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Results for “Parallel Algorithms”

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At least 199 records · Page 11Linked to original sources

PubMed2006

Coexpressionfinder: a new algorithm for finding groups of coexpressed genes.

RESULTS: A new algorithm is developed which is intended to find groups of genes whose expression values change in a concordant manner in a series of experiments with DNA arrays. This algorithm is named as CoexpressionFinder. It can find more complete and internally coordinated groups of gene expression vectors than hierarchical clustering. Also, it finds more genes having coordinated expression. The algorithm's design allows parallel execution. AVAILABILITY: The algorithm is implemented as a Java application which is freely available at: http://www.bioinformatics.ru/cf/index.jsp and http://bioinformatics.ru/cf/index.jsp.

Algorithms↗

PubMed2002

Measurable differences between sequential and parallel diagnostic decision processes for determining stroke subtype: a representation of interacting pathologies.

Stroke diagnosis depends on causal subtype. The accepted classification procedure is a succession of diagnostic tests administered in an order based on prior reported frequencies of the subtypes. The first positive test result completely determines diagnosis. An alternative approach tests multiple concomitant diagnostic hypotheses in parallel. This method permits multiple simultaneous pathologies in the patient. These two diagnostic procedures can be compared by novel numeric criteria presented here. Thrombosis, a type of ischemic stroke, results from interaction between endothelium, blood flow and blood components. We tested for ischemic stroke on thirty patients using both methods. For each patient the procedure produced an assessment of severity as an ordered set of three numbers in the interval [0, 1]. We measured the difference in diagnosis between the sequential and parallel diagnostic algorithms. The computations reveal systematic differences: The sequential procedure tends to under-diagnose and excludes any measure of interaction between pathologic elements.

Algorithms↗

PubMed2005

A Grid service for the interactive use of a parallel non-rigid registration algorithm of medical images.

OBJECTIVE: The goal of this work is to improve the usability of a non-rigid registration software for medical images. METHOD: We have built a registration grid service in order to use the interactivity of a visualization workstation and the computing power of a cluster. On the user side, the system is composed of a graphical interface that interacts in a complex and fluid manner with the registration software running on a remote cluster. CONCLUSION: Although the transmission of images back and forth between the computer running the user interface and the cluster running the registration service adds to the total registration time, it provides a user-friendly way of using the registration software without heavy infrastructure investments in hospitals. The system exhibits good performances even if the user is connected to the grid service through a low throughput network such as a wireless network interface or ADSL.

Algorithms↗

PubMed1989

To link, to infer, to understand.

A model of linkage in text processing is proposed: An external proposition and an inference belonging to one frame are superimposed to constitute understanding. A text containing four academic subjects was presented orally to students who recalled it in writing. After transforming the recalls into propositions they are entered into a nonmetric multidimensional scaling to yield a text space. The subjects' interest choices among items of the four aspects are scaled to render an interest space. The decomposition ob both as subspaces of a common space yields an angle as their overall similarity and indicates the degree of predictability from interests. As the aggregate of inferences shows directedness, correlated with volitional-motivational orientation, and inference base is assumed to intervene. It is concluded that recipients try to superimpose and thereby construct a primary stage of processing. This allows for a very general algorithm of parallel information processing (holographic thesis), perhaps constructing the properties we are used to. Motivated perception, knowledge influence, schema-directedness and contribution to coherence are rivalled out as an explanation of this process.

Adult↗

PubMed1996

Parallel computing of physical maps--a comparative study in SIMD and MIMD parallelism.

