A parallel approximate string matching under Levenshtein distance on graphics processing units using warp-shuffle operations

PubMed Central

Ho, ThienLuan; Oh, Seung-Rohk

2017-01-01

Approximate string matching with k-differences has a number of practical applications, ranging from pattern recognition to computational biology. This paper proposes an efficient memory-access algorithm for parallel approximate string matching with k-differences on Graphics Processing Units (GPUs). In the proposed algorithm, all threads in the same GPUs warp share data using warp-shuffle operation instead of accessing the shared memory. Moreover, we implement the proposed algorithm by exploiting the memory structure of GPUs to optimize its performance. Experiment results for real DNA packages revealed that the performance of the proposed algorithm and its implementation archived up to 122.64 and 1.53 times compared to that of sequential algorithm on CPU and previous parallel approximate string matching algorithm on GPUs, respectively. PMID:29016700

A privacy-preserving parallel and homomorphic encryption scheme

NASA Astrophysics Data System (ADS)

Min, Zhaoe; Yang, Geng; Shi, Jingqi

2017-04-01

In order to protect data privacy whilst allowing efficient access to data in multi-nodes cloud environments, a parallel homomorphic encryption (PHE) scheme is proposed based on the additive homomorphism of the Paillier encryption algorithm. In this paper we propose a PHE algorithm, in which plaintext is divided into several blocks and blocks are encrypted with a parallel mode. Experiment results demonstrate that the encryption algorithm can reach a speed-up ratio at about 7.1 in the MapReduce environment with 16 cores and 4 nodes.

Parallel Directionally Split Solver Based on Reformulation of Pipelined Thomas Algorithm

NASA Technical Reports Server (NTRS)

Povitsky, A.

1998-01-01

In this research an efficient parallel algorithm for 3-D directionally split problems is developed. The proposed algorithm is based on a reformulated version of the pipelined Thomas algorithm that starts the backward step computations immediately after the completion of the forward step computations for the first portion of lines This algorithm has data available for other computational tasks while processors are idle from the Thomas algorithm. The proposed 3-D directionally split solver is based on the static scheduling of processors where local and non-local, data-dependent and data-independent computations are scheduled while processors are idle. A theoretical model of parallelization efficiency is used to define optimal parameters of the algorithm, to show an asymptotic parallelization penalty and to obtain an optimal cover of a global domain with subdomains. It is shown by computational experiments and by the theoretical model that the proposed algorithm reduces the parallelization penalty about two times over the basic algorithm for the range of the number of processors (subdomains) considered and the number of grid nodes per subdomain.

Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform.

PubMed

Cao, Jianfang; Chen, Lichao; Wang, Min; Tian, Yun

2018-01-01

The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator's dual threshold and improve the edge detection performance, while the MapReduce parallel programming model facilitates parallel processing for the Canny operator to solve the processing speed and communication cost problems that occur when the Canny edge detection algorithm is applied to big data. For the experiments, we constructed datasets of different scales from the Pascal VOC2012 image database. The proposed parallel Otsu-Canny edge detection algorithm performs better than other traditional edge detection algorithms. The parallel approach reduced the running time by approximately 67.2% on a Hadoop cluster architecture consisting of 5 nodes with a dataset of 60,000 images. Overall, our approach system speeds up the system by approximately 3.4 times when processing large-scale datasets, which demonstrates the obvious superiority of our method. The proposed algorithm in this study demonstrates both better edge detection performance and improved time performance.

High-performance Chinese multiclass traffic sign detection via coarse-to-fine cascade and parallel support vector machine detectors

NASA Astrophysics Data System (ADS)

Chang, Faliang; Liu, Chunsheng

2017-09-01

The high variability of sign colors and shapes in uncontrolled environments has made the detection of traffic signs a challenging problem in computer vision. We propose a traffic sign detection (TSD) method based on coarse-to-fine cascade and parallel support vector machine (SVM) detectors to detect Chinese warning and danger traffic signs. First, a region of interest (ROI) extraction method is proposed to extract ROIs using color contrast features in local regions. The ROI extraction can reduce scanning regions and save detection time. For multiclass TSD, we propose a structure that combines a coarse-to-fine cascaded tree with a parallel structure of histogram of oriented gradients (HOG) + SVM detectors. The cascaded tree is designed to detect different types of traffic signs in a coarse-to-fine process. The parallel HOG + SVM detectors are designed to do fine detection of different types of traffic signs. The experiments demonstrate the proposed TSD method can rapidly detect multiclass traffic signs with different colors and shapes in high accuracy.

Parallel optoelectronic trinary signed-digit division

NASA Astrophysics Data System (ADS)

Alam, Mohammad S.

1999-03-01

The trinary signed-digit (TSD) number system has been found to be very useful for parallel addition and subtraction of any arbitrary length operands in constant time. Using the TSD addition and multiplication modules as the basic building blocks, we develop an efficient algorithm for performing parallel TSD division in constant time. The proposed division technique uses one TSD subtraction and two TSD multiplication steps. An optoelectronic correlator based architecture is suggested for implementation of the proposed TSD division algorithm, which fully exploits the parallelism and high processing speed of optics. An efficient spatial encoding scheme is used to ensure better utilization of space bandwidth product of the spatial light modulators used in the optoelectronic implementation.

Serial and parallel attentive visual searches: evidence from cumulative distribution functions of response times.

PubMed

Sung, Kyongje

2008-12-01

Participants searched a visual display for a target among distractors. Each of 3 experiments tested a condition proposed to require attention and for which certain models propose a serial search. Serial versus parallel processing was tested by examining effects on response time means and cumulative distribution functions. In 2 conditions, the results suggested parallel rather than serial processing, even though the tasks produced significant set-size effects. Serial processing was produced only in a condition with a difficult discrimination and a very large set-size effect. The results support C. Bundesen's (1990) claim that an extreme set-size effect leads to serial processing. Implications for parallel models of visual selection are discussed.

File concepts for parallel I/O

NASA Technical Reports Server (NTRS)

Crockett, Thomas W.

1989-01-01

The subject of input/output (I/O) was often neglected in the design of parallel computer systems, although for many problems I/O rates will limit the speedup attainable. The I/O problem is addressed by considering the role of files in parallel systems. The notion of parallel files is introduced. Parallel files provide for concurrent access by multiple processes, and utilize parallelism in the I/O system to improve performance. Parallel files can also be used conventionally by sequential programs. A set of standard parallel file organizations is proposed, organizations are suggested, using multiple storage devices. Problem areas are also identified and discussed.

Parallel solution of sparse one-dimensional dynamic programming problems

NASA Technical Reports Server (NTRS)

Nicol, David M.

1989-01-01

Parallel computation offers the potential for quickly solving large computational problems. However, it is often a non-trivial task to effectively use parallel computers. Solution methods must sometimes be reformulated to exploit parallelism; the reformulations are often more complex than their slower serial counterparts. We illustrate these points by studying the parallelization of sparse one-dimensional dynamic programming problems, those which do not obviously admit substantial parallelization. We propose a new method for parallelizing such problems, develop analytic models which help us to identify problems which parallelize well, and compare the performance of our algorithm with existing algorithms on a multiprocessor.

Hierarchical Fuzzy Control Applied to Parallel Connected UPS Inverters Using Average Current Sharing Scheme

NASA Astrophysics Data System (ADS)

Singh, Santosh Kumar; Ghatak Choudhuri, Sumit

2018-05-01

Parallel connection of UPS inverters to enhance power rating is a widely accepted practice. Inter-modular circulating currents appear when multiple inverter modules are connected in parallel to supply variable critical load. Interfacing of modules henceforth requires an intensive design, using proper control strategy. The potentiality of human intuitive Fuzzy Logic (FL) control with imprecise system model is well known and thus can be utilised in parallel-connected UPS systems. Conventional FL controller is computational intensive, especially with higher number of input variables. This paper proposes application of Hierarchical-Fuzzy Logic control for parallel connected Multi-modular inverters system for reduced computational burden on the processor for a given switching frequency. Simulated results in MATLAB environment and experimental verification using Texas TMS320F2812 DSP are included to demonstrate feasibility of the proposed control scheme.

Customizing FP-growth algorithm to parallel mining with Charm++ library

NASA Astrophysics Data System (ADS)

Puścian, Marek

2017-08-01

This paper presents a frequent item mining algorithm that was customized to handle growing data repositories. The proposed solution applies Master Slave scheme to frequent pattern growth technique. Efficient utilization of available computation units is achieved by dynamic reallocation of tasks. Conditional frequent trees are assigned to parallel workers basing on their workload. Proposed enhancements have been successfully implemented using Charm++ library. This paper discusses results of the performance of parallelized FP-growth algorithm against different datasets. The approach has been illustrated with many experiments and measurements performed using multiprocessor and multithreaded computer.

Approximation algorithms for scheduling unrelated parallel machines with release dates

NASA Astrophysics Data System (ADS)

Avdeenko, T. V.; Mesentsev, Y. A.; Estraykh, I. V.

2017-01-01

In this paper we propose approaches to optimal scheduling of unrelated parallel machines with release dates. One approach is based on the scheme of dynamic programming modified with adaptive narrowing of search domain ensuring its computational effectiveness. We discussed complexity of the exact schedules synthesis and compared it with approximate, close to optimal, solutions. Also we explain how the algorithm works for the example of two unrelated parallel machines and five jobs with release dates. Performance results that show the efficiency of the proposed approach have been given.

Multirate-based fast parallel algorithms for 2-D DHT-based real-valued discrete Gabor transform.

PubMed

Tao, Liang; Kwan, Hon Keung

2012-07-01

Novel algorithms for the multirate and fast parallel implementation of the 2-D discrete Hartley transform (DHT)-based real-valued discrete Gabor transform (RDGT) and its inverse transform are presented in this paper. A 2-D multirate-based analysis convolver bank is designed for the 2-D RDGT, and a 2-D multirate-based synthesis convolver bank is designed for the 2-D inverse RDGT. The parallel channels in each of the two convolver banks have a unified structure and can apply the 2-D fast DHT algorithm to speed up their computations. The computational complexity of each parallel channel is low and is independent of the Gabor oversampling rate. All the 2-D RDGT coefficients of an image are computed in parallel during the analysis process and can be reconstructed in parallel during the synthesis process. The computational complexity and time of the proposed parallel algorithms are analyzed and compared with those of the existing fastest algorithms for 2-D discrete Gabor transforms. The results indicate that the proposed algorithms are the fastest, which make them attractive for real-time image processing.

The role of parallelism in the real-time processing of anaphora.

PubMed

Poirier, Josée; Walenski, Matthew; Shapiro, Lewis P

2012-06-01

Parallelism effects refer to the facilitated processing of a target structure when it follows a similar, parallel structure. In coordination, a parallelism-related conjunction triggers the expectation that a second conjunct with the same structure as the first conjunct should occur. It has been proposed that parallelism effects reflect the use of the first structure as a template that guides the processing of the second. In this study, we examined the role of parallelism in real-time anaphora resolution by charting activation patterns in coordinated constructions containing anaphora, Verb-Phrase Ellipsis (VPE) and Noun-Phrase Traces (NP-traces). Specifically, we hypothesised that an expectation of parallelism would incite the parser to assume a structure similar to the first conjunct in the second, anaphora-containing conjunct. The speculation of a similar structure would result in early postulation of covert anaphora. Experiment 1 confirms that following a parallelism-related conjunction, first-conjunct material is activated in the second conjunct. Experiment 2 reveals that an NP-trace in the second conjunct is posited immediately where licensed, which is earlier than previously reported in the literature. In light of our findings, we propose an intricate relation between structural expectations and anaphor resolution.

The role of parallelism in the real-time processing of anaphora

PubMed Central

Poirier, Josée; Walenski, Matthew; Shapiro, Lewis P.

2012-01-01

Parallelism effects refer to the facilitated processing of a target structure when it follows a similar, parallel structure. In coordination, a parallelism-related conjunction triggers the expectation that a second conjunct with the same structure as the first conjunct should occur. It has been proposed that parallelism effects reflect the use of the first structure as a template that guides the processing of the second. In this study, we examined the role of parallelism in real-time anaphora resolution by charting activation patterns in coordinated constructions containing anaphora, Verb-Phrase Ellipsis (VPE) and Noun-Phrase Traces (NP-traces). Specifically, we hypothesised that an expectation of parallelism would incite the parser to assume a structure similar to the first conjunct in the second, anaphora-containing conjunct. The speculation of a similar structure would result in early postulation of covert anaphora. Experiment 1 confirms that following a parallelism-related conjunction, first-conjunct material is activated in the second conjunct. Experiment 2 reveals that an NP-trace in the second conjunct is posited immediately where licensed, which is earlier than previously reported in the literature. In light of our findings, we propose an intricate relation between structural expectations and anaphor resolution. PMID:23741080

Search asymmetries: parallel processing of uncertain sensory information.

PubMed

Vincent, Benjamin T

2011-08-01

What is the mechanism underlying search phenomena such as search asymmetry? Two-stage models such as Feature Integration Theory and Guided Search propose parallel pre-attentive processing followed by serial post-attentive processing. They claim search asymmetry effects are indicative of finding pairs of features, one processed in parallel, the other in serial. An alternative proposal is that a 1-stage parallel process is responsible, and search asymmetries occur when one stimulus has greater internal uncertainty associated with it than another. While the latter account is simpler, only a few studies have set out to empirically test its quantitative predictions, and many researchers still subscribe to the 2-stage account. This paper examines three separate parallel models (Bayesian optimal observer, max rule, and a heuristic decision rule). All three parallel models can account for search asymmetry effects and I conclude that either people can optimally utilise the uncertain sensory data available to them, or are able to select heuristic decision rules which approximate optimal performance. Copyright © 2011 Elsevier Ltd. All rights reserved.

A parallel simulated annealing algorithm for standard cell placement on a hypercube computer

NASA Technical Reports Server (NTRS)

Jones, Mark Howard

1987-01-01

A parallel version of a simulated annealing algorithm is presented which is targeted to run on a hypercube computer. A strategy for mapping the cells in a two dimensional area of a chip onto processors in an n-dimensional hypercube is proposed such that both small and large distance moves can be applied. Two types of moves are allowed: cell exchanges and cell displacements. The computation of the cost function in parallel among all the processors in the hypercube is described along with a distributed data structure that needs to be stored in the hypercube to support parallel cost evaluation. A novel tree broadcasting strategy is used extensively in the algorithm for updating cell locations in the parallel environment. Studies on the performance of the algorithm on example industrial circuits show that it is faster and gives better final placement results than the uniprocessor simulated annealing algorithms. An improved uniprocessor algorithm is proposed which is based on the improved results obtained from parallelization of the simulated annealing algorithm.

Serial and Parallel Attentive Visual Searches: Evidence from Cumulative Distribution Functions of Response Times

ERIC Educational Resources Information Center

Sung, Kyongje

2008-01-01

Participants searched a visual display for a target among distractors. Each of 3 experiments tested a condition proposed to require attention and for which certain models propose a serial search. Serial versus parallel processing was tested by examining effects on response time means and cumulative distribution functions. In 2 conditions, the…

Type synthesis for 4-DOF parallel press mechanism using GF set theory

NASA Astrophysics Data System (ADS)

He, Jun; Gao, Feng; Meng, Xiangdun; Guo, Weizhong

2015-07-01

Parallel mechanisms is used in the large capacity servo press to avoid the over-constraint of the traditional redundant actuation. Currently, the researches mainly focus on the performance analysis for some specific parallel press mechanisms. However, the type synthesis and evaluation of parallel press mechanisms is seldom studied, especially for the four degrees of freedom(DOF) press mechanisms. The type synthesis of 4-DOF parallel press mechanisms is carried out based on the generalized function(GF) set theory. Five design criteria of 4-DOF parallel press mechanisms are firstly proposed. The general procedure of type synthesis of parallel press mechanisms is obtained, which includes number synthesis, symmetrical synthesis of constraint GF sets, decomposition of motion GF sets and design of limbs. Nine combinations of constraint GF sets of 4-DOF parallel press mechanisms, ten combinations of GF sets of active limbs, and eleven combinations of GF sets of passive limbs are synthesized. Thirty-eight kinds of press mechanisms are presented and then different structures of kinematic limbs are designed. Finally, the geometrical constraint complexity( GCC), kinematic pair complexity( KPC), and type complexity( TC) are proposed to evaluate the press types and the optimal press type is achieved. The general methodologies of type synthesis and evaluation for parallel press mechanism are suggested.

Cache-Oblivious parallel SIMD Viterbi decoding for sequence search in HMMER.

PubMed

Ferreira, Miguel; Roma, Nuno; Russo, Luis M S

2014-05-30

HMMER is a commonly used bioinformatics tool based on Hidden Markov Models (HMMs) to analyze and process biological sequences. One of its main homology engines is based on the Viterbi decoding algorithm, which was already highly parallelized and optimized using Farrar's striped processing pattern with Intel SSE2 instruction set extension. A new SIMD vectorization of the Viterbi decoding algorithm is proposed, based on an SSE2 inter-task parallelization approach similar to the DNA alignment algorithm proposed by Rognes. Besides this alternative vectorization scheme, the proposed implementation also introduces a new partitioning of the Markov model that allows a significantly more efficient exploitation of the cache locality. Such optimization, together with an improved loading of the emission scores, allows the achievement of a constant processing throughput, regardless of the innermost-cache size and of the dimension of the considered model. The proposed optimized vectorization of the Viterbi decoding algorithm was extensively evaluated and compared with the HMMER3 decoder to process DNA and protein datasets, proving to be a rather competitive alternative implementation. Being always faster than the already highly optimized ViterbiFilter implementation of HMMER3, the proposed Cache-Oblivious Parallel SIMD Viterbi (COPS) implementation provides a constant throughput and offers a processing speedup as high as two times faster, depending on the model's size.

Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform

PubMed Central

Wang, Min; Tian, Yun

2018-01-01

The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator's dual threshold and improve the edge detection performance, while the MapReduce parallel programming model facilitates parallel processing for the Canny operator to solve the processing speed and communication cost problems that occur when the Canny edge detection algorithm is applied to big data. For the experiments, we constructed datasets of different scales from the Pascal VOC2012 image database. The proposed parallel Otsu-Canny edge detection algorithm performs better than other traditional edge detection algorithms. The parallel approach reduced the running time by approximately 67.2% on a Hadoop cluster architecture consisting of 5 nodes with a dataset of 60,000 images. Overall, our approach system speeds up the system by approximately 3.4 times when processing large-scale datasets, which demonstrates the obvious superiority of our method. The proposed algorithm in this study demonstrates both better edge detection performance and improved time performance. PMID:29861711

Performance of parallel computation using CUDA for solving the one-dimensional elasticity equations

NASA Astrophysics Data System (ADS)

Darmawan, J. B. B.; Mungkasi, S.

2017-01-01

In this paper, we investigate the performance of parallel computation in solving the one-dimensional elasticity equations. Elasticity equations are usually implemented in engineering science. Solving these equations fast and efficiently is desired. Therefore, we propose the use of parallel computation. Our parallel computation uses CUDA of the NVIDIA. Our research results show that parallel computation using CUDA has a great advantage and is powerful when the computation is of large scale.

A mixed parallel strategy for the solution of coupled multi-scale problems at finite strains

NASA Astrophysics Data System (ADS)

Lopes, I. A. Rodrigues; Pires, F. M. Andrade; Reis, F. J. P.

2018-02-01

A mixed parallel strategy for the solution of homogenization-based multi-scale constitutive problems undergoing finite strains is proposed. The approach aims to reduce the computational time and memory requirements of non-linear coupled simulations that use finite element discretization at both scales (FE^2). In the first level of the algorithm, a non-conforming domain decomposition technique, based on the FETI method combined with a mortar discretization at the interface of macroscopic subdomains, is employed. A master-slave scheme, which distributes tasks by macroscopic element and adopts dynamic scheduling, is then used for each macroscopic subdomain composing the second level of the algorithm. This strategy allows the parallelization of FE^2 simulations in computers with either shared memory or distributed memory architectures. The proposed strategy preserves the quadratic rates of asymptotic convergence that characterize the Newton-Raphson scheme. Several examples are presented to demonstrate the robustness and efficiency of the proposed parallel strategy.

A more secure parallel keyed hash function based on chaotic neural network

NASA Astrophysics Data System (ADS)

Huang, Zhongquan

2011-08-01

Although various hash functions based on chaos or chaotic neural network were proposed, most of them can not work efficiently in parallel computing environment. Recently, an algorithm for parallel keyed hash function construction based on chaotic neural network was proposed [13]. However, there is a strict limitation in this scheme that its secret keys must be nonce numbers. In other words, if the keys are used more than once in this scheme, there will be some potential security flaw. In this paper, we analyze the cause of vulnerability of the original one in detail, and then propose the corresponding enhancement measures, which can remove the limitation on the secret keys. Theoretical analysis and computer simulation indicate that the modified hash function is more secure and practical than the original one. At the same time, it can keep the parallel merit and satisfy the other performance requirements of hash function, such as good statistical properties, high message and key sensitivity, and strong collision resistance, etc.

Multi-objective problem of the modified distributed parallel machine and assembly scheduling problem (MDPMASP) with eligibility constraints

NASA Astrophysics Data System (ADS)

Amallynda, I.; Santosa, B.

2017-11-01

This paper proposes a new generalization of the distributed parallel machine and assembly scheduling problem (DPMASP) with eligibility constraints referred to as the modified distributed parallel machine and assembly scheduling problem (MDPMASP) with eligibility constraints. Within this generalization, we assume that there are a set non-identical factories or production lines, each one with a set unrelated parallel machine with different speeds in processing them disposed to a single assembly machine in series. A set of different products that are manufactured through an assembly program of a set of components (jobs) according to the requested demand. Each product requires several kinds of jobs with different sizes. Beside that we also consider to the multi-objective problem (MOP) of minimizing mean flow time and the number of tardy products simultaneously. This is known to be NP-Hard problem, is important to practice, as the former criterions to reflect the customer's demand and manufacturer's perspective. This is a realistic and complex problem with wide range of possible solutions, we propose four simple heuristics and two metaheuristics to solve it. Various parameters of the proposed metaheuristic algorithms are discussed and calibrated by means of Taguchi technique. All proposed algorithms are tested by Matlab software. Our computational experiments indicate that the proposed problem and fourth proposed algorithms are able to be implemented and can be used to solve moderately-sized instances, and giving efficient solutions, which are close to optimum in most cases.

A Proposed Solution to the Problem with Using Completely Random Data to Assess the Number of Factors with Parallel Analysis

ERIC Educational Resources Information Center

Green, Samuel B.; Levy, Roy; Thompson, Marilyn S.; Lu, Min; Lo, Wen-Juo

2012-01-01

A number of psychometricians have argued for the use of parallel analysis to determine the number of factors. However, parallel analysis must be viewed at best as a heuristic approach rather than a mathematically rigorous one. The authors suggest a revision to parallel analysis that could improve its accuracy. A Monte Carlo study is conducted to…

Cache-Oblivious parallel SIMD Viterbi decoding for sequence search in HMMER

PubMed Central

2014-01-01

Background HMMER is a commonly used bioinformatics tool based on Hidden Markov Models (HMMs) to analyze and process biological sequences. One of its main homology engines is based on the Viterbi decoding algorithm, which was already highly parallelized and optimized using Farrar’s striped processing pattern with Intel SSE2 instruction set extension. Results A new SIMD vectorization of the Viterbi decoding algorithm is proposed, based on an SSE2 inter-task parallelization approach similar to the DNA alignment algorithm proposed by Rognes. Besides this alternative vectorization scheme, the proposed implementation also introduces a new partitioning of the Markov model that allows a significantly more efficient exploitation of the cache locality. Such optimization, together with an improved loading of the emission scores, allows the achievement of a constant processing throughput, regardless of the innermost-cache size and of the dimension of the considered model. Conclusions The proposed optimized vectorization of the Viterbi decoding algorithm was extensively evaluated and compared with the HMMER3 decoder to process DNA and protein datasets, proving to be a rather competitive alternative implementation. Being always faster than the already highly optimized ViterbiFilter implementation of HMMER3, the proposed Cache-Oblivious Parallel SIMD Viterbi (COPS) implementation provides a constant throughput and offers a processing speedup as high as two times faster, depending on the model’s size. PMID:24884826

Parallel evolutionary computation in bioinformatics applications.

PubMed

Pinho, Jorge; Sobral, João Luis; Rocha, Miguel

2013-05-01

A large number of optimization problems within the field of Bioinformatics require methods able to handle its inherent complexity (e.g. NP-hard problems) and also demand increased computational efforts. In this context, the use of parallel architectures is a necessity. In this work, we propose ParJECoLi, a Java based library that offers a large set of metaheuristic methods (such as Evolutionary Algorithms) and also addresses the issue of its efficient execution on a wide range of parallel architectures. The proposed approach focuses on the easiness of use, making the adaptation to distinct parallel environments (multicore, cluster, grid) transparent to the user. Indeed, this work shows how the development of the optimization library can proceed independently of its adaptation for several architectures, making use of Aspect-Oriented Programming. The pluggable nature of parallelism related modules allows the user to easily configure its environment, adding parallelism modules to the base source code when needed. The performance of the platform is validated with two case studies within biological model optimization. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

High figure of merit ultra-compact 3-channel parallel-connected photonic crystal mini-hexagonal-H1 defect microcavity sensor array

NASA Astrophysics Data System (ADS)

Wang, Chunhong; Sun, Fujun; Fu, Zhongyuan; Ding, Zhaoxiang; Wang, Chao; Zhou, Jian; Wang, Jiawen; Tian, Huiping

2017-08-01

In this paper, a photonic crystal (PhC) butt-coupled mini-hexagonal-H1 defect (MHHD) microcavity sensor is proposed. The MHHD microcavity is designed by introducing six mini-holes into the initial H1 defect region. Further, based on a well-designed 1 ×3 PhC Beam Splitter and three optimal MHHD microcavity sensors with different lattice constants (a), a 3-channel parallel-connected PhC sensor array on monolithic silicon on insulator (SOI) is proposed. Finite-difference time-domain (FDTD) simulations method is performed to demonstrate the high performance of our structures. As statistics show, the quality factor (Q) of our optimal MHHD microcavity attains higher than 7×104, while the sensitivity (S) reaches up to 233 nm/RIU(RIU = refractive index unit). Thus, the figure of merit (FOM) >104 of the sensor is obtained, which is enhanced by two orders of magnitude compared to the previous butt-coupled sensors [1-4]. As for the 3-channel parallel-connected PhC MHHD microcavity sensor array, the FOMs of three independent MHHD microcavity sensors are 8071, 8250 and 8250, respectively. In addition, the total footprint of the proposed 3-channel parallel-connected PhC sensor array is ultra-compactness of 12.5 μm ×31 μm (width × length). Therefore, the proposed high FOM sensor array is an ideal platform for realizing ultra-compact highly parallel refractive index (RI) sensing.

Solving the multiple-set split equality common fixed-point problem of firmly quasi-nonexpansive operators.

PubMed

Zhao, Jing; Zong, Haili

2018-01-01

In this paper, we propose parallel and cyclic iterative algorithms for solving the multiple-set split equality common fixed-point problem of firmly quasi-nonexpansive operators. We also combine the process of cyclic and parallel iterative methods and propose two mixed iterative algorithms. Our several algorithms do not need any prior information about the operator norms. Under mild assumptions, we prove weak convergence of the proposed iterative sequences in Hilbert spaces. As applications, we obtain several iterative algorithms to solve the multiple-set split equality problem.

Modified current follower-based immittance function simulators

NASA Astrophysics Data System (ADS)

Alpaslan, Halil; Yuce, Erkan

2017-12-01

In this paper, four immittance function simulators consisting of a single modified current follower with single Z- terminal and a minimum number of passive components are proposed. The first proposed circuit can provide +L parallel with +R and the second proposed one can realise -L parallel with -R. The third proposed structure can provide +L series with +R and the fourth proposed one can realise -L series with -R. However, all the proposed immittance function simulators need a single resistive matching constraint. Parasitic impedance effects on all the proposed immittance function simulators are investigated. A second-order current-mode (CM) high-pass filter derived from the first proposed immittance function simulator is given as an application example. Also, a second-order CM low-pass filter derived from the third proposed immittance function simulator is given as an application example. A number of simulation results based on SPICE programme and an experimental test result are given to verify the theory.

A fully coupled method for massively parallel simulation of hydraulically driven fractures in 3-dimensions: FULLY COUPLED PARALLEL SIMULATION OF HYDRAULIC FRACTURES IN 3-D

DOE PAGES

Settgast, Randolph R.; Fu, Pengcheng; Walsh, Stuart D. C.; ...

2016-09-18

This study describes a fully coupled finite element/finite volume approach for simulating field-scale hydraulically driven fractures in three dimensions, using massively parallel computing platforms. The proposed method is capable of capturing realistic representations of local heterogeneities, layering and natural fracture networks in a reservoir. A detailed description of the numerical implementation is provided, along with numerical studies comparing the model with both analytical solutions and experimental results. The results demonstrate the effectiveness of the proposed method for modeling large-scale problems involving hydraulically driven fractures in three dimensions.

Research on the supercapacitor support schemes for LVRT of variable-frequency drive in the thermal power plant

NASA Astrophysics Data System (ADS)

Han, Qiguo; Zhu, Kai; Shi, Wenming; Wu, Kuayu; Chen, Kai

2018-02-01

In order to solve the problem of low voltage ride through(LVRT) of the major auxiliary equipment’s variable-frequency drive (VFD) in thermal power plant, the scheme of supercapacitor paralleled in the DC link of VFD is put forward, furthermore, two solutions of direct parallel support and voltage boost parallel support of supercapacitor are proposed. The capacitor values for the relevant motor loads are calculated according to the law of energy conservation, and they are verified by Matlab simulation. At last, a set of test prototype is set up, and the test results prove the feasibility of the proposed schemes.

A fully coupled method for massively parallel simulation of hydraulically driven fractures in 3-dimensions: FULLY COUPLED PARALLEL SIMULATION OF HYDRAULIC FRACTURES IN 3-D

DOE Office of Scientific and Technical Information (OSTI.GOV)

Settgast, Randolph R.; Fu, Pengcheng; Walsh, Stuart D. C.

This study describes a fully coupled finite element/finite volume approach for simulating field-scale hydraulically driven fractures in three dimensions, using massively parallel computing platforms. The proposed method is capable of capturing realistic representations of local heterogeneities, layering and natural fracture networks in a reservoir. A detailed description of the numerical implementation is provided, along with numerical studies comparing the model with both analytical solutions and experimental results. The results demonstrate the effectiveness of the proposed method for modeling large-scale problems involving hydraulically driven fractures in three dimensions.

Accelerating separable footprint (SF) forward and back projection on GPU

NASA Astrophysics Data System (ADS)

Xie, Xiaobin; McGaffin, Madison G.; Long, Yong; Fessler, Jeffrey A.; Wen, Minhua; Lin, James

2017-03-01

Statistical image reconstruction (SIR) methods for X-ray CT can improve image quality and reduce radiation dosages over conventional reconstruction methods, such as filtered back projection (FBP). However, SIR methods require much longer computation time. The separable footprint (SF) forward and back projection technique simplifies the calculation of intersecting volumes of image voxels and finite-size beams in a way that is both accurate and efficient for parallel implementation. We propose a new method to accelerate the SF forward and back projection on GPU with NVIDIA's CUDA environment. For the forward projection, we parallelize over all detector cells. For the back projection, we parallelize over all 3D image voxels. The simulation results show that the proposed method is faster than the acceleration method of the SF projectors proposed by Wu and Fessler.13 We further accelerate the proposed method using multiple GPUs. The results show that the computation time is reduced approximately proportional to the number of GPUs.

Computational strategies for three-dimensional flow simulations on distributed computer systems. Ph.D. Thesis Semiannual Status Report, 15 Aug. 1993 - 15 Feb. 1994

NASA Technical Reports Server (NTRS)

Weed, Richard Allen; Sankar, L. N.

1994-01-01

An increasing amount of research activity in computational fluid dynamics has been devoted to the development of efficient algorithms for parallel computing systems. The increasing performance to price ratio of engineering workstations has led to research to development procedures for implementing a parallel computing system composed of distributed workstations. This thesis proposal outlines an ongoing research program to develop efficient strategies for performing three-dimensional flow analysis on distributed computing systems. The PVM parallel programming interface was used to modify an existing three-dimensional flow solver, the TEAM code developed by Lockheed for the Air Force, to function as a parallel flow solver on clusters of workstations. Steady flow solutions were generated for three different wing and body geometries to validate the code and evaluate code performance. The proposed research will extend the parallel code development to determine the most efficient strategies for unsteady flow simulations.

Analysis of series resonant converter with series-parallel connection

NASA Astrophysics Data System (ADS)

Lin, Bor-Ren; Huang, Chien-Lan

2011-02-01

In this study, a parallel inductor-inductor-capacitor (LLC) resonant converter series-connected on the primary side and parallel-connected on the secondary side is presented for server power supply systems. Based on series resonant behaviour, the power metal-oxide-semiconductor field-effect transistors are turned on at zero voltage switching and the rectifier diodes are turned off at zero current switching. Thus, the switching losses on the power semiconductors are reduced. In the proposed converter, the primary windings of the two LLC converters are connected in series. Thus, the two converters have the same primary currents to ensure that they can supply the balance load current. On the output side, two LLC converters are connected in parallel to share the load current and to reduce the current stress on the secondary windings and the rectifier diodes. In this article, the principle of operation, steady-state analysis and design considerations of the proposed converter are provided and discussed. Experiments with a laboratory prototype with a 24 V/21 A output for server power supply were performed to verify the effectiveness of the proposed converter.

Bit-parallel arithmetic in a massively-parallel associative processor

NASA Technical Reports Server (NTRS)

Scherson, Isaac D.; Kramer, David A.; Alleyne, Brian D.

1992-01-01

A simple but powerful new architecture based on a classical associative processor model is presented. Algorithms for performing the four basic arithmetic operations both for integer and floating point operands are described. For m-bit operands, the proposed architecture makes it possible to execute complex operations in O(m) cycles as opposed to O(m exp 2) for bit-serial machines. A word-parallel, bit-parallel, massively-parallel computing system can be constructed using this architecture with VLSI technology. The operation of this system is demonstrated for the fast Fourier transform and matrix multiplication.

A PIPO Boost Converter with Low Ripple and Medium Current Application

NASA Astrophysics Data System (ADS)

Bandri, S.; Sofian, A.; Ismail, F.

2018-04-01

This paper presents a Parallel Input Parallel Output (PIPO) boost converter is proposed to gain power ability of converter, and reduce current inductors. The proposed technique will distribute current for n-parallel inductor and switching component. Four parallel boost converters implement on input voltage 20.5Vdc to generate output voltage 28.8Vdc. The PIPO boost converter applied phase shift pulse width modulation which will compare with conventional PIPO boost converters by using a similar pulse for every switching component. The current ripple reduction shows an advantage PIPO boost converter then conventional boost converter. Varies loads and duty cycle will be simulated and analyzed to verify the performance of PIPO boost converter. Finally, the unbalance of current inductor is able to be verified on four area of duty cycle in less than 0.6.

Toward a Model Framework of Generalized Parallel Componential Processing of Multi-Symbol Numbers

ERIC Educational Resources Information Center

Huber, Stefan; Cornelsen, Sonja; Moeller, Korbinian; Nuerk, Hans-Christoph

2015-01-01

In this article, we propose and evaluate a new model framework of parallel componential multi-symbol number processing, generalizing the idea of parallel componential processing of multi-digit numbers to the case of negative numbers by considering the polarity signs similar to single digits. In a first step, we evaluated this account by defining…

Parallel and Serial Grouping of Image Elements in Visual Perception

ERIC Educational Resources Information Center

Houtkamp, Roos; Roelfsema, Pieter R.

2010-01-01

The visual system groups image elements that belong to an object and segregates them from other objects and the background. Important cues for this grouping process are the Gestalt criteria, and most theories propose that these are applied in parallel across the visual scene. Here, we find that Gestalt grouping can indeed occur in parallel in some…

Traffic Simulations on Parallel Computers Using Domain Decomposition Techniques

DOT National Transportation Integrated Search

1995-01-01

Large scale simulations of Intelligent Transportation Systems (ITS) can only be acheived by using the computing resources offered by parallel computing architectures. Domain decomposition techniques are proposed which allow the performance of traffic...

An annealed chaotic maximum neural network for bipartite subgraph problem.

PubMed

Wang, Jiahai; Tang, Zheng; Wang, Ronglong

2004-04-01

In this paper, based on maximum neural network, we propose a new parallel algorithm that can help the maximum neural network escape from local minima by including a transient chaotic neurodynamics for bipartite subgraph problem. The goal of the bipartite subgraph problem, which is an NP- complete problem, is to remove the minimum number of edges in a given graph such that the remaining graph is a bipartite graph. Lee et al. presented a parallel algorithm using the maximum neural model (winner-take-all neuron model) for this NP- complete problem. The maximum neural model always guarantees a valid solution and greatly reduces the search space without a burden on the parameter-tuning. However, the model has a tendency to converge to a local minimum easily because it is based on the steepest descent method. By adding a negative self-feedback to the maximum neural network, we proposed a new parallel algorithm that introduces richer and more flexible chaotic dynamics and can prevent the network from getting stuck at local minima. After the chaotic dynamics vanishes, the proposed algorithm is then fundamentally reined by the gradient descent dynamics and usually converges to a stable equilibrium point. The proposed algorithm has the advantages of both the maximum neural network and the chaotic neurodynamics. A large number of instances have been simulated to verify the proposed algorithm. The simulation results show that our algorithm finds the optimum or near-optimum solution for the bipartite subgraph problem superior to that of the best existing parallel algorithms.

A parallel algorithm for generation and assembly of finite element stiffness and mass matrices

NASA Technical Reports Server (NTRS)

Storaasli, O. O.; Carmona, E. A.; Nguyen, D. T.; Baddourah, M. A.

1991-01-01

A new algorithm is proposed for parallel generation and assembly of the finite element stiffness and mass matrices. The proposed assembly algorithm is based on a node-by-node approach rather than the more conventional element-by-element approach. The new algorithm's generality and computation speed-up when using multiple processors are demonstrated for several practical applications on multi-processor Cray Y-MP and Cray 2 supercomputers.

Implementation of a parallel protein structure alignment service on cloud.

