A queueing model for predicting message latency in uni-directional <Emphasis Type="Italic">k</Emphasis>-ary <Emphasis Type="Italic">n</Emphasis>-cubes with deterministic routing and non-uniform traffic

The interconnection network is one of the key architectural components in any parallel computer. The distribution of the traffic injected into the network is among the factors that greatly influences network performance. The uniform traffic pattern has been adopted in many existing network performance evaluation studies due to the tractability of the resulting analytical modelling approach. However, many real applications exhibit non-uniform traffic patterns such as hot-spot traffic. K-ary n-cubes have been the mostly widely used in the implementation of practical parallel systems. Extensive research studies have been conducted on the performance modelling and evaluation of these networks. Nonetheless, most of these studies have been confined to uniform traffic distributions and have been based on software simulation. The present paper proposes a new stochastic model to predict message latency in k-ary n-cubes with deterministic routing in the presence of hot-spot traffic. The model has been validated through simulation experiments and has shown a close agreement with simulation results.

Meta-communications in component-based communication frameworks for grids

Applications are faced with several network-related problems on current grids: heterogeneous networks, firewalls, NAT, private IP addresses, non-routed networks, performance problems on WAN. Moreover, the requirements concerning communications are varied and the acceptable tradeoffs highly depends on the applications. A solution to reach the flexibility regarding communication on grids is the use of a component-based communication framework. The users then compose their own protocol stacks by assembling building blocks in the way they want. However, a truly flexible and dynamic component-based communication framework needs a meta-communication channel for its out-of-band communications required by dynamic component assembly in a consistent way on multiple nodes. The meta-communication channel is useful for some “brokered” communication methods, too, and in particular those designed to cross firewalls. The meta-communication channel has often been the “weakest link” of component-based communication frameworks: bottleneck for the performance, back-door from the security point of view, and limited connectivity. In this article, we present an architecture for a meta-communication channel that suffers from none of the aforementioned limitations. It exhibits good properties regarding connectivity, security and performance. Thus, the gain in flexibility brought by software components may be fully exploited without trading anything against flexibility.

Efficient shared memory and RDMA based collectives on multi-rail QsNetII SMP clusters

Clusters of Symmetric Multiprocessors (SMP) are more commonplace than ever in achieving high-performance. Scientific applications running on clusters employ collective communications extensively. Shared memory communication and Remote Direct Memory Access (RDMA) over multi-rail networks are promising approaches in addressing the increasing demand on intra-node and inter-node communications, and thereby in boosting the performance of collectives in emerging multi-core SMP clusters. In this regard, this paper designs and evaluates two classes of collective communication algorithms directly at the Elan user-level over multi-rail Quadrics QsNet^II with message striping: 1) RDMA-based traditional multi-port algorithms for gather, all-gather, and all-to-all collectives for medium to large messages, and 2) RDMA-based and SMP-aware multi-port all-gather algorithms for small to medium size messages. The multi-port RDMA-based Direct algorithm for gather and all-to-all collectives gain an improvement of up to 2.15 for 4 KB messages over elan_gather(), and up to 2.26 for 2 KB messages over elan_alltoall(), respectively. For the all-gather, our SMP-aware Bruck algorithm outperforms all other all-gather algorithms including elan_gather() for 512 B to 8 KB messages, with a 1.96 improvement factor for 4 KB messages. Our multi-port Direct all-gather is the best algorithm for 16 KB to 1 MB, and outperforms elan_gather() by a factor of 1.49 for 32 KB messages. Experimentation with real applications has shown up to 1.47 communication speedup can be achieved using the proposed all-gather algorithms.

The design and implementation of MPI collective operations for clusters in long-and-fast networks

Several MPI systems for Grid environment, in which clusters are connected by wide-area networks, have been proposed. However, the algorithms of collective communication in such MPI systems assume relatively low bandwidth wide-area networks, and they are not designed for the fast wide-area networks that are becoming available. On the other hand, for cluster MPI systems, a bcast algorithm by van de Geijn, et al. and an allreduce algorithm by Rabenseifner have been proposed, which are efficient in a high bi-section bandwidth environment. We modify those algorithms so as to effectively utilize fast wide-area inter-cluster networks and to control the number of nodes which can transfer data simultaneously through wide-area networks to avoid congestion. We confirmed the effectiveness of the modified algorithms by experiments using a 10 Gbps emulated WAN environment. The environment consists of two clusters, where each cluster consists of nodes with 1 Gbps Ethernet links and a switch with a 10 Gbps upper link. The two clusters are connected through a 10 Gbps WAN emulator which can insert latency. In a 10 millisecond latency environment, when the message size is 32 MB, the proposed bcast and allreduce are 1.6 and 3.2 times faster, respectively, than the algorithms used in existing MPI systems for Grid environment.