Ordering clones from a genomic library into physical maps of whole chromosomes presents a central computational problem in genetics. Chromosome reconstruction via clone ordering is usually isomorphic to the NP-complete Optimal Linear Arrangement problem. Parallel SIMD and MIMD algorithms for simulated annealing based on Markov chain distribution are proposed and applied to the problem of chromosome reconstruction via clone ordering. Perturbation methods and problem-specific annealing heuristics are proposed and described. The SIMD algorithms are implemented on a 2048 processor MasPar MP-2 system which is an SIMD 2-D toroidal mesh architecture whereas the MIMD algorithms are implemented on an 8 processor Intel iPSC/860 which is an MIMD hypercube architecture. A comparative analysis of the various SIMD and MIMD algorithms is presented in which the convergence, speedup, and scalability characteristics of the various algorithms are analyzed and discussed. On a fine-grained, massively parallel SIMD architecture with a low synchronization overhead such as the MasPar MP-2, a parallel simulated annealing algorithm based on multiple periodically interacting searches performs the best. For a coarse-grained MIMD architecture with high synchronization overhead such as the Intel iPSC/860, a parallel simulated annealing algorithm based on multiple independent searches yields the best results. In either case, distribution of clonal data across multiple processors is shown to exacerbate the tendency of the parallel simulated annealing algorithm to get trapped in a local optimum.

Algorithms↗

PubMed2003

Parallelization of four-component calculations. II. Symmetry-driven parallelization of the 4-Spinor CCSD algorithm.

Given the importance of the Coupled-cluster (CC) method as an efficient and accurate way to take electron correlation into account, we extend the parallelization technique in the second part of this series also to the 4-Spinor CCSD algorithm implemented in the Dirac-Fock packages DIRAC and MOLFDIR. The present implementation is based on the availability of the transformed molecular two-electron integrals on an external storage medium. The linearity of the CC equations in these two-electron integrals is used in a parallelization strategy that is based on distribution of the two largest integral classes that carry three or four virtual spinor indices. The corresponding partial contributions to the T(1) and T(2) amplitudes are calculated on each node and added using Message Passing Interface (MPI) library calls. Although we did not employ a master/slave principle, one specific node was assigned to also perform the remaining serial parts of the algorithm. In the critical sections considerable savings in storage requirements and computer time could be achieved, and this allows for computations on larger systems in the framework of four-component theory.

Journal Article↗

PubMed2003

An algorithm for identification of regulatory signals in unaligned DNA sequences, its testing and parallel implementation.

We describe an algorithm (IRSA) for identification of common regulatory signals in samples of unaligned DNA sequences. The algorithm was tested on randomly generated sequences of fixed length with implanted signal of length 15 with 4 mutations, and on natural upstream regions of bacterial genes regulated by PurR, ArgR and CRP. Then it was applied to upstream regions of orthologous genes from Escherichia coli and related genomes. Some new palindromic binding and direct repeats signals were identified. Finally we present a parallel version suitable for computers supporting the MPI protocol. This implementation is not strictly bounded by the number of available processors. The computation speed linearly depends on the number of processors.

Algorithms↗

PubMed1997

World Wide Web interface for advanced SPECT reconstruction algorithms implemented on a remote massively parallel computer.

Data from Single Photon Emission Computed Tomography (SPECT) studies are blurred by inevitable physical phenomena occurring during data acquisition. These errors may be compensated by means of reconstruction algorithms which take into account accurate physical models of the data acquisition procedure. Unfortunately, this approach involves high memory requirements as well as a high computational burden which cannot be afforded by the computer systems of SPECT acquisition devices. In this work the possibility of accessing High Performance Computing and Networking (HPCN) resources through a World Wide Web interface for the advanced reconstruction of SPECT data in a clinical environment was investigated. An iterative algorithm with an accurate model of the variable system response was ported on the Multiple Instruction Multiple Data (MIMD) parallel architecture of a Cray T3D massively parallel computer. The system was accessible even from low cost PC-based workstations through standard TCP/IP networking. A speedup factor of 148 was predicted by the benchmarks run on the Cray T3D. A complete brain study of 30 (64 x 64) slices was reconstructed from a set of 90 (64 x 64) projections with ten iterations of the conjugate gradients algorithm in 9 s which corresponds to an actual speed-up factor of 135. The technique was extended to a more accurate 3D modeling of the system response for a true 3D reconstruction of SPECT data; the reconstruction time of the same data set with this more accurate model was 5 min. This work demonstrates the possibility of exploiting remote HPCN resources from hospital sites by means of low cost workstations using standard communication protocols and an user-friendly WWW interface without particular problems for routine use.

