Hamiltonian cycles in faulty random geometric networks

In this paper we analyze the Hamiltonian properties of faulty random networks. This consideration is of interest when considering wireless broadcast networks. A random geometric network is a graph whose vertices correspond to points uniformly and independently distributed in the unit square, and whose edges connect any pair of vertices if their distance is below some specified bound. A faulty random geometric network is a random geometric network whose vertices or edges fail at random. Algorithms to find Hamiltonian cycles in faulty random geometric networks are presented.Postprint (published version

Combining spectral sequencing and parallel simulated annealing for the MinLA problem

In this paper we present and analyze new sequential and parallel heuristics to approximate the Minimum Linear Arrangement problem (MinLA). The heuristics consist in obtaining a first global solution using Spectral Sequencing and improving it locally through Simulated Annealing. In order to accelerate the annealing process, we present a special neighborhood distribution that tends to favor moves with high probability to be accepted. We show how to make use of this neighborhood to parallelize the Metropolis stage on distributed memory machines by mapping partitions of the input graph to processors and performing moves concurrently. The paper reports the results obtained with this new heuristic when applied to a set of large graphs, including graphs arising from finite elements methods and graphs arising from VLSI applications. Compared to other heuristics, the measurements obtained show that the new heuristic improves the solution quality, decreases the running time and offers an excellent speedup when ran on a commodity network made of nine personal computers.Postprint (published version

Under-the-cell routing to improve manufacturability

The progressive miniaturization of technology and the unequal scalability of the BEOL and FEOL layers aggravate the routing congestion problem and have a negative impact on manufacturability. Standard cells are designed in a way that they can be treated as black boxes during physical design. However, this abstraction often prevents an efficient use of its internal free resources. This paper proposes an effective approach for using internal routing resources without sacrificing modularity. By using cell generation tools for regular layouts, libraries are enriched with cell instances that have lateral pins and allow under-the-cell connections between adjacent cells, thus reducing pin count, via count and routing congestion. An approach to generate cells with regular layouts and lateral pins is proposed. Additionally, algorithms to maximize the impact of under-the-cell routing are presented. The proposed techniques are integrated in an industrial design flow. Experimental results show a significant reduction of design rule check violations with negligible impact on timing.Peer ReviewedPostprint (author's final draft

A hierarchical mathematical model for automatic pipelining and allocation using elastic systems

The advent of FPGA-based accelerators has encouraged the use of high-level synthesis (HLS) for rapid prototyping and design space exploration. In this context, design optimization at behavioral level becomes a critical task for the delivery of high-quality solutions. Time elasticity opens a new avenue of optimizations that can be applied after HLS and before logic synthesis, proposing new sequential transformations that expand beyond classical retiming and enlarge the register-transfer level (RTL) exploration space. This paper proposes a mathematical model for RTL transformations that exploit elasticity to select the best implementation for each functional unit and add pipeline registers to increase performance. Two simple examples are used to validate the effectiveness and potential benefits of the model.Peer ReviewedPostprint (author's final draft

A Distributed algorithm to find Hamiltonian cycles in Gnp random graphs

In this paper, we present a distributed algorithm to find Hamiltonian cycles in random binomial graphs Gnp. The algorithm works on a synchronous distributed setting by first creating a small cycle, then covering almost all vertices in the graph with several disjoint paths, and finally patching these paths and the uncovered vertices to the cycle. Our analysis shows that, with high probability, our algorithm is able to find a Hamiltonian cycle in Gnp when p_n=omega(sqrt{log n}/n^{1/4}). Moreover, we conduct an average case complexity analysis that shows that our algorithm terminates in expected sub-linear time, namely in O(n^{3/4+epsilon}) pulses.Postprint (published version

Computación en Internet: librería MALLBA para problemas de optimización.

Postprint (published version

Programación-1: Una asignatura orientada a la resolución de problemas

En este artículo presentamos el nuevo método docente de la asignatura Programació-1 en la Facultat d’Informàtica de Barcelona de la Universitat Politècnica de Catalunya, y damos cuenta de los resultados obtenidos durante los cinco cuatrimestres de aplicación. El curso proporciona un sistema automático de verificación de soluciones para una colección de casi 300 ejercicios cuidadosamente ordenados. Este sistema automático se usa también en la evaluación de los estudiantes durante los exámenes, que se realizan con un ordenador. Además, el sistema permite obtener datos objetivos sobre el progreso de los estudiantes a lo largo del curso.Peer Reviewe

Development and experimental testing and comparison of topology-control algorithms in sensor networks

This work is an experimental evaluation of topology-control protocols real in wireless sensor networks. Topology control is considered to be a fundamental technique to reduce energy consumption and radio interference. But, to the best of our knowledge, it has only been tested using simulators and there are no evaluations of topology-control protocols in real environments. With this work we intend to fill this gap.Postprint (published version

Linear orderings of random geometric graphs (extended abstract)

In random geometric graphs, vertices are randomly distributed on [0,1]^2 and pairs of vertices are connected by edges whenever they are sufficiently close together. Layout problems seek a linear ordering of the vertices of a graph such that a certain measure is minimized. In this paper, we study several layout problems on random geometric graphs: Bandwidth, Minimum Linear Arrangement, Minimum Cut, Minimum Sum Cut, Vertex Separation and Bisection. We first prove that some of these problems remain \NP-complete even for geometric graphs. Afterwards, we compute lower bounds that hold with high probability on random geometric graphs. Finally, we characterize the probabilistic behavior of the lexicographic ordering for our layout problems on the class of random geometric graphs.Postprint (published version

Convergence theorems for some layout measures on random lattice and random geometric graphs

This work deals with convergence theorems and bounds on the cost of several layout measures for lattice graphs, random lattice graphs and sparse random geometric graphs. For full square lattices, we give optimal layouts for the problems still open. Our convergence theorems can be viewed as an analogue of the Beardwood, Halton and Hammersley theorem for the Euclidian TSP on random points in the $d$-dimensional cube. As the considered layout measures are non-subadditive, we use percolation theory to obtain our results on random lattices and random geometric graphs. In particular, we deal with the subcritical regimes on these class of graphs.Postprint (published version