Dispersed information diffusion with level and schema-based coordination in mobile peer to peer networks

Several open ended issues for high resource availability in mobile peer to peer networks have been examined in the recent past. Different approaches were conducted for supporting information distribution and availability, through guided or unguided packet diffusion. The majority of the recently proposed approaches try to benefit from the spatial characteristics of the dynamically varying topologies. In this work a directed information diffusion scheme is examined using a level and schema-based coordination, applied in mobile peer to peer networks. The prioritization degree of any requested advert is modeled and enables directed prioritized diffusions to end mobile users that are traversing a certain geographic region (location based advertisements). The proposed method is robust in disseminating redundant messages to users while maintaining connectivity through Gradual Energy Tree-based (GET) configuration. Simulation is performed for the examination and performance evaluation of the proposed scheme, taking into account the modeled prioritization as well as the diffusion accuracy by using the Hierarchical and Non-hierarchical GET configuration.

Modeling brain dynamics using computational neurogenetic approach

The paper introduces a novel computational approach to brain dynamics modeling that integrates dynamic gene–protein regulatory networks with a neural network model. Interaction of genes and proteins in neurons affects the dynamics of the whole neural network. Through tuning the gene–protein interaction network and the initial gene/protein expression values, different states of the neural network dynamics can be achieved. A generic computational neurogenetic model is introduced that implements this approach. It is illustrated by means of a simple neurogenetic model of a spiking neural network of the generation of local field potential. Our approach allows for investigation of how deleted or mutated genes can alter the dynamics of a model neural network. We conclude with the proposal how to extend this approach to model cognitive neurodynamics.

One oxidant,many pathways: a theoretical perspective of monooxygenation mechanisms by cytochrome P450 enzymes

Density functional theoretical studies of monooxygenation reactivity of the high-valent oxoiron(IV) porphyrin cation-radical compound of cytochrome P450, the so-called Compound I, and of its precursor, the ferric(III)-hydroperoxide species, are described. The degeneracy of the spin states of Compound I, its electron deficiency, and dense orbital manifold lead to two-state and multi-state reactivity scenarios and may thereby create reactivity patterns as though belonging to two or more different oxidants. Most of the controversies in the experimental data are reconciled using Compound I as the sole competent oxidant. Theory finds ferric(III)-hydroperoxide to be a very sluggish oxidant, noncompetitive with Compound I. If and when Compound I is absent, P450 oxidation will logically proceed by another form, but this has to be more reactive than ferric(III)-hydroperoxide. Theoretical studies are conducted to pinpoint such an oxidant for P450.

The connectionist framework for gene regulation

I show that gene regulation networks are qualitatively consistent and therefore sufficiently similar to linearly seperable connectionist networks to warrant that the connectionist framework be applied to gene regulation. On this view, natural selection designs gene regulation networks to overcome the difficulty of development. I offer some general lessons about their evolvability that can be learned by examining the generic features of connectionist networks.

A mobile agent model for fault-tolerant manipulation on distributed objects

In this paper, we discuss how to realize fault-tolerant applications on distributed objects. Servers supporting objects can be fault-tolerant by taking advantage of replication and checkpointing technologies. However, there is no discussion on how application programs being performed on clients are tolerant of clients faults. For example, servers might block in the two-phase commitment protocol due to the client fault. We newly discuss how to make application programs fault-tolerant by taking advantage of mobile agent technologies where a program can move from a computer to another computer in networks. An application program to be performed on a faulty computer can be performed on another operational computer by moving the program in the mobile agent model. In this paper, we discuss a transactional agent model where a reliable and efficient application for manipulating objects in multiple computers is realized in the mobile agent model. In the transactional agent model, only a small part of the application program named routing subagent moves around computers. A routing subagent autonomously finds a computer which to visit next. We discuss a hierarchical navigation map which computer should be visited price to another computer in a transactional agent. A routing subagent makes a decision on which computer visit for the hierarchical navigation map. Programs manipulating objects in a computer are loaded to the computer on arrival of the routing subagent in order to reduce the communication overhead. This part of the transactional agent is a manipulating subagent. The manipulation subagent still exists on the computer even after the routing subagent leaves the computer in order to hold objects until the commitment. We assume every computer may stop by fault while networks are reliable. There are kinds of faulty computers for a transactional agent; current, destination, and sibling computers where a transactional agent now exists, will move, and has visited, respectively. The types of faults are detected by neighbouring manipulation subagents by communicating with each other. If some of the manipulation subagents are faulty, the routing subagent has to be aborted. However, the routing subagent is still moving. We discuss how to efficiently deliver the abort message to the moving routing subagent. We evaluate the transactional agent model in terms of how long it takes to abort the routing subagent if some computer is faulty.