Algorithms↗

PubMed1992

Searching for distantly related protein sequences in large databases by parallel processing on a transputer machine.

AliMac is an implementation of a sensitive sequence alignment algorithm on a parallel computer. The method achieves reliable alignments for very distantly related sequences from a combined use of amino acid exchange weights and physicochemical characteristics. The algorithm is computing intensive and its usage on conventional computers is limited to a relatively small number of sequences. The parallel implementation uses a Macintosh IIcx host computer and 21 transputers and achieves 22 times the speed of a VAX 8650 at a fraction of the cost. This paper describes the AliMac hardware and software and discusses problems and peculiarities of parallel implementations, especially with transputers. Finally, several popular sequence alignment algorithms are compared in their ability to detect distantly related sequences in searching large databases.

Algorithms↗

PubMed2000

A transparent tool for seemingly difficult calibrations: the parallel calibration method.

A new easy-to-understand calibration method for the analysis of spectral data is developed. The "parallel calibration" method is logically simple and intuitive yet often provides an improvement over more complex standard calibration methods. A description of the algorithm with a technical justification for the parallel algorithm is presented, underscoring the simplicity of the approach. In addition, performance as compared to that of the standard methods of classical least-squares (CLS) and partial least-squares (PLS) regression is studied. Calibrations are carried out on a computer-generated simulation data set as well as two scientific data sets. The results show that the parallel method gives results comparable to or better than those of CLS and PLS methods in terms of mean squared error.

Algorithms↗

PubMed1996

Parallel processing of chemical information in a local area network--III. Using genetic algorithms for conformational analysis of biomacromolecules.

Multi-dimensional nuclear magnetic resonance experiments are an excellent means of revealing the three-dimensional structure of biomacromolecules in solution. However, the search space in the conformational analysis of biomacromolecules, using multi-dimensional NMR data, is huge and complex. This calls for global optimization techniques with good sampling properties. This paper describes a genetic algorithm that optimizes the fit between (simulated) experimental two-dimensional Nuclear Overhauser Effect spectra and the corresponding calculated spectra for trial structures. This is a very computational intensive procedure. Speed-up of performance is achieved by parallelizing the algorithm, i.e. creating small subpopulations of trial structures, each of which can be processed on different processors. Good sampling behavior is obtained by initializing each subpopulation with its own random seed and the introduction of a migration operator. The latter replaces the best performing individual from one subpopulation with the worst performing individual from another subpopulation after a predetermined number of generations. A parallel genetic algorithm for the conformational analysis of nucleic acids is developed using the software package HYDRA. It is demonstrated that, for the data sets used in the study, a considerable reduction in computation time is obtained for the parallel genetic algorithm as compared to a sequential implementation, while the same optimal solutions are found.

Algorithms↗

PubMed1995

Parallel sequence alignment in limited space.

Sequence comparison with affine gap costs is a problem that is readily parallelizable on simple single-instruction, multiple-data stream (SIMD) parallel processors using only constant space per processing element. Unfortunately, the twin problem of sequence alignment, finding the optimal character-by-character correspondence between two sequences, is more complicated. While the innovative O(n2)-time and O(n)-space serial algorithm has been parallelized for multiple-instruction, multiple-data stream (MIMD) computers with only a communication-time slowdown, typically O(log n), it is not suitable for hardware-efficient SIMD parallel processors with only local communication. This paper proposes several methods of computing sequence alignments with limited memory per processing element. The algorithms are also well-suited to serial implementation. The simpler algorithms feature, for an arbitrary integer L, a factor of L slowdown in exchange for reducing space requirements from O(n) to O(L square root of n) per processing element. Using this result, we describe an O(n log n) parallel time algorithm that requires O(log n) space per processing element on O(n) SIMD processing elements with only a mesh or linear interconnection network.

Algorithms↗

PubMed2003

Algorithmic scalability in globally constrained conservative parallel discrete event simulations of asynchronous systems.