PubMed

Hung, Che-Lun; Lin, Yaw-Ling

2013-01-01

Protein structure alignment has become an important strategy by which to identify evolutionary relationships between protein sequences. Several alignment tools are currently available for online comparison of protein structures. In this paper, we propose a parallel protein structure alignment service based on the Hadoop distribution framework. This service includes a protein structure alignment algorithm, a refinement algorithm, and a MapReduce programming model. The refinement algorithm refines the result of alignment. To process vast numbers of protein structures in parallel, the alignment and refinement algorithms are implemented using MapReduce. We analyzed and compared the structure alignments produced by different methods using a dataset randomly selected from the PDB database. The experimental results verify that the proposed algorithm refines the resulting alignments more accurately than existing algorithms. Meanwhile, the computational performance of the proposed service is proportional to the number of processors used in our cloud platform.

Implementation of a Parallel Protein Structure Alignment Service on Cloud

PubMed Central

Hung, Che-Lun; Lin, Yaw-Ling

2013-01-01

Protein structure alignment has become an important strategy by which to identify evolutionary relationships between protein sequences. Several alignment tools are currently available for online comparison of protein structures. In this paper, we propose a parallel protein structure alignment service based on the Hadoop distribution framework. This service includes a protein structure alignment algorithm, a refinement algorithm, and a MapReduce programming model. The refinement algorithm refines the result of alignment. To process vast numbers of protein structures in parallel, the alignment and refinement algorithms are implemented using MapReduce. We analyzed and compared the structure alignments produced by different methods using a dataset randomly selected from the PDB database. The experimental results verify that the proposed algorithm refines the resulting alignments more accurately than existing algorithms. Meanwhile, the computational performance of the proposed service is proportional to the number of processors used in our cloud platform. PMID:23671842

Multi-LED parallel transmission for long distance underwater VLC system with one SPAD receiver

NASA Astrophysics Data System (ADS)

Wang, Chao; Yu, Hong-Yi; Zhu, Yi-Jun; Wang, Tao; Ji, Ya-Wei

2018-03-01

In this paper, a multiple light emitting diode (LED) chips parallel transmission (Multi-LED-PT) scheme for underwater visible light communication system with one photon-counting single photon avalanche diode (SPAD) receiver is proposed. As the lamp always consists of multi-LED chips, the data rate could be improved when we drive these multi-LED chips parallel by using the interleaver-division-multiplexing technique. For each chip, the on-off-keying modulation is used to reduce the influence of clipping. Then a serial successive interference cancellation detection algorithm based on ideal Poisson photon-counting channel by the SPAD is proposed. Finally, compared to the SPAD-based direct current-biased optical orthogonal frequency division multiplexing system, the proposed Multi-LED-PT system could improve the error-rate performance and anti-nonlinearity performance significantly under the effects of absorption, scattering and weak turbulence-induced channel fading together.

A visual parallel-BCI speller based on the time-frequency coding strategy.

PubMed

Xu, Minpeng; Chen, Long; Zhang, Lixin; Qi, Hongzhi; Ma, Lan; Tang, Jiabei; Wan, Baikun; Ming, Dong

2014-04-01

Spelling is one of the most important issues in brain-computer interface (BCI) research. This paper is to develop a visual parallel-BCI speller system based on the time-frequency coding strategy in which the sub-speller switching among four simultaneously presented sub-spellers and the character selection are identified in a parallel mode. The parallel-BCI speller was constituted by four independent P300+SSVEP-B (P300 plus SSVEP blocking) spellers with different flicker frequencies, thereby all characters had a specific time-frequency code. To verify its effectiveness, 11 subjects were involved in the offline and online spellings. A classification strategy was designed to recognize the target character through jointly using the canonical correlation analysis and stepwise linear discriminant analysis. Online spellings showed that the proposed parallel-BCI speller had a high performance, reaching the highest information transfer rate of 67.4 bit min(-1), with an average of 54.0 bit min(-1) and 43.0 bit min(-1) in the three rounds and five rounds, respectively. The results indicated that the proposed parallel-BCI could be effectively controlled by users with attention shifting fluently among the sub-spellers, and highly improved the BCI spelling performance.

A 0.13-µm implementation of 5 Gb/s and 3-mW folded parallel architecture for AES algorithm

NASA Astrophysics Data System (ADS)

Rahimunnisa, K.; Karthigaikumar, P.; Kirubavathy, J.; Jayakumar, J.; Kumar, S. Suresh

2014-02-01

A new architecture for encrypting and decrypting the confidential data using Advanced Encryption Standard algorithm is presented in this article. This structure combines the folded structure with parallel architecture to increase the throughput. The whole architecture achieved high throughput with less power. The proposed architecture is implemented in 0.13-µm Complementary metal-oxide-semiconductor (CMOS) technology. The proposed structure is compared with different existing structures, and from the result it is proved that the proposed structure gives higher throughput and less power compared to existing works.

Experimental characterization of a binary actuated parallel manipulator

NASA Astrophysics Data System (ADS)

Giuseppe, Carbone

2016-05-01

This paper describes the BAPAMAN (Binary Actuated Parallel MANipulator) series of parallel manipulators that has been conceived at Laboratory of Robotics and Mechatronics (LARM). Basic common characteristics of BAPAMAN series are described. In particular, it is outlined the use of a reduced number of active degrees of freedom, the use of design solutions with flexural joints and Shape Memory Alloy (SMA) actuators for achieving miniaturization, cost reduction and easy operation features. Given the peculiarities of BAPAMAN architecture, specific experimental tests have been proposed and carried out with the aim to validate the proposed design and to evaluate the practical operation performance and the characteristics of a built prototype, in particular, in terms of operation and workspace characteristics.

Parallel processing architecture for computing inverse differential kinematic equations of the PUMA arm

NASA Technical Reports Server (NTRS)

Hsia, T. C.; Lu, G. Z.; Han, W. H.

1987-01-01

In advanced robot control problems, on-line computation of inverse Jacobian solution is frequently required. Parallel processing architecture is an effective way to reduce computation time. A parallel processing architecture is developed for the inverse Jacobian (inverse differential kinematic equation) of the PUMA arm. The proposed pipeline/parallel algorithm can be inplemented on an IC chip using systolic linear arrays. This implementation requires 27 processing cells and 25 time units. Computation time is thus significantly reduced.

Design and implementation of a novel modal space active force control concept for spatial multi-DOF parallel robotic manipulators actuated by electrical actuators.

PubMed

Yang, Chifu; Zhao, Jinsong; Li, Liyi; Agrawal, Sunil K

2018-01-01

Robotic spine brace based on parallel-actuated robotic system is a new device for treatment and sensing of scoliosis, however, the strong dynamic coupling and anisotropy problem of parallel manipulators result in accuracy loss of rehabilitation force control, including big error in direction and value of force. A novel active force control strategy named modal space force control is proposed to solve these problems. Considering the electrical driven system and contact environment, the mathematical model of spatial parallel manipulator is built. The strong dynamic coupling problem in force field is described via experiments as well as the anisotropy problem of work space of parallel manipulators. The effects of dynamic coupling on control design and performances are discussed, and the influences of anisotropy on accuracy are also addressed. With mass/inertia matrix and stiffness matrix of parallel manipulators, a modal matrix can be calculated by using eigenvalue decomposition. Making use of the orthogonality of modal matrix with mass matrix of parallel manipulators, the strong coupled dynamic equations expressed in work space or joint space of parallel manipulator may be transformed into decoupled equations formulated in modal space. According to this property, each force control channel is independent of others in the modal space, thus we proposed modal space force control concept which means the force controller is designed in modal space. A modal space active force control is designed and implemented with only a simple PID controller employed as exampled control method to show the differences, uniqueness, and benefits of modal space force control. Simulation and experimental results show that the proposed modal space force control concept can effectively overcome the effects of the strong dynamic coupling and anisotropy problem in the physical space, and modal space force control is thus a very useful control framework, which is better than the current joint space control and work space control. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

[CMACPAR an modified parallel neuro-controller for control processes].

PubMed

Ramos, E; Surós, R

1999-01-01

CMACPAR is a Parallel Neurocontroller oriented to real time systems as for example Control Processes. Its characteristics are mainly a fast learning algorithm, a reduced number of calculations, great generalization capacity, local learning and intrinsic parallelism. This type of neurocontroller is used in real time applications required by refineries, hydroelectric centers, factories, etc. In this work we present the analysis and the parallel implementation of a modified scheme of the Cerebellar Model CMAC for the n-dimensional space projection using a mean granularity parallel neurocontroller. The proposed memory management allows for a significant memory reduction in training time and required memory size.

Parallelizing flow-accumulation calculations on graphics processing units—From iterative DEM preprocessing algorithm to recursive multiple-flow-direction algorithm

NASA Astrophysics Data System (ADS)

Qin, Cheng-Zhi; Zhan, Lijun

2012-06-01

As one of the important tasks in digital terrain analysis, the calculation of flow accumulations from gridded digital elevation models (DEMs) usually involves two steps in a real application: (1) using an iterative DEM preprocessing algorithm to remove the depressions and flat areas commonly contained in real DEMs, and (2) using a recursive flow-direction algorithm to calculate the flow accumulation for every cell in the DEM. Because both algorithms are computationally intensive, quick calculation of the flow accumulations from a DEM (especially for a large area) presents a practical challenge to personal computer (PC) users. In recent years, rapid increases in hardware capacity of the graphics processing units (GPUs) provided in modern PCs have made it possible to meet this challenge in a PC environment. Parallel computing on GPUs using a compute-unified-device-architecture (CUDA) programming model has been explored to speed up the execution of the single-flow-direction algorithm (SFD). However, the parallel implementation on a GPU of the multiple-flow-direction (MFD) algorithm, which generally performs better than the SFD algorithm, has not been reported. Moreover, GPU-based parallelization of the DEM preprocessing step in the flow-accumulation calculations has not been addressed. This paper proposes a parallel approach to calculate flow accumulations (including both iterative DEM preprocessing and a recursive MFD algorithm) on a CUDA-compatible GPU. For the parallelization of an MFD algorithm (MFD-md), two different parallelization strategies using a GPU are explored. The first parallelization strategy, which has been used in the existing parallel SFD algorithm on GPU, has the problem of computing redundancy. Therefore, we designed a parallelization strategy based on graph theory. The application results show that the proposed parallel approach to calculate flow accumulations on a GPU performs much faster than either sequential algorithms or other parallel GPU-based algorithms based on existing parallelization strategies.

Enhancing sedimentation by improving flow conditions using parallel retrofit baffles.

PubMed

He, Cheng; Scott, Eric; Rochfort, Quintin

2015-09-01

In this study, placing parallel-connected baffles in the vicinity of the inlet was proposed to improve hydraulic conditions for enhancing TSS (total suspended solids) removal. The purpose of the retrofit baffle design is to divide the large and fast inflow into smaller and slower flows to increase flow uniformity. This avoids short-circuiting and increases residence time in the sedimentation basin. The newly proposed parallel-connected baffle configuration was assessed in the laboratory by comparing its TSS removal performance and the optimal flow residence time with those from the widely used series-connected baffles. The experimental results showed that the parallel-connected baffles outperformed the series-connected baffles because it could disperse flow faster and in less space by splitting the large inflow into many small branches instead of solely depending on flow internal friction over a longer flow path, as was the case under the series-connected baffles. Being able to dampen faster flow before entering the sedimentation basin is critical to reducing the possibility of disturbing any settled particles, especially under high inflow conditions. Also, for a large sedimentation basin, it may be more economically feasible to deploy the proposed parallel retrofit baffle in the vicinity of the inlet than series-connected baffles throughout the entire settling basin. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

An information-theoretic approach to motor action decoding with a reconfigurable parallel architecture.

PubMed

Craciun, Stefan; Brockmeier, Austin J; George, Alan D; Lam, Herman; Príncipe, José C

2011-01-01

Methods for decoding movements from neural spike counts using adaptive filters often rely on minimizing the mean-squared error. However, for non-Gaussian distribution of errors, this approach is not optimal for performance. Therefore, rather than using probabilistic modeling, we propose an alternate non-parametric approach. In order to extract more structure from the input signal (neuronal spike counts) we propose using minimum error entropy (MEE), an information-theoretic approach that minimizes the error entropy as part of an iterative cost function. However, the disadvantage of using MEE as the cost function for adaptive filters is the increase in computational complexity. In this paper we present a comparison between the decoding performance of the analytic Wiener filter and a linear filter trained with MEE, which is then mapped to a parallel architecture in reconfigurable hardware tailored to the computational needs of the MEE filter. We observe considerable speedup from the hardware design. The adaptation of filter weights for the multiple-input, multiple-output linear filters, necessary in motor decoding, is a highly parallelizable algorithm. It can be decomposed into many independent computational blocks with a parallel architecture readily mapped to a field-programmable gate array (FPGA) and scales to large numbers of neurons. By pipelining and parallelizing independent computations in the algorithm, the proposed parallel architecture has sublinear increases in execution time with respect to both window size and filter order.

Cedar Project---Original goals and progress to date

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cybenko, G.; Kuck, D.; Padua, D.

1990-11-28

This work encompasses a broad attack on high speed parallel processing. Hardware, software, applications development, and performance evaluation and visualization as well as research topics are proposed. Our goal is to develop practical parallel processing for the 1990's.

New Bandwidth Efficient Parallel Concatenated Coding Schemes

NASA Technical Reports Server (NTRS)

Denedetto, S.; Divsalar, D.; Montorsi, G.; Pollara, F.

1996-01-01

We propose a new solution to parallel concatenation of trellis codes with multilevel amplitude/phase modulations and a suitable iterative decoding structure. Examples are given for throughputs 2 bits/sec/Hz with 8PSK and 16QAM signal constellations.

Optimization by nonhierarchical asynchronous decomposition

NASA Technical Reports Server (NTRS)

Shankar, Jayashree; Ribbens, Calvin J.; Haftka, Raphael T.; Watson, Layne T.

1992-01-01

Large scale optimization problems are tractable only if they are somehow decomposed. Hierarchical decompositions are inappropriate for some types of problems and do not parallelize well. Sobieszczanski-Sobieski has proposed a nonhierarchical decomposition strategy for nonlinear constrained optimization that is naturally parallel. Despite some successes on engineering problems, the algorithm as originally proposed fails on simple two dimensional quadratic programs. The algorithm is carefully analyzed for quadratic programs, and a number of modifications are suggested to improve its robustness.

Signal-domain optimization metrics for MPRAGE RF pulse design in parallel transmission at 7 tesla.

PubMed

Gras, V; Vignaud, A; Mauconduit, F; Luong, M; Amadon, A; Le Bihan, D; Boulant, N

2016-11-01

Standard radiofrequency pulse design strategies focus on minimizing the deviation of the flip angle from a target value, which is sufficient but not necessary for signal homogeneity. An alternative approach, based directly on the signal, here is proposed for the MPRAGE sequence, and is developed in the parallel transmission framework with the use of the k T -points parametrization. The flip angle-homogenizing and the proposed methods were investigated numerically under explicit power and specific absorption rate constraints and tested experimentally in vivo on a 7 T parallel transmission system enabling real time local specific absorption rate monitoring. Radiofrequency pulse performance was assessed by a careful analysis of the signal and contrast between white and gray matter. Despite a slight reduction of the flip angle uniformity, an improved signal and contrast homogeneity with a significant reduction of the specific absorption rate was achieved with the proposed metric in comparison with standard pulse designs. The proposed joint optimization of the inversion and excitation pulses enables significant reduction of the specific absorption rate in the MPRAGE sequence while preserving image quality. The work reported thus unveils a possible direction to increase the potential of ultra-high field MRI and parallel transmission. Magn Reson Med 76:1431-1442, 2016. © 2015 International Society for Magnetic Resonance in Medicine. © 2015 International Society for Magnetic Resonance in Medicine.

An Asynchronous Many-Task Implementation of In-Situ Statistical Analysis using Legion.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pebay, Philippe Pierre; Bennett, Janine Camille

2015-11-01

In this report, we propose a framework for the design and implementation of in-situ analy- ses using an asynchronous many-task (AMT) model, using the Legion programming model together with the MiniAero mini-application as a surrogate for full-scale parallel scientific computing applications. The bulk of this work consists of converting the Learn/Derive/Assess model which we had initially developed for parallel statistical analysis using MPI [PTBM11], from a SPMD to an AMT model. In this goal, we propose an original use of the concept of Legion logical regions as a replacement for the parallel communication schemes used for the only operation ofmore » the statistics engines that require explicit communication. We then evaluate this proposed scheme in a shared memory environment, using the Legion port of MiniAero as a proxy for a full-scale scientific application, as a means to provide input data sets of variable size for the in-situ statistical analyses in an AMT context. We demonstrate in particular that the approach has merit, and warrants further investigation, in collaboration with ongoing efforts to improve the overall parallel performance of the Legion system.« less

Big data driven cycle time parallel prediction for production planning in wafer manufacturing

NASA Astrophysics Data System (ADS)

Wang, Junliang; Yang, Jungang; Zhang, Jie; Wang, Xiaoxi; Zhang, Wenjun Chris

2018-07-01

Cycle time forecasting (CTF) is one of the most crucial issues for production planning to keep high delivery reliability in semiconductor wafer fabrication systems (SWFS). This paper proposes a novel data-intensive cycle time (CT) prediction system with parallel computing to rapidly forecast the CT of wafer lots with large datasets. First, a density peak based radial basis function network (DP-RBFN) is designed to forecast the CT with the diverse and agglomerative CT data. Second, the network learning method based on a clustering technique is proposed to determine the density peak. Third, a parallel computing approach for network training is proposed in order to speed up the training process with large scaled CT data. Finally, an experiment with respect to SWFS is presented, which demonstrates that the proposed CTF system can not only speed up the training process of the model but also outperform the radial basis function network, the back-propagation-network and multivariate regression methodology based CTF methods in terms of the mean absolute deviation and standard deviation.

Cloud computing-based TagSNP selection algorithm for human genome data.

PubMed

Hung, Che-Lun; Chen, Wen-Pei; Hua, Guan-Jie; Zheng, Huiru; Tsai, Suh-Jen Jane; Lin, Yaw-Ling

2015-01-05

Single nucleotide polymorphisms (SNPs) play a fundamental role in human genetic variation and are used in medical diagnostics, phylogeny construction, and drug design. They provide the highest-resolution genetic fingerprint for identifying disease associations and human features. Haplotypes are regions of linked genetic variants that are closely spaced on the genome and tend to be inherited together. Genetics research has revealed SNPs within certain haplotype blocks that introduce few distinct common haplotypes into most of the population. Haplotype block structures are used in association-based methods to map disease genes. In this paper, we propose an efficient algorithm for identifying haplotype blocks in the genome. In chromosomal haplotype data retrieved from the HapMap project website, the proposed algorithm identified longer haplotype blocks than an existing algorithm. To enhance its performance, we extended the proposed algorithm into a parallel algorithm that copies data in parallel via the Hadoop MapReduce framework. The proposed MapReduce-paralleled combinatorial algorithm performed well on real-world data obtained from the HapMap dataset; the improvement in computational efficiency was proportional to the number of processors used.

An L1-norm phase constraint for half-Fourier compressed sensing in 3D MR imaging.

PubMed

Li, Guobin; Hennig, Jürgen; Raithel, Esther; Büchert, Martin; Paul, Dominik; Korvink, Jan G; Zaitsev, Maxim

2015-10-01

In most half-Fourier imaging methods, explicit phase replacement is used. In combination with parallel imaging, or compressed sensing, half-Fourier reconstruction is usually performed in a separate step. The purpose of this paper is to report that integration of half-Fourier reconstruction into iterative reconstruction minimizes reconstruction errors. The L1-norm phase constraint for half-Fourier imaging proposed in this work is compared with the L2-norm variant of the same algorithm, with several typical half-Fourier reconstruction methods. Half-Fourier imaging with the proposed phase constraint can be seamlessly combined with parallel imaging and compressed sensing to achieve high acceleration factors. In simulations and in in-vivo experiments half-Fourier imaging with the proposed L1-norm phase constraint enables superior performance both reconstruction of image details and with regard to robustness against phase estimation errors. The performance and feasibility of half-Fourier imaging with the proposed L1-norm phase constraint is reported. Its seamless combination with parallel imaging and compressed sensing enables use of greater acceleration in 3D MR imaging.

Cloud Computing-Based TagSNP Selection Algorithm for Human Genome Data

PubMed Central

Hung, Che-Lun; Chen, Wen-Pei; Hua, Guan-Jie; Zheng, Huiru; Tsai, Suh-Jen Jane; Lin, Yaw-Ling

2015-01-01

Single nucleotide polymorphisms (SNPs) play a fundamental role in human genetic variation and are used in medical diagnostics, phylogeny construction, and drug design. They provide the highest-resolution genetic fingerprint for identifying disease associations and human features. Haplotypes are regions of linked genetic variants that are closely spaced on the genome and tend to be inherited together. Genetics research has revealed SNPs within certain haplotype blocks that introduce few distinct common haplotypes into most of the population. Haplotype block structures are used in association-based methods to map disease genes. In this paper, we propose an efficient algorithm for identifying haplotype blocks in the genome. In chromosomal haplotype data retrieved from the HapMap project website, the proposed algorithm identified longer haplotype blocks than an existing algorithm. To enhance its performance, we extended the proposed algorithm into a parallel algorithm that copies data in parallel via the Hadoop MapReduce framework. The proposed MapReduce-paralleled combinatorial algorithm performed well on real-world data obtained from the HapMap dataset; the improvement in computational efficiency was proportional to the number of processors used. PMID:25569088

Efficiency Analysis of the Parallel Implementation of the SIMPLE Algorithm on Multiprocessor Computers

NASA Astrophysics Data System (ADS)

Lashkin, S. V.; Kozelkov, A. S.; Yalozo, A. V.; Gerasimov, V. Yu.; Zelensky, D. K.

2017-12-01

This paper describes the details of the parallel implementation of the SIMPLE algorithm for numerical solution of the Navier-Stokes system of equations on arbitrary unstructured grids. The iteration schemes for the serial and parallel versions of the SIMPLE algorithm are implemented. In the description of the parallel implementation, special attention is paid to computational data exchange among processors under the condition of the grid model decomposition using fictitious cells. We discuss the specific features for the storage of distributed matrices and implementation of vector-matrix operations in parallel mode. It is shown that the proposed way of matrix storage reduces the number of interprocessor exchanges. A series of numerical experiments illustrates the effect of the multigrid SLAE solver tuning on the general efficiency of the algorithm; the tuning involves the types of the cycles used (V, W, and F), the number of iterations of a smoothing operator, and the number of cells for coarsening. Two ways (direct and indirect) of efficiency evaluation for parallelization of the numerical algorithm are demonstrated. The paper presents the results of solving some internal and external flow problems with the evaluation of parallelization efficiency by two algorithms. It is shown that the proposed parallel implementation enables efficient computations for the problems on a thousand processors. Based on the results obtained, some general recommendations are made for the optimal tuning of the multigrid solver, as well as for selecting the optimal number of cells per processor.

Externally Calibrated Parallel Imaging for 3D Multispectral Imaging Near Metallic Implants Using Broadband Ultrashort Echo Time Imaging

PubMed Central

Wiens, Curtis N.; Artz, Nathan S.; Jang, Hyungseok; McMillan, Alan B.; Reeder, Scott B.

2017-01-01

Purpose To develop an externally calibrated parallel imaging technique for three-dimensional multispectral imaging (3D-MSI) in the presence of metallic implants. Theory and Methods A fast, ultrashort echo time (UTE) calibration acquisition is proposed to enable externally calibrated parallel imaging techniques near metallic implants. The proposed calibration acquisition uses a broadband radiofrequency (RF) pulse to excite the off-resonance induced by the metallic implant, fully phase-encoded imaging to prevent in-plane distortions, and UTE to capture rapidly decaying signal. The performance of the externally calibrated parallel imaging reconstructions was assessed using phantoms and in vivo examples. Results Phantom and in vivo comparisons to self-calibrated parallel imaging acquisitions show that significant reductions in acquisition times can be achieved using externally calibrated parallel imaging with comparable image quality. Acquisition time reductions are particularly large for fully phase-encoded methods such as spectrally resolved fully phase-encoded three-dimensional (3D) fast spin-echo (SR-FPE), in which scan time reductions of up to 8 min were obtained. Conclusion A fully phase-encoded acquisition with broadband excitation and UTE enabled externally calibrated parallel imaging for 3D-MSI, eliminating the need for repeated calibration regions at each frequency offset. Significant reductions in acquisition time can be achieved, particularly for fully phase-encoded methods like SR-FPE. PMID:27403613

Big Data: A Parallel Particle Swarm Optimization-Back-Propagation Neural Network Algorithm Based on MapReduce.

PubMed

Cao, Jianfang; Cui, Hongyan; Shi, Hao; Jiao, Lijuan

2016-01-01

A back-propagation (BP) neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural network algorithm, we proposed a parallel design and realization method for a particle swarm optimization (PSO)-optimized BP neural network based on MapReduce on the Hadoop platform using both the PSO algorithm and a parallel design. The PSO algorithm was used to optimize the BP neural network's initial weights and thresholds and improve the accuracy of the classification algorithm. The MapReduce parallel programming model was utilized to achieve parallel processing of the BP algorithm, thereby solving the problems of hardware and communication overhead when the BP neural network addresses big data. Datasets on 5 different scales were constructed using the scene image library from the SUN Database. The classification accuracy of the parallel PSO-BP neural network algorithm is approximately 92%, and the system efficiency is approximately 0.85, which presents obvious advantages when processing big data. The algorithm proposed in this study demonstrated both higher classification accuracy and improved time efficiency, which represents a significant improvement obtained from applying parallel processing to an intelligent algorithm on big data.

Some fast elliptic solvers on parallel architectures and their complexities

NASA Technical Reports Server (NTRS)

Gallopoulos, E.; Saad, Y.

1989-01-01

The discretization of separable elliptic partial differential equations leads to linear systems with special block tridiagonal matrices. Several methods are known to solve these systems, the most general of which is the Block Cyclic Reduction (BCR) algorithm which handles equations with nonconstant coefficients. A method was recently proposed to parallelize and vectorize BCR. In this paper, the mapping of BCR on distributed memory architectures is discussed, and its complexity is compared with that of other approaches including the Alternating-Direction method. A fast parallel solver is also described, based on an explicit formula for the solution, which has parallel computational compelxity lower than that of parallel BCR.

Some fast elliptic solvers on parallel architectures and their complexities

NASA Technical Reports Server (NTRS)

Gallopoulos, E.; Saad, Youcef

1989-01-01

The discretization of separable elliptic partial differential equations leads to linear systems with special block triangular matrices. Several methods are known to solve these systems, the most general of which is the Block Cyclic Reduction (BCR) algorithm which handles equations with nonconsistant coefficients. A method was recently proposed to parallelize and vectorize BCR. Here, the mapping of BCR on distributed memory architectures is discussed, and its complexity is compared with that of other approaches, including the Alternating-Direction method. A fast parallel solver is also described, based on an explicit formula for the solution, which has parallel computational complexity lower than that of parallel BCR.

An Optimization System with Parallel Processing for Reducing Common-Mode Current on Electronic Control Unit

NASA Astrophysics Data System (ADS)

Okazaki, Yuji; Uno, Takanori; Asai, Hideki

In this paper, we propose an optimization system with parallel processing for reducing electromagnetic interference (EMI) on electronic control unit (ECU). We adopt simulated annealing (SA), genetic algorithm (GA) and taboo search (TS) to seek optimal solutions, and a Spice-like circuit simulator to analyze common-mode current. Therefore, the proposed system can determine the adequate combinations of the parasitic inductance and capacitance values on printed circuit board (PCB) efficiently and practically, to reduce EMI caused by the common-mode current. Finally, we apply the proposed system to an example circuit to verify the validity and efficiency of the system.

Parallel algorithm for computation of second-order sequential best rotations

NASA Astrophysics Data System (ADS)

Redif, Soydan; Kasap, Server

2013-12-01

Algorithms for computing an approximate polynomial matrix eigenvalue decomposition of para-Hermitian systems have emerged as a powerful, generic signal processing tool. A technique that has shown much success in this regard is the sequential best rotation (SBR2) algorithm. Proposed is a scheme for parallelising SBR2 with a view to exploiting the modern architectural features and inherent parallelism of field-programmable gate array (FPGA) technology. Experiments show that the proposed scheme can achieve low execution times while requiring minimal FPGA resources.

Computer architecture evaluation for structural dynamics computations: Project summary

NASA Technical Reports Server (NTRS)

Standley, Hilda M.

1989-01-01

The intent of the proposed effort is the examination of the impact of the elements of parallel architectures on the performance realized in a parallel computation. To this end, three major projects are developed: a language for the expression of high level parallelism, a statistical technique for the synthesis of multicomputer interconnection networks based upon performance prediction, and a queueing model for the analysis of shared memory hierarchies.

YAPPA: a Compiler-Based Parallelization Framework for Irregular Applications on MPSoCs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lovergine, Silvia; Tumeo, Antonino; Villa, Oreste

Modern embedded systems include hundreds of cores. Because of the difficulty in providing a fast, coherent memory architecture, these systems usually rely on non-coherent, non-uniform memory architectures with private memories for each core. However, programming these systems poses significant challenges. The developer must extract large amounts of parallelism, while orchestrating communication among cores to optimize application performance. These issues become even more significant with irregular applications, which present data sets difficult to partition, unpredictable memory accesses, unbalanced control flow and fine grained communication. Hand-optimizing every single aspect is hard and time-consuming, and it often does not lead to the expectedmore » performance. There is a growing gap between such complex and highly-parallel architectures and the high level languages used to describe the specification, which were designed for simpler systems and do not consider these new issues. In this paper we introduce YAPPA (Yet Another Parallel Programming Approach), a compilation framework for the automatic parallelization of irregular applications on modern MPSoCs based on LLVM. We start by considering an efficient parallel programming approach for irregular applications on distributed memory systems. We then propose a set of transformations that can reduce the development and optimization effort. The results of our initial prototype confirm the correctness of the proposed approach.« less

A visual parallel-BCI speller based on the time-frequency coding strategy

NASA Astrophysics Data System (ADS)

Xu, Minpeng; Chen, Long; Zhang, Lixin; Qi, Hongzhi; Ma, Lan; Tang, Jiabei; Wan, Baikun; Ming, Dong

2014-04-01

Objective. Spelling is one of the most important issues in brain-computer interface (BCI) research. This paper is to develop a visual parallel-BCI speller system based on the time-frequency coding strategy in which the sub-speller switching among four simultaneously presented sub-spellers and the character selection are identified in a parallel mode. Approach. The parallel-BCI speller was constituted by four independent P300+SSVEP-B (P300 plus SSVEP blocking) spellers with different flicker frequencies, thereby all characters had a specific time-frequency code. To verify its effectiveness, 11 subjects were involved in the offline and online spellings. A classification strategy was designed to recognize the target character through jointly using the canonical correlation analysis and stepwise linear discriminant analysis. Main results. Online spellings showed that the proposed parallel-BCI speller had a high performance, reaching the highest information transfer rate of 67.4 bit min-1, with an average of 54.0 bit min-1 and 43.0 bit min-1 in the three rounds and five rounds, respectively. Significance. The results indicated that the proposed parallel-BCI could be effectively controlled by users with attention shifting fluently among the sub-spellers, and highly improved the BCI spelling performance.

Parallel transmit beamforming using orthogonal frequency division multiplexing applied to harmonic imaging--a feasibility study.

PubMed

Demi, Libertario; Verweij, Martin D; Van Dongen, Koen W A

2012-11-01

Real-time 2-D or 3-D ultrasound imaging systems are currently used for medical diagnosis. To achieve the required data acquisition rate, these systems rely on parallel beamforming, i.e., a single wide-angled beam is used for transmission and several narrow parallel beams are used for reception. When applied to harmonic imaging, the demand for high-amplitude pressure wave fields, necessary to generate the harmonic components, conflicts with the use of a wide-angled beam in transmission because this results in a large spatial decay of the acoustic pressure. To enhance the amplitude of the harmonics, it is preferable to do the reverse: transmit several narrow parallel beams and use a wide-angled beam in reception. Here, this concept is investigated to determine whether it can be used for harmonic imaging. The method proposed in this paper relies on orthogonal frequency division multiplexing (OFDM), which is used to create distinctive parallel beams in transmission. To test the proposed method, a numerical study has been performed, in which the transmit, receive, and combined beam profiles generated by a linear array have been simulated for the second-harmonic component. Compared with standard parallel beamforming, application of the proposed technique results in a gain of 12 dB for the main beam and in a reduction of the side lobes. Experimental verification in water has also been performed. Measurements obtained with a single-element emitting transducer and a hydrophone receiver confirm the possibility of exciting a practical ultrasound transducer with multiple Gaussian modulated pulses, each having a different center frequency, and the capability to generate distinguishable second-harmonic components.

Design of high-performance parallelized gene predictors in MATLAB.

PubMed

Rivard, Sylvain Robert; Mailloux, Jean-Gabriel; Beguenane, Rachid; Bui, Hung Tien

2012-04-10

This paper proposes a method of implementing parallel gene prediction algorithms in MATLAB. The proposed designs are based on either Goertzel's algorithm or on FFTs and have been implemented using varying amounts of parallelism on a central processing unit (CPU) and on a graphics processing unit (GPU). Results show that an implementation using a straightforward approach can require over 4.5 h to process 15 million base pairs (bps) whereas a properly designed one could perform the same task in less than five minutes. In the best case, a GPU implementation can yield these results in 57 s. The present work shows how parallelism can be used in MATLAB for gene prediction in very large DNA sequences to produce results that are over 270 times faster than a conventional approach. This is significant as MATLAB is typically overlooked due to its apparent slow processing time even though it offers a convenient environment for bioinformatics. From a practical standpoint, this work proposes two strategies for accelerating genome data processing which rely on different parallelization mechanisms. Using a CPU, the work shows that direct access to the MEX function increases execution speed and that the PARFOR construct should be used in order to take full advantage of the parallelizable Goertzel implementation. When the target is a GPU, the work shows that data needs to be segmented into manageable sizes within the GFOR construct before processing in order to minimize execution time.

An equivalent viscoelastic model for rock mass with parallel joints

NASA Astrophysics Data System (ADS)

Li, Jianchun; Ma, Guowei; Zhao, Jian

2010-03-01

An equivalent viscoelastic medium model is proposed for rock mass with parallel joints. A concept of "virtual wave source (VWS)" is proposed to take into account the wave reflections between the joints. The equivalent model can be effectively applied to analyze longitudinal wave propagation through discontinuous media with parallel joints. Parameters in the equivalent viscoelastic model are derived analytically based on longitudinal wave propagation across a single rock joint. The proposed model is then verified by applying identical incident waves to the discontinuous and equivalent viscoelastic media at one end to compare the output waves at the other end. When the wavelength of the incident wave is sufficiently long compared to the joint spacing, the effect of the VWS on wave propagation in rock mass is prominent. The results from the equivalent viscoelastic medium model are very similar to those determined from the displacement discontinuity method. Frequency dependence and joint spacing effect on the equivalent viscoelastic model and the VWS method are discussed.

A scalable parallel black oil simulator on distributed memory parallel computers

NASA Astrophysics Data System (ADS)

Wang, Kun; Liu, Hui; Chen, Zhangxin

2015-11-01

This paper presents our work on developing a parallel black oil simulator for distributed memory computers based on our in-house parallel platform. The parallel simulator is designed to overcome the performance issues of common simulators that are implemented for personal computers and workstations. The finite difference method is applied to discretize the black oil model. In addition, some advanced techniques are employed to strengthen the robustness and parallel scalability of the simulator, including an inexact Newton method, matrix decoupling methods, and algebraic multigrid methods. A new multi-stage preconditioner is proposed to accelerate the solution of linear systems from the Newton methods. Numerical experiments show that our simulator is scalable and efficient, and is capable of simulating extremely large-scale black oil problems with tens of millions of grid blocks using thousands of MPI processes on parallel computers.

Efficient operator splitting algorithm for joint sparsity-regularized SPIRiT-based parallel MR imaging reconstruction.

PubMed

Duan, Jizhong; Liu, Yu; Jing, Peiguang

2018-02-01

Self-consistent parallel imaging (SPIRiT) is an auto-calibrating model for the reconstruction of parallel magnetic resonance imaging, which can be formulated as a regularized SPIRiT problem. The Projection Over Convex Sets (POCS) method was used to solve the formulated regularized SPIRiT problem. However, the quality of the reconstructed image still needs to be improved. Though methods such as NonLinear Conjugate Gradients (NLCG) can achieve higher spatial resolution, these methods always demand very complex computation and converge slowly. In this paper, we propose a new algorithm to solve the formulated Cartesian SPIRiT problem with the JTV and JL1 regularization terms. The proposed algorithm uses the operator splitting (OS) technique to decompose the problem into a gradient problem and a denoising problem with two regularization terms, which is solved by our proposed split Bregman based denoising algorithm, and adopts the Barzilai and Borwein method to update step size. Simulation experiments on two in vivo data sets demonstrate that the proposed algorithm is 1.3 times faster than ADMM for datasets with 8 channels. Especially, our proposal is 2 times faster than ADMM for the dataset with 32 channels. Copyright © 2017 Elsevier Inc. All rights reserved.

New 2D diffraction model and its applications to terahertz parallel-plate waveguide power splitters

PubMed Central

Zhang, Fan; Song, Kaijun; Fan, Yong

2017-01-01

A two-dimensional (2D) diffraction model for the calculation of the diffraction field in 2D space and its applications to terahertz parallel-plate waveguide power splitters are proposed in this paper. Compared with the Huygens-Fresnel principle in three-dimensional (3D) space, the proposed model provides an approximate analytical expression to calculate the diffraction field in 2D space. The diffraction filed is regarded as the superposition integral in 2D space. The calculated results obtained from the proposed diffraction model agree well with the ones by software HFSS based on the element method (FEM). Based on the proposed 2D diffraction model, two parallel-plate waveguide power splitters are presented. The splitters consist of a transmitting horn antenna, reflectors, and a receiving antenna array. The reflector is cylindrical parabolic with superimposed surface relief to efficiently couple the transmitted wave into the receiving antenna array. The reflector is applied as computer-generated holograms to match the transformed field to the receiving antenna aperture field. The power splitters were optimized by a modified real-coded genetic algorithm. The computed results of the splitters agreed well with the ones obtained by software HFSS verify the novel design method for power splitter, which shows good applied prospects of the proposed 2D diffraction model. PMID:28181514

Approximate kernel competitive learning.

