Parallel Exhaustive Search without Coordination

We analyze parallel algorithms in the context of exhaustive search over totally ordered sets. Imagine an infinite list of "boxes", with a "treasure" hidden in one of them, where the boxes' order reflects the importance of finding the treasure in a given box. At each time step, a search protocol executed by a searcher has the ability to peek into one box, and see whether the treasure is present or not. By equally dividing the workload between them, $k$ searchers can find the treasure $k$ times faster than one searcher. However, this straightforward strategy is very sensitive to failures (e.g., crashes of processors), and overcoming this issue seems to require a large amount of communication. We therefore address the question of designing parallel search algorithms maximizing their speed-up and maintaining high levels of robustness, while minimizing the amount of resources for coordination. Based on the observation that algorithms that avoid communication are inherently robust, we analyze the best running time performance of non-coordinating algorithms. Specifically, we devise non-coordinating algorithms that achieve a speed-up of $9/8$ for two searchers, a speed-up of $4/3$ for three searchers, and in general, a speed-up of $\frac{k}{4}(1+1/k)^2$ for any $k\geq 1$ searchers. Thus, asymptotically, the speed-up is only four times worse compared to the case of full-coordination, and our algorithms are surprisingly simple and hence applicable. Moreover, these bounds are tight in a strong sense as no non-coordinating search algorithm can achieve better speed-ups. Overall, we highlight that, in faulty contexts in which coordination between the searchers is technically difficult to implement, intrusive with respect to privacy, and/or costly in term of resources, it might well be worth giving up on coordination, and simply run our non-coordinating exhaustive search algorithms

Division of Labour and Social Coordination Modes : A simple simulation model

This paper presents a preliminary investigation of the relationship between the process of functional division of labour and the modes in which activities and plans are coordinated. We consider a very simple production process: a given heap of bank-notes has to be counted by a group of accountants. Because of limited individual capabilities and/or the possibilities of mistakes and external disturbances, the task has to be divided among several accountants and a hierarchical coordination problem arises. We can imagine several different ways of socially implementing coordination of devided tasks. 1) a central planner can compute the optimal architecture of the system; 2) a central planner can promote quantity adjustments by moving accountants from hierarchical levels where there exist idle resources to levels where resources are insufficient; 3) quasi-market mechanisms can use quantity or price signals for promoting decentralized adjustments. By means of a simple simulation model, based on Genetic Algorithms and Classifiers Systems, we can study the dynamic efficiency properties of each coordination mode and in particular their capability, speed and cost of adaptation to changing environmental situations (i.e. variations of the size of the task and/or variations of agents' capabilities). Such interesting issues as returns to scale, specialization and workers exploitation can be easily studied in the same model

Structure identification methods for atomistic simulations of crystalline materials

We discuss existing and new computational analysis techniques to classify local atomic arrangements in large-scale atomistic computer simulations of crystalline solids. This article includes a performance comparison of typical analysis algorithms such as Common Neighbor Analysis, Centrosymmetry Analysis, Bond Angle Analysis, Bond Order Analysis, and Voronoi Analysis. In addition we propose a simple extension to the Common Neighbor Analysis method that makes it suitable for multi-phase systems. Finally, we introduce a new structure identification algorithm, the Neighbor Distance Analysis, that is designed to identify atomic structure units in grain boundaries

Coordination and Antenna Domain Formation in Cloud-RAN systems

We study here the problem of Antenna Domain Formation (ADF) in cloud RAN systems, whereby multiple remote radio-heads (RRHs) are each to be assigned to a set of antenna domains (ADs), such that the total interference between the ADs is minimized. We formulate the corresponding optimization problem, by introducing the concept of \emph{interference coupling coefficients} among pairs of radio-heads. We then propose a low-overhead algorithm that allows the problem to be solved in a distributed fashion, among the aggregation nodes (ANs), and establish basic convergence results. Moreover, we also propose a simple relaxation to the problem, thus enabling us to characterize its maximum performance. We follow a layered coordination structure: after the ADs are formed, radio-heads are clustered to perform coordinated beamforming using the well known Weighted-MMSE algorithm. Finally, our simulations show that using the proposed ADF mechanism would significantly increase the sum-rate of the system (with respect to random assignment of radio-heads).Comment: 7 pages, IEEE International Conference on Communications 2016 (ICC 2016