The Contribution of Mere Recognition to the P300 Effect in a Concealed Information Test

In two experiments, we investigated the role of mere recognition in a P300 based CIT. Mere recognition was isolated by having participants respond based on an irrelevant dimension of the stimuli. In Experiment 1 stimuli consisted of familiar and unfamiliar faces, with a dot placed on the left or the right cheeck. Participants responded according to dot location. In the second experiment, participants were presented with autobiographical information, alternated with irrelevant stimuli, while instructed to respond based on the case of the stimuli. Results showed that with both familiar faces, and autobiographical information, mere recognition was sufficient to elicit a P300.

Consistency principle in biological dynamical systems

We propose a principle of consistency between different hierarchical levels of biological systems. Given a consistency between molecule replication and cell reproduction, universal statistical laws on cellular chemical abundances are derived and confirmed experimentally. They include a power law distribution of gene expressions, a lognormal distribution of cellular chemical abundances over cells, and embedding of the power law into the network connectivity distribution. Second, given a consistency between genotype and phenotype, a general relationship between phenotype fluctuations by genetic variation and isogenic phenotypic fluctuation by developmental noise is derived. Third, we discuss the chaos mechanism for stem cell differentiation with autonomous regulation, resulting from a consistency between cell reproduction and growth of the cell ensemble.

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Spike-time reliability of layered neural oscillator networks

We study the reliability of layered networks of coupled “type I” neural oscillators in response to fluctuating input signals. Reliability means that a signal elicits essentially identical responses upon repeated presentations, regardless of the network’s initial condition. We study reliability on two distinct scales: neuronal reliability, which concerns the repeatability of spike times of individual neurons embedded within a network, and pooled-response reliability, which concerns the repeatability of total synaptic outputs from a subpopulation of the neurons in a network. We find that neuronal reliability depends strongly both on the overall architecture of a network, such as whether it is arranged into one or two layers, and on the strengths of the synaptic connections. Specifically, for the type of single-neuron dynamics and coupling considered, single-layer networks are found to be very reliable, while two-layer networks lose their reliability with the introduction of even a small amount of feedback. As expected, pooled responses for large enough populations become more reliable, even when individual neurons are not. We also study the effects of noise on reliability, and find that noise that affects all neurons similarly has much greater impact on reliability than noise that affects each neuron differently. Qualitative explanations are proposed for the phenomena observed.

Synchronization properties of networks of electrically coupled neurons in the presence of noise and heterogeneities

We investigate how synchrony can be generated or induced in networks of electrically coupled integrate-and-fire neurons subject to noisy and heterogeneous inputs. Using analytical tools, we find that in a network under constant external inputs, synchrony can appear via a Hopf bifurcation from the asynchronous state to an oscillatory state. In a homogeneous net work, in the oscillatory state all neurons fire in synchrony, while in a heterogeneous network synchrony is looser, many neurons skipping cycles of the oscillation. If the transmission of action potentials via the electrical synapses is effectively excitatory, the Hopf bifurcation is supercritical, while effectively inhibitory transmission due to pronounced hyperpolarization leads to a subcritical bifurcation. In the latter case, the network exhibits bistability between an asynchronous state and an oscillatory state where all the neurons fire in synchrony. Finally we show that for time-varying external inputs, electrical coupling enhances the synchronization in an asynchronous network via a resonance at the firing-rate frequency.

XenLoop: a transparent high performance inter-VM network loopback

Advances in virtualization technology have focused mainly on strengthening the isolation barrier between virtual machines (VMs) that are co-resident within a single physical machine. At the same time, a large category of communication intensive distributed applications and software components exist, such as web services, high performance grid applications, transaction processing, and graphics rendering, that often wish to communicate across this isolation barrier with other endpoints on co-resident VMs. State of the art inter-VM communication mechanisms do not adequately address the requirements of such applications. TCP/UDP based network communication tends to perform poorly when used between co-resident VMs, but has the advantage of being transparent to user applications. Other solutions exploit inter-domain shared memory mechanisms to improve communication latency and bandwidth, but require applications or user libraries to be rewritten against customized APIs—something not practical for a large majority of distributed applications. In this paper, we present the design and implementation of a fully transparent and high performance inter-VM network loopback channel, called XenLoop, in the Xen virtual machine environment. XenLoop does not sacrifice user-level transparency and yet achieves high communication performance between co-resident guest VMs. XenLoop intercepts outgoing network packets beneath the network layer and shepherds the packets destined to co-resident VMs through a high-speed inter-VM shared memory channel that bypasses the virtualized network interface. Guest VMs using XenLoop can migrate transparently across machines without disrupting ongoing network communications, and seamlessly switch between the standard network path and the XenLoop channel. In our evaluation using a number of unmodified benchmarks, we observe that XenLoop can reduce the inter-VM round trip latency by up to a factor of 5 and increase bandwidth by a up to a factor of 6.