PubMed

Wu, Jian-Sheng; Zheng, Wei-Shi; Lai, Jian-Huang

2015-03-01

Kernel competitive learning has been successfully used to achieve robust clustering. However, kernel competitive learning (KCL) is not scalable for large scale data processing, because (1) it has to calculate and store the full kernel matrix that is too large to be calculated and kept in the memory and (2) it cannot be computed in parallel. In this paper we develop a framework of approximate kernel competitive learning for processing large scale dataset. The proposed framework consists of two parts. First, it derives an approximate kernel competitive learning (AKCL), which learns kernel competitive learning in a subspace via sampling. We provide solid theoretical analysis on why the proposed approximation modelling would work for kernel competitive learning, and furthermore, we show that the computational complexity of AKCL is largely reduced. Second, we propose a pseudo-parallelled approximate kernel competitive learning (PAKCL) based on a set-based kernel competitive learning strategy, which overcomes the obstacle of using parallel programming in kernel competitive learning and significantly accelerates the approximate kernel competitive learning for large scale clustering. The empirical evaluation on publicly available datasets shows that the proposed AKCL and PAKCL can perform comparably as KCL, with a large reduction on computational cost. Also, the proposed methods achieve more effective clustering performance in terms of clustering precision against related approximate clustering approaches. Copyright © 2014 Elsevier Ltd. All rights reserved.

Parallel compression/decompression-based datapath architecture for multibeam mask writers

NASA Astrophysics Data System (ADS)

Chaudhary, Narendra; Savari, Serap A.

2017-06-01

Multibeam electron beam systems will be used in the future for mask writing and for complimentary lithography. The major challenges of the multibeam systems are in meeting throughput requirements and in handling the large data volumes associated with writing grayscale data on the wafer. In terms of future communications and computational requirements Amdahl's Law suggests that a simple increase of computation power and parallelism may not be a sustainable solution. We propose a parallel data compression algorithm to exploit the sparsity of mask data and a grayscale video-like representation of data. To improve the communication and computational efficiency of these systems at the write time we propose an alternate datapath architecture partly motivated by multibeam direct write lithography and partly motivated by the circuit testing literature, where parallel decompression reduces clock cycles. We explain a deflection plate architecture inspired by NuFlare Technology's multibeam mask writing system and how our datapath architecture can be easily added to it to improve performance.

Parallel compression/decompression-based datapath architecture for multibeam mask writers

NASA Astrophysics Data System (ADS)

Chaudhary, Narendra; Savari, Serap A.

2017-10-01

Multibeam electron beam systems will be used in the future for mask writing and for complementary lithography. The major challenges of the multibeam systems are in meeting throughput requirements and in handling the large data volumes associated with writing grayscale data on the wafer. In terms of future communications and computational requirements, Amdahl's law suggests that a simple increase of computation power and parallelism may not be a sustainable solution. We propose a parallel data compression algorithm to exploit the sparsity of mask data and a grayscale video-like representation of data. To improve the communication and computational efficiency of these systems at the write time, we propose an alternate datapath architecture partly motivated by multibeam direct-write lithography and partly motivated by the circuit testing literature, where parallel decompression reduces clock cycles. We explain a deflection plate architecture inspired by NuFlare Technology's multibeam mask writing system and how our datapath architecture can be easily added to it to improve performance.

Parallel Rendering of Large Time-Varying Volume Data

NASA Technical Reports Server (NTRS)

Garbutt, Alexander E.

2005-01-01

Interactive visualization of large time-varying 3D volume datasets has been and still is a great challenge to the modem computational world. It stretches the limits of the memory capacity, the disk space, the network bandwidth and the CPU speed of a conventional computer. In this SURF project, we propose to develop a parallel volume rendering program on SGI's Prism, a cluster computer equipped with state-of-the-art graphic hardware. The proposed program combines both parallel computing and hardware rendering in order to achieve an interactive rendering rate. We use 3D texture mapping and a hardware shader to implement 3D volume rendering on each workstation. We use SGI's VisServer to enable remote rendering using Prism's graphic hardware. And last, we will integrate this new program with ParVox, a parallel distributed visualization system developed at JPL. At the end of the project, we Will demonstrate remote interactive visualization using this new hardware volume renderer on JPL's Prism System using a time-varying dataset from selected JPL applications.

Parallel computation of level set method for 500 Hz visual servo control

NASA Astrophysics Data System (ADS)

Fei, Xianfeng; Igarashi, Yasunobu; Hashimoto, Koichi

2008-11-01

We propose a 2D microorganism tracking system using a parallel level set method and a column parallel vision system (CPV). This system keeps a single microorganism in the middle of the visual field under a microscope by visual servoing an automated stage. We propose a new energy function for the level set method. This function constrains an amount of light intensity inside the detected object contour to control the number of the detected objects. This algorithm is implemented in CPV system and computational time for each frame is 2 [ms], approximately. A tracking experiment for about 25 s is demonstrated. Also we demonstrate a single paramecium can be kept tracking even if other paramecia appear in the visual field and contact with the tracked paramecium.

Parameter Estimation of Fractional-Order Chaotic Systems by Using Quantum Parallel Particle Swarm Optimization Algorithm

PubMed Central

Huang, Yu; Guo, Feng; Li, Yongling; Liu, Yufeng

2015-01-01

Parameter estimation for fractional-order chaotic systems is an important issue in fractional-order chaotic control and synchronization and could be essentially formulated as a multidimensional optimization problem. A novel algorithm called quantum parallel particle swarm optimization (QPPSO) is proposed to solve the parameter estimation for fractional-order chaotic systems. The parallel characteristic of quantum computing is used in QPPSO. This characteristic increases the calculation of each generation exponentially. The behavior of particles in quantum space is restrained by the quantum evolution equation, which consists of the current rotation angle, individual optimal quantum rotation angle, and global optimal quantum rotation angle. Numerical simulation based on several typical fractional-order systems and comparisons with some typical existing algorithms show the effectiveness and efficiency of the proposed algorithm. PMID:25603158

A transient-enhanced NMOS low dropout voltage regulator with parallel feedback compensation

NASA Astrophysics Data System (ADS)

Han, Wang; Lin, Tan

2016-02-01

This paper presents a transient-enhanced NMOS low-dropout regulator (LDO) for portable applications with parallel feedback compensation. The parallel feedback structure adds a dynamic zero to get an adequate phase margin with a load current variation from 0 to 1 A. A class-AB error amplifier and a fast charging/discharging unit are adopted to enhance the transient performance. The proposed LDO has been implemented in a 0.35 μm BCD process. From experimental results, the regulator can operate with a minimum dropout voltage of 150 mV at a maximum 1 A load and IQ of 165 μA. Under the full range load current step, the voltage undershoot and overshoot of the proposed LDO are reduced to 38 mV and 27 mV respectively.

Evaluation of the power consumption of a high-speed parallel robot

NASA Astrophysics Data System (ADS)

Han, Gang; Xie, Fugui; Liu, Xin-Jun

2018-06-01

An inverse dynamic model of a high-speed parallel robot is established based on the virtual work principle. With this dynamic model, a new evaluation method is proposed to measure the power consumption of the robot during pick-and-place tasks. The power vector is extended in this method and used to represent the collinear velocity and acceleration of the moving platform. Afterward, several dynamic performance indices, which are homogenous and possess obvious physical meanings, are proposed. These indices can evaluate the power input and output transmissibility of the robot in a workspace. The distributions of the power input and output transmissibility of the high-speed parallel robot are derived with these indices and clearly illustrated in atlases. Furtherly, a low-power-consumption workspace is selected for the robot.

Externally calibrated parallel imaging for 3D multispectral imaging near metallic implants using broadband ultrashort echo time imaging.

PubMed

Wiens, Curtis N; Artz, Nathan S; Jang, Hyungseok; McMillan, Alan B; Reeder, Scott B

2017-06-01

To develop an externally calibrated parallel imaging technique for three-dimensional multispectral imaging (3D-MSI) in the presence of metallic implants. A fast, ultrashort echo time (UTE) calibration acquisition is proposed to enable externally calibrated parallel imaging techniques near metallic implants. The proposed calibration acquisition uses a broadband radiofrequency (RF) pulse to excite the off-resonance induced by the metallic implant, fully phase-encoded imaging to prevent in-plane distortions, and UTE to capture rapidly decaying signal. The performance of the externally calibrated parallel imaging reconstructions was assessed using phantoms and in vivo examples. Phantom and in vivo comparisons to self-calibrated parallel imaging acquisitions show that significant reductions in acquisition times can be achieved using externally calibrated parallel imaging with comparable image quality. Acquisition time reductions are particularly large for fully phase-encoded methods such as spectrally resolved fully phase-encoded three-dimensional (3D) fast spin-echo (SR-FPE), in which scan time reductions of up to 8 min were obtained. A fully phase-encoded acquisition with broadband excitation and UTE enabled externally calibrated parallel imaging for 3D-MSI, eliminating the need for repeated calibration regions at each frequency offset. Significant reductions in acquisition time can be achieved, particularly for fully phase-encoded methods like SR-FPE. Magn Reson Med 77:2303-2309, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

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

PubMed

Bhandarkar, S M; Chirravuri, S; Arnold, J

1996-01-01

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.

Big Data: A Parallel Particle Swarm Optimization-Back-Propagation Neural Network Algorithm Based on MapReduce

PubMed Central

Cao, Jianfang; Cui, Hongyan; Shi, Hao; Jiao, Lijuan

2016-01-01

A back-propagation (BP) neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural network algorithm, we proposed a parallel design and realization method for a particle swarm optimization (PSO)-optimized BP neural network based on MapReduce on the Hadoop platform using both the PSO algorithm and a parallel design. The PSO algorithm was used to optimize the BP neural network’s initial weights and thresholds and improve the accuracy of the classification algorithm. The MapReduce parallel programming model was utilized to achieve parallel processing of the BP algorithm, thereby solving the problems of hardware and communication overhead when the BP neural network addresses big data. Datasets on 5 different scales were constructed using the scene image library from the SUN Database. The classification accuracy of the parallel PSO-BP neural network algorithm is approximately 92%, and the system efficiency is approximately 0.85, which presents obvious advantages when processing big data. The algorithm proposed in this study demonstrated both higher classification accuracy and improved time efficiency, which represents a significant improvement obtained from applying parallel processing to an intelligent algorithm on big data. PMID:27304987

Parallel conjugate gradient algorithms for manipulator dynamic simulation

NASA Technical Reports Server (NTRS)

Fijany, Amir; Scheld, Robert E.

1989-01-01

Parallel conjugate gradient algorithms for the computation of multibody dynamics are developed for the specialized case of a robot manipulator. For an n-dimensional positive-definite linear system, the Classical Conjugate Gradient (CCG) algorithms are guaranteed to converge in n iterations, each with a computation cost of O(n); this leads to a total computational cost of O(n sq) on a serial processor. A conjugate gradient algorithms is presented that provide greater efficiency using a preconditioner, which reduces the number of iterations required, and by exploiting parallelism, which reduces the cost of each iteration. Two Preconditioned Conjugate Gradient (PCG) algorithms are proposed which respectively use a diagonal and a tridiagonal matrix, composed of the diagonal and tridiagonal elements of the mass matrix, as preconditioners. Parallel algorithms are developed to compute the preconditioners and their inversions in O(log sub 2 n) steps using n processors. A parallel algorithm is also presented which, on the same architecture, achieves the computational time of O(log sub 2 n) for each iteration. Simulation results for a seven degree-of-freedom manipulator are presented. Variants of the proposed algorithms are also developed which can be efficiently implemented on the Robot Mathematics Processor (RMP).

Symmetry Breaking by Parallel Flow Shear

NASA Astrophysics Data System (ADS)

Li, Jiacong; Diamond, Patrick

2015-11-01

Plasma rotation is important in reducing turbulent transport, suppressing MHD instabilities, and is beneficial to confinement. Intrinsic rotation without an external momentum input is of interest for its plausible application on ITER. k∥ spectrum asymmetry is required for residual Reynolds stress that drives the intrinsic rotation. Parallel flows are reported in linear devices without magnetic shear. In CSDX, parallel flows are mostly peaked in the core [Thakur et al., 2014]; more robust flows and reversed profiles are seen in PANTA [Oldenburger, et al. 2012]. A novel mechanism for symmetry breaking in momentum transport is proposed. Magnetic shear or mean flow profile are not required. A seed parallel flow shear (PFS) sets the sign of residual stress by selecting certain modes to grow faster. The resulted spectrum imbalance leads to a nonzero residual stress, which further drives a parallel flow with ∇n as the free energy source, adding to the shear until saturated by diffusion. Balanced flow gradient is set by Π∥Res /χϕ . Residual stress is calculated for ITG turbulence and collisional drift wave turbulence where electron-ion and electron-neutral collisions are discussed and compared. Numerical simulation is proposed for testing the effect of PFS.

Parallel processing in finite element structural analysis

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.

1987-01-01

A brief review is made of the fundamental concepts and basic issues of parallel processing. Discussion focuses on parallel numerical algorithms, performance evaluation of machines and algorithms, and parallelism in finite element computations. A computational strategy is proposed for maximizing the degree of parallelism at different levels of the finite element analysis process including: 1) formulation level (through the use of mixed finite element models); 2) analysis level (through additive decomposition of the different arrays in the governing equations into the contributions to a symmetrized response plus correction terms); 3) numerical algorithm level (through the use of operator splitting techniques and application of iterative processes); and 4) implementation level (through the effective combination of vectorization, multitasking and microtasking, whenever available).

Parallelized Stochastic Cutoff Method for Long-Range Interacting Systems

NASA Astrophysics Data System (ADS)

Endo, Eishin; Toga, Yuta; Sasaki, Munetaka

2015-07-01

We present a method of parallelizing the stochastic cutoff (SCO) method, which is a Monte-Carlo method for long-range interacting systems. After interactions are eliminated by the SCO method, we subdivide a lattice into noninteracting interpenetrating sublattices. This subdivision enables us to parallelize the Monte-Carlo calculation in the SCO method. Such subdivision is found by numerically solving the vertex coloring of a graph created by the SCO method. We use an algorithm proposed by Kuhn and Wattenhofer to solve the vertex coloring by parallel computation. This method was applied to a two-dimensional magnetic dipolar system on an L × L square lattice to examine its parallelization efficiency. The result showed that, in the case of L = 2304, the speed of computation increased about 102 times by parallel computation with 288 processors.

CSAPR Parallel Proposal (77 FR 10350)

EPA Pesticide Factsheets

EPA proposes additional revisions to certain portions of the Transport Rule (Federal Implementation Plans: Interstate Transport of Fine Particulate Matter and Ozone and Correction of SIP Approvals, published August 8, 2011).

Implementation of DFT application on ternary optical computer

NASA Astrophysics Data System (ADS)

Junjie, Peng; Youyi, Fu; Xiaofeng, Zhang; Shuai, Kong; Xinyu, Wei

2018-03-01

As its characteristics of huge number of data bits and low energy consumption, optical computing may be used in the applications such as DFT etc. which needs a lot of computation and can be implemented in parallel. According to this, DFT implementation methods in full parallel as well as in partial parallel are presented. Based on resources ternary optical computer (TOC), extensive experiments were carried out. Experimental results show that the proposed schemes are correct and feasible. They provide a foundation for further exploration of the applications on TOC that needs a large amount calculation and can be processed in parallel.

Trinary signed-digit arithmetic using an efficient encoding scheme

NASA Astrophysics Data System (ADS)

Salim, W. Y.; Alam, M. S.; Fyath, R. S.; Ali, S. A.

2000-09-01

The trinary signed-digit (TSD) number system is of interest for ultrafast optoelectronic computing systems since it permits parallel carry-free addition and borrow-free subtraction of two arbitrary length numbers in constant time. In this paper, a simple coding scheme is proposed to encode the decimal number directly into the TSD form. The coding scheme enables one to perform parallel one-step TSD arithmetic operation. The proposed coding scheme uses only a 5-combination coding table instead of the 625-combination table reported recently for recoded TSD arithmetic technique.

One-step trinary signed-digit arithmetic using an efficient encoding scheme

NASA Astrophysics Data System (ADS)

Salim, W. Y.; Fyath, R. S.; Ali, S. A.; Alam, Mohammad S.

2000-11-01

The trinary signed-digit (TSD) number system is of interest for ultra fast optoelectronic computing systems since it permits parallel carry-free addition and borrow-free subtraction of two arbitrary length numbers in constant time. In this paper, a simple coding scheme is proposed to encode the decimal number directly into the TSD form. The coding scheme enables one to perform parallel one-step TSD arithmetic operation. The proposed coding scheme uses only a 5-combination coding table instead of the 625-combination table reported recently for recoded TSD arithmetic technique.

Distributed computing feasibility in a non-dedicated homogeneous distributed system

NASA Technical Reports Server (NTRS)

Leutenegger, Scott T.; Sun, Xian-He

1993-01-01

The low cost and availability of clusters of workstations have lead researchers to re-explore distributed computing using independent workstations. This approach may provide better cost/performance than tightly coupled multiprocessors. In practice, this approach often utilizes wasted cycles to run parallel jobs. The feasibility of such a non-dedicated parallel processing environment assuming workstation processes have preemptive priority over parallel tasks is addressed. An analytical model is developed to predict parallel job response times. Our model provides insight into how significantly workstation owner interference degrades parallel program performance. A new term task ratio, which relates the parallel task demand to the mean service demand of nonparallel workstation processes, is introduced. It was proposed that task ratio is a useful metric for determining how large the demand of a parallel applications must be in order to make efficient use of a non-dedicated distributed system.

Enhancing PC Cluster-Based Parallel Branch-and-Bound Algorithms for the Graph Coloring Problem

NASA Astrophysics Data System (ADS)

Taoka, Satoshi; Takafuji, Daisuke; Watanabe, Toshimasa

A branch-and-bound algorithm (BB for short) is the most general technique to deal with various combinatorial optimization problems. Even if it is used, computation time is likely to increase exponentially. So we consider its parallelization to reduce it. It has been reported that the computation time of a parallel BB heavily depends upon node-variable selection strategies. And, in case of a parallel BB, it is also necessary to prevent increase in communication time. So, it is important to pay attention to how many and what kind of nodes are to be transferred (called sending-node selection strategy). In this paper, for the graph coloring problem, we propose some sending-node selection strategies for a parallel BB algorithm by adopting MPI for parallelization and experimentally evaluate how these strategies affect computation time of a parallel BB on a PC cluster network.

Parallel Digital Phase-Locked Loops

NASA Technical Reports Server (NTRS)

Sadr, Ramin; Shah, Biren N.; Hinedi, Sami M.

1995-01-01

Wide-band microwave receivers of proposed type include digital phase-locked loops in which band-pass filtering and down-conversion of input signals implemented by banks of multirate digital filters operating in parallel. Called "parallel digital phase-locked loops" to distinguish them from other digital phase-locked loops. Systems conceived as cost-effective solution to problem of filtering signals at high sampling rates needed to accommodate wide input frequency bands. Each of M filters process 1/M of spectrum of signal.

Silicon-fiber blanket solar-cell array concept

NASA Technical Reports Server (NTRS)

Eliason, J. T.

1973-01-01

Proposed economical manufacture of solar-cell arrays involves parallel, planar weaving of filaments made of doped silicon fibers with diffused radial junction. Each filament is a solar cell connected either in series or parallel with others to form a blanket of deposited grids or attached electrode wire mesh screens.

Creating IRT-Based Parallel Test Forms Using the Genetic Algorithm Method

ERIC Educational Resources Information Center

Sun, Koun-Tem; Chen, Yu-Jen; Tsai, Shu-Yen; Cheng, Chien-Fen

2008-01-01

In educational measurement, the construction of parallel test forms is often a combinatorial optimization problem that involves the time-consuming selection of items to construct tests having approximately the same test information functions (TIFs) and constraints. This article proposes a novel method, genetic algorithm (GA), to construct parallel…

Issues of planning trajectory of parallel robots taking into account zones of singularity

NASA Astrophysics Data System (ADS)

Rybak, L. A.; Khalapyan, S. Y.; Gaponenko, E. V.

2018-03-01

A method for determining the design characteristics of a parallel robot necessary to provide specified parameters of its working space that satisfy the controllability requirement is developed. The experimental verification of the proposed method was carried out using an approximate planar 3-RPR mechanism.

29 CFR 1952.232 - Completion of developmental steps and certification.

Code of Federal Regulations, 2014 CFR

2014-07-01

.... Penalties for willful violations causing death of an employee are covered under KRS chapters 434, 503 and..., citations, proposed penalties (parallel to the Federal 29 CFR part 1903) and variances (parallel to the... were expanded to provide for: (1) Penalties for failure to correct violations; (2) Mandatory penalties...

29 CFR 1952.232 - Completion of developmental steps and certification.

Code of Federal Regulations, 2013 CFR

2013-07-01

.... Penalties for willful violations causing death of an employee are covered under KRS chapters 434, 503 and..., citations, proposed penalties (parallel to the Federal 29 CFR part 1903) and variances (parallel to the... were expanded to provide for: (1) Penalties for failure to correct violations; (2) Mandatory penalties...

29 CFR 1952.232 - Completion of developmental steps and certification.

Code of Federal Regulations, 2011 CFR

2011-07-01

.... Penalties for willful violations causing death of an employee are covered under KRS chapters 434, 503 and..., citations, proposed penalties (parallel to the Federal 29 CFR part 1903) and variances (parallel to the... were expanded to provide for: (1) Penalties for failure to correct violations; (2) Mandatory penalties...

29 CFR 1952.232 - Completion of developmental steps and certification.

Code of Federal Regulations, 2012 CFR

2012-07-01

.... Penalties for willful violations causing death of an employee are covered under KRS chapters 434, 503 and..., citations, proposed penalties (parallel to the Federal 29 CFR part 1903) and variances (parallel to the... were expanded to provide for: (1) Penalties for failure to correct violations; (2) Mandatory penalties...

Dimensional synthesis of a 3-DOF parallel manipulator with full circle rotation

NASA Astrophysics Data System (ADS)

Ni, Yanbing; Wu, Nan; Zhong, Xueyong; Zhang, Biao

2015-07-01

Parallel robots are widely used in the academic and industrial fields. In spite of the numerous achievements in the design and dimensional synthesis of the low-mobility parallel robots, few research efforts are directed towards the asymmetric 3-DOF parallel robots whose end-effector can realize 2 translational and 1 rotational(2T1R) motion. In order to develop a manipulator with the capability of full circle rotation to enlarge the workspace, a new 2T1R parallel mechanism is proposed. The modeling approach and kinematic analysis of this proposed mechanism are investigated. Using the method of vector analysis, the inverse kinematic equations are established. This is followed by a vigorous proof that this mechanism attains an annular workspace through its circular rotation and 2 dimensional translations. Taking the first order perturbation of the kinematic equations, the error Jacobian matrix which represents the mapping relationship between the error sources of geometric parameters and the end-effector position errors is derived. With consideration of the constraint conditions of pressure angles and feasible workspace, the dimensional synthesis is conducted with a goal to minimize the global comprehensive performance index. The dimension parameters making the mechanism to have optimal error mapping and kinematic performance are obtained through the optimization algorithm. All these research achievements lay the foundation for the prototype building of such kind of parallel robots.

IOPA: I/O-aware parallelism adaption for parallel programs

PubMed Central

Liu, Tao; Liu, Yi; Qian, Chen; Qian, Depei

2017-01-01

With the development of multi-/many-core processors, applications need to be written as parallel programs to improve execution efficiency. For data-intensive applications that use multiple threads to read/write files simultaneously, an I/O sub-system can easily become a bottleneck when too many of these types of threads exist; on the contrary, too few threads will cause insufficient resource utilization and hurt performance. Therefore, programmers must pay much attention to parallelism control to find the appropriate number of I/O threads for an application. This paper proposes a parallelism control mechanism named IOPA that can adjust the parallelism of applications to adapt to the I/O capability of a system and balance computing resources and I/O bandwidth. The programming interface of IOPA is also provided to programmers to simplify parallel programming. IOPA is evaluated using multiple applications with both solid state and hard disk drives. The results show that the parallel applications using IOPA can achieve higher efficiency than those with a fixed number of threads. PMID:28278236

IOPA: I/O-aware parallelism adaption for parallel programs.

PubMed

Liu, Tao; Liu, Yi; Qian, Chen; Qian, Depei

2017-01-01

With the development of multi-/many-core processors, applications need to be written as parallel programs to improve execution efficiency. For data-intensive applications that use multiple threads to read/write files simultaneously, an I/O sub-system can easily become a bottleneck when too many of these types of threads exist; on the contrary, too few threads will cause insufficient resource utilization and hurt performance. Therefore, programmers must pay much attention to parallelism control to find the appropriate number of I/O threads for an application. This paper proposes a parallelism control mechanism named IOPA that can adjust the parallelism of applications to adapt to the I/O capability of a system and balance computing resources and I/O bandwidth. The programming interface of IOPA is also provided to programmers to simplify parallel programming. IOPA is evaluated using multiple applications with both solid state and hard disk drives. The results show that the parallel applications using IOPA can achieve higher efficiency than those with a fixed number of threads.

Bilingual parallel programming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Foster, I.; Overbeek, R.

1990-01-01

Numerous experiments have demonstrated that computationally intensive algorithms support adequate parallelism to exploit the potential of large parallel machines. Yet successful parallel implementations of serious applications are rare. The limiting factor is clearly programming technology. None of the approaches to parallel programming that have been proposed to date -- whether parallelizing compilers, language extensions, or new concurrent languages -- seem to adequately address the central problems of portability, expressiveness, efficiency, and compatibility with existing software. In this paper, we advocate an alternative approach to parallel programming based on what we call bilingual programming. We present evidence that this approach providesmore » and effective solution to parallel programming problems. The key idea in bilingual programming is to construct the upper levels of applications in a high-level language while coding selected low-level components in low-level languages. This approach permits the advantages of a high-level notation (expressiveness, elegance, conciseness) to be obtained without the cost in performance normally associated with high-level approaches. In addition, it provides a natural framework for reusing existing code.« less

AC losses in horizontally parallel HTS tapes for possible wireless power transfer applications

NASA Astrophysics Data System (ADS)

Shen, Boyang; Geng, Jianzhao; Zhang, Xiuchang; Fu, Lin; Li, Chao; Zhang, Heng; Dong, Qihuan; Ma, Jun; Gawith, James; Coombs, T. A.

2017-12-01

This paper presents the concept of using horizontally parallel HTS tapes with AC loss study, and the investigation on possible wireless power transfer (WPT) applications. An example of three parallel HTS tapes was proposed, whose AC loss study was carried out both from experiment using electrical method; and simulation using 2D H-formulation on the FEM platform of COMSOL Multiphysics. The electromagnetic induction around the three parallel tapes was monitored using COMSOL simulation. The electromagnetic induction and AC losses generated by a conventional three turn coil was simulated as well, and then compared to the case of three parallel tapes with the same AC transport current. The analysis demonstrates that HTS parallel tapes could be potentially used into wireless power transfer systems, which could have lower total AC losses than conventional HTS coils.

Spacecraft Onboard Interface Services: Current Status and Roadmap

NASA Astrophysics Data System (ADS)

Prochazka, Marek; Lopez Trescastro, Jorge; Krueger, Sabine

2016-08-01

Spacecraft Onboard Interface Services (SOIS) is a set of CCSDS standards defining communication stack services to interact with hardware equipment onboard spacecraft. In 2014 ESA kicked off three parallel activities to critically review the SOIS standards, use legacy spacecraft flight software (FSW), make it compliant to a preselected subset of SOIS standards and make performance and architecture assessment. As a part of the three parallel activities, led by Airbus DS Toulouse, OHB Bremen and Thales Alenia Space Cannes respectively, it was to provide feedback back to ESA and CCSDS and also to propose a roadmap of transition towards an operational FSW system fully compliant to applicable SOIS standards. The objective of the paper is twofold: Firstly it is to summarise main results of the three parallel activities and secondly, based on the results, to propose a roadmap for the future.

A rapid parallelization of cone-beam projection and back-projection operator based on texture fetching interpolation

NASA Astrophysics Data System (ADS)

Xie, Lizhe; Hu, Yining; Chen, Yang; Shi, Luyao

2015-03-01

Projection and back-projection are the most computational consuming parts in Computed Tomography (CT) reconstruction. Parallelization strategies using GPU computing techniques have been introduced. We in this paper present a new parallelization scheme for both projection and back-projection. The proposed method is based on CUDA technology carried out by NVIDIA Corporation. Instead of build complex model, we aimed on optimizing the existing algorithm and make it suitable for CUDA implementation so as to gain fast computation speed. Besides making use of texture fetching operation which helps gain faster interpolation speed, we fixed sampling numbers in the computation of projection, to ensure the synchronization of blocks and threads, thus prevents the latency caused by inconsistent computation complexity. Experiment results have proven the computational efficiency and imaging quality of the proposed method.

A scheme for solving the plane-plane challenge in force measurements at the nanoscale.

PubMed

Siria, Alessandro; Huant, Serge; Auvert, Geoffroy; Comin, Fabio; Chevrier, Joel

2010-05-19

Non-contact interaction between two parallel flat surfaces is a central paradigm in sciences. This situation is the starting point for a wealth of different models: the capacitor description in electrostatics, hydrodynamic flow, thermal exchange, the Casimir force, direct contact study, third body confinement such as liquids or films of soft condensed matter. The control of parallelism is so demanding that no versatile single force machine in this geometry has been proposed so far. Using a combination of nanopositioning based on inertial motors, of microcrystal shaping with a focused-ion beam (FIB) and of accurate in situ and real-time control of surface parallelism with X-ray diffraction, we propose here a "gedanken" surface-force machine that should enable one to measure interactions between movable surfaces separated by gaps in the micrometer and nanometer ranges.

Power-balancing instantaneous optimization energy management for a novel series-parallel hybrid electric bus

NASA Astrophysics Data System (ADS)

Sun, Dongye; Lin, Xinyou; Qin, Datong; Deng, Tao

2012-11-01

Energy management(EM) is a core technique of hybrid electric bus(HEB) in order to advance fuel economy performance optimization and is unique for the corresponding configuration. There are existing algorithms of control strategy seldom take battery power management into account with international combustion engine power management. In this paper, a type of power-balancing instantaneous optimization(PBIO) energy management control strategy is proposed for a novel series-parallel hybrid electric bus. According to the characteristic of the novel series-parallel architecture, the switching boundary condition between series and parallel mode as well as the control rules of the power-balancing strategy are developed. The equivalent fuel model of battery is implemented and combined with the fuel of engine to constitute the objective function which is to minimize the fuel consumption at each sampled time and to coordinate the power distribution in real-time between the engine and battery. To validate the proposed strategy effective and reasonable, a forward model is built based on Matlab/Simulink for the simulation and the dSPACE autobox is applied to act as a controller for hardware in-the-loop integrated with bench test. Both the results of simulation and hardware-in-the-loop demonstrate that the proposed strategy not only enable to sustain the battery SOC within its operational range and keep the engine operation point locating the peak efficiency region, but also the fuel economy of series-parallel hybrid electric bus(SPHEB) dramatically advanced up to 30.73% via comparing with the prototype bus and a similar improvement for PBIO strategy relative to rule-based strategy, the reduction of fuel consumption is up to 12.38%. The proposed research ensures the algorithm of PBIO is real-time applicability, improves the efficiency of SPHEB system, as well as suite to complicated configuration perfectly.

An OpenACC-Based Unified Programming Model for Multi-accelerator Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Jungwon; Lee, Seyong; Vetter, Jeffrey S

2015-01-01

This paper proposes a novel SPMD programming model of OpenACC. Our model integrates the different granularities of parallelism from vector-level parallelism to node-level parallelism into a single, unified model based on OpenACC. It allows programmers to write programs for multiple accelerators using a uniform programming model whether they are in shared or distributed memory systems. We implement a prototype of our model and evaluate its performance with a GPU-based supercomputer using three benchmark applications.

Parallel Computing:. Some Activities in High Energy Physics

NASA Astrophysics Data System (ADS)

Willers, Ian

This paper examines some activities in High Energy Physics that utilise parallel computing. The topic includes all computing from the proposed SIMD front end detectors, the farming applications, high-powered RISC processors and the large machines in the computer centers. We start by looking at the motivation behind using parallelism for general purpose computing. The developments around farming are then described from its simplest form to the more complex system in Fermilab. Finally, there is a list of some developments that are happening close to the experiments.

GPU-Based Point Cloud Superpositioning for Structural Comparisons of Protein Binding Sites.

PubMed

Leinweber, Matthias; Fober, Thomas; Freisleben, Bernd

2018-01-01

In this paper, we present a novel approach to solve the labeled point cloud superpositioning problem for performing structural comparisons of protein binding sites. The solution is based on a parallel evolution strategy that operates on large populations and runs on GPU hardware. The proposed evolution strategy reduces the likelihood of getting stuck in a local optimum of the multimodal real-valued optimization problem represented by labeled point cloud superpositioning. The performance of the GPU-based parallel evolution strategy is compared to a previously proposed CPU-based sequential approach for labeled point cloud superpositioning, indicating that the GPU-based parallel evolution strategy leads to qualitatively better results and significantly shorter runtimes, with speed improvements of up to a factor of 1,500 for large populations. Binary classification tests based on the ATP, NADH, and FAD protein subsets of CavBase, a database containing putative binding sites, show average classification rate improvements from about 92 percent (CPU) to 96 percent (GPU). Further experiments indicate that the proposed GPU-based labeled point cloud superpositioning approach can be superior to traditional protein comparison approaches based on sequence alignments.

Improved interior wall detection using designated dictionaries in compressive urban sensing problems

NASA Astrophysics Data System (ADS)

Lagunas, Eva; Amin, Moeness G.; Ahmad, Fauzia; Nájar, Montse

2013-05-01

In this paper, we address sparsity-based imaging of building interior structures for through-the-wall radar imaging and urban sensing applications. The proposed approach utilizes information about common building construction practices to form an appropriate sparse representation of the building layout. With a ground based SAR system, and considering that interior walls are either parallel or perpendicular to the exterior walls, the antenna at each position would receive reflections from the walls parallel to the radar's scan direction as well as from the corners between two meeting walls. We propose a two-step approach for wall detection and localization. In the first step, a dictionary of possible wall locations is used to recover the positions of both interior and exterior walls that are parallel to the scan direction. A follow-on step uses a dictionary of possible corner reflectors to locate wall-wall junctions along the detected wall segments, thereby determining the true wall extents and detecting walls perpendicular to the scan direction. The utility of the proposed approach is demonstrated using simulated data.

A low-complexity Reed-Solomon decoder using new key equation solver

NASA Astrophysics Data System (ADS)

Xie, Jun; Yuan, Songxin; Tu, Xiaodong; Zhang, Chongfu

2006-09-01

This paper presents a low-complexity parallel Reed-Solomon (RS) (255,239) decoder architecture using a novel pipelined variable stages recursive Modified Euclidean (ME) algorithm for optical communication. The pipelined four-parallel syndrome generator is proposed. The time multiplexing and resource sharing schemes are used in the novel recursive ME algorithm to reduce the logic gate count. The new key equation solver can be shared by two decoder macro. A new Chien search cell which doesn't need initialization is proposed in the paper. The proposed decoder can be used for 2.5Gb/s data rates device. The decoder is implemented in Altera' Stratixll device. The resource utilization is reduced about 40% comparing to the conventional method.

Rapid code acquisition algorithms employing PN matched filters

NASA Technical Reports Server (NTRS)

Su, Yu T.

1988-01-01

The performance of four algorithms using pseudonoise matched filters (PNMFs), for direct-sequence spread-spectrum systems, is analyzed. They are: parallel search with fix dwell detector (PL-FDD), parallel search with sequential detector (PL-SD), parallel-serial search with fix dwell detector (PS-FDD), and parallel-serial search with sequential detector (PS-SD). The operation characteristic for each detector and the mean acquisition time for each algorithm are derived. All the algorithms are studied in conjunction with the noncoherent integration technique, which enables the system to operate in the presence of data modulation. Several previous proposals using PNMF are seen as special cases of the present algorithms.

Increased Energy Delivery for Parallel Battery Packs with No Regulated Bus

NASA Astrophysics Data System (ADS)

Hsu, Chung-Ti

In this dissertation, a new approach to paralleling different battery types is presented. A method for controlling charging/discharging of different battery packs by using low-cost bi-directional switches instead of DC-DC converters is proposed. The proposed system architecture, algorithms, and control techniques allow batteries with different chemistry, voltage, and SOC to be properly charged and discharged in parallel without causing safety problems. The physical design and cost for the energy management system is substantially reduced. Additionally, specific types of failures in the maximum power point tracking (MPPT) in a photovoltaic (PV) system when tracking only the load current of a DC-DC converter are analyzed. The periodic nonlinear load current will lead MPPT realized by the conventional perturb and observe (P&O) algorithm to be problematic. A modified MPPT algorithm is proposed and it still only requires typically measured signals, yet is suitable for both linear and periodic nonlinear loads. Moreover, for a modular DC-DC converter using several converters in parallel, the input power from PV panels is processed and distributed at the module level. Methods for properly implementing distributed MPPT are studied. A new approach to efficient MPPT under partial shading conditions is presented. The power stage architecture achieves fast input current change rate by combining a current-adjustable converter with a few converters operating at a constant current.

Real-time implementation of optimized maximum noise fraction transform for feature extraction of hyperspectral images

NASA Astrophysics Data System (ADS)

Wu, Yuanfeng; Gao, Lianru; Zhang, Bing; Zhao, Haina; Li, Jun

2014-01-01

We present a parallel implementation of the optimized maximum noise fraction (G-OMNF) transform algorithm for feature extraction of hyperspectral images on commodity graphics processing units (GPUs). The proposed approach explored the algorithm data-level concurrency and optimized the computing flow. We first defined a three-dimensional grid, in which each thread calculates a sub-block data to easily facilitate the spatial and spectral neighborhood data searches in noise estimation, which is one of the most important steps involved in OMNF. Then, we optimized the processing flow and computed the noise covariance matrix before computing the image covariance matrix to reduce the original hyperspectral image data transmission. These optimization strategies can greatly improve the computing efficiency and can be applied to other feature extraction algorithms. The proposed parallel feature extraction algorithm was implemented on an Nvidia Tesla GPU using the compute unified device architecture and basic linear algebra subroutines library. Through the experiments on several real hyperspectral images, our GPU parallel implementation provides a significant speedup of the algorithm compared with the CPU implementation, especially for highly data parallelizable and arithmetically intensive algorithm parts, such as noise estimation. In order to further evaluate the effectiveness of G-OMNF, we used two different applications: spectral unmixing and classification for evaluation. Considering the sensor scanning rate and the data acquisition time, the proposed parallel implementation met the on-board real-time feature extraction.

Parallel-Processing Equalizers for Multi-Gbps Communications

NASA Technical Reports Server (NTRS)

Gray, Andrew; Ghuman, Parminder; Hoy, Scott; Satorius, Edgar H.

