Saber: window-based hybrid stream processing for heterogeneous architectures

Modern servers have become heterogeneous, often combining multicore CPUs with many-core GPGPUs. Such heterogeneous architectures have the potential to improve the performance of data-intensive stream processing applications, but they are not supported by current relational stream processing engines. For an engine to exploit a heterogeneous architecture, it must execute streaming SQL queries with sufficient data-parallelism to fully utilise all available heterogeneous processors, and decide how to use each in the most effective way. It must do this while respecting the semantics of streaming SQL queries, in particular with regard to window handling. We describe SABER, a hybrid high-performance relational stream processing engine for CPUs and GPGPUs. SABER executes windowbased streaming SQL queries in a data-parallel fashion using all available CPU and GPGPU cores. Instead of statically assigning query operators to heterogeneous processors, SABER employs a new adaptive heterogeneous lookahead scheduling strategy, which increases the share of queries executing on the processor that yields the highest performance. To hide data movement costs, SABER pipelines the transfer of stream data between different memory types and the CPU/GPGPU. Our experimental comparison against state-ofthe-art engines shows that SABER increases processing throughput while maintaining low latency for a wide range of streaming SQL queries with small and large windows sizes

Simulation of Consensus Model of Deffuant et al on a Barabasi-Albert Network

In the consensus model with bounded confidence, studied by Deffuant et al. (2000), two randomly selected people who differ not too much in their opinion both shift their opinions towards each other. Now we restrict this exchange of information to people connected by a scale-free network. As a result, the number of different final opinions (when no complete consensus is formed) is proportional to the number of people.Comment: 7 pages including 3 figs; Int.J.MOd.Phys.C 15, issue 2; programming error correcte

Universality of the Threshold for Complete Consensus for the Opinion Dynamics of Deffuant et al

In the compromise model of Deffuant et al., opinions are real numbers between 0 and 1 and two agents are compatible if the difference of their opinions is smaller than the confidence bound parameter \epsilon. The opinions of a randomly chosen pair of compatible agents get closer to each other. We provide strong numerical evidence that the threshold value of \epsilon above which all agents share the same opinion in the final configuration is 1/2, independently of the underlying social topology.Comment: 8 pages, 4 figures, to appear in Int. J. Mod. Phys. C 15, issue

Bridging Gaps Among Scientific Disciplines. Paper Presented on IIASA's 20th Anniversary

IIASA celebrated its twentieth anniversary on May 12-13 with its fourth general conference, IIASA '92: An International Conference on the Challenges to Systems Analysis in the Nineties and Beyond. The conference focused on the relations between environment and development and on studies that integrate the methods and findings of several disciplines. The role of systems analysis, a method especially suited to taking account of the linkages between phenomena and of the hierarchical organization of the natural and social world, was also assessed, taking account of the implications this has for IIASA's research approach and activities. This paper is one of six IIASA Collaborative Papers published as part of the report on the conference, an earlier instalment of which was Science and Sustainability, published in 1992. Professor Koptyug's paper is written from the viewpoint of a chemist, but of one who has an unusual consciousness of error in estimates of some of the vital parameters affecting the environment. He finds a variation of 100 percent between the low and high estimates of absorption of carbon dioxide by the oceans, and adding that to the similar variation in estimate of emissions and related quantities he ends up with a four-fold variation between the lowest and the highest rate of accumulation of carbon dioxide in the atmosphere. Yet the paper does not argue from this that we should do nothing until we know more. We know in what directions we have to move as we try for stability, and are learning something about directions we should not try. A lesson was learned in this latter sense from the building of a dam across a bay in the Caspian Sea in order to reduce evaporation. The story is that with the agricultural and industrial development along the Volga River the level of the Caspian Sea fell by three meters between 1933 and 1977. It was hoped that the darn separating off the Black Jaws Gulf would counteract the withdrawal of water from higher up. But there seems at the same time to have been a flow of water of unknown origin into the Caspian Sea. The Gulf dried out by evaporation, while the Caspian Sea rose a wholly unanticipated 13 centimeters per year. Such a rise was disastrous for people living along the coast, and the dam is now to be destroyed. For me the lesson is not that we should never do anything about the environment, hut rather that we should look very closely and be very sure of our knowledge base before we try smart tricks with the planet in the hope of neutralizing the effects of irresponsible industrialization. One such smart trick that was fortunately checked before it started to be built was the diversion southward of four major rivers that flow into the Arctic Ocean. No one has any way of estimating what unanticipated results might come from that, what uncontrollable positive feedback loops it might initiate. These are among the things I have learned from Professor Koptyug's paper

