --- Egypt's triangular Sinai Peninsula lies in the center of this view, photographed from the Space Shuttle Atlantis, with the dark greens of the Nile delta lower right. In this southwesterly view, the Red Sea, with its characteristic parallel coastlines, stretches toward the top. At the bottom of the image, the Suez Canal appears as an irregular line joining the Red Sea to the Mediterranean Sea (lower left). The Dead Sea in central Israel, with its light blue salt ponds at the south end, appears on the left margin.

N,N′-Bis(3,5-dichloro­benzyl­idene)­ethane-1,2-diamine

PubMed Central

Fun, Hoong-Kun; Kia, Reza

2008-01-01

The mol­ecule of the title Schiff base compound, C16H12Cl4N2, lies across an inversion centre and adopts an E configuration with respect to the azomethine C=N bond. The imine groups are coplanar with the aromatic rings. Within the mol­ecule, the planar units are parallel but extend in opposite directions from the dimethyl­ene bridge. In the crystal structure, mol­ecules are linked together by inter­molecular C—H⋯Cl hydrogen bonds along the a axis. PMID:21580993

Alignment of x-ray tube focal spots for spectral measurement.

PubMed

Nishizawa, K; Maekoshi, H; Kamiya, Y; Kobayashi, Y; Ohara, K; Sakuma, S

1982-01-01

A general method to align a diagnostic x-ray machine for x-ray spectrum measurement purpose was theoretically and experimentally investigated by means of the optical alignment of focal pinhole images. Focal pinhole images were obtained by using a multi-pinholed lead plate. the vertical plane, including the central axis and tube axis, was decided upon by observing the symmetry of focal images. the central axis was designated as a line through the center of focus parallel to the target surface lying in the vertical plane. A method to determine the manipulation of the central axis in any direction is presented.