2004-01-01

Architectures have been proposed for the design of frequency-domain least-mean-square complex equalizers that would be integral parts of parallel- processing digital receivers of multi-gigahertz radio signals and other quadrature-phase-shift-keying (QPSK) or 16-quadrature-amplitude-modulation (16-QAM) of data signals at rates of multiple gigabits per second. Equalizers as used here denotes receiver subsystems that compensate for distortions in the phase and frequency responses of the broad-band radio-frequency channels typically used to convey such signals. The proposed architectures are suitable for realization in very-large-scale integrated (VLSI) circuitry and, in particular, complementary metal oxide semiconductor (CMOS) application- specific integrated circuits (ASICs) operating at frequencies lower than modulation symbol rates. A digital receiver of the type to which the proposed architecture applies (see Figure 1) would include an analog-to-digital converter (A/D) operating at a rate, fs, of 4 samples per symbol period. To obtain the high speed necessary for sampling, the A/D and a 1:16 demultiplexer immediately following it would be constructed as GaAs integrated circuits. The parallel-processing circuitry downstream of the demultiplexer, including a demodulator followed by an equalizer, would operate at a rate of only fs/16 (in other words, at 1/4 of the symbol rate). The output from the equalizer would be four parallel streams of in-phase (I) and quadrature (Q) samples.

Score Equating and Nominally Parallel Language Tests.

ERIC Educational Resources Information Center

Moy, Raymond

Score equating requires that the forms to be equated are functionally parallel. That is, the two test forms should rank order examinees in a similar fashion. In language proficiency testing situations, this assumption is often put into doubt because of the numerous tests that have been proposed as measures of language proficiency and the…

Fast, Massively Parallel Data Processors

NASA Technical Reports Server (NTRS)

Heaton, Robert A.; Blevins, Donald W.; Davis, ED

1994-01-01

Proposed fast, massively parallel data processor contains 8x16 array of processing elements with efficient interconnection scheme and options for flexible local control. Processing elements communicate with each other on "X" interconnection grid with external memory via high-capacity input/output bus. This approach to conditional operation nearly doubles speed of various arithmetic operations.

Hybrid parallel computing architecture for multiview phase shifting

NASA Astrophysics Data System (ADS)

Zhong, Kai; Li, Zhongwei; Zhou, Xiaohui; Shi, Yusheng; Wang, Congjun

2014-11-01

The multiview phase-shifting method shows its powerful capability in achieving high resolution three-dimensional (3-D) shape measurement. Unfortunately, this ability results in very high computation costs and 3-D computations have to be processed offline. To realize real-time 3-D shape measurement, a hybrid parallel computing architecture is proposed for multiview phase shifting. In this architecture, the central processing unit can co-operate with the graphic processing unit (GPU) to achieve hybrid parallel computing. The high computation cost procedures, including lens distortion rectification, phase computation, correspondence, and 3-D reconstruction, are implemented in GPU, and a three-layer kernel function model is designed to simultaneously realize coarse-grained and fine-grained paralleling computing. Experimental results verify that the developed system can perform 50 fps (frame per second) real-time 3-D measurement with 260 K 3-D points per frame. A speedup of up to 180 times is obtained for the performance of the proposed technique using a NVIDIA GT560Ti graphics card rather than a sequential C in a 3.4 GHZ Inter Core i7 3770.

Accelerating EPI distortion correction by utilizing a modern GPU-based parallel computation.

PubMed

Yang, Yao-Hao; Huang, Teng-Yi; Wang, Fu-Nien; Chuang, Tzu-Chao; Chen, Nan-Kuei

2013-04-01

The combination of phase demodulation and field mapping is a practical method to correct echo planar imaging (EPI) geometric distortion. However, since phase dispersion accumulates in each phase-encoding step, the calculation complexity of phase modulation is Ny-fold higher than conventional image reconstructions. Thus, correcting EPI images via phase demodulation is generally a time-consuming task. Parallel computing by employing general-purpose calculations on graphics processing units (GPU) can accelerate scientific computing if the algorithm is parallelized. This study proposes a method that incorporates the GPU-based technique into phase demodulation calculations to reduce computation time. The proposed parallel algorithm was applied to a PROPELLER-EPI diffusion tensor data set. The GPU-based phase demodulation method reduced the EPI distortion correctly, and accelerated the computation. The total reconstruction time of the 16-slice PROPELLER-EPI diffusion tensor images with matrix size of 128 × 128 was reduced from 1,754 seconds to 101 seconds by utilizing the parallelized 4-GPU program. GPU computing is a promising method to accelerate EPI geometric correction. The resulting reduction in computation time of phase demodulation should accelerate postprocessing for studies performed with EPI, and should effectuate the PROPELLER-EPI technique for clinical practice. Copyright © 2011 by the American Society of Neuroimaging.

WFIRST: Science from the Guest Investigator and Parallel Observation Programs

NASA Astrophysics Data System (ADS)

Postman, Marc; Nataf, David; Furlanetto, Steve; Milam, Stephanie; Robertson, Brant; Williams, Ben; Teplitz, Harry; Moustakas, Leonidas; Geha, Marla; Gilbert, Karoline; Dickinson, Mark; Scolnic, Daniel; Ravindranath, Swara; Strolger, Louis; Peek, Joshua; Marc Postman

2018-01-01

The Wide Field InfraRed Survey Telescope (WFIRST) mission will provide an extremely rich archival dataset that will enable a broad range of scientific investigations beyond the initial objectives of the proposed key survey programs. The scientific impact of WFIRST will thus be significantly expanded by a robust Guest Investigator (GI) archival research program. We will present examples of GI research opportunities ranging from studies of the properties of a variety of Solar System objects, surveys of the outer Milky Way halo, comprehensive studies of cluster galaxies, to unique and new constraints on the epoch of cosmic re-ionization and the assembly of galaxies in the early universe.WFIRST will also support the acquisition of deep wide-field imaging and slitless spectroscopic data obtained in parallel during campaigns with the coronagraphic instrument (CGI). These parallel wide-field imager (WFI) datasets can provide deep imaging data covering several square degrees at no impact to the scheduling of the CGI program. A competitively selected program of well-designed parallel WFI observation programs will, like the GI science above, maximize the overall scientific impact of WFIRST. We will give two examples of parallel observations that could be conducted during a proposed CGI program centered on a dozen nearby stars.

A fast pulse design for parallel excitation with gridding conjugate gradient.

PubMed

Feng, Shuo; Ji, Jim

2013-01-01

Parallel excitation (pTx) is recognized as a crucial technique in high field MRI to address the transmit field inhomogeneity problem. However, it can be time consuming to design pTx pulses which is not desirable. In this work, we propose a pulse design with gridding conjugate gradient (CG) based on the small-tip-angle approximation. The two major time consuming matrix-vector multiplications are substituted by two operators which involves with FFT and gridding only. Simulation results have shown that the proposed method is 3 times faster than conventional method and the memory cost is reduced by 1000 times.

A parallel-machine scheduling problem with two competing agents

NASA Astrophysics Data System (ADS)

Lee, Wen-Chiung; Chung, Yu-Hsiang; Wang, Jen-Ya

2017-06-01

Scheduling with two competing agents has become popular in recent years. Most of the research has focused on single-machine problems. This article considers a parallel-machine problem, the objective of which is to minimize the total completion time of jobs from the first agent given that the maximum tardiness of jobs from the second agent cannot exceed an upper bound. The NP-hardness of this problem is also examined. A genetic algorithm equipped with local search is proposed to search for the near-optimal solution. Computational experiments are conducted to evaluate the proposed genetic algorithm.

The source of dual-task limitations: Serial or parallel processing of multiple response selections?

PubMed Central

Marois, René

2014-01-01

Although it is generally recognized that the concurrent performance of two tasks incurs costs, the sources of these dual-task costs remain controversial. The serial bottleneck model suggests that serial postponement of task performance in dual-task conditions results from a central stage of response selection that can only process one task at a time. Cognitive-control models, by contrast, propose that multiple response selections can proceed in parallel, but that serial processing of task performance is predominantly adopted because its processing efficiency is higher than that of parallel processing. In the present study, we empirically tested this proposition by examining whether parallel processing would occur when it was more efficient and financially rewarded. The results indicated that even when parallel processing was more efficient and was incentivized by financial reward, participants still failed to process tasks in parallel. We conclude that central information processing is limited by a serial bottleneck. PMID:23864266

Parallel transformation of K-SVD solar image denoising algorithm

NASA Astrophysics Data System (ADS)

Liang, Youwen; Tian, Yu; Li, Mei

2017-02-01

The images obtained by observing the sun through a large telescope always suffered with noise due to the low SNR. K-SVD denoising algorithm can effectively remove Gauss white noise. Training dictionaries for sparse representations is a time consuming task, due to the large size of the data involved and to the complexity of the training algorithms. In this paper, an OpenMP parallel programming language is proposed to transform the serial algorithm to the parallel version. Data parallelism model is used to transform the algorithm. Not one atom but multiple atoms updated simultaneously is the biggest change. The denoising effect and acceleration performance are tested after completion of the parallel algorithm. Speedup of the program is 13.563 in condition of using 16 cores. This parallel version can fully utilize the multi-core CPU hardware resources, greatly reduce running time and easily to transplant in multi-core platform.

Demonstration of an optoelectronic interconnect architecture for a parallel modified signed-digit adder and subtracter

NASA Astrophysics Data System (ADS)

Sun, Degui; Wang, Na-Xin; He, Li-Ming; Weng, Zhao-Heng; Wang, Daheng; Chen, Ray T.

1996-06-01

A space-position-logic-encoding scheme is proposed and demonstrated. This encoding scheme not only makes the best use of the convenience of binary logic operation, but is also suitable for the trinary property of modified signed- digit (MSD) numbers. Based on the space-position-logic-encoding scheme, a fully parallel modified signed-digit adder and subtractor is built using optoelectronic switch technologies in conjunction with fiber-multistage 3D optoelectronic interconnects. Thus an effective combination of a parallel algorithm and a parallel architecture is implemented. In addition, the performance of the optoelectronic switches used in this system is experimentally studied and verified. Both the 3-bit experimental model and the experimental results of a parallel addition and a parallel subtraction are provided and discussed. Finally, the speed ratio between the MSD adder and binary adders is discussed and the advantage of the MSD in operating speed is demonstrated.

PRIM: An Efficient Preconditioning Iterative Reweighted Least Squares Method for Parallel Brain MRI Reconstruction.

PubMed

Xu, Zheng; Wang, Sheng; Li, Yeqing; Zhu, Feiyun; Huang, Junzhou

2018-02-08

The most recent history of parallel Magnetic Resonance Imaging (pMRI) has in large part been devoted to finding ways to reduce acquisition time. While joint total variation (JTV) regularized model has been demonstrated as a powerful tool in increasing sampling speed for pMRI, however, the major bottleneck is the inefficiency of the optimization method. While all present state-of-the-art optimizations for the JTV model could only reach a sublinear convergence rate, in this paper, we squeeze the performance by proposing a linear-convergent optimization method for the JTV model. The proposed method is based on the Iterative Reweighted Least Squares algorithm. Due to the complexity of the tangled JTV objective, we design a novel preconditioner to further accelerate the proposed method. Extensive experiments demonstrate the superior performance of the proposed algorithm for pMRI regarding both accuracy and efficiency compared with state-of-the-art methods.

Fast encryption of RGB color digital images using a tweakable cellular automaton based schema

NASA Astrophysics Data System (ADS)

Faraoun, Kamel Mohamed

2014-12-01

We propose a new tweakable construction of block-enciphers using second-order reversible cellular automata, and we apply it to encipher RGB-colored images. The proposed construction permits a parallel encryption of the image content by extending the standard definition of a block cipher to take into account a supplementary parameter used as a tweak (nonce) to control the behavior of the cipher from one region of the image to the other, and hence avoid the necessity to use slow sequential encryption's operating modes. The proposed construction defines a flexible pseudorandom permutation that can be used with efficacy to solve the electronic code book problem without the need to a specific sequential mode. Obtained results from various experiments show that the proposed schema achieves high security and execution performances, and enables an interesting mode of selective area decryption due to the parallel character of the approach.

A Parallel Saturation Algorithm on Shared Memory Architectures

NASA Technical Reports Server (NTRS)

Ezekiel, Jonathan; Siminiceanu

2007-01-01

Symbolic state-space generators are notoriously hard to parallelize. However, the Saturation algorithm implemented in the SMART verification tool differs from other sequential symbolic state-space generators in that it exploits the locality of ring events in asynchronous system models. This paper explores whether event locality can be utilized to efficiently parallelize Saturation on shared-memory architectures. Conceptually, we propose to parallelize the ring of events within a decision diagram node, which is technically realized via a thread pool. We discuss the challenges involved in our parallel design and conduct experimental studies on its prototypical implementation. On a dual-processor dual core PC, our studies show speed-ups for several example models, e.g., of up to 50% for a Kanban model, when compared to running our algorithm only on a single core.

Synthesizing parallel imaging applications using the CAP (computer-aided parallelization) tool

NASA Astrophysics Data System (ADS)

Gennart, Benoit A.; Mazzariol, Marc; Messerli, Vincent; Hersch, Roger D.

1997-12-01

Imaging applications such as filtering, image transforms and compression/decompression require vast amounts of computing power when applied to large data sets. These applications would potentially benefit from the use of parallel processing. However, dedicated parallel computers are expensive and their processing power per node lags behind that of the most recent commodity components. Furthermore, developing parallel applications remains a difficult task: writing and debugging the application is difficult (deadlocks), programs may not be portable from one parallel architecture to the other, and performance often comes short of expectations. In order to facilitate the development of parallel applications, we propose the CAP computer-aided parallelization tool which enables application programmers to specify at a high-level of abstraction the flow of data between pipelined-parallel operations. In addition, the CAP tool supports the programmer in developing parallel imaging and storage operations. CAP enables combining efficiently parallel storage access routines and image processing sequential operations. This paper shows how processing and I/O intensive imaging applications must be implemented to take advantage of parallelism and pipelining between data access and processing. This paper's contribution is (1) to show how such implementations can be compactly specified in CAP, and (2) to demonstrate that CAP specified applications achieve the performance of custom parallel code. The paper analyzes theoretically the performance of CAP specified applications and demonstrates the accuracy of the theoretical analysis through experimental measurements.

Array signal recovery algorithm for a single-RF-channel DBF array

NASA Astrophysics Data System (ADS)

Zhang, Duo; Wu, Wen; Fang, Da Gang

2016-12-01

An array signal recovery algorithm based on sparse signal reconstruction theory is proposed for a single-RF-channel digital beamforming (DBF) array. A single-RF-channel antenna array is a low-cost antenna array in which signals are obtained from all antenna elements by only one microwave digital receiver. The spatially parallel array signals are converted into time-sequence signals, which are then sampled by the system. The proposed algorithm uses these time-sequence samples to recover the original parallel array signals by exploiting the second-order sparse structure of the array signals. Additionally, an optimization method based on the artificial bee colony (ABC) algorithm is proposed to improve the reconstruction performance. Using the proposed algorithm, the motion compensation problem for the single-RF-channel DBF array can be solved effectively, and the angle and Doppler information for the target can be simultaneously estimated. The effectiveness of the proposed algorithms is demonstrated by the results of numerical simulations.

A Developmental Perspective on Peer Rejection, Deviant Peer Affiliation, and Conduct Problems Among Youth.

PubMed

Chen, Diane; Drabick, Deborah A G; Burgers, Darcy E

2015-12-01

Peer rejection and deviant peer affiliation are linked consistently to the development and maintenance of conduct problems. Two proposed models may account for longitudinal relations among these peer processes and conduct problems: the (a) sequential mediation model, in which peer rejection in childhood and deviant peer affiliation in adolescence mediate the link between early externalizing behaviors and more serious adolescent conduct problems; and (b) parallel process model, in which peer rejection and deviant peer affiliation are considered independent processes that operate simultaneously to increment risk for conduct problems. In this review, we evaluate theoretical models and evidence for associations among conduct problems and (a) peer rejection and (b) deviant peer affiliation. We then consider support for the sequential mediation and parallel process models. Next, we propose an integrated model incorporating both the sequential mediation and parallel process models. Future research directions and implications for prevention and intervention efforts are discussed.

A Developmental Perspective on Peer Rejection, Deviant Peer Affiliation, and Conduct Problems among Youth

PubMed Central

Chen, Diane; Drabick, Deborah A. G.; Burgers, Darcy E.

2015-01-01

Peer rejection and deviant peer affiliation are linked consistently to the development and maintenance of conduct problems. Two proposed models may account for longitudinal relations among these peer processes and conduct problems: the (a) sequential mediation model, in which peer rejection in childhood and deviant peer affiliation in adolescence mediate the link between early externalizing behaviors and more serious adolescent conduct problems; and (b) parallel process model, in which peer rejection and deviant peer affiliation are considered independent processes that operate simultaneously to increment risk for conduct problems. In this review, we evaluate theoretical models and evidence for associations among conduct problems and (a) peer rejection and (b) deviant peer affiliation. We then consider support for the sequential mediation and parallel process models. Next, we propose an integrated model incorporating both the sequential mediation and parallel process models. Future research directions and implications for prevention and intervention efforts are discussed. PMID:25410430

Conceptual design and kinematic analysis of a novel parallel robot for high-speed pick-and-place operations

NASA Astrophysics Data System (ADS)

Meng, Qizhi; Xie, Fugui; Liu, Xin-Jun

2018-06-01

This paper deals with the conceptual design, kinematic analysis and workspace identification of a novel four degrees-of-freedom (DOFs) high-speed spatial parallel robot for pick-and-place operations. The proposed spatial parallel robot consists of a base, four arms and a 1½ mobile platform. The mobile platform is a major innovation that avoids output singularity and offers the advantages of both single and double platforms. To investigate the characteristics of the robot's DOFs, a line graph method based on Grassmann line geometry is adopted in mobility analysis. In addition, the inverse kinematics is derived, and the constraint conditions to identify the correct solution are also provided. On the basis of the proposed concept, the workspace of the robot is identified using a set of presupposed parameters by taking input and output transmission index as the performance evaluation criteria.

Sequential and parallel image restoration: neural network implementations.

PubMed

Figueiredo, M T; Leitao, J N

1994-01-01

Sequential and parallel image restoration algorithms and their implementations on neural networks are proposed. For images degraded by linear blur and contaminated by additive white Gaussian noise, maximum a posteriori (MAP) estimation and regularization theory lead to the same high dimension convex optimization problem. The commonly adopted strategy (in using neural networks for image restoration) is to map the objective function of the optimization problem into the energy of a predefined network, taking advantage of its energy minimization properties. Departing from this approach, we propose neural implementations of iterative minimization algorithms which are first proved to converge. The developed schemes are based on modified Hopfield (1985) networks of graded elements, with both sequential and parallel updating schedules. An algorithm supported on a fully standard Hopfield network (binary elements and zero autoconnections) is also considered. Robustness with respect to finite numerical precision is studied, and examples with real images are presented.

Crystal MD: The massively parallel molecular dynamics software for metal with BCC structure

NASA Astrophysics Data System (ADS)

Hu, Changjun; Bai, He; He, Xinfu; Zhang, Boyao; Nie, Ningming; Wang, Xianmeng; Ren, Yingwen

2017-02-01

Material irradiation effect is one of the most important keys to use nuclear power. However, the lack of high-throughput irradiation facility and knowledge of evolution process, lead to little understanding of the addressed issues. With the help of high-performance computing, we could make a further understanding of micro-level-material. In this paper, a new data structure is proposed for the massively parallel simulation of the evolution of metal materials under irradiation environment. Based on the proposed data structure, we developed the new molecular dynamics software named Crystal MD. The simulation with Crystal MD achieved over 90% parallel efficiency in test cases, and it takes more than 25% less memory on multi-core clusters than LAMMPS and IMD, which are two popular molecular dynamics simulation software. Using Crystal MD, a two trillion particles simulation has been performed on Tianhe-2 cluster.

Enhancing membrane protein subcellular localization prediction by parallel fusion of multi-view features.

PubMed

Yu, Dongjun; Wu, Xiaowei; Shen, Hongbin; Yang, Jian; Tang, Zhenmin; Qi, Yong; Yang, Jingyu

2012-12-01

Membrane proteins are encoded by ~ 30% in the genome and function importantly in the living organisms. Previous studies have revealed that membrane proteins' structures and functions show obvious cell organelle-specific properties. Hence, it is highly desired to predict membrane protein's subcellular location from the primary sequence considering the extreme difficulties of membrane protein wet-lab studies. Although many models have been developed for predicting protein subcellular locations, only a few are specific to membrane proteins. Existing prediction approaches were constructed based on statistical machine learning algorithms with serial combination of multi-view features, i.e., different feature vectors are simply serially combined to form a super feature vector. However, such simple combination of features will simultaneously increase the information redundancy that could, in turn, deteriorate the final prediction accuracy. That's why it was often found that prediction success rates in the serial super space were even lower than those in a single-view space. The purpose of this paper is investigation of a proper method for fusing multiple multi-view protein sequential features for subcellular location predictions. Instead of serial strategy, we propose a novel parallel framework for fusing multiple membrane protein multi-view attributes that will represent protein samples in complex spaces. We also proposed generalized principle component analysis (GPCA) for feature reduction purpose in the complex geometry. All the experimental results through different machine learning algorithms on benchmark membrane protein subcellular localization datasets demonstrate that the newly proposed parallel strategy outperforms the traditional serial approach. We also demonstrate the efficacy of the parallel strategy on a soluble protein subcellular localization dataset indicating the parallel technique is flexible to suite for other computational biology problems. The software and datasets are available at: http://www.csbio.sjtu.edu.cn/bioinf/mpsp.

Hierarchical fractional-step approximations and parallel kinetic Monte Carlo algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arampatzis, Giorgos, E-mail: garab@math.uoc.gr; Katsoulakis, Markos A., E-mail: markos@math.umass.edu; Plechac, Petr, E-mail: plechac@math.udel.edu

2012-10-01

We present a mathematical framework for constructing and analyzing parallel algorithms for lattice kinetic Monte Carlo (KMC) simulations. The resulting algorithms have the capacity to simulate a wide range of spatio-temporal scales in spatially distributed, non-equilibrium physiochemical processes with complex chemistry and transport micro-mechanisms. Rather than focusing on constructing exactly the stochastic trajectories, our approach relies on approximating the evolution of observables, such as density, coverage, correlations and so on. More specifically, we develop a spatial domain decomposition of the Markov operator (generator) that describes the evolution of all observables according to the kinetic Monte Carlo algorithm. This domain decompositionmore » corresponds to a decomposition of the Markov generator into a hierarchy of operators and can be tailored to specific hierarchical parallel architectures such as multi-core processors or clusters of Graphical Processing Units (GPUs). Based on this operator decomposition, we formulate parallel Fractional step kinetic Monte Carlo algorithms by employing the Trotter Theorem and its randomized variants; these schemes, (a) are partially asynchronous on each fractional step time-window, and (b) are characterized by their communication schedule between processors. The proposed mathematical framework allows us to rigorously justify the numerical and statistical consistency of the proposed algorithms, showing the convergence of our approximating schemes to the original serial KMC. The approach also provides a systematic evaluation of different processor communicating schedules. We carry out a detailed benchmarking of the parallel KMC schemes using available exact solutions, for example, in Ising-type systems and we demonstrate the capabilities of the method to simulate complex spatially distributed reactions at very large scales on GPUs. Finally, we discuss work load balancing between processors and propose a re-balancing scheme based on probabilistic mass transport methods.« less

A General-purpose Framework for Parallel Processing of Large-scale LiDAR Data

NASA Astrophysics Data System (ADS)

Li, Z.; Hodgson, M.; Li, W.

2016-12-01

Light detection and ranging (LiDAR) technologies have proven efficiency to quickly obtain very detailed Earth surface data for a large spatial extent. Such data is important for scientific discoveries such as Earth and ecological sciences and natural disasters and environmental applications. However, handling LiDAR data poses grand geoprocessing challenges due to data intensity and computational intensity. Previous studies received notable success on parallel processing of LiDAR data to these challenges. However, these studies either relied on high performance computers and specialized hardware (GPUs) or focused mostly on finding customized solutions for some specific algorithms. We developed a general-purpose scalable framework coupled with sophisticated data decomposition and parallelization strategy to efficiently handle big LiDAR data. Specifically, 1) a tile-based spatial index is proposed to manage big LiDAR data in the scalable and fault-tolerable Hadoop distributed file system, 2) two spatial decomposition techniques are developed to enable efficient parallelization of different types of LiDAR processing tasks, and 3) by coupling existing LiDAR processing tools with Hadoop, this framework is able to conduct a variety of LiDAR data processing tasks in parallel in a highly scalable distributed computing environment. The performance and scalability of the framework is evaluated with a series of experiments conducted on a real LiDAR dataset using a proof-of-concept prototype system. The results show that the proposed framework 1) is able to handle massive LiDAR data more efficiently than standalone tools; and 2) provides almost linear scalability in terms of either increased workload (data volume) or increased computing nodes with both spatial decomposition strategies. We believe that the proposed framework provides valuable references on developing a collaborative cyberinfrastructure for processing big earth science data in a highly scalable environment.

Competitive Parallel Processing For Compression Of Data

NASA Technical Reports Server (NTRS)

Diner, Daniel B.; Fender, Antony R. H.

1990-01-01

Momentarily-best compression algorithm selected. Proposed competitive-parallel-processing system compresses data for transmission in channel of limited band-width. Likely application for compression lies in high-resolution, stereoscopic color-television broadcasting. Data from information-rich source like color-television camera compressed by several processors, each operating with different algorithm. Referee processor selects momentarily-best compressed output.

Methods and Models for the Construction of Weakly Parallel Tests. Research Report 90-4.

ERIC Educational Resources Information Center

Adema, Jos J.

Methods are proposed for the construction of weakly parallel tests, that is, tests with the same test information function. A mathematical programing model for constructing tests with a prespecified test information function and a heuristic for assigning items to tests such that their information functions are equal play an important role in the…

Analysis of Serial and Parallel Algorithms for Use in Molecular Dynamics.. Review and Proposals

NASA Astrophysics Data System (ADS)

Mazzone, A. M.

This work analyzes the stability and accuracy of multistep methods, either for serial or parallel calculations, applied to molecular dynamics simulations. Numerical testing is made by evaluating the equilibrium configurations of mono-elemental crystalline lattices of metallic and semiconducting type (Ag and Si, respectively) and of a cubic CuY compound.

A systemic approach for modeling biological evolution using Parallel DEVS.

PubMed

Heredia, Daniel; Sanz, Victorino; Urquia, Alfonso; Sandín, Máximo

2015-08-01

A new model for studying the evolution of living organisms is proposed in this manuscript. The proposed model is based on a non-neodarwinian systemic approach. The model is focused on considering several controversies and open discussions about modern evolutionary biology. Additionally, a simplification of the proposed model, named EvoDEVS, has been mathematically described using the Parallel DEVS formalism and implemented as a computer program using the DEVSLib Modelica library. EvoDEVS serves as an experimental platform to study different conditions and scenarios by means of computer simulations. Two preliminary case studies are presented to illustrate the behavior of the model and validate its results. EvoDEVS is freely available at http://www.euclides.dia.uned.es. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Load Forecasting Based Distribution System Network Reconfiguration -- A Distributed Data-Driven Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Huaiguang; Zhang, Yingchen; Muljadi, Eduard

In this paper, a short-term load forecasting approach based network reconfiguration is proposed in a parallel manner. Specifically, a support vector regression (SVR) based short-term load forecasting approach is designed to provide an accurate load prediction and benefit the network reconfiguration. Because of the nonconvexity of the three-phase balanced optimal power flow, a second-order cone program (SOCP) based approach is used to relax the optimal power flow problem. Then, the alternating direction method of multipliers (ADMM) is used to compute the optimal power flow in distributed manner. Considering the limited number of the switches and the increasing computation capability, themore » proposed network reconfiguration is solved in a parallel way. The numerical results demonstrate the feasible and effectiveness of the proposed approach.« less

Geospatial Applications on Different Parallel and Distributed Systems in enviroGRIDS Project

NASA Astrophysics Data System (ADS)

Rodila, D.; Bacu, V.; Gorgan, D.

2012-04-01

The execution of Earth Science applications and services on parallel and distributed systems has become a necessity especially due to the large amounts of Geospatial data these applications require and the large geographical areas they cover. The parallelization of these applications comes to solve important performance issues and can spread from task parallelism to data parallelism as well. Parallel and distributed architectures such as Grid, Cloud, Multicore, etc. seem to offer the necessary functionalities to solve important problems in the Earth Science domain: storing, distribution, management, processing and security of Geospatial data, execution of complex processing through task and data parallelism, etc. A main goal of the FP7-funded project enviroGRIDS (Black Sea Catchment Observation and Assessment System supporting Sustainable Development) [1] is the development of a Spatial Data Infrastructure targeting this catchment region but also the development of standardized and specialized tools for storing, analyzing, processing and visualizing the Geospatial data concerning this area. For achieving these objectives, the enviroGRIDS deals with the execution of different Earth Science applications, such as hydrological models, Geospatial Web services standardized by the Open Geospatial Consortium (OGC) and others, on parallel and distributed architecture to maximize the obtained performance. This presentation analysis the integration and execution of Geospatial applications on different parallel and distributed architectures and the possibility of choosing among these architectures based on application characteristics and user requirements through a specialized component. Versions of the proposed platform have been used in enviroGRIDS project on different use cases such as: the execution of Geospatial Web services both on Web and Grid infrastructures [2] and the execution of SWAT hydrological models both on Grid and Multicore architectures [3]. The current focus is to integrate in the proposed platform the Cloud infrastructure, which is still a paradigm with critical problems to be solved despite the great efforts and investments. Cloud computing comes as a new way of delivering resources while using a large set of old as well as new technologies and tools for providing the necessary functionalities. The main challenges in the Cloud computing, most of them identified also in the Open Cloud Manifesto 2009, address resource management and monitoring, data and application interoperability and portability, security, scalability, software licensing, etc. We propose a platform able to execute different Geospatial applications on different parallel and distributed architectures such as Grid, Cloud, Multicore, etc. with the possibility of choosing among these architectures based on application characteristics and complexity, user requirements, necessary performances, cost support, etc. The execution redirection on a selected architecture is realized through a specialized component and has the purpose of offering a flexible way in achieving the best performances considering the existing restrictions.

Optimal Design of Passive Power Filters Based on Pseudo-parallel Genetic Algorithm

NASA Astrophysics Data System (ADS)

Li, Pei; Li, Hongbo; Gao, Nannan; Niu, Lin; Guo, Liangfeng; Pei, Ying; Zhang, Yanyan; Xu, Minmin; Chen, Kerui

2017-05-01

The economic costs together with filter efficiency are taken as targets to optimize the parameter of passive filter. Furthermore, the method of combining pseudo-parallel genetic algorithm with adaptive genetic algorithm is adopted in this paper. In the early stages pseudo-parallel genetic algorithm is introduced to increase the population diversity, and adaptive genetic algorithm is used in the late stages to reduce the workload. At the same time, the migration rate of pseudo-parallel genetic algorithm is improved to change with population diversity adaptively. Simulation results show that the filter designed by the proposed method has better filtering effect with lower economic cost, and can be used in engineering.

A time-parallel approach to strong-constraint four-dimensional variational data assimilation

NASA Astrophysics Data System (ADS)

Rao, Vishwas; Sandu, Adrian

2016-05-01

A parallel-in-time algorithm based on an augmented Lagrangian approach is proposed to solve four-dimensional variational (4D-Var) data assimilation problems. The assimilation window is divided into multiple sub-intervals that allows parallelization of cost function and gradient computations. The solutions to the continuity equations across interval boundaries are added as constraints. The augmented Lagrangian approach leads to a different formulation of the variational data assimilation problem than the weakly constrained 4D-Var. A combination of serial and parallel 4D-Vars to increase performance is also explored. The methodology is illustrated on data assimilation problems involving the Lorenz-96 and the shallow water models.

Using a constraint on the parallel velocity when determining electric fields with EISCAT

NASA Technical Reports Server (NTRS)

Caudal, G.; Blanc, M.

1988-01-01

A method is proposed to determine the perpendicular components of the ion velocity vector (and hence the perpendicular electric field) from EISCAT tristatic measurements, in which one introduces an additional constraint on the parallel velocity, in order to take account of our knowledge that the parallel velocity of ions is small. This procedure removes some artificial features introduced when the tristatic geometry becomes too unfavorable. It is particularly well suited for the southernmost or northernmost positions of the tristatic measurements performed by meridian scan experiments (CP3 mode).

Data decomposition method for parallel polygon rasterization considering load balancing

NASA Astrophysics Data System (ADS)

Zhou, Chen; Chen, Zhenjie; Liu, Yongxue; Li, Feixue; Cheng, Liang; Zhu, A.-xing; Li, Manchun

2015-12-01

It is essential to adopt parallel computing technology to rapidly rasterize massive polygon data. In parallel rasterization, it is difficult to design an effective data decomposition method. Conventional methods ignore load balancing of polygon complexity in parallel rasterization and thus fail to achieve high parallel efficiency. In this paper, a novel data decomposition method based on polygon complexity (DMPC) is proposed. First, four factors that possibly affect the rasterization efficiency were investigated. Then, a metric represented by the boundary number and raster pixel number in the minimum bounding rectangle was developed to calculate the complexity of each polygon. Using this metric, polygons were rationally allocated according to the polygon complexity, and each process could achieve balanced loads of polygon complexity. To validate the efficiency of DMPC, it was used to parallelize different polygon rasterization algorithms and tested on different datasets. Experimental results showed that DMPC could effectively parallelize polygon rasterization algorithms. Furthermore, the implemented parallel algorithms with DMPC could achieve good speedup ratios of at least 15.69 and generally outperformed conventional decomposition methods in terms of parallel efficiency and load balancing. In addition, the results showed that DMPC exhibited consistently better performance for different spatial distributions of polygons.

Optimizing Crawler4j using MapReduce Programming Model

NASA Astrophysics Data System (ADS)

Siddesh, G. M.; Suresh, Kavya; Madhuri, K. Y.; Nijagal, Madhushree; Rakshitha, B. R.; Srinivasa, K. G.

2017-06-01

World wide web is a decentralized system that consists of a repository of information on the basis of web pages. These web pages act as a source of information or data in the present analytics world. Web crawlers are used for extracting useful information from web pages for different purposes. Firstly, it is used in web search engines where the web pages are indexed to form a corpus of information and allows the users to query on the web pages. Secondly, it is used for web archiving where the web pages are stored for later analysis phases. Thirdly, it can be used for web mining where the web pages are monitored for copyright purposes. The amount of information processed by the web crawler needs to be improved by using the capabilities of modern parallel processing technologies. In order to solve the problem of parallelism and the throughput of crawling this work proposes to optimize the Crawler4j using the Hadoop MapReduce programming model by parallelizing the processing of large input data. Crawler4j is a web crawler that retrieves useful information about the pages that it visits. The crawler Crawler4j coupled with data and computational parallelism of Hadoop MapReduce programming model improves the throughput and accuracy of web crawling. The experimental results demonstrate that the proposed solution achieves significant improvements with respect to performance and throughput. Hence the proposed approach intends to carve out a new methodology towards optimizing web crawling by achieving significant performance gain.

Parallel microscope-based fluorescence, absorbance and time-of-flight mass spectrometry detection for high performance liquid chromatography and determination of glucosamine in urine.

PubMed

Xiong, Bo; Wang, Ling-Ling; Li, Qiong; Nie, Yu-Ting; Cheng, Shuang-Shuang; Zhang, Hui; Sun, Ren-Qiang; Wang, Yu-Jiao; Zhou, Hong-Bin

2015-11-01

A parallel microscope-based laser-induced fluorescence (LIF), ultraviolet-visible absorbance (UV) and time-of-flight mass spectrometry (TOF-MS) detection for high performance liquid chromatography (HPLC) was achieved and used to determine glucosamine in urines. First, a reliable and convenient LIF detection was developed based on an inverted microscope and corresponding modulations. Parallel HPLC-LIF/UV/TOF-MS detection was developed by the combination of preceding Microscope-based LIF detection and HPLC coupled with UV and TOF-MS. The proposed setup, due to its parallel scheme, was free of the influence from photo bleaching in LIF detection. Rhodamine B, glutamic acid and glucosamine have been determined to evaluate its performance. Moreover, the proposed strategy was used to determine the glucosamine in urines, and subsequent results suggested that glucosamine, which was widely used in the prevention of the bone arthritis, was metabolized to urines within 4h. Furthermore, its concentration in urines decreased to 5.4mM at 12h. Efficient glucosamine detection was achieved based on a sensitive quantification (LIF), a universal detection (UV) and structural characterizations (TOF-MS). This application indicated that the proposed strategy was sensitive, universal and versatile, and it was capable of improved analysis, especially for analytes with low concentrations in complex samples, compared with conventional HPLC-UV/TOF-MS. Copyright © 2015 Elsevier B.V. All rights reserved.

A 2D MTF approach to evaluate and guide dynamic imaging developments.

PubMed

Chao, Tzu-Cheng; Chung, Hsiao-Wen; Hoge, W Scott; Madore, Bruno

2010-02-01

As the number and complexity of partially sampled dynamic imaging methods continue to increase, reliable strategies to evaluate performance may prove most useful. In the present work, an analytical framework to evaluate given reconstruction methods is presented. A perturbation algorithm allows the proposed evaluation scheme to perform robustly without requiring knowledge about the inner workings of the method being evaluated. A main output of the evaluation process consists of a two-dimensional modulation transfer function, an easy-to-interpret visual rendering of a method's ability to capture all combinations of spatial and temporal frequencies. Approaches to evaluate noise properties and artifact content at all spatial and temporal frequencies are also proposed. One fully sampled phantom and three fully sampled cardiac cine datasets were subsampled (R = 4 and 8) and reconstructed with the different methods tested here. A hybrid method, which combines the main advantageous features observed in our assessments, was proposed and tested in a cardiac cine application, with acceleration factors of 3.5 and 6.3 (skip factors of 4 and 8, respectively). This approach combines features from methods such as k-t sensitivity encoding, unaliasing by Fourier encoding the overlaps in the temporal dimension-sensitivity encoding, generalized autocalibrating partially parallel acquisition, sensitivity profiles from an array of coils for encoding and reconstruction in parallel, self, hybrid referencing with unaliasing by Fourier encoding the overlaps in the temporal dimension and generalized autocalibrating partially parallel acquisition, and generalized autocalibrating partially parallel acquisition-enhanced sensitivity maps for sensitivity encoding reconstructions.

Runtime support for parallelizing data mining algorithms

NASA Astrophysics Data System (ADS)

Jin, Ruoming; Agrawal, Gagan

2002-03-01

With recent technological advances, shared memory parallel machines have become more scalable, and offer large main memories and high bus bandwidths. They are emerging as good platforms for data warehousing and data mining. In this paper, we focus on shared memory parallelization of data mining algorithms. We have developed a series of techniques for parallelization of data mining algorithms, including full replication, full locking, fixed locking, optimized full locking, and cache-sensitive locking. Unlike previous work on shared memory parallelization of specific data mining algorithms, all of our techniques apply to a large number of common data mining algorithms. In addition, we propose a reduction-object based interface for specifying a data mining algorithm. We show how our runtime system can apply any of the technique we have developed starting from a common specification of the algorithm.