Exact decoherence to pointer states in free open quantum systems is universal

In this paper it is shown that exact decoherence to minimal uncertainty Gaussian pointer states is generic for free quantum particles coupled to a heat bath. More specifically, the paper is concerned with damped free particles linearly coupled under product initial conditions to a heat bath at arbitrary temperature, with arbitrary coupling strength and spectral densities covering the Ohmic, subohmic, and supraohmic regime. Then it is true that there exists a time t_c such that for times t>t_c the state can always be exactly represented as a mixture (convex combination) of particular minimal uncertainty Gaussian states, regardless of and independent from the initial state. This exact `localisation' is hence not a feature specific to high temperatures and weak damping limit, but is rather a generic property of damped free particles.Comment: 4 pages, 1 figur

Dynamics of Majority Rule

We introduce a 2-state opinion dynamics model where agents evolve by majority rule. In each update, a group of agents is specified whose members then all adopt the local majority state. In the mean-field limit, where a group consists of randomly-selected agents, consensus is reached in a time that scales ln N, where N is the number of agents. On finite-dimensional lattices, where a group is a contiguous cluster, the consensus time fluctuates strongly between realizations and grows as a dimension-dependent power of N. The upper critical dimension appears to be larger than 4. The final opinion always equals that of the initial majority except in one dimension.Comment: 4 pages, 3 figures, 2-column revtex4 format; annoying typo fixed in Eq.(1); a similar typo fixed in Eq.(6) and some references update

Non-equilibrium phase transition in negotiation dynamics

We introduce a model of negotiation dynamics whose aim is that of mimicking the mechanisms leading to opinion and convention formation in a population of individuals. The negotiation process, as opposed to ``herding-like'' or ``bounded confidence'' driven processes, is based on a microscopic dynamics where memory and feedback play a central role. Our model displays a non-equilibrium phase transition from an absorbing state in which all agents reach a consensus to an active stationary state characterized either by polarization or fragmentation in clusters of agents with different opinions. We show the exystence of at least two different universality classes, one for the case with two possible opinions and one for the case with an unlimited number of opinions. The phase transition is studied analytically and numerically for various topologies of the agents' interaction network. In both cases the universality classes do not seem to depend on the specific interaction topology, the only relevant feature being the total number of different opinions ever present in the system.Comment: 4 pages, 4 figure

Role of social environment and social clustering in spread of opinions in co-evolving networks

Taking a pragmatic approach to the processes involved in the phenomena of collective opinion formation, we investigate two specific modifications to the co-evolving network voter model of opinion formation, studied by Holme and Newman [1]. First, we replace the rewiring probability parameter by a distribution of probability of accepting or rejecting opinions between individuals, accounting for the asymmetric influences in relationships among individuals in a social group. Second, we modify the rewiring step by a path-length-based preference for rewiring that reinforces local clustering. We have investigated the influences of these modifications on the outcomes of the simulations of this model. We found that varying the shape of the distribution of probability of accepting or rejecting opinions can lead to the emergence of two qualitatively distinct final states, one having several isolated connected components each in internal consensus leading to the existence of diverse set of opinions and the other having one single dominant connected component with each node within it having the same opinion. Furthermore, and more importantly, we found that the initial clustering in network can also induce similar transitions. Our investigation also brings forward that these transitions are governed by a weak and complex dependence on system size. We found that the networks in the final states of the model have rich structural properties including the small world property for some parameter regimes. [1] P. Holme and M. Newman, Phys. Rev. E 74, 056108 (2006)

Volatility clustering and scaling for financial time series due to attractor bubbling

A microscopic model of financial markets is considered, consisting of many interacting agents (spins) with global coupling and discrete-time thermal bath dynamics, similar to random Ising systems. The interactions between agents change randomly in time. In the thermodynamic limit the obtained time series of price returns show chaotic bursts resulting from the emergence of attractor bubbling or on-off intermittency, resembling the empirical financial time series with volatility clustering. For a proper choice of the model parameters the probability distributions of returns exhibit power-law tails with scaling exponents close to the empirical ones.Comment: For related publications see http://www.helbing.or

Molecular Model of Dynamic Social Network Based on E-mail communication

In this work we consider an application of physically inspired sociodynamical model to the modelling of the evolution of email-based social network. Contrary to the standard approach of sociodynamics, which assumes expressing of system dynamics with heuristically defined simple rules, we postulate the inference of these rules from the real data and their application within a dynamic molecular model. We present how to embed the n-dimensional social space in Euclidean one. Then, inspired by the Lennard-Jones potential, we define a data-driven social potential function and apply the resultant force to a real e-mail communication network in a course of a molecular simulation, with network nodes taking on the role of interacting particles. We discuss all steps of the modelling process, from data preparation, through embedding and the molecular simulation itself, to transformation from the embedding space back to a graph structure. The conclusions, drawn from examining the resultant networks in stable, minimum-energy states, emphasize the role of the embedding process projecting the non–metric social graph into the Euclidean space, the significance of the unavoidable loss of information connected with this procedure and the resultant preservation of global rather than local properties of the initial network. We also argue applicability of our method to some classes of problems, while also signalling the areas which require further research in order to expand this applicability domain