Search results for "Parallel algorithm"
showing 10 items of 32 documents
A distributed genetic algorithm for restoration of vertical line scratches
2008
This paper reports a distributed algorithm for the restoration of still frames corrupted by vertical line scratches. The restoration is here approached as an optimisation problem, and is solved using an ad-hoc Genetic Algorithm. The distributed algorithm is designed following a pipeline logical structure. The front end is a network of standard workstations with heterogeneous operating systems. The quality of image is appreciable and the computational time is quite low with respect the sequential version.
Parallel simulation of dense two-dimensional polymer systems
1990
Abstract We present a parallel algorithm for the simulation of dense lattice polymer systems. The algorithm will be given for a two-dimensional system although the algorithm can be generalized to higher dimensions. We discuss timing results and applications.
Scheduled Relaxation Jacobi method: improvements and applications
2016
Elliptic partial differential equations (ePDEs) appear in a wide variety of areas of mathematics, physics and engineering. Typically, ePDEs must be solved numerically, which sets an ever growing demand for efficient and highly parallel algorithms to tackle their computational solution. The Scheduled Relaxation Jacobi (SRJ) is a promising class of methods, atypical for combining simplicity and efficiency, that has been recently introduced for solving linear Poisson-like ePDEs. The SRJ methodology relies on computing the appropriate parameters of a multilevel approach with the goal of minimizing the number of iterations needed to cut down the residuals below specified tolerances. The efficien…
A Maximal-Space Algorithm for the Container Loading Problem
2008
In this paper, a greedy randomized adaptive search procedure (GRASP) for the container loading problem is presented. This approach is based on a constructive block heuristic that builds upon the concept of maximal space, a nondisjoint representation of the free space in a container. This new algorithm is extensively tested over the complete set of Bischoff and Ratcliff problems [Bischoff, E. E., M. S. W. Ratcliff. 1995. Issues in the development of approaches to container loading. Omega 23 377–390], ranging from weakly heterogeneous to strongly heterogeneous cargo, and outperforms all the known nonparallel approaches that, partially or completely, have used this set of test problems. When …
Parallel Construction and Query of Index Data Structures for Pattern Matching on Square Matrices
1999
AbstractWe describe fast parallel algorithms for building index data structures that can be used to gather various statistics on square matrices. The main data structure is the Lsuffix tree, which is a generalization of the classical suffix tree for strings. Given ann×ntext matrixA, we build our data structures inO(logn) time withn2processors on a CRCW PRAM, so that we can quickly processAin parallel as follows: (i) report some statistical information aboutA, e.g., find the largest repeated square submatrices that appear at least twice inAor determine, for each position inA, the smallest submatrix that occurs only there; (ii) given, on-line, anm×mpattern matrixPAT, check whether it occurs i…
Parallel Calculation of CCSDT and Mk-MRCCSDT Energies.
2010
A scheme for the parallel calculation of energies at the coupled-cluster singles, doubles, and triples (CCSDT) level of theory, several approximate iterative CCSDT schemes (CCSDT-1a, CCSDT-1b, CCSDT-2, CCSDT-3, and CC3), and for the state-specific multireference coupled-cluster ansatz suggested by Mukherjee with a full treatment of triple excitations (Mk-MRCCSDT) is presented. The proposed scheme is based on the adaptation of a highly efficient serial coupled-cluster code leading to a communication-minimized implementation by parallelizing the time-determining steps. The parallel algorithm is tailored for affordable cluster architectures connected by standard communication networks such as …
Gl-learning
2016
In this paper, we present a new open-source software library, Gl-learning, for grammatical inference. The rise of new application scenarios in recent years has required optimized methods to address knowledge extraction from huge amounts of data and to model highly complex systems. Our library implements the main state-of-the-art algorithms in the grammatical inference field (RPNI, EDSM, L*), redesigned through the OpenMP library for a parallel execution that drastically decreases execution times. To our best knowledge, it is also the first comprehensive library including a noise tolerance learning algorithm, such as Blue*, that significantly broadens the range of the potential application s…
Parallel Collision Queries on the GPU
2013
We present parallel algorithms to accelerate collision tests of rigid body objects for a high number of independent transformations as they occur in sampling-based motion planning and path validation problems. We compare various GPU approaches with a different level of parallelism against each other and against a parallel CPU implementation. Our algorithms require no sophisticated load balancing schemes. They make no assumption on the distribution of the input transformations and require no pre-processing. Yet, we can perform up to 1 million collision tests per second with our best GPU implementation in our benchmarks. This is about 2.5X faster than our reference multi-core CPU implementati…
Some Afterthoughts on Hopfield Networks
1999
In the present paper we investigate four relatively independent issues, which complete our knowledge regarding the computational aspects of popular Hopfield nets. In Section 2 of the paper, the computational equivalence of convergent asymmetric and Hopfield nets is shown with respect to network size. In Section 3, the convergence time of Hopfield nets is analyzed in terms of bit representations. In Section 4, a polynomial time approximate algorithm for the minimum energy problem is shown. In Section 5, the Turing universality of analog Hopfield nets is studied. peerReviewed
An adaptive method for Volterra–Fredholm integral equations on the half line
2009
AbstractIn this paper we develop a direct quadrature method for solving Volterra–Fredholm integral equations on an unbounded spatial domain. These problems, when related to some important physical and biological phenomena, are characterized by kernels that present variable peaks along space. The method we propose is adaptive in the sense that the number of spatial nodes of the quadrature formula varies with the position of the peaks. The convergence of the method is studied and its performances are illustrated by means of a few significative examples. The parallel algorithm which implements the method and its performances are described.