Calibrationless parallel magnetic resonance imaging: a joint sparsity model.

PubMed

Majumdar, Angshul; Chaudhury, Kunal Narayan; Ward, Rabab

2013-12-05

State-of-the-art parallel MRI techniques either explicitly or implicitly require certain parameters to be estimated, e.g., the sensitivity map for SENSE, SMASH and interpolation weights for GRAPPA, SPIRiT. Thus all these techniques are sensitive to the calibration (parameter estimation) stage. In this work, we have proposed a parallel MRI technique that does not require any calibration but yields reconstruction results that are at par with (or even better than) state-of-the-art methods in parallel MRI. Our proposed method required solving non-convex analysis and synthesis prior joint-sparsity problems. This work also derives the algorithms for solving them. Experimental validation was carried out on two datasets-eight channel brain and eight channel Shepp-Logan phantom. Two sampling methods were used-Variable Density Random sampling and non-Cartesian Radial sampling. For the brain data, acceleration factor of 4 was used and for the other an acceleration factor of 6 was used. The reconstruction results were quantitatively evaluated based on the Normalised Mean Squared Error between the reconstructed image and the originals. The qualitative evaluation was based on the actual reconstructed images. We compared our work with four state-of-the-art parallel imaging techniques; two calibrated methods-CS SENSE and l1SPIRiT and two calibration free techniques-Distributed CS and SAKE. Our method yields better reconstruction results than all of them.

Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing

PubMed Central

Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin

2016-01-01

With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate. PMID:27070606

Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing.

PubMed

Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin

2016-04-07

With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.

Parallel-vector unsymmetric Eigen-Solver on high performance computers

NASA Technical Reports Server (NTRS)

Nguyen, Duc T.; Jiangning, Qin

1993-01-01

The popular QR algorithm for solving all eigenvalues of an unsymmetric matrix is reviewed. Among the basic components in the QR algorithm, it was concluded from this study, that the reduction of an unsymmetric matrix to a Hessenberg form (before applying the QR algorithm itself) can be done effectively by exploiting the vector speed and multiple processors offered by modern high-performance computers. Numerical examples of several test cases have indicated that the proposed parallel-vector algorithm for converting a given unsymmetric matrix to a Hessenberg form offers computational advantages over the existing algorithm. The time saving obtained by the proposed methods is increased as the problem size increased.

Distributed Function Mining for Gene Expression Programming Based on Fast Reduction.

PubMed

Deng, Song; Yue, Dong; Yang, Le-chan; Fu, Xiong; Feng, Ya-zhou

2016-01-01

For high-dimensional and massive data sets, traditional centralized gene expression programming (GEP) or improved algorithms lead to increased run-time and decreased prediction accuracy. To solve this problem, this paper proposes a new improved algorithm called distributed function mining for gene expression programming based on fast reduction (DFMGEP-FR). In DFMGEP-FR, fast attribution reduction in binary search algorithms (FAR-BSA) is proposed to quickly find the optimal attribution set, and the function consistency replacement algorithm is given to solve integration of the local function model. Thorough comparative experiments for DFMGEP-FR, centralized GEP and the parallel gene expression programming algorithm based on simulated annealing (parallel GEPSA) are included in this paper. For the waveform, mushroom, connect-4 and musk datasets, the comparative results show that the average time-consumption of DFMGEP-FR drops by 89.09%%, 88.85%, 85.79% and 93.06%, respectively, in contrast to centralized GEP and by 12.5%, 8.42%, 9.62% and 13.75%, respectively, compared with parallel GEPSA. Six well-studied UCI test data sets demonstrate the efficiency and capability of our proposed DFMGEP-FR algorithm for distributed function mining.

Virtual earthquake engineering laboratory with physics-based degrading materials on parallel computers

NASA Astrophysics Data System (ADS)

Cho, In Ho

For the last few decades, we have obtained tremendous insight into underlying microscopic mechanisms of degrading quasi-brittle materials from persistent and near-saintly efforts in laboratories, and at the same time we have seen unprecedented evolution in computational technology such as massively parallel computers. Thus, time is ripe to embark on a novel approach to settle unanswered questions, especially for the earthquake engineering community, by harmoniously combining the microphysics mechanisms with advanced parallel computing technology. To begin with, it should be stressed that we placed a great deal of emphasis on preserving clear meaning and physical counterparts of all the microscopic material models proposed herein, since it is directly tied to the belief that by doing so, the more physical mechanisms we incorporate, the better prediction we can obtain. We departed from reviewing representative microscopic analysis methodologies, selecting out "fixed-type" multidirectional smeared crack model as the base framework for nonlinear quasi-brittle materials, since it is widely believed to best retain the physical nature of actual cracks. Microscopic stress functions are proposed by integrating well-received existing models to update normal stresses on the crack surfaces (three orthogonal surfaces are allowed to initiate herein) under cyclic loading. Unlike the normal stress update, special attention had to be paid to the shear stress update on the crack surfaces, due primarily to the well-known pathological nature of the fixed-type smeared crack model---spurious large stress transfer over the open crack under nonproportional loading. In hopes of exploiting physical mechanism to resolve this deleterious nature of the fixed crack model, a tribology-inspired three-dimensional (3d) interlocking mechanism has been proposed. Following the main trend of tribology (i.e., the science and engineering of interacting surfaces), we introduced the base fabric of solid particle-soft matrix to explain realistic interlocking over rough crack surfaces, and the adopted Gaussian distribution feeds random particle sizes to the entire domain. Validation against a well-documented rough crack experiment reveals promising accuracy of the proposed 3d interlocking model. A consumed energy-based damage model has been proposed for the weak correlation between the normal and shear stresses on the crack surfaces, and also for describing the nature of irrecoverable damage. Since the evaluation of the consumed energy is directly linked to the microscopic deformation, which can be efficiently tracked on the crack surfaces, the proposed damage model is believed to provide a more physical interpretation than existing damage mechanics, which fundamentally stem from mathematical derivation with few physical counterparts. Another novel point of the present work lies in the topological transition-based "smart" steel bar model, notably with evolving compressive buckling length. We presented a systematic framework of information flow between the key ingredients of composite materials (i.e., steel bar and its surrounding concrete elements). The smart steel model suggested can incorporate smooth transition during reversal loading, tensile rupture, early buckling after reversal from excessive tensile loading, and even compressive buckling. Especially, the buckling length is made to evolve according to the damage states of the surrounding elements of each bar, while all other dominant models leave the length unchanged. What lies behind all the aforementioned novel attempts is, of course, the problem-optimized parallel platform. In fact, the parallel computing in our field has been restricted to monotonic shock or blast loading with explicit algorithm which is characteristically feasible to be parallelized. In the present study, efficient parallelization strategies for the highly demanding implicit nonlinear finite element analysis (FEA) program for real-scale reinforced concrete (RC) structures under cyclic loading are proposed. Quantitative comparison of state-of-the-art parallel strategies, in terms of factorization, had been carried out, leading to the problem-optimized solver, which is successfully embracing the penalty method and banded nature. Particularly, the penalty method employed imparts considerable smoothness to the global response, which yields a practical superiority of the parallel triangular system solver over other advanced solvers such as parallel preconditioned conjugate gradient method. Other salient issues on parallelization are also addressed. The parallel platform established offers unprecedented access to simulations of real-scale structures, giving new understanding about the physics-based mechanisms adopted and probabilistic randomness at the entire system level. Particularly, the platform enables bold simulations of real-scale RC structures exposed to cyclic loading---H-shaped wall system and 4-story T-shaped wall system. The simulations show the desired capability of accurate prediction of global force-displacement responses, postpeak softening behavior, and compressive buckling of longitudinal steel bars. It is fascinating to see that intrinsic randomness of the 3d interlocking model appears to cause "localized" damage of the real-scale structures, which is consistent with reported observations in different fields such as granular media. Equipped with accuracy, stability and scalability as demonstrated so far, the parallel platform is believed to serve as a fertile ground for the introducing of further physical mechanisms into various research fields as well as the earthquake engineering community. In the near future, it can be further expanded to run in concert with reliable FEA programs such as FRAME3d or OPENSEES. Following the central notion of "multiscale" analysis technique, actual infrastructures exposed to extreme natural hazard can be successfully tackled by this next generation analysis tool---the harmonious union of the parallel platform and a general FEA program. At the same time, any type of experiments can be easily conducted by this "virtual laboratory."

Exploring the Sensitivity of Horn's Parallel Analysis to the Distributional Form of Random Data

ERIC Educational Resources Information Center

Dinno, Alexis

2009-01-01

Horn's parallel analysis (PA) is the method of consensus in the literature on empirical methods for deciding how many components/factors to retain. Different authors have proposed various implementations of PA. Horn's seminal 1965 article, a 1996 article by Thompson and Daniel, and a 2004 article by Hayton, Allen, and Scarpello all make assertions…

"Parallel Leadership in an "Unparallel" World"--Cultural Constraints on the Transferability of Western Educational Leadership Theories across Cultures

ERIC Educational Resources Information Center

Goh, Jonathan Wee Pin

2009-01-01

With the global economy becoming more integrated, the issues of cross-cultural relevance and transferability of leadership theories and practices have become increasingly urgent. Drawing upon the concept of parallel leadership in schools proposed by Crowther, Kaagan, Ferguson, and Hann as an example, the purpose of this paper is to examine the…

Automatic partitioning of unstructured meshes for the parallel solution of problems in computational mechanics

NASA Technical Reports Server (NTRS)

Farhat, Charbel; Lesoinne, Michel

1993-01-01

Most of the recently proposed computational methods for solving partial differential equations on multiprocessor architectures stem from the 'divide and conquer' paradigm and involve some form of domain decomposition. For those methods which also require grids of points or patches of elements, it is often necessary to explicitly partition the underlying mesh, especially when working with local memory parallel processors. In this paper, a family of cost-effective algorithms for the automatic partitioning of arbitrary two- and three-dimensional finite element and finite difference meshes is presented and discussed in view of a domain decomposed solution procedure and parallel processing. The influence of the algorithmic aspects of a solution method (implicit/explicit computations), and the architectural specifics of a multiprocessor (SIMD/MIMD, startup/transmission time), on the design of a mesh partitioning algorithm are discussed. The impact of the partitioning strategy on load balancing, operation count, operator conditioning, rate of convergence and processor mapping is also addressed. Finally, the proposed mesh decomposition algorithms are demonstrated with realistic examples of finite element, finite volume, and finite difference meshes associated with the parallel solution of solid and fluid mechanics problems on the iPSC/2 and iPSC/860 multiprocessors.

Stiffness modeling of compliant parallel mechanisms and applications in the performance analysis of a decoupled parallel compliant stage

NASA Astrophysics Data System (ADS)

Jiang, Yao; Li, Tie-Min; Wang, Li-Ping

2015-09-01

This paper investigates the stiffness modeling of compliant parallel mechanism (CPM) based on the matrix method. First, the general compliance matrix of a serial flexure chain is derived. The stiffness modeling of CPMs is next discussed in detail, considering the relative positions of the applied load and the selected displacement output point. The derived stiffness models have simple and explicit forms, and the input, output, and coupling stiffness matrices of the CPM can easily be obtained. The proposed analytical model is applied to the stiffness modeling and performance analysis of an XY parallel compliant stage with input and output decoupling characteristics. Then, the key geometrical parameters of the stage are optimized to obtain the minimum input decoupling degree. Finally, a prototype of the compliant stage is developed and its input axial stiffness, coupling characteristics, positioning resolution, and circular contouring performance are tested. The results demonstrate the excellent performance of the compliant stage and verify the effectiveness of the proposed theoretical model. The general stiffness models provided in this paper will be helpful for performance analysis, especially in determining coupling characteristics, and the structure optimization of the CPM.

An Intrinsic Algorithm for Parallel Poisson Disk Sampling on Arbitrary Surfaces.

PubMed

Ying, Xiang; Xin, Shi-Qing; Sun, Qian; He, Ying

2013-03-08

Poisson disk sampling plays an important role in a variety of visual computing, due to its useful statistical property in distribution and the absence of aliasing artifacts. While many effective techniques have been proposed to generate Poisson disk distribution in Euclidean space, relatively few work has been reported to the surface counterpart. This paper presents an intrinsic algorithm for parallel Poisson disk sampling on arbitrary surfaces. We propose a new technique for parallelizing the dart throwing. Rather than the conventional approaches that explicitly partition the spatial domain to generate the samples in parallel, our approach assigns each sample candidate a random and unique priority that is unbiased with regard to the distribution. Hence, multiple threads can process the candidates simultaneously and resolve conflicts by checking the given priority values. It is worth noting that our algorithm is accurate as the generated Poisson disks are uniformly and randomly distributed without bias. Our method is intrinsic in that all the computations are based on the intrinsic metric and are independent of the embedding space. This intrinsic feature allows us to generate Poisson disk distributions on arbitrary surfaces. Furthermore, by manipulating the spatially varying density function, we can obtain adaptive sampling easily.

Multisensor Parallel Largest Ellipsoid Distributed Data Fusion with Unknown Cross-Covariances

PubMed Central

Liu, Baoyu; Zhan, Xingqun; Zhu, Zheng H.

2017-01-01

As the largest ellipsoid (LE) data fusion algorithm can only be applied to two-sensor system, in this contribution, parallel fusion structure is proposed to introduce the LE algorithm into a multisensor system with unknown cross-covariances, and three parallel fusion structures based on different estimate pairing methods are presented and analyzed. In order to assess the influence of fusion structure on fusion performance, two fusion performance assessment parameters are defined as Fusion Distance and Fusion Index. Moreover, the formula for calculating the upper bounds of actual fused error covariances of the presented multisensor LE fusers is also provided. Demonstrated with simulation examples, the Fusion Index indicates fuser’s actual fused accuracy and its sensitivity to the sensor orders, as well as its robustness to the accuracy of newly added sensors. Compared to the LE fuser with sequential structure, the LE fusers with proposed parallel structures not only significantly improve their properties in these aspects, but also embrace better performances in consistency and computation efficiency. The presented multisensor LE fusers generally have better accuracies than covariance intersection (CI) fusion algorithm and are consistent when the local estimates are weakly correlated. PMID:28661442

A Dual Super-Element Domain Decomposition Approach for Parallel Nonlinear Finite Element Analysis

NASA Astrophysics Data System (ADS)

Jokhio, G. A.; Izzuddin, B. A.

2015-05-01

This article presents a new domain decomposition method for nonlinear finite element analysis introducing the concept of dual partition super-elements. The method extends ideas from the displacement frame method and is ideally suited for parallel nonlinear static/dynamic analysis of structural systems. In the new method, domain decomposition is realized by replacing one or more subdomains in a "parent system," each with a placeholder super-element, where the subdomains are processed separately as "child partitions," each wrapped by a dual super-element along the partition boundary. The analysis of the overall system, including the satisfaction of equilibrium and compatibility at all partition boundaries, is realized through direct communication between all pairs of placeholder and dual super-elements. The proposed method has particular advantages for matrix solution methods based on the frontal scheme, and can be readily implemented for existing finite element analysis programs to achieve parallelization on distributed memory systems with minimal intervention, thus overcoming memory bottlenecks typically faced in the analysis of large-scale problems. Several examples are presented in this article which demonstrate the computational benefits of the proposed parallel domain decomposition approach and its applicability to the nonlinear structural analysis of realistic structural systems.

Son of IXION: A Steady State Centrifugally Confined Plasma for Fusion*

NASA Astrophysics Data System (ADS)

Hassam, Adil

1996-11-01

A magnetic confinement scheme in which the inertial, u.grad(u), forces effect parallel confinement is proposed. The basic geometry is mirror-like as far as the poloidal field goes or, more simply, multipole (FM-1) type. The rotation is toroidal in this geometry. A supersonic rotation can effect complete parallel confinement, with the usual magnetic mirror force rendered irrelevant. The rotation shear, in addition, aids in the suppression of the flute mode. This suppression is not complete which indicates the addition of a toroidal field, at maximum of the order of the poloidal field. We show that at rotation in excess of Mach 3, the parallel particle and heat losses can be minimized to below the Lawson breakeven point. The crossfield transport can be expected to be better than tokamaks on account of the large velocity shear. Other advantages of the scheme are that it is steady state and disruption free. An exploratory experiment that tests equilibrium, parallel detachment, and MHD stability is proposed. The concept resembles earlier (Geneva, 1958) experiments on "homopolar generators" and a mirror configuration called IXION. Ixion, Greek mythological king, was forever strapped to a rotating, flaming wheel. *Work supported by DOE

Performance of the Heavy Flavor Tracker (HFT) detector in star experiment at RHIC

NASA Astrophysics Data System (ADS)

Alruwaili, Manal

With the growing technology, the number of the processors is becoming massive. Current supercomputer processing will be available on desktops in the next decade. For mass scale application software development on massive parallel computing available on desktops, existing popular languages with large libraries have to be augmented with new constructs and paradigms that exploit massive parallel computing and distributed memory models while retaining the user-friendliness. Currently, available object oriented languages for massive parallel computing such as Chapel, X10 and UPC++ exploit distributed computing, data parallel computing and thread-parallelism at the process level in the PGAS (Partitioned Global Address Space) memory model. However, they do not incorporate: 1) any extension at for object distribution to exploit PGAS model; 2) the programs lack the flexibility of migrating or cloning an object between places to exploit load balancing; and 3) lack the programming paradigms that will result from the integration of data and thread-level parallelism and object distribution. In the proposed thesis, I compare different languages in PGAS model; propose new constructs that extend C++ with object distribution and object migration; and integrate PGAS based process constructs with these extensions on distributed objects. Object cloning and object migration. Also a new paradigm MIDD (Multiple Invocation Distributed Data) is presented when different copies of the same class can be invoked, and work on different elements of a distributed data concurrently using remote method invocations. I present new constructs, their grammar and their behavior. The new constructs have been explained using simple programs utilizing these constructs.

Real-time implementations of image segmentation algorithms on shared memory multicore architecture: a survey (Conference Presentation)

NASA Astrophysics Data System (ADS)

Akil, Mohamed

2017-05-01

The real-time processing is getting more and more important in many image processing applications. Image segmentation is one of the most fundamental tasks image analysis. As a consequence, many different approaches for image segmentation have been proposed. The watershed transform is a well-known image segmentation tool. The watershed transform is a very data intensive task. To achieve acceleration and obtain real-time processing of watershed algorithms, parallel architectures and programming models for multicore computing have been developed. This paper focuses on the survey of the approaches for parallel implementation of sequential watershed algorithms on multicore general purpose CPUs: homogeneous multicore processor with shared memory. To achieve an efficient parallel implementation, it's necessary to explore different strategies (parallelization/distribution/distributed scheduling) combined with different acceleration and optimization techniques to enhance parallelism. In this paper, we give a comparison of various parallelization of sequential watershed algorithms on shared memory multicore architecture. We analyze the performance measurements of each parallel implementation and the impact of the different sources of overhead on the performance of the parallel implementations. In this comparison study, we also discuss the advantages and disadvantages of the parallel programming models. Thus, we compare the OpenMP (an application programming interface for multi-Processing) with Ptheads (POSIX Threads) to illustrate the impact of each parallel programming model on the performance of the parallel implementations.

A high performance parallel computing architecture for robust image features

NASA Astrophysics Data System (ADS)

Zhou, Renyan; Liu, Leibo; Wei, Shaojun

2014-03-01

A design of parallel architecture for image feature detection and description is proposed in this article. The major component of this architecture is a 2D cellular network composed of simple reprogrammable processors, enabling the Hessian Blob Detector and Haar Response Calculation, which are the most computing-intensive stage of the Speeded Up Robust Features (SURF) algorithm. Combining this 2D cellular network and dedicated hardware for SURF descriptors, this architecture achieves real-time image feature detection with minimal software in the host processor. A prototype FPGA implementation of the proposed architecture achieves 1318.9 GOPS general pixel processing @ 100 MHz clock and achieves up to 118 fps in VGA (640 × 480) image feature detection. The proposed architecture is stand-alone and scalable so it is easy to be migrated into VLSI implementation.

Advances in Parallelization for Large Scale Oct-Tree Mesh Generation

NASA Technical Reports Server (NTRS)

O'Connell, Matthew; Karman, Steve L.

2015-01-01

Despite great advancements in the parallelization of numerical simulation codes over the last 20 years, it is still common to perform grid generation in serial. Generating large scale grids in serial often requires using special "grid generation" compute machines that can have more than ten times the memory of average machines. While some parallel mesh generation techniques have been proposed, generating very large meshes for LES or aeroacoustic simulations is still a challenging problem. An automated method for the parallel generation of very large scale off-body hierarchical meshes is presented here. This work enables large scale parallel generation of off-body meshes by using a novel combination of parallel grid generation techniques and a hybrid "top down" and "bottom up" oct-tree method. Meshes are generated using hardware commonly found in parallel compute clusters. The capability to generate very large meshes is demonstrated by the generation of off-body meshes surrounding complex aerospace geometries. Results are shown including a one billion cell mesh generated around a Predator Unmanned Aerial Vehicle geometry, which was generated on 64 processors in under 45 minutes.

Boundedness and exponential convergence in a chemotaxis model for tumor invasion

NASA Astrophysics Data System (ADS)

Jin, Hai-Yang; Xiang, Tian

2016-12-01

We revisit the following chemotaxis system modeling tumor invasion {ut=Δu-∇ṡ(u∇v),x∈Ω,t>0,vt=Δv+wz,x∈Ω,t>0,wt=-wz,x∈Ω,t>0,zt=Δz-z+u,x∈Ω,t>0, in a smooth bounded domain Ω \\subset {{{R}}n}(n≥slant 1) with homogeneous Neumann boundary and initial conditions. This model was recently proposed by Fujie et al (2014 Adv. Math. Sci. Appl. 24 67-84) as a model for tumor invasion with the role of extracellular matrix incorporated, and was analyzed later by Fujie et al (2016 Discrete Contin. Dyn. Syst. 36 151-69), showing the uniform boundedness and convergence for n≤slant 3 . In this work, we first show that the {{L}∞} -boundedness of the system can be reduced to the boundedness of \\parallel u(\\centerdot,t){{\\parallel}{{L\\frac{n{4}+ɛ}}(Ω )}} for some ɛ >0 alone, and then, for n≥slant 4 , if the initial data \\parallel {{u}0}{{\\parallel}{{L\\frac{n{4}}}}} , \\parallel {{z}0}{{\\parallel}{{L\\frac{n{2}}}}} and \\parallel \

Concurrent computation of attribute filters on shared memory parallel machines.

PubMed

Wilkinson, Michael H F; Gao, Hui; Hesselink, Wim H; Jonker, Jan-Eppo; Meijster, Arnold

2008-10-01

Morphological attribute filters have not previously been parallelized, mainly because they are both global and non-separable. We propose a parallel algorithm that achieves efficient parallelism for a large class of attribute filters, including attribute openings, closings, thinnings and thickenings, based on Salembier's Max-Trees and Min-trees. The image or volume is first partitioned in multiple slices. We then compute the Max-trees of each slice using any sequential Max-Tree algorithm. Subsequently, the Max-trees of the slices can be merged to obtain the Max-tree of the image. A C-implementation yielded good speed-ups on both a 16-processor MIPS 14000 parallel machine, and a dual-core Opteron-based machine. It is shown that the speed-up of the parallel algorithm is a direct measure of the gain with respect to the sequential algorithm used. Furthermore, the concurrent algorithm shows a speed gain of up to 72 percent on a single-core processor, due to reduced cache thrashing.

Development of a parallel demodulation system used for extrinsic Fabry-Perot interferometer and fiber Bragg grating sensors.

PubMed

Jiang, Junfeng; Liu, Tiegen; Zhang, Yimo; Liu, Lina; Zha, Ying; Zhang, Fan; Wang, Yunxin; Long, Pin

2006-01-20

A parallel demodulation system for extrinsic Fabry-Perot interferometer (EFPI) and fiber Bragg grating (FBG) sensors is presented, which is based on a Michelson interferometer and combines the methods of low-coherence interference and a Fourier-transform spectrum. The parallel demodulation theory is modeled with Fourier-transform spectrum technology, and a signal separation method with an EFPI and FBG is proposed. The design of an optical path difference scanning and sampling method without a reference light is described. Experiments show that the parallel demodulation system has good spectrum demodulation and low-coherence interference demodulation performance. It can realize simultaneous strain and temperature measurements while keeping the whole system configuration less complex.

Dynamic modeling of parallel robots for computed-torque control implementation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Codourey, A.

1998-12-01

In recent years, increased interest in parallel robots has been observed. Their control with modern theory, such as the computed-torque method, has, however, been restrained, essentially due to the difficulty in establishing a simple dynamic model that can be calculated in real time. In this paper, a simple method based on the virtual work principle is proposed for modeling parallel robots. The mass matrix of the robot, needed for decoupling control strategies, does not explicitly appear in the formulation; however, it can be computed separately, based on kinetic energy considerations. The method is applied to the DELTA parallel robot, leadingmore » to a very efficient model that has been implemented in a real-time computed-torque control algorithm.« less

Performance Comparison of a Set of Periodic and Non-Periodic Tridiagonal Solvers on SP2 and Paragon Parallel Computers

NASA Technical Reports Server (NTRS)

Sun, Xian-He; Moitra, Stuti

1996-01-01

Various tridiagonal solvers have been proposed in recent years for different parallel platforms. In this paper, the performance of three tridiagonal solvers, namely, the parallel partition LU algorithm, the parallel diagonal dominant algorithm, and the reduced diagonal dominant algorithm, is studied. These algorithms are designed for distributed-memory machines and are tested on an Intel Paragon and an IBM SP2 machines. Measured results are reported in terms of execution time and speedup. Analytical study are conducted for different communication topologies and for different tridiagonal systems. The measured results match the analytical results closely. In addition to address implementation issues, performance considerations such as problem sizes and models of speedup are also discussed.

Parallel algorithms for placement and routing in VLSI design. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Brouwer, Randall Jay

1991-01-01

The computational requirements for high quality synthesis, analysis, and verification of very large scale integration (VLSI) designs have rapidly increased with the fast growing complexity of these designs. Research in the past has focused on the development of heuristic algorithms, special purpose hardware accelerators, or parallel algorithms for the numerous design tasks to decrease the time required for solution. Two new parallel algorithms are proposed for two VLSI synthesis tasks, standard cell placement and global routing. The first algorithm, a parallel algorithm for global routing, uses hierarchical techniques to decompose the routing problem into independent routing subproblems that are solved in parallel. Results are then presented which compare the routing quality to the results of other published global routers and which evaluate the speedups attained. The second algorithm, a parallel algorithm for cell placement and global routing, hierarchically integrates a quadrisection placement algorithm, a bisection placement algorithm, and the previous global routing algorithm. Unique partitioning techniques are used to decompose the various stages of the algorithm into independent tasks which can be evaluated in parallel. Finally, results are presented which evaluate the various algorithm alternatives and compare the algorithm performance to other placement programs. Measurements are presented on the parallel speedups available.

Parallel phase-shifting self-interference digital holography with faithful reconstruction using compressive sensing

NASA Astrophysics Data System (ADS)

Wan, Yuhong; Man, Tianlong; Wu, Fan; Kim, Myung K.; Wang, Dayong

2016-11-01

We present a new self-interference digital holographic approach that allows single-shot capturing three-dimensional intensity distribution of the spatially incoherent objects. The Fresnel incoherent correlation holographic microscopy is combined with parallel phase-shifting technique to instantaneously obtain spatially multiplexed phase-shifting holograms. The compressive-sensing-based reconstruction algorithm is implemented to reconstruct the original object from the under sampled demultiplexed holograms. The scheme is verified with simulations. The validity of the proposed method is experimentally demonstrated in an indirectly way by simulating the use of specific parallel phase-shifting recording device.

Efficient implementation of parallel three-dimensional FFT on clusters of PCs

NASA Astrophysics Data System (ADS)

Takahashi, Daisuke

2003-05-01

In this paper, we propose a high-performance parallel three-dimensional fast Fourier transform (FFT) algorithm on clusters of PCs. The three-dimensional FFT algorithm can be altered into a block three-dimensional FFT algorithm to reduce the number of cache misses. We show that the block three-dimensional FFT algorithm improves performance by utilizing the cache memory effectively. We use the block three-dimensional FFT algorithm to implement the parallel three-dimensional FFT algorithm. We succeeded in obtaining performance of over 1.3 GFLOPS on an 8-node dual Pentium III 1 GHz PC SMP cluster.

Applications and accuracy of the parallel diagonal dominant algorithm

NASA Technical Reports Server (NTRS)

Sun, Xian-He

1993-01-01

The Parallel Diagonal Dominant (PDD) algorithm is a highly efficient, ideally scalable tridiagonal solver. In this paper, a detailed study of the PDD algorithm is given. First the PDD algorithm is introduced. Then the algorithm is extended to solve periodic tridiagonal systems. A variant, the reduced PDD algorithm, is also proposed. Accuracy analysis is provided for a class of tridiagonal systems, the symmetric, and anti-symmetric Toeplitz tridiagonal systems. Implementation results show that the analysis gives a good bound on the relative error, and the algorithm is a good candidate for the emerging massively parallel machines.

Evidence for Field-parallel Electron Acceleration in Solar Flares

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haerendel, G.

It is proposed that the coincidence of higher brightness and upward electric current observed by Janvier et al. during a flare indicates electron acceleration by field-parallel potential drops sustained by extremely strong field-aligned currents of the order of 10{sup 4} A m{sup −2}. A consequence of this is the concentration of the currents in sheets with widths of the order of 1 m. The high current density suggests that the field-parallel potential drops are maintained by current-driven anomalous resistivity. The origin of these currents remains a strong challenge for theorists.

Parallel implementation of all-digital timing recovery for high-speed and real-time optical coherent receivers.

PubMed

Zhou, Xian; Chen, Xue

2011-05-09

The digital coherent receivers combine coherent detection with digital signal processing (DSP) to compensate for transmission impairments, and therefore are a promising candidate for future high-speed optical transmission system. However, the maximum symbol rate supported by such real-time receivers is limited by the processing rate of hardware. In order to cope with this difficulty, the parallel processing algorithms is imperative. In this paper, we propose a novel parallel digital timing recovery loop (PDTRL) based on our previous work. Furthermore, for increasing the dynamic dispersion tolerance range of receivers, we embed a parallel adaptive equalizer in the PDTRL. This parallel joint scheme (PJS) can be used to complete synchronization, equalization and polarization de-multiplexing simultaneously. Finally, we demonstrate that PDTRL and PJS allow the hardware to process 112 Gbit/s POLMUX-DQPSK signal at the hundreds MHz range. © 2011 Optical Society of America

Segmentation of remotely sensed data using parallel region growing

NASA Technical Reports Server (NTRS)

Tilton, J. C.; Cox, S. C.

1983-01-01

The improved spatial resolution of the new earth resources satellites will increase the need for effective utilization of spatial information in machine processing of remotely sensed data. One promising technique is scene segmentation by region growing. Region growing can use spatial information in two ways: only spatially adjacent regions merge together, and merging criteria can be based on region-wide spatial features. A simple region growing approach is described in which the similarity criterion is based on region mean and variance (a simple spatial feature). An effective way to implement region growing for remote sensing is as an iterative parallel process on a large parallel processor. A straightforward parallel pixel-based implementation of the algorithm is explored and its efficiency is compared with sequential pixel-based, sequential region-based, and parallel region-based implementations. Experimental results from on aircraft scanner data set are presented, as is a discussioon of proposed improvements to the segmentation algorithm.

ParaBTM: A Parallel Processing Framework for Biomedical Text Mining on Supercomputers.

PubMed

Xing, Yuting; Wu, Chengkun; Yang, Xi; Wang, Wei; Zhu, En; Yin, Jianping

2018-04-27

A prevailing way of extracting valuable information from biomedical literature is to apply text mining methods on unstructured texts. However, the massive amount of literature that needs to be analyzed poses a big data challenge to the processing efficiency of text mining. In this paper, we address this challenge by introducing parallel processing on a supercomputer. We developed paraBTM, a runnable framework that enables parallel text mining on the Tianhe-2 supercomputer. It employs a low-cost yet effective load balancing strategy to maximize the efficiency of parallel processing. We evaluated the performance of paraBTM on several datasets, utilizing three types of named entity recognition tasks as demonstration. Results show that, in most cases, the processing efficiency can be greatly improved with parallel processing, and the proposed load balancing strategy is simple and effective. In addition, our framework can be readily applied to other tasks of biomedical text mining besides NER.

Fast hydrological model calibration based on the heterogeneous parallel computing accelerated shuffled complex evolution method

NASA Astrophysics Data System (ADS)

Kan, Guangyuan; He, Xiaoyan; Ding, Liuqian; Li, Jiren; Hong, Yang; Zuo, Depeng; Ren, Minglei; Lei, Tianjie; Liang, Ke

2018-01-01

Hydrological model calibration has been a hot issue for decades. The shuffled complex evolution method developed at the University of Arizona (SCE-UA) has been proved to be an effective and robust optimization approach. However, its computational efficiency deteriorates significantly when the amount of hydrometeorological data increases. In recent years, the rise of heterogeneous parallel computing has brought hope for the acceleration of hydrological model calibration. This study proposed a parallel SCE-UA method and applied it to the calibration of a watershed rainfall-runoff model, the Xinanjiang model. The parallel method was implemented on heterogeneous computing systems using OpenMP and CUDA. Performance testing and sensitivity analysis were carried out to verify its correctness and efficiency. Comparison results indicated that heterogeneous parallel computing-accelerated SCE-UA converged much more quickly than the original serial version and possessed satisfactory accuracy and stability for the task of fast hydrological model calibration.

pWeb: A High-Performance, Parallel-Computing Framework for Web-Browser-Based Medical Simulation.

PubMed

Halic, Tansel; Ahn, Woojin; De, Suvranu

2014-01-01

This work presents a pWeb - a new language and compiler for parallelization of client-side compute intensive web applications such as surgical simulations. The recently introduced HTML5 standard has enabled creating unprecedented applications on the web. Low performance of the web browser, however, remains the bottleneck of computationally intensive applications including visualization of complex scenes, real time physical simulations and image processing compared to native ones. The new proposed language is built upon web workers for multithreaded programming in HTML5. The language provides fundamental functionalities of parallel programming languages as well as the fork/join parallel model which is not supported by web workers. The language compiler automatically generates an equivalent parallel script that complies with the HTML5 standard. A case study on realistic rendering for surgical simulations demonstrates enhanced performance with a compact set of instructions.

A parallel graded-mesh FDTD algorithm for human-antenna interaction problems.

PubMed

Catarinucci, Luca; Tarricone, Luciano

2009-01-01

The finite difference time domain method (FDTD) is frequently used for the numerical solution of a wide variety of electromagnetic (EM) problems and, among them, those concerning human exposure to EM fields. In many practical cases related to the assessment of occupational EM exposure, large simulation domains are modeled and high space resolution adopted, so that strong memory and central processing unit power requirements have to be satisfied. To better afford the computational effort, the use of parallel computing is a winning approach; alternatively, subgridding techniques are often implemented. However, the simultaneous use of subgridding schemes and parallel algorithms is very new. In this paper, an easy-to-implement and highly-efficient parallel graded-mesh (GM) FDTD scheme is proposed and applied to human-antenna interaction problems, demonstrating its appropriateness in dealing with complex occupational tasks and showing its capability to guarantee the advantages of a traditional subgridding technique without affecting the parallel FDTD performance.

Generalized parallel-perspective stereo mosaics from airborne video.

PubMed

Zhu, Zhigang; Hanson, Allen R; Riseman, Edward M

2004-02-01

In this paper, we present a new method for automatically and efficiently generating stereoscopic mosaics by seamless registration of images collected by a video camera mounted on an airborne platform. Using a parallel-perspective representation, a pair of geometrically registered stereo mosaics can be precisely constructed under quite general motion. A novel parallel ray interpolation for stereo mosaicing (PRISM) approach is proposed to make stereo mosaics seamless in the presence of obvious motion parallax and for rather arbitrary scenes. Parallel-perspective stereo mosaics generated with the PRISM method have better depth resolution than perspective stereo due to the adaptive baseline geometry. Moreover, unlike previous results showing that parallel-perspective stereo has a constant depth error, we conclude that the depth estimation error of stereo mosaics is in fact a linear function of the absolute depths of a scene. Experimental results on long video sequences are given.

Scaling Support Vector Machines On Modern HPC Platforms

DOE Office of Scientific and Technical Information (OSTI.GOV)

You, Yang; Fu, Haohuan; Song, Shuaiwen

2015-02-01

We designed and implemented MIC-SVM, a highly efficient parallel SVM for x86 based multicore and many-core architectures, such as the Intel Ivy Bridge CPUs and Intel Xeon Phi co-processor (MIC). We propose various novel analysis methods and optimization techniques to fully utilize the multilevel parallelism provided by these architectures and serve as general optimization methods for other machine learning tools.

Versatile photonic microwave waveforms generation using a dual-parallel Mach-Zehnder modulator without other dispersive elements

NASA Astrophysics Data System (ADS)

Bai, Guang-Fu; Hu, Lin; Jiang, Yang; Tian, Jing; Zi, Yue-Jiao; Wu, Ting-Wei; Huang, Feng-Qin

2017-08-01

In this paper, a photonic microwave waveform generator based on a dual-parallel Mach-Zehnder modulator is proposed and experimentally demonstrated. In this reported scheme, only one radio frequency signal is used to drive the dual-parallel Mach-Zehnder modulator. Meanwhile, dispersive elements or filters are not required in the proposed scheme, which make the scheme simpler and more stable. In this way, six variables can be adjusted. Through the different combinations of these variables, basic waveforms with full duty and small duty cycle can be generated. Tunability of the generator can be achieved by adjusting the frequency of the RF signal and the optical carrier. The corresponding theoretical analysis and simulation have been conducted. With guidance of theory and simulation, proof-of-concept experiments are carried out. The basic waveforms, including Gaussian, saw-up, and saw-down waveforms, with full duty and small duty cycle are generated at the repetition rate of 2 GHz. The theoretical and simulation results agree with the experimental results very well.

Design of k-Space Channel Combination Kernels and Integration with Parallel Imaging

PubMed Central

Beatty, Philip J.; Chang, Shaorong; Holmes, James H.; Wang, Kang; Brau, Anja C. S.; Reeder, Scott B.; Brittain, Jean H.