Spatial variation of airborne pollen over south-east France: characterization and implications for monitoring networks management

The French airborne pollen monitoring network (RNSA) is currently regrouping 70 Hirst-type pollen traps covering the whole French territory. The aim of this paper is to introduce a simple statistical methodology that can be used to characterize pollen spatial variation. This pilot study is restricted to a limited portion of the RNSA network (18 monitoring stations), eight taxa of allergenic relevance, and a 3-year period (2003–2005). The first step of the approach consisted in quantifying the trap-to-trap pollen similarities on the basis of an original index, called mean Pollinic Distance (mPD), that relies on the comparison of pollen concentration time series. Regression analyses were next conducted with different spatial variables. Distance, latitude and altitude differences were identified as significant predictors of pollen variations, as measured by mPD. In order to further characterize pollen spatial properties, cluster analysis was performed with mPD as the distance estimate. Interestingly, the clusters of sites identified on the basis of the similarity of their pollen profiles, correspond to distinct geographic areas that might be interpreted as homogeneous air masses. The results have major implications for monitoring networks management since they provide an objective basis (1) for choosing the relevant scale to elaborate and supply pollen-related information, and (2) for optimizing networks configuration.

Hierarchical analysis of piecewise affine models of gene regulatory networks

A key point in the analysis of dynamical models of biological systems is to handle systems of relatively high dimensions. In the present paper we propose a method to hierarchically organize a certain type of piecewise affine (PWA) differential systems. This specific class of systems has been extensively studied for the past few years, as it provides a good framework to model gene regulatory networks. The method, shown on several examples, allows a qualitative analysis of the asymptotic behavior of a PWA system, decomposing it into several smaller subsystems. This technique, based on the well-known strongly connected components decomposition, is not new. However, its adaptation to the non-smooth PWA differential equations turns out to be quite relevant because of the strong discrete structure underlying these equations. Its biological relevance is shown on a 7-dimensional PWA system modeling the gene network responsible for the carbon starvation response in Escherichia coli.

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Causal networks in simulated neural systems

Neurons engage in causal interactions with one another and with the surrounding body and environment. Neural systems can therefore be analyzed in terms of causal networks, without assumptions about information processing, neural coding, and the like. Here, we review a series of studies analyzing causal networks in simulated neural systems using a combination of Granger causality analysis and graph theory. Analysis of a simple target-fixation model shows that causal networks provide intuitive representations of neural dynamics during behavior which can be validated by lesion experiments. Extension of the approach to a neurorobotic model of the hippocampus and surrounding areas identifies shifting causal pathways during learning of a spatial navigation task. Analysis of causal interactions at the population level in the model shows that behavioral learning is accompanied by selection of specific causal pathways—“causal cores”—from among large and variable repertoires of neuronal interactions. Finally, we argue that a causal network perspective may be useful for characterizing the complex neural dynamics underlying consciousness.

Analyzing the performance of optical multistage interconnection networks with limited crosstalk

Analytical modeling techniques can be used to study the performance of optical multistage interconnection network (OMIN) effectively. MINs have assumed importance in recent times, because of their cost-effectiveness. An N×N MIN consists of a mapping from N processors to N memories, with log ₂ N stages of 2×2 switches with N/2 switches per stage. The interest is on the study of the performance of unbuffered optical multistage interconnection network using the banyan network. The uniform reference model approach is assumed for the purpose of analysis. In this paper the analytical modeling approach is applied to an N×N OMIN with limited crosstalk (conflicts between messages) up to (log ₂ N−1). Messages with switch conflicts satisfying the constraint of (log ₂ N−1) are allowed to pass in the same group, but in case of a link conflict, the message is routed in a different group. The analysis is performed by calculating the bandwidth and throughput of the network operating under a load l and allowing random traffic and using a greedy routing strategy. A number of equations are derived using the theory of probability and the performance curves are plotted. The results obtained show that the performance of the network improves by allowing limited crosstalk in the network.