On Neighborhood Tree Search

We consider the neighborhood tree induced by alternating the use of different neighborhood structures within a local search descent. We investigate the issue of designing a search strategy operating at the neighborhood tree level by exploring different paths of the tree in a heuristic way. We show that allowing the search to 'backtrack' to a previously visited solution and resuming the iterative variable neighborhood descent by 'pruning' the already explored neighborhood branches leads to the design of effective and efficient search heuristics. We describe this idea by discussing its basic design components within a generic algorithmic scheme and we propose some simple and intuitive strategies to guide the search when traversing the neighborhood tree. We conduct a thorough experimental analysis of this approach by considering two different problem domains, namely, the Total Weighted Tardiness Problem (SMTWTP), and the more sophisticated Location Routing Problem (LRP). We show that independently of the considered domain, the approach is highly competitive. In particular, we show that using different branching and backtracking strategies when exploring the neighborhood tree allows us to achieve different trade-offs in terms of solution quality and computing cost.Comment: Genetic and Evolutionary Computation Conference (GECCO'12) (2012

Local Maps: New Insights into Mobile Agent Algorithms

In this paper, we study the complexity of computing with mobile agents having small local knowledge. In particular, we show that the number of mobile agents and the amount of local information given initially to agents can significantly influence the time complexity of resolving a distributed problem. Our results are based on a generic scheme allowing to transform a message passing algorithm, running on an $n$-node graph $G$, into a mobile agent one. By generic, we mean that the scheme is independent of both the message passing algorithm and the graph $G$. Our scheme, coupled with a well-chosen clustered representation of the graph, induces $\widetilde{O}(1) ratio between the time complexity of the obtained mobile agent algorithm and the time complexity of the original message passing counterpart, while using$\widetilde{O}(n)$mobile agents. If only$k$agents are allowed ($k$is an integer parameter), then we show that the time ratio is$O(n/\sqrt{k})$. As a consequence, we show that any global labeling function of$G$can be computed by exactly$n$mobile agents knowing their$n^{\epsilon}$-neighborhood in$\widetilde{O}(D)$time,$D$is the diameter of the graph and$\epsilon$is an arbitrary small constant. We apply our generic results for the fundamental problem of computing a leader (resp. a BFS tree) under the additional restriction of$\widetilde{O}(1)$(resp.$\widetilde{O}(n)$) memory bits per agent, and obtain$\widetilde{O}(D)$ time algorithms

Parallel Branch-and-Bound in Multi-core Multi-CPU Multi-GPU Heterogeneous Environments

International audienceWe investigate the design of parallel B&B in large scale heterogeneous compute environments where processing units can be composed of a mixture of multiple shared memory cores, multiple distributed CPUs and multiple GPUs devices. We describe two approaches addressing the critical issue of how to map B&B workload with the different levels of parallelism exposed by the target compute platform. We also contribute a throughout large scale experimental study which allows us to derive a comprehensive and fair analysis of the proposed approaches under different system configurations using up to 16 GPUs and up to 512 CPU-cores. Our results shed more light on the main challenges one has to face when tackling B&B algorithms while describing efficient techniques to address them. In particular, we are able to obtain linear speed-ups at moderate scales where adaptive load balancing among the heterogeneous compute resources is shown to have a significant impact on performance. At the largest scales, intra-node parallelism and hybrid decentralized load balancing is shown to have a crucial importance in order to alleviate locking issues among shared memory threads and to scale the distributed resources while optimizing communication costs and minimizing idle time

A Note on Node Coloring in the SINR Model

A $\xi$-coloring of a graph $G$ is a coloring of the nodes of $G$ with $\xi$ colors in such a way any two neighboring nodes have different colors. We prove that there exists a $O(\Delta \log n)$ time distributed algorithm computing a $O(\Delta)$-colroing for unit disc graphs under the signal-to-interference-plus-noise ratio (SINR)-based physical model ($\Delta$ is the maximum degree of the graph). We also show that, for a well defined constant $d$, a $d$-hop $O(\Delta)$-coloring allows us to schedule an interference free MAC protocol under the physical SINR constraints. For instance this allows us to prove that any point-to-point message passing algorithm with running time $\tau$ can be simulated in the SINR model in $O(\Delta (\log n + \tau))$ time using messages of well chosen size. All our algorithms are proved to be correct with high probability

A Note on Node Coloring in the SINR Model

A $\xi$-coloring of a graph $G$ is a coloring of the nodes of $G$ with $\xi$ colors in such a way any two neighboring nodes have different colors. We prove that there exists a $O(\Delta \log n)$ time distributed algorithm computing a $O(\Delta)$-colroing for unit disc graphs under the signal-to-interference-plus-noise ratio (SINR)-based physical model ($\Delta$ is the maximum degree of the graph). We also show that, for a well defined constant $d$, a $d$-hop $O(\Delta)$-coloring allows us to schedule an interference free MAC protocol under the physical SINR constraints. For instance this allows us to prove that any point-to-point message passing algorithm with running time $\tau$ can be simulated in the SINR model in $O(\Delta (\log n + \tau))$ time using messages of well chosen size. All our algorithms are proved to be correct with high probability