2014-01-01

Purpose In this work, a new method is described for producing local k-space channel combination kernels using a small amount of low-resolution multichannel calibration data. Additionally, this work describes how these channel combination kernels can be combined with local k-space unaliasing kernels produced by the calibration phase of parallel imaging methods such as GRAPPA, PARS and ARC. Methods Experiments were conducted to evaluate both the image quality and computational efficiency of the proposed method compared to a channel-by-channel parallel imaging approach with image-space sum-of-squares channel combination. Results Results indicate comparable image quality overall, with some very minor differences seen in reduced field-of-view imaging. It was demonstrated that this method enables a speed up in computation time on the order of 3–16X for 32-channel data sets. Conclusion The proposed method enables high quality channel combination to occur earlier in the reconstruction pipeline, reducing computational and memory requirements for image reconstruction. PMID:23943602

Parallel replica dynamics method for bistable stochastic reaction networks: Simulation and sensitivity analysis

NASA Astrophysics Data System (ADS)

Wang, Ting; Plecháč, Petr

2017-12-01

Stochastic reaction networks that exhibit bistable behavior are common in systems biology, materials science, and catalysis. Sampling of stationary distributions is crucial for understanding and characterizing the long-time dynamics of bistable stochastic dynamical systems. However, simulations are often hindered by the insufficient sampling of rare transitions between the two metastable regions. In this paper, we apply the parallel replica method for a continuous time Markov chain in order to improve sampling of the stationary distribution in bistable stochastic reaction networks. The proposed method uses parallel computing to accelerate the sampling of rare transitions. Furthermore, it can be combined with the path-space information bounds for parametric sensitivity analysis. With the proposed methodology, we study three bistable biological networks: the Schlögl model, the genetic switch network, and the enzymatic futile cycle network. We demonstrate the algorithmic speedup achieved in these numerical benchmarks. More significant acceleration is expected when multi-core or graphics processing unit computer architectures and programming tools such as CUDA are employed.

Joint carrier phase and frequency-offset estimation with parallel implementation for dual-polarization coherent receiver.

PubMed

Lu, Jianing; Li, Xiang; Fu, Songnian; Luo, Ming; Xiang, Meng; Zhou, Huibin; Tang, Ming; Liu, Deming

2017-03-06

We present dual-polarization complex-weighted, decision-aided, maximum-likelihood algorithm with superscalar parallelization (SSP-DP-CW-DA-ML) for joint carrier phase and frequency-offset estimation (FOE) in coherent optical receivers. By pre-compensation of the phase offset between signals in dual polarizations, the performance can be substantially improved. Meanwhile, with the help of modified SSP-based parallel implementation, the acquisition time of FO and the required number of training symbols are reduced by transferring the complex weights of the filters between adjacent buffers, where differential coding/decoding is not required. Simulation results show that the laser linewidth tolerance of our proposed algorithm is comparable to traditional blind phase search (BPS), while a complete FOE range of ± symbol rate/2 can be achieved. Finally, performance of our proposed algorithm is experimentally verified under the scenario of back-to-back (B2B) transmission using 10 Gbaud DP-16/32-QAM formats.

What is adaptive about adaptive decision making? A parallel constraint satisfaction account.

PubMed

Glöckner, Andreas; Hilbig, Benjamin E; Jekel, Marc

2014-12-01

There is broad consensus that human cognition is adaptive. However, the vital question of how exactly this adaptivity is achieved has remained largely open. Herein, we contrast two frameworks which account for adaptive decision making, namely broad and general single-mechanism accounts vs. multi-strategy accounts. We propose and fully specify a single-mechanism model for decision making based on parallel constraint satisfaction processes (PCS-DM) and contrast it theoretically and empirically against a multi-strategy account. To achieve sufficiently sensitive tests, we rely on a multiple-measure methodology including choice, reaction time, and confidence data as well as eye-tracking. Results show that manipulating the environmental structure produces clear adaptive shifts in choice patterns - as both frameworks would predict. However, results on the process level (reaction time, confidence), in information acquisition (eye-tracking), and from cross-predicting choice consistently corroborate single-mechanisms accounts in general, and the proposed parallel constraint satisfaction model for decision making in particular. Copyright © 2014 Elsevier B.V. All rights reserved.

Gyrokinetic theory of turbulent acceleration and momentum conservation in tokamak plasmas

NASA Astrophysics Data System (ADS)

Lu, WANG; Shuitao, PENG; P, H. DIAMOND

2018-07-01

Understanding the generation of intrinsic rotation in tokamak plasmas is crucial for future fusion reactors such as ITER. We proposed a new mechanism named turbulent acceleration for the origin of the intrinsic parallel rotation based on gyrokinetic theory. The turbulent acceleration acts as a local source or sink of parallel rotation, i.e., volume force, which is different from the divergence of residual stress, i.e., surface force. However, the order of magnitude of turbulent acceleration can be comparable to that of the divergence of residual stress for electrostatic ion temperature gradient (ITG) turbulence. A possible theoretical explanation for the experimental observation of electron cyclotron heating induced decrease of co-current rotation was also proposed via comparison between the turbulent acceleration driven by ITG turbulence and that driven by collisionless trapped electron mode turbulence. We also extended this theory to electromagnetic ITG turbulence and investigated the electromagnetic effects on intrinsic parallel rotation drive. Finally, we demonstrated that the presence of turbulent acceleration does not conflict with momentum conservation.

Concentric Parallel Combining Balun for Millimeter-Wave Power Amplifier in Low-Power CMOS with High-Power Density

NASA Astrophysics Data System (ADS)

Han, Jiang-An; Kong, Zhi-Hui; Ma, Kaixue; Yeo, Kiat Seng; Lim, Wei Meng

2016-11-01

This paper presents a novel balun for a millimeter-wave power amplifier (PA) design to achieve high-power density in a 65-nm low-power (LP) CMOS process. By using a concentric winding technique, the proposed parallel combining balun with compact size accomplishes power combining and unbalance-balance conversion concurrently. For calculating its power combination efficiency in the condition of various amplitude and phase wave components, a method basing on S-parameters is derived. Based on the proposed parallel combining balun, a fabricated 60-GHz industrial, scientific, and medical (ISM) band PA with single-ended I/O achieves an 18.9-dB gain and an 8.8-dBm output power at 1-dB compression and 14.3-dBm saturated output power ( P sat) at 62 GHz. This PA occupying only a 0.10-mm2 core area has demonstrated a high-power density of 269.15 mW/mm2 in 65 nm LP CMOS.

A 12-bit high-speed column-parallel two-step single-slope analog-to-digital converter (ADC) for CMOS image sensors.

PubMed

Lyu, Tao; Yao, Suying; Nie, Kaiming; Xu, Jiangtao

2014-11-17

A 12-bit high-speed column-parallel two-step single-slope (SS) analog-to-digital converter (ADC) for CMOS image sensors is proposed. The proposed ADC employs a single ramp voltage and multiple reference voltages, and the conversion is divided into coarse phase and fine phase to improve the conversion rate. An error calibration scheme is proposed to correct errors caused by offsets among the reference voltages. The digital-to-analog converter (DAC) used for the ramp generator is based on the split-capacitor array with an attenuation capacitor. Analysis of the DAC's linearity performance versus capacitor mismatch and parasitic capacitance is presented. A prototype 1024 × 32 Time Delay Integration (TDI) CMOS image sensor with the proposed ADC architecture has been fabricated in a standard 0.18 μm CMOS process. The proposed ADC has average power consumption of 128 μW and a conventional rate 6 times higher than the conventional SS ADC. A high-quality image, captured at the line rate of 15.5 k lines/s, shows that the proposed ADC is suitable for high-speed CMOS image sensors.

Efficient method to design RF pulses for parallel excitation MRI using gridding and conjugate gradient

PubMed Central

Feng, Shuo

2014-01-01

Parallel excitation (pTx) techniques with multiple transmit channels have been widely used in high field MRI imaging to shorten the RF pulse duration and/or reduce the specific absorption rate (SAR). However, the efficiency of pulse design still needs substantial improvement for practical real-time applications. In this paper, we present a detailed description of a fast pulse design method with Fourier domain gridding and a conjugate gradient method. Simulation results of the proposed method show that the proposed method can design pTx pulses at an efficiency 10 times higher than that of the conventional conjugate-gradient based method, without reducing the accuracy of the desirable excitation patterns. PMID:24834420

Efficient method to design RF pulses for parallel excitation MRI using gridding and conjugate gradient.

PubMed

Feng, Shuo; Ji, Jim

2014-04-01

Parallel excitation (pTx) techniques with multiple transmit channels have been widely used in high field MRI imaging to shorten the RF pulse duration and/or reduce the specific absorption rate (SAR). However, the efficiency of pulse design still needs substantial improvement for practical real-time applications. In this paper, we present a detailed description of a fast pulse design method with Fourier domain gridding and a conjugate gradient method. Simulation results of the proposed method show that the proposed method can design pTx pulses at an efficiency 10 times higher than that of the conventional conjugate-gradient based method, without reducing the accuracy of the desirable excitation patterns.

A novel visual hardware behavioral language

NASA Technical Reports Server (NTRS)

Li, Xueqin; Cheng, H. D.

1992-01-01

Most hardware behavioral languages just use texts to describe the behavior of the desired hardware design. This is inconvenient for VLSI designers who enjoy using the schematic approach. The proposed visual hardware behavioral language has the ability to graphically express design information using visual parallel models (blocks), visual sequential models (processes) and visual data flow graphs (which consist of primitive operational icons, control icons, and Data and Synchro links). Thus, the proposed visual hardware behavioral language can not only specify hardware concurrent and sequential functionality, but can also visually expose parallelism, sequentiality, and disjointness (mutually exclusive operations) for the hardware designers. That would make the hardware designers capture the design ideas easily and explicitly using this visual hardware behavioral language.

Design of a 6-DOF upper limb rehabilitation exoskeleton with parallel actuated joints.

PubMed

Chen, Yanyan; Li, Ge; Zhu, Yanhe; Zhao, Jie; Cai, Hegao

2014-01-01

In this paper, a 6-DOF wearable upper limb exoskeleton with parallel actuated joints which perfectly mimics human motions is proposed. The upper limb exoskeleton assists the movement of physically weak people. Compared with the existing upper limb exoskeletons which are mostly designed using a serial structure with large movement space but small stiffness and poor wearable ability, a prototype for motion assistance based on human anatomy structure has been developed in our design. Moreover, the design adopts balls instead of bearings to save space, which simplifies the structure and reduces the cost of the mechanism. The proposed design also employs deceleration processes to ensure that the transmission ratio of each joint is coincident.

Robust High-Resolution Cloth Using Parallelism, History-Based Collisions and Accurate Friction

PubMed Central

Selle, Andrew; Su, Jonathan; Irving, Geoffrey; Fedkiw, Ronald

2015-01-01

In this paper we simulate high resolution cloth consisting of up to 2 million triangles which allows us to achieve highly detailed folds and wrinkles. Since the level of detail is also influenced by object collision and self collision, we propose a more accurate model for cloth-object friction. We also propose a robust history-based repulsion/collision framework where repulsions are treated accurately and efficiently on a per time step basis. Distributed memory parallelism is used for both time evolution and collisions and we specifically address Gauss-Seidel ordering of repulsion/collision response. This algorithm is demonstrated by several high-resolution and high-fidelity simulations. PMID:19147895

Optical computing using optical flip-flops in Fourier processors: use in matrix multiplication and discrete linear transforms.

PubMed

Ando, S; Sekine, S; Mita, M; Katsuo, S

1989-12-15

An architecture and the algorithms for matrix multiplication using optical flip-flops (OFFs) in optical processors are proposed based on residue arithmetic. The proposed system is capable of processing all elements of matrices in parallel utilizing the information retrieving ability of optical Fourier processors. The employment of OFFs enables bidirectional data flow leading to a simpler architecture and the burden of residue-to-decimal (or residue-to-binary) conversion to operation time can be largely reduced by processing all elements in parallel. The calculated characteristics of operation time suggest a promising use of the system in a real time 2-D linear transform.

The development of a revised version of multi-center molecular Ornstein-Zernike equation

NASA Astrophysics Data System (ADS)

Kido, Kentaro; Yokogawa, Daisuke; Sato, Hirofumi

2012-04-01

Ornstein-Zernike (OZ)-type theory is a powerful tool to obtain 3-dimensional solvent distribution around solute molecule. Recently, we proposed multi-center molecular OZ method, which is suitable for parallel computing of 3D solvation structure. The distribution function in this method consists of two components, namely reference and residue parts. Several types of the function were examined as the reference part to investigate the numerical robustness of the method. As the benchmark, the method is applied to water, benzene in aqueous solution and single-walled carbon nanotube in chloroform solution. The results indicate that fully-parallelization is achieved by utilizing the newly proposed reference functions.

Airfoil-based electromagnetic energy harvester containing parallel array motion between moving coil and multi-pole magnets towards enhanced power density.

PubMed

Leung, Chung Ming; Wang, Ya; Chen, Wusi

2016-11-01

In this letter, the airfoil-based electromagnetic energy harvester containing parallel array motion between moving coil and trajectory matching multi-pole magnets was investigated. The magnets were aligned in an alternatively magnetized formation of 6 magnets to explore enhanced power density. In particular, the magnet array was positioned in parallel to the trajectory of the tip coil within its tip deflection span. The finite element simulations of the magnetic flux density and induced voltages at an open circuit condition were studied to find the maximum number of alternatively magnetized magnets that was required for the proposed energy harvester. Experimental results showed that the energy harvester with a pair of 6 alternatively magnetized linear magnet arrays was able to generate an induced voltage (V o ) of 20 V, with an open circuit condition, and 475 mW, under a 30 Ω optimal resistance load operating with the wind speed (U) at 7 m/s and a natural bending frequency of 3.54 Hz. Compared to the traditional electromagnetic energy harvester with a single magnet moving through a coil, the proposed energy harvester, containing multi-pole magnets and parallel array motion, enables the moving coil to accumulate a stronger magnetic flux in each period of the swinging motion. In addition to the comparison made with the airfoil-based piezoelectric energy harvester of the same size, our proposed electromagnetic energy harvester generates 11 times more power output, which is more suitable for high-power-density energy harvesting applications at regions with low environmental frequency.

A FAST ITERATIVE METHOD FOR SOLVING THE EIKONAL EQUATION ON TRIANGULATED SURFACES*

PubMed Central

Fu, Zhisong; Jeong, Won-Ki; Pan, Yongsheng; Kirby, Robert M.; Whitaker, Ross T.

2012-01-01

This paper presents an efficient, fine-grained parallel algorithm for solving the Eikonal equation on triangular meshes. The Eikonal equation, and the broader class of Hamilton–Jacobi equations to which it belongs, have a wide range of applications from geometric optics and seismology to biological modeling and analysis of geometry and images. The ability to solve such equations accurately and efficiently provides new capabilities for exploring and visualizing parameter spaces and for solving inverse problems that rely on such equations in the forward model. Efficient solvers on state-of-the-art, parallel architectures require new algorithms that are not, in many cases, optimal, but are better suited to synchronous updates of the solution. In previous work [W. K. Jeong and R. T. Whitaker, SIAM J. Sci. Comput., 30 (2008), pp. 2512–2534], the authors proposed the fast iterative method (FIM) to efficiently solve the Eikonal equation on regular grids. In this paper we extend the fast iterative method to solve Eikonal equations efficiently on triangulated domains on the CPU and on parallel architectures, including graphics processors. We propose a new local update scheme that provides solutions of first-order accuracy for both architectures. We also propose a novel triangle-based update scheme and its corresponding data structure for efficient irregular data mapping to parallel single-instruction multiple-data (SIMD) processors. We provide detailed descriptions of the implementations on a single CPU, a multicore CPU with shared memory, and SIMD architectures with comparative results against state-of-the-art Eikonal solvers. PMID:22641200

Investigation of multichannel phased array performance for fetal MR imaging on 1.5T clinical MR system

PubMed Central

Li, Ye; Pang, Yong; Vigneron, Daniel; Glenn, Orit; Xu, Duan; Zhang, Xiaoliang

2011-01-01

Fetal MRI on 1.5T clinical scanner has been increasingly becoming a powerful imaging tool for studying fetal brain abnormalities in vivo. Due to limited availability of dedicated fetal phased arrays, commercial torso or cardiac phased arrays are routinely used for fetal scans, which are unable to provide optimized SNR and parallel imaging performance with a small number coil elements, and insufficient coverage and filling factor. This poses a demand for the investigation and development of dedicated and efficient radiofrequency (RF) hardware to improve fetal imaging. In this work, an investigational approach to simulate the performance of multichannel flexible phased arrays is proposed to find a better solution to fetal MR imaging. A 32 channel fetal array is presented to increase coil sensitivity, coverage and parallel imaging performance. The electromagnetic field distribution of each element of the fetal array is numerically simulated by using finite-difference time-domain (FDTD) method. The array performance, including B1 coverage, parallel reconstructed images and artifact power, is then theoretically calculated and compared with the torso array. Study results show that the proposed array is capable of increasing B1 field strength as well as sensitivity homogeneity in the entire area of uterus. This would ensure high quality imaging regardless of the location of the fetus in the uterus. In addition, the paralleling imaging performance of the proposed fetal array is validated by using artifact power comparison with torso array. These results demonstrate the feasibility of the 32 channel flexible array for fetal MR imaging at 1.5T. PMID:22408747

Parallel Implementation of 3-D Iterative Reconstruction With Intra-Thread Update for the jPET-D4

NASA Astrophysics Data System (ADS)

Lam, Chih Fung; Yamaya, Taiga; Obi, Takashi; Yoshida, Eiji; Inadama, Naoko; Shibuya, Kengo; Nishikido, Fumihiko; Murayama, Hideo

2009-02-01

One way to speed-up iterative image reconstruction is by parallel computing with a computer cluster. However, as the number of computing threads increases, parallel efficiency decreases due to network transfer delay. In this paper, we proposed a method to reduce data transfer between computing threads by introducing an intra-thread update. The update factor is collected from each slave thread and a global image is updated as usual in the first K sub-iteration. In the rest of the sub-iterations, the global image is only updated at an interval which is controlled by a parameter L. In between that interval, the intra-thread update is carried out whereby an image update is performed in each slave thread locally. We investigated combinations of K and L parameters based on parallel implementation of RAMLA for the jPET-D4 scanner. Our evaluation used four workstations with a total of 16 slave threads. Each slave thread calculated a different set of LORs which are divided according to ring difference numbers. We assessed image quality of the proposed method with a hotspot simulation phantom. The figure of merit was the full-width-half-maximum of hotspots and the background normalized standard deviation. At an optimum K and L setting, we did not find significant change in the output images. We also applied the proposed method to a Hoffman phantom experiment and found the difference due to intra-thread update was negligible. With the intra-thread update, computation time could be reduced by about 23%.

Modeling Cooperative Threads to Project GPU Performance for Adaptive Parallelism

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meng, Jiayuan; Uram, Thomas; Morozov, Vitali A.

Most accelerators, such as graphics processing units (GPUs) and vector processors, are particularly suitable for accelerating massively parallel workloads. On the other hand, conventional workloads are developed for multi-core parallelism, which often scale to only a few dozen OpenMP threads. When hardware threads significantly outnumber the degree of parallelism in the outer loop, programmers are challenged with efficient hardware utilization. A common solution is to further exploit the parallelism hidden deep in the code structure. Such parallelism is less structured: parallel and sequential loops may be imperfectly nested within each other, neigh boring inner loops may exhibit different concurrency patternsmore » (e.g. Reduction vs. Forall), yet have to be parallelized in the same parallel section. Many input-dependent transformations have to be explored. A programmer often employs a larger group of hardware threads to cooperatively walk through a smaller outer loop partition and adaptively exploit any encountered parallelism. This process is time-consuming and error-prone, yet the risk of gaining little or no performance remains high for such workloads. To reduce risk and guide implementation, we propose a technique to model workloads with limited parallelism that can automatically explore and evaluate transformations involving cooperative threads. Eventually, our framework projects the best achievable performance and the most promising transformations without implementing GPU code or using physical hardware. We envision our technique to be integrated into future compilers or optimization frameworks for autotuning.« less

ProperCAD: A portable object-oriented parallel environment for VLSI CAD

NASA Technical Reports Server (NTRS)

Ramkumar, Balkrishna; Banerjee, Prithviraj

1993-01-01

Most parallel algorithms for VLSI CAD proposed to date have one important drawback: they work efficiently only on machines that they were designed for. As a result, algorithms designed to date are dependent on the architecture for which they are developed and do not port easily to other parallel architectures. A new project under way to address this problem is described. A Portable object-oriented parallel environment for CAD algorithms (ProperCAD) is being developed. The objectives of this research are (1) to develop new parallel algorithms that run in a portable object-oriented environment (CAD algorithms using a general purpose platform for portable parallel programming called CARM is being developed and a C++ environment that is truly object-oriented and specialized for CAD applications is also being developed); and (2) to design the parallel algorithms around a good sequential algorithm with a well-defined parallel-sequential interface (permitting the parallel algorithm to benefit from future developments in sequential algorithms). One CAD application that has been implemented as part of the ProperCAD project, flat VLSI circuit extraction, is described. The algorithm, its implementation, and its performance on a range of parallel machines are discussed in detail. It currently runs on an Encore Multimax, a Sequent Symmetry, Intel iPSC/2 and i860 hypercubes, a NCUBE 2 hypercube, and a network of Sun Sparc workstations. Performance data for other applications that were developed are provided: namely test pattern generation for sequential circuits, parallel logic synthesis, and standard cell placement.

Parallel algorithm of real-time infrared image restoration based on total variation theory

NASA Astrophysics Data System (ADS)

Zhu, Ran; Li, Miao; Long, Yunli; Zeng, Yaoyuan; An, Wei

2015-10-01

Image restoration is a necessary preprocessing step for infrared remote sensing applications. Traditional methods allow us to remove the noise but penalize too much the gradients corresponding to edges. Image restoration techniques based on variational approaches can solve this over-smoothing problem for the merits of their well-defined mathematical modeling of the restore procedure. The total variation (TV) of infrared image is introduced as a L1 regularization term added to the objective energy functional. It converts the restoration process to an optimization problem of functional involving a fidelity term to the image data plus a regularization term. Infrared image restoration technology with TV-L1 model exploits the remote sensing data obtained sufficiently and preserves information at edges caused by clouds. Numerical implementation algorithm is presented in detail. Analysis indicates that the structure of this algorithm can be easily implemented in parallelization. Therefore a parallel implementation of the TV-L1 filter based on multicore architecture with shared memory is proposed for infrared real-time remote sensing systems. Massive computation of image data is performed in parallel by cooperating threads running simultaneously on multiple cores. Several groups of synthetic infrared image data are used to validate the feasibility and effectiveness of the proposed parallel algorithm. Quantitative analysis of measuring the restored image quality compared to input image is presented. Experiment results show that the TV-L1 filter can restore the varying background image reasonably, and that its performance can achieve the requirement of real-time image processing.

GPU accelerated dynamic functional connectivity analysis for functional MRI data.

PubMed

Akgün, Devrim; Sakoğlu, Ünal; Esquivel, Johnny; Adinoff, Bryon; Mete, Mutlu

2015-07-01

Recent advances in multi-core processors and graphics card based computational technologies have paved the way for an improved and dynamic utilization of parallel computing techniques. Numerous applications have been implemented for the acceleration of computationally-intensive problems in various computational science fields including bioinformatics, in which big data problems are prevalent. In neuroimaging, dynamic functional connectivity (DFC) analysis is a computationally demanding method used to investigate dynamic functional interactions among different brain regions or networks identified with functional magnetic resonance imaging (fMRI) data. In this study, we implemented and analyzed a parallel DFC algorithm based on thread-based and block-based approaches. The thread-based approach was designed to parallelize DFC computations and was implemented in both Open Multi-Processing (OpenMP) and Compute Unified Device Architecture (CUDA) programming platforms. Another approach developed in this study to better utilize CUDA architecture is the block-based approach, where parallelization involves smaller parts of fMRI time-courses obtained by sliding-windows. Experimental results showed that the proposed parallel design solutions enabled by the GPUs significantly reduce the computation time for DFC analysis. Multicore implementation using OpenMP on 8-core processor provides up to 7.7× speed-up. GPU implementation using CUDA yielded substantial accelerations ranging from 18.5× to 157× speed-up once thread-based and block-based approaches were combined in the analysis. Proposed parallel programming solutions showed that multi-core processor and CUDA-supported GPU implementations accelerated the DFC analyses significantly. Developed algorithms make the DFC analyses more practical for multi-subject studies with more dynamic analyses. Copyright © 2015 Elsevier Ltd. All rights reserved.

Critical appraisal of arguments for the delayed-start design proposed as alternative to the parallel-group randomized clinical trial design in the field of rare disease.

PubMed

Spineli, Loukia M; Jenz, Eva; Großhennig, Anika; Koch, Armin

2017-08-17

A number of papers have proposed or evaluated the delayed-start design as an alternative to the standard two-arm parallel group randomized clinical trial (RCT) design in the field of rare disease. However the discussion is felt to lack a sufficient degree of consideration devoted to the true virtues of the delayed start design and the implications either in terms of required sample-size, overall information, or interpretation of the estimate in the context of small populations. To evaluate whether there are real advantages of the delayed-start design particularly in terms of overall efficacy and sample size requirements as a proposed alternative to the standard parallel group RCT in the field of rare disease. We used a real-life example to compare the delayed-start design with the standard RCT in terms of sample size requirements. Then, based on three scenarios regarding the development of the treatment effect over time, the advantages, limitations and potential costs of the delayed-start design are discussed. We clarify that delayed-start design is not suitable for drugs that establish an immediate treatment effect, but for drugs with effects developing over time, instead. In addition, the sample size will always increase as an implication for a reduced time on placebo resulting in a decreased treatment effect. A number of papers have repeated well-known arguments to justify the delayed-start design as appropriate alternative to the standard parallel group RCT in the field of rare disease and do not discuss the specific needs of research methodology in this field. The main point is that a limited time on placebo will result in an underestimated treatment effect and, in consequence, in larger sample size requirements compared to those expected under a standard parallel-group design. This also impacts on benefit-risk assessment.

Hardware-efficient implementation of digital FIR filter using fast first-order moment algorithm

NASA Astrophysics Data System (ADS)

Cao, Li; Liu, Jianguo; Xiong, Jun; Zhang, Jing

2018-03-01

As the digital finite impulse response (FIR) filter can be transformed into the shift-add form of multiple small-sized firstorder moments, based on the existing fast first-order moment algorithm, this paper presents a novel multiplier-less structure to calculate any number of sequential filtering results in parallel. The theoretical analysis on its hardware and time-complexities reveals that by appropriately setting the degree of parallelism and the decomposition factor of a fixed word width, the proposed structure may achieve better area-time efficiency than the existing two-dimensional (2-D) memoryless-based filter. To evaluate the performance concretely, the proposed designs for different taps along with the existing 2-D memoryless-based filters, are synthesized by Synopsys Design Compiler with 0.18-μm SMIC library. The comparisons show that the proposed design has less area-time complexity and power consumption when the number of filter taps is larger than 48.

Measurement of the Microwave Refractive Index of Materials Based on Parallel Plate Waveguides

NASA Astrophysics Data System (ADS)

Zhao, F.; Pei, J.; Kan, J. S.; Zhao, Q.

2017-12-01

An electrical field scanning apparatus based on a parallel plate waveguide method is constructed, which collects the amplitude and phase matrices as a function of the relative position. On the basis of such data, a method for calculating the refractive index of the measured wedge samples is proposed in this paper. The measurement and calculation results of different PTFE samples reveal that the refractive index measured by the apparatus is substantially consistent with the refractive index inferred with the permittivity of the sample. The proposed refractive index calculation method proposed in this paper is a competitive method for the characterization of the refractive index of materials with positive refractive index. Since the apparatus and method can be used to measure and calculate arbitrary direction of the microwave propagation, it is believed that both of them can be applied to the negative refractive index materials, such as metamaterials or “left-handed” materials.

A high performance parallel algorithm for 1-D FFT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agarwal, R.C.; Gustavson, F.G.; Zubair, M.

1994-12-31

In this paper the authors propose a parallel high performance FFT algorithm based on a multi-dimensional formulation. They use this to solve a commonly encountered FFT based kernel on a distributed memory parallel machine, the IBM scalable parallel system, SP1. The kernel requires a forward FFT computation of an input sequence, multiplication of the transformed data by a coefficient array, and finally an inverse FFT computation of the resultant data. They show that the multi-dimensional formulation helps in reducing the communication costs and also improves the single node performance by effectively utilizing the memory system of the node. They implementedmore » this kernel on the IBM SP1 and observed a performance of 1.25 GFLOPS on a 64-node machine.« less

Distributed and parallel approach for handle and perform huge datasets

NASA Astrophysics Data System (ADS)

Konopko, Joanna

2015-12-01

Big Data refers to the dynamic, large and disparate volumes of data comes from many different sources (tools, machines, sensors, mobile devices) uncorrelated with each others. It requires new, innovative and scalable technology to collect, host and analytically process the vast amount of data. Proper architecture of the system that perform huge data sets is needed. In this paper, the comparison of distributed and parallel system architecture is presented on the example of MapReduce (MR) Hadoop platform and parallel database platform (DBMS). This paper also analyzes the problem of performing and handling valuable information from petabytes of data. The both paradigms: MapReduce and parallel DBMS are described and compared. The hybrid architecture approach is also proposed and could be used to solve the analyzed problem of storing and processing Big Data.

Simulating coupled dynamics of a rigid-flexible multibody system and compressible fluid

NASA Astrophysics Data System (ADS)

Hu, Wei; Tian, Qiang; Hu, HaiYan

2018-04-01

As a subsequent work of previous studies of authors, a new parallel computation approach is proposed to simulate the coupled dynamics of a rigid-flexible multibody system and compressible fluid. In this approach, the smoothed particle hydrodynamics (SPH) method is used to model the compressible fluid, the natural coordinate formulation (NCF) and absolute nodal coordinate formulation (ANCF) are used to model the rigid and flexible bodies, respectively. In order to model the compressible fluid properly and efficiently via SPH method, three measures are taken as follows. The first is to use the Riemann solver to cope with the fluid compressibility, the second is to define virtual particles of SPH to model the dynamic interaction between the fluid and the multibody system, and the third is to impose the boundary conditions of periodical inflow and outflow to reduce the number of SPH particles involved in the computation process. Afterwards, a parallel computation strategy is proposed based on the graphics processing unit (GPU) to detect the neighboring SPH particles and to solve the dynamic equations of SPH particles in order to improve the computation efficiency. Meanwhile, the generalized-alpha algorithm is used to solve the dynamic equations of the multibody system. Finally, four case studies are given to validate the proposed parallel computation approach.

Proposed scheme for parallel 10Gb/s VSR system and its verilog HDL realization

NASA Astrophysics Data System (ADS)

Zhou, Yi; Chen, Hongda; Zuo, Chao; Jia, Jiuchun; Shen, Rongxuan; Chen, Xiongbin

2005-02-01

This paper proposes a novel and innovative scheme for 10Gb/s parallel Very Short Reach (VSR) optical communication system. The optimized scheme properly manages the SDH/SONET redundant bytes and adjusts the position of error detecting bytes and error correction bytes. Compared with the OIF-VSR4-01.0 proposal, the scheme has a coding process module. The SDH/SONET frames in transmission direction are disposed as follows: (1) The Framer-Serdes Interface (FSI) gets 16×622.08Mb/s STM-64 frame. (2) The STM-64 frame is byte-wise stripped across 12 channels, all channels are data channels. During this process, the parity bytes and CRC bytes are generated in the similar way as OIF-VSR4-01.0 and stored in the code process module. (3) The code process module will regularly convey the additional parity bytes and CRC bytes to all 12 data channels. (4) After the 8B/10B coding, the 12 channels is transmitted to the parallel VCSEL array. The receive process approximately in reverse order of transmission process. By applying this scheme to 10Gb/s VSR system, the frame size in VSR system is reduced from 15552×12 bytes to 14040×12 bytes, the system redundancy is reduced obviously.

Improved preconditioned conjugate gradient algorithm and application in 3D inversion of gravity-gradiometry data

NASA Astrophysics Data System (ADS)

Wang, Tai-Han; Huang, Da-Nian; Ma, Guo-Qing; Meng, Zhao-Hai; Li, Ye

2017-06-01

With the continuous development of full tensor gradiometer (FTG) measurement techniques, three-dimensional (3D) inversion of FTG data is becoming increasingly used in oil and gas exploration. In the fast processing and interpretation of large-scale high-precision data, the use of the graphics processing unit process unit (GPU) and preconditioning methods are very important in the data inversion. In this paper, an improved preconditioned conjugate gradient algorithm is proposed by combining the symmetric successive over-relaxation (SSOR) technique and the incomplete Choleksy decomposition conjugate gradient algorithm (ICCG). Since preparing the preconditioner requires extra time, a parallel implement based on GPU is proposed. The improved method is then applied in the inversion of noisecontaminated synthetic data to prove its adaptability in the inversion of 3D FTG data. Results show that the parallel SSOR-ICCG algorithm based on NVIDIA Tesla C2050 GPU achieves a speedup of approximately 25 times that of a serial program using a 2.0 GHz Central Processing Unit (CPU). Real airborne gravity-gradiometry data from Vinton salt dome (southwest Louisiana, USA) are also considered. Good results are obtained, which verifies the efficiency and feasibility of the proposed parallel method in fast inversion of 3D FTG data.

Wavelet-based de-noising algorithm for images acquired with parallel magnetic resonance imaging (MRI).

PubMed

Delakis, Ioannis; Hammad, Omer; Kitney, Richard I

2007-07-07

Wavelet-based de-noising has been shown to improve image signal-to-noise ratio in magnetic resonance imaging (MRI) while maintaining spatial resolution. Wavelet-based de-noising techniques typically implemented in MRI require that noise displays uniform spatial distribution. However, images acquired with parallel MRI have spatially varying noise levels. In this work, a new algorithm for filtering images with parallel MRI is presented. The proposed algorithm extracts the edges from the original image and then generates a noise map from the wavelet coefficients at finer scales. The noise map is zeroed at locations where edges have been detected and directional analysis is also used to calculate noise in regions of low-contrast edges that may not have been detected. The new methodology was applied on phantom and brain images and compared with other applicable de-noising techniques. The performance of the proposed algorithm was shown to be comparable with other techniques in central areas of the images, where noise levels are high. In addition, finer details and edges were maintained in peripheral areas, where noise levels are low. The proposed methodology is fully automated and can be applied on final reconstructed images without requiring sensitivity profiles or noise matrices of the receiver coils, therefore making it suitable for implementation in a clinical MRI setting.

Optimal Golomb Ruler Sequences Generation for Optical WDM Systems: A Novel Parallel Hybrid Multi-objective Bat Algorithm

NASA Astrophysics Data System (ADS)

Bansal, Shonak; Singh, Arun Kumar; Gupta, Neena

2017-02-01

In real-life, multi-objective engineering design problems are very tough and time consuming optimization problems due to their high degree of nonlinearities, complexities and inhomogeneity. Nature-inspired based multi-objective optimization algorithms are now becoming popular for solving multi-objective engineering design problems. This paper proposes original multi-objective Bat algorithm (MOBA) and its extended form, namely, novel parallel hybrid multi-objective Bat algorithm (PHMOBA) to generate shortest length Golomb ruler called optimal Golomb ruler (OGR) sequences at a reasonable computation time. The OGRs found their application in optical wavelength division multiplexing (WDM) systems as channel-allocation algorithm to reduce the four-wave mixing (FWM) crosstalk. The performances of both the proposed algorithms to generate OGRs as optical WDM channel-allocation is compared with other existing classical computing and nature-inspired algorithms, including extended quadratic congruence (EQC), search algorithm (SA), genetic algorithms (GAs), biogeography based optimization (BBO) and big bang-big crunch (BB-BC) optimization algorithms. Simulations conclude that the proposed parallel hybrid multi-objective Bat algorithm works efficiently as compared to original multi-objective Bat algorithm and other existing algorithms to generate OGRs for optical WDM systems. The algorithm PHMOBA to generate OGRs, has higher convergence and success rate than original MOBA. The efficiency improvement of proposed PHMOBA to generate OGRs up to 20-marks, in terms of ruler length and total optical channel bandwidth (TBW) is 100 %, whereas for original MOBA is 85 %. Finally the implications for further research are also discussed.

Anomalous pinch of turbulent plasmas driven by the magnetic-drift-induced Lorentz force through the Stokes-Einstein relation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Shaojie, E-mail: wangsj@ustc.edu.cn

It is found that the Lorentz force generated by the magnetic drift drives a generic plasma pinch flux of particle, energy and momentum through the Stokes-Einstein relation. The proposed theoretical model applies for both electrons and ions, trapped particles, and passing particles. An anomalous parallel current pinch due to the electrostatic turbulence with long parallel wave-length is predicted.

Scheduling for Locality in Shared-Memory Multiprocessors

DTIC Science & Technology

1993-05-01

Submitted in Partial Fulfillment of the Requirements for the Degree ’)iIC Q(JALfryT INSPECTED 5 DOCTOR OF PHILOSOPHY I Accesion For Supervised by NTIS CRAM... architecture on parallel program performance, explain the implications of this trend on popular parallel programming models, and propose system software to 0...decomoosition and scheduling algorithms. I. SUIUECT TERMS IS. NUMBER OF PAGES shared-memory multiprocessors; architecture trends; loop 110 scheduling

Field-parallel Acceleration: Comment on the Paper “Electric Currents on the Flare Ribbons: Observations and Standard Model” by Janvier et al. (2014, ApJ, 788, 60)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haerendel, G.

It is proposed that the coincidence of higher brightness and upward electric current observed by Janvier et al. during a flare indicates electron acceleration by field-parallel potential drops sustained by extremely strong field-aligned currents of order 10{sup 4} A m{sup −2}. A few consequences are discussed here.

Multi-Objective and Multidisciplinary Design Optimisation (MDO) of UAV Systems using Hierarchical Asynchronous Parallel Evolutionary Algorithms

DTIC Science & Technology

2007-09-17

been proposed; these include a combination of variable fidelity models, parallelisation strategies and hybridisation techniques (Coello, Veldhuizen et...Coello et al (Coello, Veldhuizen et al. 2002). 4.4.2 HIERARCHICAL POPULATION TOPOLOGY A hierarchical population topology, when integrated into...to hybrid parallel Multi-Objective Evolutionary Algorithms (pMOEA) (Cantu-Paz 2000; Veldhuizen , Zydallis et al. 2003); it uses a master slave

Role of APOE Isoforms in the Pathogenesis of TBI induced Alzheimer’s Disease

DTIC Science & Technology

2016-10-01

deletion, APOE targeted replacement, complex breeding, CCI model optimization, mRNA library generation, high throughput massive parallel sequencing...demonstrate that the lack of Abca1 increases amyloid plaques and decreased APOE protein levels in AD-model mice. In this proposal we will test the hypothesis...injury, inflammatory reaction, transcriptome, high throughput massive parallel sequencing, mRNA-seq., behavioral testing, memory impairment, recovery 3

A Parallel Compact Multi-Dimensional Numerical Algorithm with Aeroacoustics Applications

NASA Technical Reports Server (NTRS)

Povitsky, Alex; Morris, Philip J.