We consider parallel simulations for asynchronous systems employing L processing elements that are arranged on a ring. Processors communicate only among the nearest neighbors and advance their local simulated time only if it is guaranteed that this does not violate causality. In simulations with no constraints, in the infinite L limit the utilization scales [Korniss et al., Phys. Rev. Lett. 84, 1351 (2000)]; but, the width of the virtual time horizon diverges (i.e., the measurement phase of the algorithm does not scale). In this work, we introduce a moving Delta-window global constraint, which modifies the algorithm so that the measurement phase scales as well. We present results of systematic studies in which the system size (i.e., L and the volume load per processor) as well as the constraint are varied. The Delta constraint eliminates the extreme fluctuations in the virtual time horizon, provides a bound on its width, and controls the average progress rate. The width of the Delta window can serve as a tuning parameter that, for a given volume load per processor, could be adjusted to optimize the utilization, so as to maximize the efficiency. This result may find numerous applications in modeling the evolution of general spatially extended short-range interacting systems with asynchronous dynamics, including dynamic Monte Carlo studies.

Journal Article↗

PubMed2000

MIAX: a system for assessment of macromolecular interaction. 3) A parallel hybrid GA for flexible protein docking.

We propose a parallel hybrid genetic algorithm for flexible protein-protein docking in order to improve the conventional rigid-body models to manipulate protein-protein interactions. The proposed hybrid algorithm is a combination of an evolutionary algorithm with a simulated annealing one, yielding a powerful protein-complex conformation-searching engine. Parallelization of the procedure makes possible to reach high algorithm performance, in both, execution times and size of treated monomers and complexes. Knowledge on side chain flexibility is extracted by means of an exhaustive analysis of crystallographic data on proteins and protein complexes. Results demonstrate the competency of the algorithm since comparison of calculated and crystallographic data accounts for a maximum of 2.5A in RMS difference, including side chain conformation. The system allows routine analysis of this fundamental molecular biology problem important to elucidate bio-macromolecular function in biophysical and biochemical mechanisms involving molecular recognition and interaction, yielding simultaneously clues for designing new proteins and enzymes directed to different purposes.

Algorithms↗

PubMed2004

Contrast-enhanced three-dimensional pulmonary perfusion magnetic resonance imaging: intraindividual comparison of 1.0 M gadobutrol and 0.5 M Gd-DTPA at three dose levels.

RATIONALE AND OBJECTIVES: To compare 1.0 M gadobutrol and 0.5 M Gd-DTPA for contrast-enhanced three-dimensional pulmonary perfusion magnetic resonance imaging (3D MRI). MATERIALS AND METHODS: Ten healthy volunteers (3 females; 7 males; median age, 27 years; age range, 18-31 years) were examined with contrast-enhanced dynamic 3D MRI with parallel acquisition technique (FLASH 3D; reconstruction algorithm: generalized autocalibrating partially parallel acquisitions; acceleration factor: 2; TE/TR/alpha: 0.8/1.9 milliseconds/40 degrees; FOV: 500 x 375 mm; matrix: 256 x 86; slab thickness: 180 mm; 36 partitions; voxel size: 4.4 x 2 x 5 mm; TA: 1.48 seconds). Twenty-five consecutive data sets were acquired after intravenous injection of 0.025, 0.05, and 0.1 mmol/kg body weight of gadobutrol and Gd-DTPA. Quantitative measurements of peak signal-to-noise ratios (SNR) of both lungs were performed independently by 3 readers. Bolus transit times through the lungs were assessed from signal intensity time curves. RESULTS: The peak SNR in the lungs was comparable between gadobutrol and Gd-DTPA at all dose levels (15.7 vs. 15.5 at 0.1 mmol/kg bw; 12.9 vs. 12.5 at 0.05 mmol/kg bw; 7.6 vs. 8.9 at 0.025 mmol/kg bw). A dose of 0.1 mmol/kg achieved the highest peak SNR compared with all other dose levels (P < 0.05). A higher peak SNR was observed in gravity dependent lung (P < 0.05). Despite different injection volumes, transit times of the contrast bolus did not differ between both agents. CONCLUSION: Higher concentrated gadolinium chelates offer no advantage over standard 0.5 M Gd-DTPA for contrast-enhanced 3D MRI of lung perfusion.

