Iterated Local Search for de Novo Genomic Sequencing

in Lecture Notes in Computer Science (2010), 6114

The sequencing process of a DNA chain for reading its components supposes a complex process, since only small DNA fragments can be read nowadays. Therefore, the use of optimization algorithms is required ... [more ▼]

The sequencing process of a DNA chain for reading its components supposes a complex process, since only small DNA fragments can be read nowadays. Therefore, the use of optimization algorithms is required to rebuild a single chain from all the small pieces. We address here a simplified version of the problem, in which no errors in the sequencing process are allowed. The methods typically used in the literature for this problem are not satisfactory when solving realistic size instances, so there is a need for new more efficient and accurate methods. We propose a new iterated local search algorithm, highly competitive with the best algorithms in the literature, and considerably faster. [less ▲]

DENS: Data Center Energy-Efficient Network-Aware Scheduling

in IEEE/ACM International Conference on Green Computing and Communications (GreenCom), Hangzhou, China, 2010 (2010)

In modern data centers, energy consumption accounts for a considerably large slice of operational expenses. The state of the art in data center energy optimization is focusing only on job distribution ... [more ▼]

In modern data centers, energy consumption accounts for a considerably large slice of operational expenses. The state of the art in data center energy optimization is focusing only on job distribution between computing servers based on workload or thermal profiles. This paper underlines the role of communication fabric in data center energy consumption and presents a scheduling approach that combines energy efficiency and network awareness, termed DENS. The DENS methodology balances the energy consumption of a data center, individual job performance, and traffic demands. The proposed approach optimizes the tradeoff between job consolidation (to minimize the amount of computing servers) and distribution of traffic patterns (to avoid hotspots in the data center network). [less ▲]

Hybrid Cellular Genetic Algorithm for Global Trajectory Optimization Problem

in International Conference on Metaheuristics and Nature Inspired Computing (2010)

Multi-objective Robust Static Mapping of Independent Tasks on Grids

in World Conference in Computational Intelligence (WCCI) (2010)

We study the problem of efficiently allocating incoming independent tasks onto the resources of a Grid system. Typically, it is assumed that the estimated time to compute each task on every machine is ... [more ▼]

We study the problem of efficiently allocating incoming independent tasks onto the resources of a Grid system. Typically, it is assumed that the estimated time to compute each task on every machine is known. We are making the same assumption in this work, but we allow the existence of inaccuracies in these values. Our schedule will be robust versus such inaccuracies, ensuring that even when the estimated time to compute all the tasks is increased by a given percentage, the makespan of the schedule (i.e., the time when the last machine finishes its tasks) will not grow behind that percentage. We propose a new multi-objective definition of the problem, optimizing at the same time the makespan of the schedule and its robustness. Four well-known multi-objective evolutionary algorithms are used to find competitive results to the new problem. Finally, a new population initialization method for scheduling problems is proposed, leading to more efficient and accurate algorithms. [less ▲]

Deskilling HPL - Using an Evolutionary Algorithm to Automate Cluster Benchmarking

in Proceedings of 8th Intl. conf. on Parallel Processing and Applied Mathematics (PPAM 2009) (2009, September), 6068(LNCS), 102--114

The High-Performance Linpack (HPL) benchmark is the ac- cepted standard for measuring the capacity of the world’s most powerful computers, which are ranked twice yearly in the Top 500 List. Since just a ... [more ▼]

The High-Performance Linpack (HPL) benchmark is the ac- cepted standard for measuring the capacity of the world’s most powerful computers, which are ranked twice yearly in the Top 500 List. Since just a small deficit in performance can cost a computer several places, it is impor- tant to tune the benchmark to obtain the best possible result. However, the adjustment of HPL’s seventeen configuration parameters to obtain maximum performance is a time-consuming task that must be performed by hand. In a previous paper, we provided a preliminary study that proposed the tuning of HPL parameters by means of an Evolutionary Algorithm. The approach was validated on a small cluster hosted at the University of Luxembourg. In this article, we extend this initial work by describing Acbea, a fully-automatic benchmark tuning tool that performs both the configuration and installation of HPL followed by an automatic search for optimized parameters that will lead to the best benchmark results. Experiments have been conducted to validate this tool on several clusters, exploiting in particular the Grid’5000 infrastructure. [less ▲]

Probabilistic Packet Relaying in Wireless Mobile Ad Hoc Network

in Parallel Processing and Applied Mathematics (2009)

Parallel implementation of domain decomposition algorithm for molecular dynamics

in PARENG 2007 (2009)

The objective of this study is to apply a domain decomposition algorithm to the La- grangian based Discrete Particle Method (DPM). The latter deals with the thermal decomposition of solid e.g. biomass ... [more ▼]

The objective of this study is to apply a domain decomposition algorithm to the La- grangian based Discrete Particle Method (DPM). The latter deals with the thermal decomposition of solid e.g. biomass fuel particles. It considers each particle as an individual entity that is represented by an instantiation of a class. Modelizing thermal conversion of biomass in real systems involves a large number of particles. This can be achieved in a reasonable computing time only through a parallel implementation able to distribute the particles e.g. objects onto the participating processors. This pa- per present such an implementation based on Orthogonal Recursive Bisection (ORB) method. Due to the fact that the particles may take arbitrary positions within the do- main, a particular issue addressed by the domain decomposition technic used in this work is to generate a load balance for each processors as uniform as possible. Fur- thermore, the particles are coupled via heat transfer. One challenge for the designed algorithm is then to identify the nearest neighbours of each particle so that the nec- essary information can be communicated between them. Since the positions of all particles are subject to change and may migrate from one processor to another, the communication links together with the number of neighbors are highly dynamic. The implementation is carried out using the KAAPI API, a C++ library for parallel pro- gramming that allows to execute ?ne/medium grain multithreaded computation with dynamic data ?ow synchronizations. First results are very promising since they indi- cate that our algorithm creates sub domains with an average imbalance ranging from 2.5% to 6.3% for uniformly distributed particles. [less ▲]

A Multi-Agent Organizational Model for Coevolutionary Optimization

in ANNIE '09: Proceedings of the 19th international conference on Articial Neural Networks In Engineering (to appear) (2009)

Multi Agent Organisation for Coevolutionary Optimization

in 1st International Workshop on Organizational Modeling (ORGMOD'09) (2009)

GreenCloud: A Packet-level Simulator of Energy-aware Cloud Computing Data Centers

in IEEE Global Communications Conference (GLOBECOM), Miami, FL, USA, 2009 (2009)