1999-01-01

In this study we propose a novel method to parallelize high-order compact numerical algorithms for the solution of three-dimensional PDEs (Partial Differential Equations) in a space-time domain. For this numerical integration most of the computer time is spent in computation of spatial derivatives at each stage of the Runge-Kutta temporal update. The most efficient direct method to compute spatial derivatives on a serial computer is a version of Gaussian elimination for narrow linear banded systems known as the Thomas algorithm. In a straightforward pipelined implementation of the Thomas algorithm processors are idle due to the forward and backward recurrences of the Thomas algorithm. To utilize processors during this time, we propose to use them for either non-local data independent computations, solving lines in the next spatial direction, or local data-dependent computations by the Runge-Kutta method. To achieve this goal, control of processor communication and computations by a static schedule is adopted. Thus, our parallel code is driven by a communication and computation schedule instead of the usual "creative, programming" approach. The obtained parallelization speed-up of the novel algorithm is about twice as much as that for the standard pipelined algorithm and close to that for the explicit DRP algorithm.

LORAKS Makes Better SENSE: Phase-Constrained Partial Fourier SENSE Reconstruction without Phase Calibration

PubMed Central

Kim, Tae Hyung; Setsompop, Kawin; Haldar, Justin P.

2016-01-01

Purpose Parallel imaging and partial Fourier acquisition are two classical approaches for accelerated MRI. Methods that combine these approaches often rely on prior knowledge of the image phase, but the need to obtain this prior information can place practical restrictions on the data acquisition strategy. In this work, we propose and evaluate SENSE-LORAKS, which enables combined parallel imaging and partial Fourier reconstruction without requiring prior phase information. Theory and Methods The proposed formulation is based on combining the classical SENSE model for parallel imaging data with the more recent LORAKS framework for MR image reconstruction using low-rank matrix modeling. Previous LORAKS-based methods have successfully enabled calibrationless partial Fourier parallel MRI reconstruction, but have been most successful with nonuniform sampling strategies that may be hard to implement for certain applications. By combining LORAKS with SENSE, we enable highly-accelerated partial Fourier MRI reconstruction for a broader range of sampling trajectories, including widely-used calibrationless uniformly-undersampled trajectories. Results Our empirical results with retrospectively undersampled datasets indicate that when SENSE-LORAKS reconstruction is combined with an appropriate k-space sampling trajectory, it can provide substantially better image quality at high-acceleration rates relative to existing state-of-the-art reconstruction approaches. Conclusion The SENSE-LORAKS framework provides promising new opportunities for highly-accelerated MRI. PMID:27037836

Parallel Hough Transform-Based Straight Line Detection and Its FPGA Implementation in Embedded Vision

PubMed Central

Lu, Xiaofeng; Song, Li; Shen, Sumin; He, Kang; Yu, Songyu; Ling, Nam

2013-01-01

Hough Transform has been widely used for straight line detection in low-definition and still images, but it suffers from execution time and resource requirements. Field Programmable Gate Arrays (FPGA) provide a competitive alternative for hardware acceleration to reap tremendous computing performance. In this paper, we propose a novel parallel Hough Transform (PHT) and FPGA architecture-associated framework for real-time straight line detection in high-definition videos. A resource-optimized Canny edge detection method with enhanced non-maximum suppression conditions is presented to suppress most possible false edges and obtain more accurate candidate edge pixels for subsequent accelerated computation. Then, a novel PHT algorithm exploiting spatial angle-level parallelism is proposed to upgrade computational accuracy by improving the minimum computational step. Moreover, the FPGA based multi-level pipelined PHT architecture optimized by spatial parallelism ensures real-time computation for 1,024 × 768 resolution videos without any off-chip memory consumption. This framework is evaluated on ALTERA DE2-115 FPGA evaluation platform at a maximum frequency of 200 MHz, and it can calculate straight line parameters in 15.59 ms on the average for one frame. Qualitative and quantitative evaluation results have validated the system performance regarding data throughput, memory bandwidth, resource, speed and robustness. PMID:23867746

Parallel Hough Transform-based straight line detection and its FPGA implementation in embedded vision.

PubMed

Lu, Xiaofeng; Song, Li; Shen, Sumin; He, Kang; Yu, Songyu; Ling, Nam

2013-07-17

Hough Transform has been widely used for straight line detection in low-definition and still images, but it suffers from execution time and resource requirements. Field Programmable Gate Arrays (FPGA) provide a competitive alternative for hardware acceleration to reap tremendous computing performance. In this paper, we propose a novel parallel Hough Transform (PHT) and FPGA architecture-associated framework for real-time straight line detection in high-definition videos. A resource-optimized Canny edge detection method with enhanced non-maximum suppression conditions is presented to suppress most possible false edges and obtain more accurate candidate edge pixels for subsequent accelerated computation. Then, a novel PHT algorithm exploiting spatial angle-level parallelism is proposed to upgrade computational accuracy by improving the minimum computational step. Moreover, the FPGA based multi-level pipelined PHT architecture optimized by spatial parallelism ensures real-time computation for 1,024 × 768 resolution videos without any off-chip memory consumption. This framework is evaluated on ALTERA DE2-115 FPGA evaluation platform at a maximum frequency of 200 MHz, and it can calculate straight line parameters in 15.59 ms on the average for one frame. Qualitative and quantitative evaluation results have validated the system performance regarding data throughput, memory bandwidth, resource, speed and robustness.

Dynamic programming in parallel boundary detection with application to ultrasound intima-media segmentation.

PubMed

Zhou, Yuan; Cheng, Xinyao; Xu, Xiangyang; Song, Enmin

2013-12-01

Segmentation of carotid artery intima-media in longitudinal ultrasound images for measuring its thickness to predict cardiovascular diseases can be simplified as detecting two nearly parallel boundaries within a certain distance range, when plaque with irregular shapes is not considered. In this paper, we improve the implementation of two dynamic programming (DP) based approaches to parallel boundary detection, dual dynamic programming (DDP) and piecewise linear dual dynamic programming (PL-DDP). Then, a novel DP based approach, dual line detection (DLD), which translates the original 2-D curve position to a 4-D parameter space representing two line segments in a local image segment, is proposed to solve the problem while maintaining efficiency and rotation invariance. To apply the DLD to ultrasound intima-media segmentation, it is imbedded in a framework that employs an edge map obtained from multiplication of the responses of two edge detectors with different scales and a coupled snake model that simultaneously deforms the two contours for maintaining parallelism. The experimental results on synthetic images and carotid arteries of clinical ultrasound images indicate improved performance of the proposed DLD compared to DDP and PL-DDP, with respect to accuracy and efficiency. Copyright © 2013 Elsevier B.V. All rights reserved.

Fully parallel write/read in resistive synaptic array for accelerating on-chip learning

NASA Astrophysics Data System (ADS)

Gao, Ligang; Wang, I.-Ting; Chen, Pai-Yu; Vrudhula, Sarma; Seo, Jae-sun; Cao, Yu; Hou, Tuo-Hung; Yu, Shimeng

2015-11-01

A neuro-inspired computing paradigm beyond the von Neumann architecture is emerging and it generally takes advantage of massive parallelism and is aimed at complex tasks that involve intelligence and learning. The cross-point array architecture with synaptic devices has been proposed for on-chip implementation of the weighted sum and weight update in the learning algorithms. In this work, forming-free, silicon-process-compatible Ta/TaO x /TiO2/Ti synaptic devices are fabricated, in which >200 levels of conductance states could be continuously tuned by identical programming pulses. In order to demonstrate the advantages of parallelism of the cross-point array architecture, a novel fully parallel write scheme is designed and experimentally demonstrated in a small-scale crossbar array to accelerate the weight update in the training process, at a speed that is independent of the array size. Compared to the conventional row-by-row write scheme, it achieves >30× speed-up and >30× improvement in energy efficiency as projected in a large-scale array. If realistic synaptic device characteristics such as device variations are taken into an array-level simulation, the proposed array architecture is able to achieve ∼95% recognition accuracy of MNIST handwritten digits, which is close to the accuracy achieved by software using the ideal sparse coding algorithm.

Using Perturbed QR Factorizations To Solve Linear Least-Squares Problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Avron, Haim; Ng, Esmond G.; Toledo, Sivan

2008-03-21

We propose and analyze a new tool to help solve sparse linear least-squares problems min{sub x} {parallel}Ax-b{parallel}{sub 2}. Our method is based on a sparse QR factorization of a low-rank perturbation {cflx A} of A. More precisely, we show that the R factor of {cflx A} is an effective preconditioner for the least-squares problem min{sub x} {parallel}Ax-b{parallel}{sub 2}, when solved using LSQR. We propose applications for the new technique. When A is rank deficient we can add rows to ensure that the preconditioner is well-conditioned without column pivoting. When A is sparse except for a few dense rows we canmore » drop these dense rows from A to obtain {cflx A}. Another application is solving an updated or downdated problem. If R is a good preconditioner for the original problem A, it is a good preconditioner for the updated/downdated problem {cflx A}. We can also solve what-if scenarios, where we want to find the solution if a column of the original matrix is changed/removed. We present a spectral theory that analyzes the generalized spectrum of the pencil (A*A,R*R) and analyze the applications.« less

Proposing an Optimal Learning Architecture for the Digital Enterprise.

ERIC Educational Resources Information Center

O'Driscoll, Tony

2003-01-01

Discusses the strategic role of learning in information age organizations; analyzes parallels between the application of technology to business and the application of technology to learning; and proposes a learning architecture that aligns with the knowledge-based view of the firm and optimizes the application of technology to achieve proficiency…

A parallel finite element procedure for contact-impact problems using edge-based smooth triangular element and GPU

NASA Astrophysics Data System (ADS)

Cai, Yong; Cui, Xiangyang; Li, Guangyao; Liu, Wenyang

2018-04-01

The edge-smooth finite element method (ES-FEM) can improve the computational accuracy of triangular shell elements and the mesh partition efficiency of complex models. In this paper, an approach is developed to perform explicit finite element simulations of contact-impact problems with a graphical processing unit (GPU) using a special edge-smooth triangular shell element based on ES-FEM. Of critical importance for this problem is achieving finer-grained parallelism to enable efficient data loading and to minimize communication between the device and host. Four kinds of parallel strategies are then developed to efficiently solve these ES-FEM based shell element formulas, and various optimization methods are adopted to ensure aligned memory access. Special focus is dedicated to developing an approach for the parallel construction of edge systems. A parallel hierarchy-territory contact-searching algorithm (HITA) and a parallel penalty function calculation method are embedded in this parallel explicit algorithm. Finally, the program flow is well designed, and a GPU-based simulation system is developed, using Nvidia's CUDA. Several numerical examples are presented to illustrate the high quality of the results obtained with the proposed methods. In addition, the GPU-based parallel computation is shown to significantly reduce the computing time.

Connectionism, parallel constraint satisfaction processes, and gestalt principles: (re) introducing cognitive dynamics to social psychology.

PubMed

Read, S J; Vanman, E J; Miller, L C

1997-01-01

We argue that recent work in connectionist modeling, in particular the parallel constraint satisfaction processes that are central to many of these models, has great importance for understanding issues of both historical and current concern for social psychologists. We first provide a brief description of connectionist modeling, with particular emphasis on parallel constraint satisfaction processes. Second, we examine the tremendous similarities between parallel constraint satisfaction processes and the Gestalt principles that were the foundation for much of modem social psychology. We propose that parallel constraint satisfaction processes provide a computational implementation of the principles of Gestalt psychology that were central to the work of such seminal social psychologists as Asch, Festinger, Heider, and Lewin. Third, we then describe how parallel constraint satisfaction processes have been applied to three areas that were key to the beginnings of modern social psychology and remain central today: impression formation and causal reasoning, cognitive consistency (balance and cognitive dissonance), and goal-directed behavior. We conclude by discussing implications of parallel constraint satisfaction principles for a number of broader issues in social psychology, such as the dynamics of social thought and the integration of social information within the narrow time frame of social interaction.

Decomposition method for fast computation of gigapixel-sized Fresnel holograms on a graphics processing unit cluster.

PubMed

Jackin, Boaz Jessie; Watanabe, Shinpei; Ootsu, Kanemitsu; Ohkawa, Takeshi; Yokota, Takashi; Hayasaki, Yoshio; Yatagai, Toyohiko; Baba, Takanobu

2018-04-20

A parallel computation method for large-size Fresnel computer-generated hologram (CGH) is reported. The method was introduced by us in an earlier report as a technique for calculating Fourier CGH from 2D object data. In this paper we extend the method to compute Fresnel CGH from 3D object data. The scale of the computation problem is also expanded to 2 gigapixels, making it closer to real application requirements. The significant feature of the reported method is its ability to avoid communication overhead and thereby fully utilize the computing power of parallel devices. The method exhibits three layers of parallelism that favor small to large scale parallel computing machines. Simulation and optical experiments were conducted to demonstrate the workability and to evaluate the efficiency of the proposed technique. A two-times improvement in computation speed has been achieved compared to the conventional method, on a 16-node cluster (one GPU per node) utilizing only one layer of parallelism. A 20-times improvement in computation speed has been estimated utilizing two layers of parallelism on a very large-scale parallel machine with 16 nodes, where each node has 16 GPUs.

Observing with HST V: Improvements to the Scheduling of HST Parallel Observations

NASA Astrophysics Data System (ADS)

Taylor, D. K.; Vanorsow, D.; Lucks, M.; Henry, R.; Ratnatunga, K.; Patterson, A.

1994-12-01

Recent improvements to the Hubble Space Telescope (HST) ground system have significantly increased the frequency of pure parallel observations, i.e. the simultaneous use of multiple HST instruments by different observers. Opportunities for parallel observations are limited by a variety of timing, hardware, and scientific constraints. Formerly, such opportunities were heuristically predicted prior to the construction of the primary schedule (or calendar), and lack of complete information resulted in high rates of scheduling failures and missed opportunities. In the current process the search for parallel opportunities is delayed until the primary schedule is complete, at which point new software tools are employed to identify places where parallel observations are supported. The result has been a considerable increase in parallel throughput. A new technique, known as ``parallel crafting,'' is currently under development to streamline further the parallel scheduling process. This radically new method will replace the standard exposure logsheet with a set of abstract rules from which observation parameters will be constructed ``on the fly'' to best match the constraints of the parallel opportunity. Currently, parallel observers must specify a huge (and highly redundant) set of exposure types in order to cover all possible types of parallel opportunities. Crafting rules permit the observer to express timing, filter, and splitting preferences in a far more succinct manner. The issue of coordinated parallel observations (same PI using different instruments simultaneously), long a troublesome aspect of the ground system, is also being addressed. For Cycle 5, the Phase II Proposal Instructions now have an exposure-level PAR WITH special requirement. While only the primary's alignment will be scheduled on the calendar, new commanding will provide for parallel exposures with both instruments.

Fast l₁-SPIRiT compressed sensing parallel imaging MRI: scalable parallel implementation and clinically feasible runtime.

PubMed

Murphy, Mark; Alley, Marcus; Demmel, James; Keutzer, Kurt; Vasanawala, Shreyas; Lustig, Michael

2012-06-01

We present l₁-SPIRiT, a simple algorithm for auto calibrating parallel imaging (acPI) and compressed sensing (CS) that permits an efficient implementation with clinically-feasible runtimes. We propose a CS objective function that minimizes cross-channel joint sparsity in the wavelet domain. Our reconstruction minimizes this objective via iterative soft-thresholding, and integrates naturally with iterative self-consistent parallel imaging (SPIRiT). Like many iterative magnetic resonance imaging reconstructions, l₁-SPIRiT's image quality comes at a high computational cost. Excessively long runtimes are a barrier to the clinical use of any reconstruction approach, and thus we discuss our approach to efficiently parallelizing l₁-SPIRiT and to achieving clinically-feasible runtimes. We present parallelizations of l₁-SPIRiT for both multi-GPU systems and multi-core CPUs, and discuss the software optimization and parallelization decisions made in our implementation. The performance of these alternatives depends on the processor architecture, the size of the image matrix, and the number of parallel imaging channels. Fundamentally, achieving fast runtime requires the correct trade-off between cache usage and parallelization overheads. We demonstrate image quality via a case from our clinical experimentation, using a custom 3DFT spoiled gradient echo (SPGR) sequence with up to 8× acceleration via Poisson-disc undersampling in the two phase-encoded directions.

Fast ℓ1-SPIRiT Compressed Sensing Parallel Imaging MRI: Scalable Parallel Implementation and Clinically Feasible Runtime

PubMed Central

Murphy, Mark; Alley, Marcus; Demmel, James; Keutzer, Kurt; Vasanawala, Shreyas; Lustig, Michael

2012-01-01

We present ℓ1-SPIRiT, a simple algorithm for auto calibrating parallel imaging (acPI) and compressed sensing (CS) that permits an efficient implementation with clinically-feasible runtimes. We propose a CS objective function that minimizes cross-channel joint sparsity in the Wavelet domain. Our reconstruction minimizes this objective via iterative soft-thresholding, and integrates naturally with iterative Self-Consistent Parallel Imaging (SPIRiT). Like many iterative MRI reconstructions, ℓ1-SPIRiT’s image quality comes at a high computational cost. Excessively long runtimes are a barrier to the clinical use of any reconstruction approach, and thus we discuss our approach to efficiently parallelizing ℓ1-SPIRiT and to achieving clinically-feasible runtimes. We present parallelizations of ℓ1-SPIRiT for both multi-GPU systems and multi-core CPUs, and discuss the software optimization and parallelization decisions made in our implementation. The performance of these alternatives depends on the processor architecture, the size of the image matrix, and the number of parallel imaging channels. Fundamentally, achieving fast runtime requires the correct trade-off between cache usage and parallelization overheads. We demonstrate image quality via a case from our clinical experimentation, using a custom 3DFT Spoiled Gradient Echo (SPGR) sequence with up to 8× acceleration via poisson-disc undersampling in the two phase-encoded directions. PMID:22345529

Conceptual design of a hybrid parallel mechanism for mask exchanging of TMT

NASA Astrophysics Data System (ADS)

Wang, Jianping; Zhou, Hongfei; Li, Kexuan; Zhou, Zengxiang; Zhai, Chao

2015-10-01

Mask exchange system is an important part of the Multi-Object Broadband Imaging Echellette (MOBIE) on the Thirty Meter Telescope (TMT). To solve the problem of stiffness changing with the gravity vector of the mask exchange system in the MOBIE, the hybrid parallel mechanism design method was introduced into the whole research. By using the characteristics of high stiffness and precision of parallel structure, combined with large moving range of serial structure, a conceptual design of a hybrid parallel mask exchange system based on 3-RPS parallel mechanism was presented. According to the position requirements of the MOBIE, the SolidWorks structure model of the hybrid parallel mask exchange robot was established and the appropriate installation position without interfering with the related components and light path in the MOBIE of TMT was analyzed. Simulation results in SolidWorks suggested that 3-RPS parallel platform had good stiffness property in different gravity vector directions. Furthermore, through the research of the mechanism theory, the inverse kinematics solution of the 3-RPS parallel platform was calculated and the mathematical relationship between the attitude angle of moving platform and the angle of ball-hinges on the moving platform was established, in order to analyze the attitude adjustment ability of the hybrid parallel mask exchange robot. The proposed conceptual design has some guiding significance for the design of mask exchange system of the MOBIE on TMT.

Comparison of multihardware parallel implementations for a phase unwrapping algorithm

NASA Astrophysics Data System (ADS)

Hernandez-Lopez, Francisco Javier; Rivera, Mariano; Salazar-Garibay, Adan; Legarda-Sáenz, Ricardo

2018-04-01

Phase unwrapping is an important problem in the areas of optical metrology, synthetic aperture radar (SAR) image analysis, and magnetic resonance imaging (MRI) analysis. These images are becoming larger in size and, particularly, the availability and need for processing of SAR and MRI data have increased significantly with the acquisition of remote sensing data and the popularization of magnetic resonators in clinical diagnosis. Therefore, it is important to develop faster and accurate phase unwrapping algorithms. We propose a parallel multigrid algorithm of a phase unwrapping method named accumulation of residual maps, which builds on a serial algorithm that consists of the minimization of a cost function; minimization achieved by means of a serial Gauss-Seidel kind algorithm. Our algorithm also optimizes the original cost function, but unlike the original work, our algorithm is a parallel Jacobi class with alternated minimizations. This strategy is known as the chessboard type, where red pixels can be updated in parallel at same iteration since they are independent. Similarly, black pixels can be updated in parallel in an alternating iteration. We present parallel implementations of our algorithm for different parallel multicore architecture such as CPU-multicore, Xeon Phi coprocessor, and Nvidia graphics processing unit. In all the cases, we obtain a superior performance of our parallel algorithm when compared with the original serial version. In addition, we present a detailed comparative performance of the developed parallel versions.

Micropore extrusion-induced alignment transition from perpendicular to parallel of cylindrical domains in block copolymers.

PubMed

Qu, Ting; Zhao, Yongbin; Li, Zongbo; Wang, Pingping; Cao, Shubo; Xu, Yawei; Li, Yayuan; Chen, Aihua

2016-02-14

The orientation transition from perpendicular to parallel alignment of PEO cylindrical domains of PEO-b-PMA(Az) films has been demonstrated by extruding the block copolymer (BCP) solutions through a micropore of a plastic gastight syringe. The parallelized orientation of PEO domains induced by this micropore extrusion can be recovered to perpendicular alignment via ultrasonication of the extruded BCP solutions and subsequent annealing. A plausible mechanism is proposed in this study. The BCP films can be used as templates to prepare nanowire arrays with controlled layers, which has enormous potential application in the field of integrated circuits.

Single flux quantum voltage amplifiers

NASA Astrophysics Data System (ADS)

Golomidov, Vladimir; Kaplunenko, Vsevolod; Khabipov, Marat; Koshelets, Valery; Kaplunenko, Olga

The novel elements of the Rapid Single Flux Quantum (RSFQ) logic family — a Quasi Digital Voltage Parallel and Series Amplifiers (QDVA) have been computer simulated, designed and experimentally investigated. The Parallel QDVA consists of six stages and provides multiplication of the input voltage with factor five. The output resistance of the QDVA is five times larger than the input so this amplifier seems to be a good matching stage between RSFQL and usual semiconductor electronics. The series QDVA provides a gain factor four and involves two doublers connected by transmission line. The proposed parallel QDVA can be integrated on the same chip with a SQUID sensor.

Computation of free energy profiles with parallel adaptive dynamics

NASA Astrophysics Data System (ADS)

Lelièvre, Tony; Rousset, Mathias; Stoltz, Gabriel

2007-04-01

We propose a formulation of an adaptive computation of free energy differences, in the adaptive biasing force or nonequilibrium metadynamics spirit, using conditional distributions of samples of configurations which evolve in time. This allows us to present a truly unifying framework for these methods, and to prove convergence results for certain classes of algorithms. From a numerical viewpoint, a parallel implementation of these methods is very natural, the replicas interacting through the reconstructed free energy. We demonstrate how to improve this parallel implementation by resorting to some selection mechanism on the replicas. This is illustrated by computations on a model system of conformational changes.

Parallelization of elliptic solver for solving 1D Boussinesq model

NASA Astrophysics Data System (ADS)

Tarwidi, D.; Adytia, D.

2018-03-01

In this paper, a parallel implementation of an elliptic solver in solving 1D Boussinesq model is presented. Numerical solution of Boussinesq model is obtained by implementing a staggered grid scheme to continuity, momentum, and elliptic equation of Boussinesq model. Tridiagonal system emerging from numerical scheme of elliptic equation is solved by cyclic reduction algorithm. The parallel implementation of cyclic reduction is executed on multicore processors with shared memory architectures using OpenMP. To measure the performance of parallel program, large number of grids is varied from 28 to 214. Two test cases of numerical experiment, i.e. propagation of solitary and standing wave, are proposed to evaluate the parallel program. The numerical results are verified with analytical solution of solitary and standing wave. The best speedup of solitary and standing wave test cases is about 2.07 with 214 of grids and 1.86 with 213 of grids, respectively, which are executed by using 8 threads. Moreover, the best efficiency of parallel program is 76.2% and 73.5% for solitary and standing wave test cases, respectively.

Distribution Locational Real-Time Pricing Based Smart Building Control and Management

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hao, Jun; Dai, Xiaoxiao; Zhang, Yingchen

This paper proposes an real-virtual parallel computing scheme for smart building operations aiming at augmenting overall social welfare. The University of Denver's campus power grid and Ritchie fitness center is used for demonstrating the proposed approach. An artificial virtual system is built in parallel to the real physical system to evaluate the overall social cost of the building operation based on the social science based working productivity model, numerical experiment based building energy consumption model and the power system based real-time pricing mechanism. Through interactive feedback exchanged between the real and virtual system, enlarged social welfare, including monetary cost reductionmore » and energy saving, as well as working productivity improvements, can be achieved.« less

Plagiarism Detection for Indonesian Language using Winnowing with Parallel Processing

NASA Astrophysics Data System (ADS)

Arifin, Y.; Isa, S. M.; Wulandhari, L. A.; Abdurachman, E.

2018-03-01

The plagiarism has many forms, not only copy paste but include changing passive become active voice, or paraphrasing without appropriate acknowledgment. It happens on all language include Indonesian Language. There are many previous research that related with plagiarism detection in Indonesian Language with different method. But there are still some part that still has opportunity to improve. This research proposed the solution that can improve the plagiarism detection technique that can detect not only copy paste form but more advance than that. The proposed solution is using Winnowing with some addition process in pre-processing stage. With stemming processing in Indonesian Language and generate fingerprint in parallel processing that can saving time processing and produce the plagiarism result on the suspected document.

Symmetric nonnegative matrix factorization: algorithms and applications to probabilistic clustering.

PubMed

He, Zhaoshui; Xie, Shengli; Zdunek, Rafal; Zhou, Guoxu; Cichocki, Andrzej

2011-12-01

Nonnegative matrix factorization (NMF) is an unsupervised learning method useful in various applications including image processing and semantic analysis of documents. This paper focuses on symmetric NMF (SNMF), which is a special case of NMF decomposition. Three parallel multiplicative update algorithms using level 3 basic linear algebra subprograms directly are developed for this problem. First, by minimizing the Euclidean distance, a multiplicative update algorithm is proposed, and its convergence under mild conditions is proved. Based on it, we further propose another two fast parallel methods: α-SNMF and β -SNMF algorithms. All of them are easy to implement. These algorithms are applied to probabilistic clustering. We demonstrate their effectiveness for facial image clustering, document categorization, and pattern clustering in gene expression.

Support of Multidimensional Parallelism in the OpenMP Programming Model

NASA Technical Reports Server (NTRS)

Jin, Hao-Qiang; Jost, Gabriele

2003-01-01

OpenMP is the current standard for shared-memory programming. While providing ease of parallel programming, the OpenMP programming model also has limitations which often effect the scalability of applications. Examples for these limitations are work distribution and point-to-point synchronization among threads. We propose extensions to the OpenMP programming model which allow the user to easily distribute the work in multiple dimensions and synchronize the workflow among the threads. The proposed extensions include four new constructs and the associated runtime library. They do not require changes to the source code and can be implemented based on the existing OpenMP standard. We illustrate the concept in a prototype translator and test with benchmark codes and a cloud modeling code.

Multiple-algorithm parallel fusion of infrared polarization and intensity images based on algorithmic complementarity and synergy

NASA Astrophysics Data System (ADS)

Zhang, Lei; Yang, Fengbao; Ji, Linna; Lv, Sheng

2018-01-01

Diverse image fusion methods perform differently. Each method has advantages and disadvantages compared with others. One notion is that the advantages of different image methods can be effectively combined. A multiple-algorithm parallel fusion method based on algorithmic complementarity and synergy is proposed. First, in view of the characteristics of the different algorithms and difference-features among images, an index vector-based feature-similarity is proposed to define the degree of complementarity and synergy. This proposed index vector is a reliable evidence indicator for algorithm selection. Second, the algorithms with a high degree of complementarity and synergy are selected. Then, the different degrees of various features and infrared intensity images are used as the initial weights for the nonnegative matrix factorization (NMF). This avoids randomness of the NMF initialization parameter. Finally, the fused images of different algorithms are integrated using the NMF because of its excellent data fusing performance on independent features. Experimental results demonstrate that the visual effect and objective evaluation index of the fused images obtained using the proposed method are better than those obtained using traditional methods. The proposed method retains all the advantages that individual fusion algorithms have.

A fiber-coupled displacement measuring interferometer for determination of the posture of a reflective surface

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mao, Shuai; Hu, Peng-Cheng, E-mail: hupc@hit.edu.cn; Ding, Xue-Mei, E-mail: X.M.Ding@outlook.com

A fiber-coupled displacement measuring interferometer capable of determining of the posture of a reflective surface of a measuring mirror is proposed. The newly constructed instrument combines fiber-coupled displacement and angular measurement technologies. The proposed interferometer has advantages of both the fiber-coupled and the spatially beam-separated interferometer. A portable dual-position sensitive detector (PSD)-based unit within this proposed interferometer measures the parallelism of the two source beams to guide the fiber-coupling adjustment. The portable dual PSD-based unit measures not only the pitch and yaw of the retro-reflector but also measures the posture of the reflective surface. The experimental results of displacement calibrationmore » show that the deviations between the proposed interferometer and a reference one, Agilent 5530, at two different common beam directions are both less than ±35 nm, thus verifying the effectiveness of the beam parallelism measurement. The experimental results of angular calibration show that deviations of pitch and yaw with the auto-collimator (as a reference) are less than ±2 arc sec, thus proving the proposed interferometer’s effectiveness for determination of the posture of a reflective surface.« less

Multivariable speed synchronisation for a parallel hybrid electric vehicle drivetrain

NASA Astrophysics Data System (ADS)

Alt, B.; Antritter, F.; Svaricek, F.; Schultalbers, M.

2013-03-01

In this article, a new drivetrain configuration of a parallel hybrid electric vehicle is considered and a novel model-based control design strategy is given. In particular, the control design covers the speed synchronisation task during a restart of the internal combustion engine. The proposed multivariable synchronisation strategy is based on feedforward and decoupled feedback controllers. The performance and the robustness properties of the closed-loop system are illustrated by nonlinear simulation results.

Automatic differentiation for design sensitivity analysis of structural systems using multiple processors

NASA Technical Reports Server (NTRS)

Nguyen, Duc T.; Storaasli, Olaf O.; Qin, Jiangning; Qamar, Ramzi

1994-01-01

An automatic differentiation tool (ADIFOR) is incorporated into a finite element based structural analysis program for shape and non-shape design sensitivity analysis of structural systems. The entire analysis and sensitivity procedures are parallelized and vectorized for high performance computation. Small scale examples to verify the accuracy of the proposed program and a medium scale example to demonstrate the parallel vector performance on multiple CRAY C90 processors are included.

Integrated Task and Data Parallel Programming

NASA Technical Reports Server (NTRS)

Grimshaw, A. S.

1998-01-01

This research investigates the combination of task and data parallel language constructs within a single programming language. There are an number of applications that exhibit properties which would be well served by such an integrated language. Examples include global climate models, aircraft design problems, and multidisciplinary design optimization problems. Our approach incorporates data parallel language constructs into an existing, object oriented, task parallel language. The language will support creation and manipulation of parallel classes and objects of both types (task parallel and data parallel). Ultimately, the language will allow data parallel and task parallel classes to be used either as building blocks or managers of parallel objects of either type, thus allowing the development of single and multi-paradigm parallel applications. 1995 Research Accomplishments In February I presented a paper at Frontiers 1995 describing the design of the data parallel language subset. During the spring I wrote and defended my dissertation proposal. Since that time I have developed a runtime model for the language subset. I have begun implementing the model and hand-coding simple examples which demonstrate the language subset. I have identified an astrophysical fluid flow application which will validate the data parallel language subset. 1996 Research Agenda Milestones for the coming year include implementing a significant portion of the data parallel language subset over the Legion system. Using simple hand-coded methods, I plan to demonstrate (1) concurrent task and data parallel objects and (2) task parallel objects managing both task and data parallel objects. My next steps will focus on constructing a compiler and implementing the fluid flow application with the language. Concurrently, I will conduct a search for a real-world application exhibiting both task and data parallelism within the same program. Additional 1995 Activities During the fall I collaborated with Andrew Grimshaw and Adam Ferrari to write a book chapter which will be included in Parallel Processing in C++ edited by Gregory Wilson. I also finished two courses, Compilers and Advanced Compilers, in 1995. These courses complete my class requirements at the University of Virginia. I have only my dissertation research and defense to complete.

Integrated Task And Data Parallel Programming: Language Design

NASA Technical Reports Server (NTRS)

Grimshaw, Andrew S.; West, Emily A.

1998-01-01

his research investigates the combination of task and data parallel language constructs within a single programming language. There are an number of applications that exhibit properties which would be well served by such an integrated language. Examples include global climate models, aircraft design problems, and multidisciplinary design optimization problems. Our approach incorporates data parallel language constructs into an existing, object oriented, task parallel language. The language will support creation and manipulation of parallel classes and objects of both types (task parallel and data parallel). Ultimately, the language will allow data parallel and task parallel classes to be used either as building blocks or managers of parallel objects of either type, thus allowing the development of single and multi-paradigm parallel applications. 1995 Research Accomplishments In February I presented a paper at Frontiers '95 describing the design of the data parallel language subset. During the spring I wrote and defended my dissertation proposal. Since that time I have developed a runtime model for the language subset. I have begun implementing the model and hand-coding simple examples which demonstrate the language subset. I have identified an astrophysical fluid flow application which will validate the data parallel language subset. 1996 Research Agenda Milestones for the coming year include implementing a significant portion of the data parallel language subset over the Legion system. Using simple hand-coded methods, I plan to demonstrate (1) concurrent task and data parallel objects and (2) task parallel objects managing both task and data parallel objects. My next steps will focus on constructing a compiler and implementing the fluid flow application with the language. Concurrently, I will conduct a search for a real-world application exhibiting both task and data parallelism within the same program m. Additional 1995 Activities During the fall I collaborated with Andrew Grimshaw and Adam Ferrari to write a book chapter which will be included in Parallel Processing in C++ edited by Gregory Wilson. I also finished two courses, Compilers and Advanced Compilers, in 1995. These courses complete my class requirements at the University of Virginia. I have only my dissertation research and defense to complete.

Efficient parallel implicit methods for rotary-wing aerodynamics calculations

NASA Astrophysics Data System (ADS)

Wissink, Andrew M.

Euler/Navier-Stokes Computational Fluid Dynamics (CFD) methods are commonly used for prediction of the aerodynamics and aeroacoustics of modern rotary-wing aircraft. However, their widespread application to large complex problems is limited lack of adequate computing power. Parallel processing offers the potential for dramatic increases in computing power, but most conventional implicit solution methods are inefficient in parallel and new techniques must be adopted to realize its potential. This work proposes alternative implicit schemes for Euler/Navier-Stokes rotary-wing calculations which are robust and efficient in parallel. The first part of this work proposes an efficient parallelizable modification of the Lower Upper-Symmetric Gauss Seidel (LU-SGS) implicit operator used in the well-known Transonic Unsteady Rotor Navier Stokes (TURNS) code. The new hybrid LU-SGS scheme couples a point-relaxation approach of the Data Parallel-Lower Upper Relaxation (DP-LUR) algorithm for inter-processor communication with the Symmetric Gauss Seidel algorithm of LU-SGS for on-processor computations. With the modified operator, TURNS is implemented in parallel using Message Passing Interface (MPI) for communication. Numerical performance and parallel efficiency are evaluated on the IBM SP2 and Thinking Machines CM-5 multi-processors for a variety of steady-state and unsteady test cases. The hybrid LU-SGS scheme maintains the numerical performance of the original LU-SGS algorithm in all cases and shows a good degree of parallel efficiency. It experiences a higher degree of robustness than DP-LUR for third-order upwind solutions. The second part of this work examines use of Krylov subspace iterative solvers for the nonlinear CFD solutions. The hybrid LU-SGS scheme is used as a parallelizable preconditioner. Two iterative methods are tested, Generalized Minimum Residual (GMRES) and Orthogonal s-Step Generalized Conjugate Residual (OSGCR). The Newton method demonstrates good parallel performance on the IBM SP2, with OS-GCR giving slightly better performance than GMRES on large numbers of processors. For steady and quasi-steady calculations, the convergence rate is accelerated but the overall solution time remains about the same as the standard hybrid LU-SGS scheme. For unsteady calculations, however, the Newton method maintains a higher degree of time-accuracy which allows tbe use of larger timesteps and results in CPU savings of 20-35%.

In silico optimization of pharmacokinetic properties and receptor binding affinity simultaneously: a 'parallel progression approach to drug design' applied to β-blockers.

PubMed

Advani, Poonam; Joseph, Blessy; Ambre, Premlata; Pissurlenkar, Raghuvir; Khedkar, Vijay; Iyer, Krishna; Gabhe, Satish; Iyer, Radhakrishnan P; Coutinho, Evans

2016-01-01

The present work exploits the potential of in silico approaches for minimizing attrition of leads in the later stages of drug development. We propose a theoretical approach, wherein 'parallel' information is generated to simultaneously optimize the pharmacokinetics (PK) and pharmacodynamics (PD) of lead candidates. β-blockers, though in use for many years, have suboptimal PKs; hence are an ideal test series for the 'parallel progression approach'. This approach utilizes molecular modeling tools viz. hologram quantitative structure activity relationships, homology modeling, docking, predictive metabolism, and toxicity models. Validated models have been developed for PK parameters such as volume of distribution (log Vd) and clearance (log Cl), which together influence the half-life (t1/2) of a drug. Simultaneously, models for PD in terms of inhibition constant pKi have been developed. Thus, PK and PD properties of β-blockers were concurrently analyzed and after iterative cycling, modifications were proposed that lead to compounds with optimized PK and PD. We report some of the resultant re-engineered β-blockers with improved half-lives and pKi values comparable with marketed β-blockers. These were further analyzed by the docking studies to evaluate their binding poses. Finally, metabolic and toxicological assessment of these molecules was done through in silico methods. The strategy proposed herein has potential universal applicability, and can be used in any drug discovery scenario; provided that the data used is consistent in terms of experimental conditions, endpoints, and methods employed. Thus the 'parallel progression approach' helps to simultaneously fine-tune various properties of the drug and would be an invaluable tool during the drug development process.