Adolescent↗

PubMedDate not supplied

Area weighted convolutional interpolation for data reprojection in single photon emission computed tomography.

A data reprojection algorithm has been developed for use in single photon emission computed tomography on an array processor equipped computer system. The algorithm makes use of an accurate representation of pixel activity (uniform square pixel model of intensity distribution), and is rapidly performed due to the efficient handling of an array-based algorithm and the fast Fourier transform on parallel processing hardware. The algorithm consists of using a pixel driven nearest-neighbor projection operation to an array of subdivided projection bins. The subdivided project bin array is then convolved with the angle-dependent projection of the area of a uniform square pixel and compressed to original bin size. The new algorithm has thus been named the area weighted convolution (AWC) method of interpolation. When compared to nearest-neighbor and linear interpolation algorithms, the new AWC algorithm was found to be more accurate, having an accuracy approaching that of the line length algorithm. It also yielded an easier and more efficient implementation on parallel hardware than line length or linear interpolation, with faster execution times than either.

Biometry↗

PubMed1985

[Prediction of secondary structures of nucleic acids: algorithmic and physical aspects].

Prediction of secondary structures in nucleic acids requires both an adequate physical model and powerful calculation algorithms. In our approach, we cut the molecules in sections of which the contributions to the global energy are context-dependent but roughly additive. The structure of minimum energy is obtained by a tree search under constraints of binary incompatibilities. Our algorithm of the "incompatibility islets" is shown to be more powerful than the "bit parallel forward checking" algorithm, well known in Artificial Intelligence. Recurrent algorithms, proposed by other authors are even more rapid, but often miss the correct structures, for they demand a strict additivity of the energetic contributions, physically unjustified. New strategies, required to deal with molecules of more than 200 nucleotides are discussed. Our physical model has been improved by considering the special case of internal loops beginning with a G-A opposition. A bonus of 1.5 kcal. is attributed to such a feature, at each side of an internal loop. To illustrate our programs, we give the computed schemes for the 3' termini of the small subunit ribosomal RNA.

Base Sequence↗

PubMed2005

Genomic multiple sequence alignments: refinement using a genetic algorithm.

BACKGROUND: Genomic sequence data cannot be fully appreciated in isolation. Comparative genomics--the practice of comparing genomic sequences from different species--plays an increasingly important role in understanding the genotypic differences between species that result in phenotypic differences as well as in revealing patterns of evolutionary relationships. One of the major challenges in comparative genomics is producing a high-quality alignment between two or more related genomic sequences. In recent years, a number of tools have been developed for aligning large genomic sequences. Most utilize heuristic strategies to identify a series of strong sequence similarities, which are then used as anchors to align the regions between the anchor points. The resulting alignment is globally correct, but in many cases is suboptimal locally. We describe a new program, GenAlignRefine, which improves the overall quality of global multiple alignments by using a genetic algorithm to improve local regions of alignment. Regions of low quality are identified, realigned using the program T-Coffee, and then refined using a genetic algorithm. Because a better COFFEE (Consistency based Objective Function For alignmEnt Evaluation) score generally reflects greater alignment quality, the algorithm searches for an alignment that yields a better COFFEE score. To improve the intrinsic slowness of the genetic algorithm, GenAlignRefine was implemented as a parallel, cluster-based program. RESULTS: We tested the GenAlignRefine algorithm by running it on a Linux cluster to refine sequences from a simulation, as well as refine a multiple alignment of 15 Orthopoxvirus genomic sequences approximately 260,000 nucleotides in length that initially had been aligned by Multi-LAGAN. It took approximately 150 minutes for a 40-processor Linux cluster to optimize some 200 fuzzy (poorly aligned) regions of the orthopoxvirus alignment. Overall sequence identity increased only slightly; but significantly, this occurred at the same time that the overall alignment length decreased--through the removal of gaps--by approximately 200 gapped regions representing roughly 1,300 gaps. CONCLUSION: We have implemented a genetic algorithm in parallel mode to optimize multiple genomic sequence alignments initially generated by various alignment tools. Benchmarking experiments showed that the refinement algorithm improved genomic sequence alignments within a reasonable period of time.

Algorithms↗