Radio Network Distributed Algorithms in the Unknown Neighborhood Model

The paper deals with radio network distributed algorithms where nodes are not aware of their one hop neighborhood. Given an n-node graph modeling a multihop network of radio devices, we give a O(log^2 n) time distributed algorithm that computes w.h.p., a constant approximation value of the degree of each node. We also provide a O( \Delta log n + log^2 n) time distributed algorithm that computes w.h.p., a constant approximation value of the local maximum degree of each node, where the global maximum degree \Delta of the graph is not known. Using our algorithms as a plug-and-play procedure, we show that many existing distributed algorithms requiring the knowledge of to execute efficiently can be run with essentially the same time complexity by using the local maximum degree instead of . In other words, using the local maximum degree is sufficient to break the symmetry in a local and efficient manner. We illustrate this claim by investigating the complexity of some basic problems. First, we investigate the generic problem of simulating any classical message passing algorithm in the radio network model. Then, we study the fundamental edge/node coloring problem in the special case of unit disk graphs. The obtained results show that knowing the local maximum degree allows to coordinate the nodes locally and avoid interferences in radio networks

An infected false aneurysm of the subclavian artery in a 41-year old drug abuser

A 41-year-old man, with a history of intravenous drug abuse, presented with a mass in the right side of the neck. The mass had increased in size over a three-day period, producing local pain, hoarseness, shortness of breath, fever and pain of the right arm. Anamnesis told he performed internal jugular drug injection on a regular base. Physical examination revealed a pulsatile supraclavicular mass, with central necrotic lesions (A). Chest X-ray showed an opacity of the right hemithorax with left tracheal deviation (B). Additional computed tomographic angiography revealed a false aneurysm of the right subclavian artery, resulting in a filling defect of the axillary artery causing malperfusion (C). A midsternotomy with lateral extension was performed, which revealed an infected hematoma of a ruptured pseudo-aneurysm of the right subclavian artery. After ligation of the feeding vessels and debridement of the false aneurysm, an iatrogenic lesion of the branchio-cephalic trunk occurred, requiring interposition graft to the common carotid artery. Subsequently, a bypass graft from brachio-cephalic trunk to the humeral artery was performed (D). Postoperative course was complicated by an acute disseminated intravascular coagulation eventually leading to death An infected pseudoaneurysm of the subclavian artery as a consequence of intravenous drug use is extremely rare, with only 7 cases reported in the literature. It's a very grave entity, the risk of death is very important.Pan African Medical Journal 2015; 2

Adaptive Dynamic Load Balancing in Heterogenous Multiple GPUs-CPUs Distributed Setting: Case Study of B&B Tree Search

International audienceThe emergence of new hybrid and heterogenous multi-GPU multi-CPU large scale platforms offers new opportunities and pauses new challenges when solving difficult optimization problems. This paper targets irregular tree search algorithms in which workload is unpredictable. We propose an adaptive distributed approach allowing to distribute the load dynamically at runtime while taking into account the computing abilities of either GPUs or CPUs. Using Branch-and-Bound and Flowshop as a case study, we deployed our approach using up to 20 GPUs jointly to up to 128 CPUs. Through extensive experiments in different system configurations, we report near optimal speedups, thus providing new insights into how to take full advantage of both GPUs and CPUs power in modern computing platforms

Mobile Agents For Implementing Local Computations in Graphs

Mobile agents are a recent paradigm to facilitate the design and programming of distributed applications. However, whilst their popularity continues to grow, a uniform theory of mobile agent systems is not yet sufficiently elaborated, in comparison with classical models of distributed computation. In this paper we show how to use mobile agents as an alternative model for implementing distributed local computation rules. In doing so, we approach a general and unified framework for local computations which is consistent with the classical theory of distributed computations based on graph relabeling systems

Fourier Transform-based Surrogates for Permutation Problems

In the context of pseudo-Boolean optimization, surrogate functions based on the Walsh-Hadamard transform have been recently proposed with great success. It has been shown that lower-order components of the Walsh-Hadamard transform have usually a larger influence on the value of the objective function. Thus, creating a surrogate model using the lower-order components of the transform can provide a good approximation to the objective function. The Walsh-Hadamard transform in pseudo-Boolean optimization is a particularization in the binary representation of a Fourier transform over a finite group, precisely defined in the framework of group representation theory. Using this more general definition, it is possible to define a Fourier transform for the functions over permutations. We propose in this paper the use of surrogate functions based on the Fourier transforms over the permutation space. We check how similar the proposed surrogate models are to the original objective function and we also apply regression to learn a surrogate model based on the Fourier transform. The experimental setting includes two permutation problems for which the exact Fourier transform is unknown based on the problem parameters: the Asteroid Routing Problem and the Single Machine Total Weighted Tardiness.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Ministerio de Ciencia, Innovación y Universidades del Gobierno de España under grants PID 2020-116727RB-I00 and PRX21/00669, and by EU Horizon 2020 research and innovative program (grant 952215, TAILOR ICT-48 network). Thanks to the Supercomputing and Bioinnovation Center (SCBI) of Universidad de Málaga for their provision of computational resources and support