Parallel processing optimization strategy based on MapReduce model in cloud storage environment

NASA Astrophysics Data System (ADS)

Cui, Jianming; Liu, Jiayi; Li, Qiuyan

2017-05-01

Currently, a large number of documents in the cloud storage process employed the way of packaging after receiving all the packets. From the local transmitter this stored procedure to the server, packing and unpacking will consume a lot of time, and the transmission efficiency is low as well. A new parallel processing algorithm is proposed to optimize the transmission mode. According to the operation machine graphs model work, using MPI technology parallel execution Mapper and Reducer mechanism. It is good to use MPI technology to implement Mapper and Reducer parallel mechanism. After the simulation experiment of Hadoop cloud computing platform, this algorithm can not only accelerate the file transfer rate, but also shorten the waiting time of the Reducer mechanism. It will break through traditional sequential transmission constraints and reduce the storage coupling to improve the transmission efficiency.

Fast parallel molecular algorithms for DNA-based computation: factoring integers.

PubMed

Chang, Weng-Long; Guo, Minyi; Ho, Michael Shan-Hui

2005-06-01

The RSA public-key cryptosystem is an algorithm that converts input data to an unrecognizable encryption and converts the unrecognizable data back into its original decryption form. The security of the RSA public-key cryptosystem is based on the difficulty of factoring the product of two large prime numbers. This paper demonstrates to factor the product of two large prime numbers, and is a breakthrough in basic biological operations using a molecular computer. In order to achieve this, we propose three DNA-based algorithms for parallel subtractor, parallel comparator, and parallel modular arithmetic that formally verify our designed molecular solutions for factoring the product of two large prime numbers. Furthermore, this work indicates that the cryptosystems using public-key are perhaps insecure and also presents clear evidence of the ability of molecular computing to perform complicated mathematical operations.

Fast forward kinematics algorithm for real-time and high-precision control of the 3-RPS parallel mechanism

NASA Astrophysics Data System (ADS)

Wang, Yue; Yu, Jingjun; Pei, Xu

2018-06-01

A new forward kinematics algorithm for the mechanism of 3-RPS (R: Revolute; P: Prismatic; S: Spherical) parallel manipulators is proposed in this study. This algorithm is primarily based on the special geometric conditions of the 3-RPS parallel mechanism, and it eliminates the errors produced by parasitic motions to improve and ensure accuracy. Specifically, the errors can be less than 10-6. In this method, only the group of solutions that is consistent with the actual situation of the platform is obtained rapidly. This algorithm substantially improves calculation efficiency because the selected initial values are reasonable, and all the formulas in the calculation are analytical. This novel forward kinematics algorithm is well suited for real-time and high-precision control of the 3-RPS parallel mechanism.

A parallel implementation of a multisensor feature-based range-estimation method

NASA Technical Reports Server (NTRS)

Suorsa, Raymond E.; Sridhar, Banavar

1993-01-01

There are many proposed vision based methods to perform obstacle detection and avoidance for autonomous or semi-autonomous vehicles. All methods, however, will require very high processing rates to achieve real time performance. A system capable of supporting autonomous helicopter navigation will need to extract obstacle information from imagery at rates varying from ten frames per second to thirty or more frames per second depending on the vehicle speed. Such a system will need to sustain billions of operations per second. To reach such high processing rates using current technology, a parallel implementation of the obstacle detection/ranging method is required. This paper describes an efficient and flexible parallel implementation of a multisensor feature-based range-estimation algorithm, targeted for helicopter flight, realized on both a distributed-memory and shared-memory parallel computer.

Regional-scale calculation of the LS factor using parallel processing

NASA Astrophysics Data System (ADS)

Liu, Kai; Tang, Guoan; Jiang, Ling; Zhu, A.-Xing; Yang, Jianyi; Song, Xiaodong

2015-05-01

With the increase of data resolution and the increasing application of USLE over large areas, the existing serial implementation of algorithms for computing the LS factor is becoming a bottleneck. In this paper, a parallel processing model based on message passing interface (MPI) is presented for the calculation of the LS factor, so that massive datasets at a regional scale can be processed efficiently. The parallel model contains algorithms for calculating flow direction, flow accumulation, drainage network, slope, slope length and the LS factor. According to the existence of data dependence, the algorithms are divided into local algorithms and global algorithms. Parallel strategy are designed according to the algorithm characters including the decomposition method for maintaining the integrity of the results, optimized workflow for reducing the time taken for exporting the unnecessary intermediate data and a buffer-communication-computation strategy for improving the communication efficiency. Experiments on a multi-node system show that the proposed parallel model allows efficient calculation of the LS factor at a regional scale with a massive dataset.

Parallel computing in genomic research: advances and applications

PubMed Central

Ocaña, Kary; de Oliveira, Daniel

2015-01-01

Today’s genomic experiments have to process the so-called “biological big data” that is now reaching the size of Terabytes and Petabytes. To process this huge amount of data, scientists may require weeks or months if they use their own workstations. Parallelism techniques and high-performance computing (HPC) environments can be applied for reducing the total processing time and to ease the management, treatment, and analyses of this data. However, running bioinformatics experiments in HPC environments such as clouds, grids, clusters, and graphics processing unit requires the expertise from scientists to integrate computational, biological, and mathematical techniques and technologies. Several solutions have already been proposed to allow scientists for processing their genomic experiments using HPC capabilities and parallelism techniques. This article brings a systematic review of literature that surveys the most recently published research involving genomics and parallel computing. Our objective is to gather the main characteristics, benefits, and challenges that can be considered by scientists when running their genomic experiments to benefit from parallelism techniques and HPC capabilities. PMID:26604801

Conical Refraction of Elastic Waves by Anisotropic Metamaterials and Application for Parallel Translation of Elastic Waves.

PubMed

Ahn, Young Kwan; Lee, Hyung Jin; Kim, Yoon Young

2017-08-30

Conical refraction, which is quite well-known in electromagnetic waves, has not been explored well in elastic waves due to the lack of proper natural elastic media. Here, we propose and design a unique anisotropic elastic metamaterial slab that realizes conical refraction for horizontally incident longitudinal or transverse waves; the single-mode wave is split into two oblique coupled longitudinal-shear waves. As an interesting application, we carried out an experiment of parallel translation of an incident elastic wave system through the anisotropic metamaterial slab. The parallel translation can be useful for ultrasonic non-destructive testing of a system hidden by obstacles. While the parallel translation resembles light refraction through a parallel plate without angle deviation between entry and exit beams, this wave behavior cannot be achieved without the engineered metamaterial because an elastic wave incident upon a dissimilar medium is always split at different refraction angles into two different modes, longitudinal and shear.

The generalized accessibility and spectral gap of lower hybrid waves in tokamaks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Takahashi, Hironori

1994-03-01

The generalized accessibility of lower hybrid waves, primarily in the current drive regime of tokamak plasmas, which may include shifting, either upward or downward, of the parallel refractive index (n{sub {parallel}}), is investigated, based upon a cold plasma dispersion relation and various geometrical constraint (G.C.) relations imposed on the behavior of n{sub {parallel}}. It is shown that n{sub {parallel}} upshifting can be bounded and insufficient to bridge a large spectral gap to cause wave damping, depending upon whether the G.C. relation allows the oblique resonance to occur. The traditional n{sub {parallel}} upshifting mechanism caused by the pitch angle of magneticmore » field lines is shown to lead to contradictions with experimental observations. An upshifting mechanism brought about by the density gradient along field lines is proposed, which is not inconsistent with experimental observations, and provides plausible explanations to some unresolved issues of lower hybrid wave theory, including generation of {open_quote}seed electrons.{close_quote}« less

A path-level exact parallelization strategy for sequential simulation

NASA Astrophysics Data System (ADS)

Peredo, Oscar F.; Baeza, Daniel; Ortiz, Julián M.; Herrero, José R.

2018-01-01

Sequential Simulation is a well known method in geostatistical modelling. Following the Bayesian approach for simulation of conditionally dependent random events, Sequential Indicator Simulation (SIS) method draws simulated values for K categories (categorical case) or classes defined by K different thresholds (continuous case). Similarly, Sequential Gaussian Simulation (SGS) method draws simulated values from a multivariate Gaussian field. In this work, a path-level approach to parallelize SIS and SGS methods is presented. A first stage of re-arrangement of the simulation path is performed, followed by a second stage of parallel simulation for non-conflicting nodes. A key advantage of the proposed parallelization method is to generate identical realizations as with the original non-parallelized methods. Case studies are presented using two sequential simulation codes from GSLIB: SISIM and SGSIM. Execution time and speedup results are shown for large-scale domains, with many categories and maximum kriging neighbours in each case, achieving high speedup results in the best scenarios using 16 threads of execution in a single machine.

Parallel computing in genomic research: advances and applications.

PubMed

Ocaña, Kary; de Oliveira, Daniel

2015-01-01

Today's genomic experiments have to process the so-called "biological big data" that is now reaching the size of Terabytes and Petabytes. To process this huge amount of data, scientists may require weeks or months if they use their own workstations. Parallelism techniques and high-performance computing (HPC) environments can be applied for reducing the total processing time and to ease the management, treatment, and analyses of this data. However, running bioinformatics experiments in HPC environments such as clouds, grids, clusters, and graphics processing unit requires the expertise from scientists to integrate computational, biological, and mathematical techniques and technologies. Several solutions have already been proposed to allow scientists for processing their genomic experiments using HPC capabilities and parallelism techniques. This article brings a systematic review of literature that surveys the most recently published research involving genomics and parallel computing. Our objective is to gather the main characteristics, benefits, and challenges that can be considered by scientists when running their genomic experiments to benefit from parallelism techniques and HPC capabilities.

Parallel implementation of a Lagrangian-based model on an adaptive mesh in C++: Application to sea-ice

NASA Astrophysics Data System (ADS)

Samaké, Abdoulaye; Rampal, Pierre; Bouillon, Sylvain; Ólason, Einar

2017-12-01

We present a parallel implementation framework for a new dynamic/thermodynamic sea-ice model, called neXtSIM, based on the Elasto-Brittle rheology and using an adaptive mesh. The spatial discretisation of the model is done using the finite-element method. The temporal discretisation is semi-implicit and the advection is achieved using either a pure Lagrangian scheme or an Arbitrary Lagrangian Eulerian scheme (ALE). The parallel implementation presented here focuses on the distributed-memory approach using the message-passing library MPI. The efficiency and the scalability of the parallel algorithms are illustrated by the numerical experiments performed using up to 500 processor cores of a cluster computing system. The performance obtained by the proposed parallel implementation of the neXtSIM code is shown being sufficient to perform simulations for state-of-the-art sea ice forecasting and geophysical process studies over geographical domain of several millions squared kilometers like the Arctic region.

Parallel Reconstruction Using Null Operations (PRUNO)

PubMed Central

Zhang, Jian; Liu, Chunlei; Moseley, Michael E.

2011-01-01

A novel iterative k-space data-driven technique, namely Parallel Reconstruction Using Null Operations (PRUNO), is presented for parallel imaging reconstruction. In PRUNO, both data calibration and image reconstruction are formulated into linear algebra problems based on a generalized system model. An optimal data calibration strategy is demonstrated by using Singular Value Decomposition (SVD). And an iterative conjugate- gradient approach is proposed to efficiently solve missing k-space samples during reconstruction. With its generalized formulation and precise mathematical model, PRUNO reconstruction yields good accuracy, flexibility, stability. Both computer simulation and in vivo studies have shown that PRUNO produces much better reconstruction quality than autocalibrating partially parallel acquisition (GRAPPA), especially under high accelerating rates. With the aid of PRUO reconstruction, ultra high accelerating parallel imaging can be performed with decent image quality. For example, we have done successful PRUNO reconstruction at a reduction factor of 6 (effective factor of 4.44) with 8 coils and only a few autocalibration signal (ACS) lines. PMID:21604290

An improved non-uniformity correction algorithm and its GPU parallel implementation

NASA Astrophysics Data System (ADS)

Cheng, Kuanhong; Zhou, Huixin; Qin, Hanlin; Zhao, Dong; Qian, Kun; Rong, Shenghui

2018-05-01

The performance of SLP-THP based non-uniformity correction algorithm is seriously affected by the result of SLP filter, which always leads to image blurring and ghosting artifacts. To address this problem, an improved SLP-THP based non-uniformity correction method with curvature constraint was proposed. Here we put forward a new way to estimate spatial low frequency component. First, the details and contours of input image were obtained respectively by minimizing local Gaussian curvature and mean curvature of image surface. Then, the guided filter was utilized to combine these two parts together to get the estimate of spatial low frequency component. Finally, we brought this SLP component into SLP-THP method to achieve non-uniformity correction. The performance of proposed algorithm was verified by several real and simulated infrared image sequences. The experimental results indicated that the proposed algorithm can reduce the non-uniformity without detail losing. After that, a GPU based parallel implementation that runs 150 times faster than CPU was presented, which showed the proposed algorithm has great potential for real time application.

High-speed technique based on a parallel projection correlation procedure for digital image correlation

NASA Astrophysics Data System (ADS)

Zaripov, D. I.; Renfu, Li

2018-05-01

The implementation of high-efficiency digital image correlation methods based on a zero-normalized cross-correlation (ZNCC) procedure for high-speed, time-resolved measurements using a high-resolution digital camera is associated with big data processing and is often time consuming. In order to speed-up ZNCC computation, a high-speed technique based on a parallel projection correlation procedure is proposed. The proposed technique involves the use of interrogation window projections instead of its two-dimensional field of luminous intensity. This simplification allows acceleration of ZNCC computation up to 28.8 times compared to ZNCC calculated directly, depending on the size of interrogation window and region of interest. The results of three synthetic test cases, such as a one-dimensional uniform flow, a linear shear flow and a turbulent boundary-layer flow, are discussed in terms of accuracy. In the latter case, the proposed technique is implemented together with an iterative window-deformation technique. On the basis of the results of the present work, the proposed technique is recommended to be used for initial velocity field calculation, with further correction using more accurate techniques.

Kinematics and dynamics analysis of a quadruped walking robot with parallel leg mechanism

NASA Astrophysics Data System (ADS)

Wang, Hongbo; Sang, Lingfeng; Hu, Xing; Zhang, Dianfan; Yu, Hongnian

2013-09-01

It is desired to require a walking robot for the elderly and the disabled to have large capacity, high stiffness, stability, etc. However, the existing walking robots cannot achieve these requirements because of the weight-payload ratio and simple function. Therefore, Improvement of enhancing capacity and functions of the walking robot is an important research issue. According to walking requirements and combining modularization and reconfigurable ideas, a quadruped/biped reconfigurable walking robot with parallel leg mechanism is proposed. The proposed robot can be used for both a biped and a quadruped walking robot. The kinematics and performance analysis of a 3-UPU parallel mechanism which is the basic leg mechanism of a quadruped walking robot are conducted and the structural parameters are optimized. The results show that performance of the walking robot is optimal when the circumradius R, r of the upper and lower platform of leg mechanism are 161.7 mm, 57.7 mm, respectively. Based on the optimal results, the kinematics and dynamics of the quadruped walking robot in the static walking mode are derived with the application of parallel mechanism and influence coefficient theory, and the optimal coordination distribution of the dynamic load for the quadruped walking robot with over-determinate inputs is analyzed, which solves dynamic load coupling caused by the branches’ constraint of the robot in the walk process. Besides laying a theoretical foundation for development of the prototype, the kinematics and dynamics studies on the quadruped walking robot also boost the theoretical research of the quadruped walking and the practical applications of parallel mechanism.

Why not private health insurance? 2. Actuarial principles meet provider dreams

PubMed Central

Deber, R; Gildiner, A; Baranek, P

1999-01-01

What do insurers and employers feel about proposals to expand Canadian health care financing through private insurance, in either a parallel stream or a supplementary tier? The authors conducted 10 semistructured, open-ended interviews in the autumn and early winter of 1996 with representatives of the insurance industry and benefits managers working with large employers; respondents were identified using a snowball sampling technique. The respondents felt that proposals for parallel private plans within a competitive market are incompatible with insurance principles, as long as a well-functioning and relatively comprehensive public system continues to exist; the maintenance of a strong public system was both socially and economically desirable. With the exception of serving the niche market for the private management of return-to-work strategies, respondents showed little interest in providing parallel coverage. They were receptive to a larger role for supplementary insurance but cautioned that they are not willing to cover all delisted services. As business executives they stated that they are willing to insure only services and clients that will be profitable. PMID:10497614

Vectorial finite elements for solving the radiative transfer equation

NASA Astrophysics Data System (ADS)

Badri, M. A.; Jolivet, P.; Rousseau, B.; Le Corre, S.; Digonnet, H.; Favennec, Y.

2018-06-01

The discrete ordinate method coupled with the finite element method is often used for the spatio-angular discretization of the radiative transfer equation. In this paper we attempt to improve upon such a discretization technique. Instead of using standard finite elements, we reformulate the radiative transfer equation using vectorial finite elements. In comparison to standard finite elements, this reformulation yields faster timings for the linear system assemblies, as well as for the solution phase when using scattering media. The proposed vectorial finite element discretization for solving the radiative transfer equation is cross-validated against a benchmark problem available in literature. In addition, we have used the method of manufactured solutions to verify the order of accuracy for our discretization technique within different absorbing, scattering, and emitting media. For solving large problems of radiation on parallel computers, the vectorial finite element method is parallelized using domain decomposition. The proposed domain decomposition method scales on large number of processes, and its performance is unaffected by the changes in optical thickness of the medium. Our parallel solver is used to solve a large scale radiative transfer problem of the Kelvin-cell radiation.

GPURFSCREEN: a GPU based virtual screening tool using random forest classifier.

PubMed

Jayaraj, P B; Ajay, Mathias K; Nufail, M; Gopakumar, G; Jaleel, U C A

2016-01-01

In-silico methods are an integral part of modern drug discovery paradigm. Virtual screening, an in-silico method, is used to refine data models and reduce the chemical space on which wet lab experiments need to be performed. Virtual screening of a ligand data model requires large scale computations, making it a highly time consuming task. This process can be speeded up by implementing parallelized algorithms on a Graphical Processing Unit (GPU). Random Forest is a robust classification algorithm that can be employed in the virtual screening. A ligand based virtual screening tool (GPURFSCREEN) that uses random forests on GPU systems has been proposed and evaluated in this paper. This tool produces optimized results at a lower execution time for large bioassay data sets. The quality of results produced by our tool on GPU is same as that on a regular serial environment. Considering the magnitude of data to be screened, the parallelized virtual screening has a significantly lower running time at high throughput. The proposed parallel tool outperforms its serial counterpart by successfully screening billions of molecules in training and prediction phases.

Equivalent circuit for the characterization of the resonance mode in piezoelectric systems

NASA Astrophysics Data System (ADS)

Fernández-Afonso, Y.; García-Zaldívar, O.; Calderón-Piñar, F.

2015-12-01

The impedance properties in polarized piezoelectric can be described by electric equivalent circuits. The classic circuit used in the literature to describe real systems is formed by one resistor (R), one inductance (L) and one capacitance C connected in series and one capacity (C0) connected in parallel with the formers. Nevertheless, the equation that describe the resonance and anti-resonance frequencies depends on a complex manner of R, L, C and C0. In this work is proposed a simpler model formed by one inductance (L) and one capacity (C) in series; one capacity (C0) in parallel; one resistor (RP) in parallel and one resistor (RS) in series with other components. Unlike the traditional circuit, the equivalent circuit elements in the proposed model can be simply determined by knowing the experimental values of the resonance frequency fr, anti-resonance frequency fa, impedance module at resonance frequency |Zr|, impedance module at anti-resonance frequency |Za| and low frequency capacitance C0, without fitting the impedance experimental data to the obtained equation.

Using pre-distorted PAM-4 signal and parallel resistance circuit to enhance the passive solar cell based visible light communication

NASA Astrophysics Data System (ADS)

Wang, Hao-Yu; Wu, Jhao-Ting; Chow, Chi-Wai; Liu, Yang; Yeh, Chien-Hung; Liao, Xin-Lan; Lin, Kun-Hsien; Wu, Wei-Liang; Chen, Yi-Yuan

2018-01-01

Using solar cell (or photovoltaic cell) for visible light communication (VLC) is attractive. Apart from acting as a VLC receiver (Rx), the solar cell can provide energy harvesting. This can be used in self-powered smart devices, particularly in the emerging ;Internet of Things (IoT); networks. Here, we propose and demonstrate for the first time using pre-distortion pulse-amplitude-modulation (PAM)-4 signal and parallel resistance circuit to enhance the transmission performance of solar cell Rx based VLC. Pre-distortion is a simple non-adaptive equalization technique that can significantly mitigate the slow charging and discharging of the solar cell. The equivalent circuit model of the solar cell and the operation of using parallel resistance to increase the bandwidth of the solar cell are discussed. By using the proposed schemes, the experimental results show that the data rate of the solar cell Rx based VLC can increase from 20 kbit/s to 1.25 Mbit/s (about 60 times) with the bit error-rate (BER) satisfying the 7% forward error correction (FEC) limit.

Why not private health insurance? 2. Actuarial principles meet provider dreams.

PubMed

Deber, R; Gildiner, A; Baranek, P

1999-09-07

What do insurers and employers feel about proposals to expand Canadian health care financing through private insurance, in either a parallel stream or a supplementary tier? The authors conducted 10 semistructured, open-ended interviews in the autumn and early winter of 1996 with representatives of the insurance industry and benefits managers working with large employers; respondents were identified using a snowball sampling technique. The respondents felt that proposals for parallel private plans within a competitive market are incompatible with insurance principles, as long as a well-functioning and relatively comprehensive public system continues to exist; the maintenance of a strong public system was both socially and economically desirable. With the exception of serving the niche market for the private management of return-to-work strategies, respondents showed little interest in providing parallel coverage. They were receptive to a larger role for supplementary insurance but cautioned that they are not willing to cover all delisted services. As business executives they stated that they are willing to insure only services and clients that will be profitable.

77 FR 36964 - Approval and Promulgation of Implementation Plans; Texas; Revisions to the New Source Review (NSR...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-20

...EPA is proposing to approve revisions to the SIP for the State of Texas that relate to antibacksliding of Major NSR SIP Requirements for the one-hour ozone NAAQS; Major NNSR SIP requirements for the 1997 eight-hour ozone NAAQS; Major NSR Reform Program with Plantwide Applicability Limit (PAL) provisions; and non-PAL aspects of the Major NSR SIP requirements. EPA proposes to find that these changes to the Texas SIP comply with the Federal Clean Air Act (the Act or CAA) and EPA regulations and are consistent with EPA policies. Texas submitted revisions to these programs on June 10, 2005, and February 1, 2006. EPA disapproved these SIP revisions on September 15, 2010 (75 FR 56424). In response to the 2010 disapproval, Texas submitted revisions to these programs in two separate SIP submittals on March 11, 2011. These SIP submittals include resubmittal of the rules that were previously submitted June 10, 2005, and February 1, 2006, and subsequently disapproved by EPA on September 15, 2010. On February 22, 2012, Texas proposed further revisions to the NSR Reform Program to further clarify and ensure compliance with Federal requirements relating to NSR Reform. On May 3, 2012, Texas provided a letter to EPA which requested that EPA parallel process the revisions proposed February 22, 2012, and included a demonstration showing how its submitted rules are at least as stringent as the Federal NSR Reform Program. Texas has requested that EPA parallel process the revisions proposed February 22, 2012, and consider the May 3, 2012, letter in the review of the March 11, 2011, SIP submittals. Today, EPA is proposing to find that the March 11, 2011, SIP submittals; the February 22, 2012, proposed revisions; and the May 3, 2012, letter, address each of the grounds for EPA's September 15, 2010, disapproval and other issues related to the Texas NSR Reform revisions as identified later. Accordingly, EPA proposes to approve these two March 11, 2011, revisions; the February 22, 2012, proposed revisions for which Texas has requested parallel processing; and the May 3, 2012, letter as part of the Texas NSR SIP. EPA is proposing this action under section 110 and parts C and D of the Act.

B-MIC: An Ultrafast Three-Level Parallel Sequence Aligner Using MIC.

PubMed

Cui, Yingbo; Liao, Xiangke; Zhu, Xiaoqian; Wang, Bingqiang; Peng, Shaoliang

2016-03-01

Sequence alignment is the central process for sequence analysis, where mapping raw sequencing data to reference genome. The large amount of data generated by NGS is far beyond the process capabilities of existing alignment tools. Consequently, sequence alignment becomes the bottleneck of sequence analysis. Intensive computing power is required to address this challenge. Intel recently announced the MIC coprocessor, which can provide massive computing power. The Tianhe-2 is the world's fastest supercomputer now equipped with three MIC coprocessors each compute node. A key feature of sequence alignment is that different reads are independent. Considering this property, we proposed a MIC-oriented three-level parallelization strategy to speed up BWA, a widely used sequence alignment tool, and developed our ultrafast parallel sequence aligner: B-MIC. B-MIC contains three levels of parallelization: firstly, parallelization of data IO and reads alignment by a three-stage parallel pipeline; secondly, parallelization enabled by MIC coprocessor technology; thirdly, inter-node parallelization implemented by MPI. In this paper, we demonstrate that B-MIC outperforms BWA by a combination of those techniques using Inspur NF5280M server and the Tianhe-2 supercomputer. To the best of our knowledge, B-MIC is the first sequence alignment tool to run on Intel MIC and it can achieve more than fivefold speedup over the original BWA while maintaining the alignment precision.

Decentralized Interleaving of Paralleled Dc-Dc Buck Converters: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Brian B; Rodriguez, Miguel; Sinha, Mohit

We present a decentralized control strategy that yields switch interleaving among parallel connected dc-dc buck converters without communication. The proposed method is based on the digital implementation of the dynamics of a nonlinear oscillator circuit as the controller. Each controller is fully decentralized, i.e., it only requires the locally measured output current to synthesize the pulse width modulation (PWM) carrier waveform. By virtue of the intrinsic electrical coupling between converters, the nonlinear oscillator-based controllers converge to an interleaved state with uniform phase-spacing across PWM carriers. To the knowledge of the authors, this work represents the first fully decentralized strategy formore » switch interleaving of paralleled dc-dc buck converters.« less

Differentiating social and personal power: opposite effects on stereotyping, but parallel effects on behavioral approach tendencies.

PubMed

Lammers, Joris; Stoker, Janka I; Stapel, Diederik A

2009-12-01

How does power affect behavior? We posit that this depends on the type of power. We distinguish between social power (power over other people) and personal power (freedom from other people) and argue that these two types of power have opposite associations with independence and interdependence. We propose that when the distinction between independence and interdependence is relevant, social power and personal power will have opposite effects; however, they will have parallel effects when the distinction is irrelevant. In two studies (an experimental study and a large field study), we demonstrate this by showing that social power and personal power have opposite effects on stereotyping, but parallel effects on behavioral approach.

On some methods for improving time of reachability sets computation for the dynamic system control problem

NASA Astrophysics Data System (ADS)

Zimovets, Artem; Matviychuk, Alexander; Ushakov, Vladimir

2016-12-01

The paper presents two different approaches to reduce the time of computer calculation of reachability sets. First of these two approaches use different data structures for storing the reachability sets in the computer memory for calculation in single-threaded mode. Second approach is based on using parallel algorithms with reference to the data structures from the first approach. Within the framework of this paper parallel algorithm of approximate reachability set calculation on computer with SMP-architecture is proposed. The results of numerical modelling are presented in the form of tables which demonstrate high efficiency of parallel computing technology and also show how computing time depends on the used data structure.

State-plane analysis of parallel resonant converter

NASA Technical Reports Server (NTRS)

Oruganti, R.; Lee, F. C.

1985-01-01

A method for analyzing the complex operation of a parallel resonant converter is developed, utilizing graphical state-plane techniques. The comprehensive mode analysis uncovers, for the first time, the presence of other complex modes besides the continuous conduction mode and the discontinuous conduction mode and determines their theoretical boundaries. Based on the insight gained from the analysis, a novel, high-frequency resonant buck converter is proposed. The voltage conversion ratio of the new converter is almost independent of load.

On high-latitude convection field inhomogeneities, parallel electric fields and inverted-V precipitation events

NASA Technical Reports Server (NTRS)

Lennartsson, W.

1977-01-01

A simple model of a static electric field with a component parallel to the magnetic field is proposed for calculating the electric field and current distributions at various altitudes when the horizontal distribution of the convection electric field is given at a certain altitude above the auroral ionosphere. The model is shown to be compatible with satellite observations of inverted-V electron precipitation structures and associated irregularities in the convection electric field.

Parallel AFSA algorithm accelerating based on MIC architecture

NASA Astrophysics Data System (ADS)

Zhou, Junhao; Xiao, Hong; Huang, Yifan; Li, Yongzhao; Xu, Yuanrui

2017-05-01

Analysis AFSA past for solving the traveling salesman problem, the algorithm efficiency is often a big problem, and the algorithm processing method, it does not fully responsive to the characteristics of the traveling salesman problem to deal with, and therefore proposes a parallel join improved AFSA process. The simulation with the current TSP known optimal solutions were analyzed, the results showed that the AFSA iterations improved less, on the MIC cards doubled operating efficiency, efficiency significantly.

Parallel processing implementations of a contextual classifier for multispectral remote sensing data

NASA Technical Reports Server (NTRS)

Siegel, H. J.; Swain, P. H.; Smith, B. W.

1980-01-01

Contextual classifiers are being developed as a method to exploit the spatial/spectral context of a pixel to achieve accurate classification. Classification algorithms such as the contextual classifier typically require large amounts of computation time. One way to reduce the execution time of these tasks is through the use of parallelism. The applicability of the CDC flexible processor system and of a proposed multimicroprocessor system (PASM) for implementing contextual classifiers is examined.

LORAKS makes better SENSE: Phase-constrained partial fourier SENSE reconstruction without phase calibration.

PubMed

Kim, Tae Hyung; Setsompop, Kawin; Haldar, Justin P

2017-03-01

Parallel imaging and partial Fourier acquisition are two classical approaches for accelerated MRI. Methods that combine these approaches often rely on prior knowledge of the image phase, but the need to obtain this prior information can place practical restrictions on the data acquisition strategy. In this work, we propose and evaluate SENSE-LORAKS, which enables combined parallel imaging and partial Fourier reconstruction without requiring prior phase information. The proposed formulation is based on combining the classical SENSE model for parallel imaging data with the more recent LORAKS framework for MR image reconstruction using low-rank matrix modeling. Previous LORAKS-based methods have successfully enabled calibrationless partial Fourier parallel MRI reconstruction, but have been most successful with nonuniform sampling strategies that may be hard to implement for certain applications. By combining LORAKS with SENSE, we enable highly accelerated partial Fourier MRI reconstruction for a broader range of sampling trajectories, including widely used calibrationless uniformly undersampled trajectories. Our empirical results with retrospectively undersampled datasets indicate that when SENSE-LORAKS reconstruction is combined with an appropriate k-space sampling trajectory, it can provide substantially better image quality at high-acceleration rates relative to existing state-of-the-art reconstruction approaches. The SENSE-LORAKS framework provides promising new opportunities for highly accelerated MRI. Magn Reson Med 77:1021-1035, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Multicoil resonance-based parallel array for smart wireless power delivery.

PubMed

Mirbozorgi, S A; Sawan, M; Gosselin, B

2013-01-01

This paper presents a novel resonance-based multicoil structure as a smart power surface to wirelessly power up apparatus like mobile, animal headstage, implanted devices, etc. The proposed powering system is based on a 4-coil resonance-based inductive link, the resonance coil of which is formed by an array of several paralleled coils as a smart power transmitter. The power transmitter employs simple circuit connections and includes only one power driver circuit per multicoil resonance-based array, which enables higher power transfer efficiency and power delivery to the load. The power transmitted by the driver circuit is proportional to the load seen by the individual coil in the array. Thus, the transmitted power scales with respect to the load of the electric/electronic system to power up, and does not divide equally over every parallel coils that form the array. Instead, only the loaded coils of the parallel array transmit significant part of total transmitted power to the receiver. Such adaptive behavior enables superior power, size and cost efficiency then other solutions since it does not need to use complex detection circuitry to find the location of the load. The performance of the proposed structure is verified by measurement results. Natural load detection and covering 4 times bigger area than conventional topologies with a power transfer efficiency of 55% are the novelties of presented paper.

Optimal resonance configuration for ultrasonic wireless power transmission to millimeter-sized biomedical implants.

PubMed

Miao Meng; Kiani, Mehdi

2016-08-01

In order to achieve efficient wireless power transmission (WPT) to biomedical implants with millimeter (mm) dimensions, ultrasonic WPT links have recently been proposed. Operating both transmitter (Tx) and receiver (Rx) ultrasonic transducers at their resonance frequency (fr) is key in improving power transmission efficiency (PTE). In this paper, different resonance configurations for Tx and Rx transducers, including series and parallel resonance, have been studied to help the designers of ultrasonic WPT links to choose the optimal resonance configuration for Tx and Rx that maximizes PTE. The geometries for disk-shaped transducers of four different sets of links, operating at series-series, series-parallel, parallel-series, and parallel-parallel resonance configurations in Tx and Rx, have been found through finite-element method (FEM) simulation tools for operation at fr of 1.4 MHz. Our simulation results suggest that operating the Tx transducer with parallel resonance increases PTE, while the resonance configuration of the mm-sized Rx transducer highly depends on the load resistance, Rl. For applications that involve large Rl in the order of tens of kΩ, a parallel resonance for a mm-sized Rx leads to higher PTE, while series resonance is preferred for Rl in the order of several kΩ and below.

Parallelized multi–graphics processing unit framework for high-speed Gabor-domain optical coherence microscopy

PubMed Central

Tankam, Patrice; Santhanam, Anand P.; Lee, Kye-Sung; Won, Jungeun; Canavesi, Cristina; Rolland, Jannick P.

2014-01-01

Abstract. Gabor-domain optical coherence microscopy (GD-OCM) is a volumetric high-resolution technique capable of acquiring three-dimensional (3-D) skin images with histological resolution. Real-time image processing is needed to enable GD-OCM imaging in a clinical setting. We present a parallelized and scalable multi-graphics processing unit (GPU) computing framework for real-time GD-OCM image processing. A parallelized control mechanism was developed to individually assign computation tasks to each of the GPUs. For each GPU, the optimal number of amplitude-scans (A-scans) to be processed in parallel was selected to maximize GPU memory usage and core throughput. We investigated five computing architectures for computational speed-up in processing 1000×1000 A-scans. The proposed parallelized multi-GPU computing framework enables processing at a computational speed faster than the GD-OCM image acquisition, thereby facilitating high-speed GD-OCM imaging in a clinical setting. Using two parallelized GPUs, the image processing of a 1×1×0.6  mm3 skin sample was performed in about 13 s, and the performance was benchmarked at 6.5 s with four GPUs. This work thus demonstrates that 3-D GD-OCM data may be displayed in real-time to the examiner using parallelized GPU processing. PMID:24695868

Parallelized multi-graphics processing unit framework for high-speed Gabor-domain optical coherence microscopy.

PubMed

Tankam, Patrice; Santhanam, Anand P; Lee, Kye-Sung; Won, Jungeun; Canavesi, Cristina; Rolland, Jannick P

2014-07-01

Gabor-domain optical coherence microscopy (GD-OCM) is a volumetric high-resolution technique capable of acquiring three-dimensional (3-D) skin images with histological resolution. Real-time image processing is needed to enable GD-OCM imaging in a clinical setting. We present a parallelized and scalable multi-graphics processing unit (GPU) computing framework for real-time GD-OCM image processing. A parallelized control mechanism was developed to individually assign computation tasks to each of the GPUs. For each GPU, the optimal number of amplitude-scans (A-scans) to be processed in parallel was selected to maximize GPU memory usage and core throughput. We investigated five computing architectures for computational speed-up in processing 1000×1000 A-scans. The proposed parallelized multi-GPU computing framework enables processing at a computational speed faster than the GD-OCM image acquisition, thereby facilitating high-speed GD-OCM imaging in a clinical setting. Using two parallelized GPUs, the image processing of a 1×1×0.6  mm3 skin sample was performed in about 13 s, and the performance was benchmarked at 6.5 s with four GPUs. This work thus demonstrates that 3-D GD-OCM data may be displayed in real-time to the examiner using parallelized GPU processing.

Decoupling Principle Analysis and Development of a Parallel Three-Dimensional Force Sensor

PubMed Central

Zhao, Yanzhi; Jiao, Leihao; Weng, Dacheng; Zhang, Dan; Zheng, Rencheng

2016-01-01

In the development of the multi-dimensional force sensor, dimension coupling is the ubiquitous factor restricting the improvement of the measurement accuracy. To effectively reduce the influence of dimension coupling on the parallel multi-dimensional force sensor, a novel parallel three-dimensional force sensor is proposed using a mechanical decoupling principle, and the influence of the friction on dimension coupling is effectively reduced by making the friction rolling instead of sliding friction. In this paper, the mathematical model is established by combining with the structure model of the parallel three-dimensional force sensor, and the modeling and analysis of mechanical decoupling are carried out. The coupling degree (ε) of the designed sensor is defined and calculated, and the calculation results show that the mechanical decoupling parallel structure of the sensor possesses good decoupling performance. A prototype of the parallel three-dimensional force sensor was developed, and FEM analysis was carried out. The load calibration and data acquisition experiment system are built, and then calibration experiments were done. According to the calibration experiments, the measurement accuracy is less than 2.86% and the coupling accuracy is less than 3.02%. The experimental results show that the sensor system possesses high measuring accuracy, which provides a basis for the applied research of the parallel multi-dimensional force sensor. PMID:27649194

Proposed hardware architectures of particle filter for object tracking

NASA Astrophysics Data System (ADS)

Abd El-Halym, Howida A.; Mahmoud, Imbaby Ismail; Habib, SED

2012-12-01

In this article, efficient hardware architectures for particle filter (PF) are presented. We propose three different architectures for Sequential Importance Resampling Filter (SIRF) implementation. The first architecture is a two-step sequential PF machine, where particle sampling, weight, and output calculations are carried out in parallel during the first step followed by sequential resampling in the second step. For the weight computation step, a piecewise linear function is used instead of the classical exponential function. This decreases the complexity of the architecture without degrading the results. The second architecture speeds up the resampling step via a parallel, rather than a serial, architecture. This second architecture targets a balance between hardware resources and the speed of operation. The third architecture implements the SIRF as a distributed PF composed of several processing elements and central unit. All the proposed architectures are captured using VHDL synthesized using Xilinx environment, and verified using the ModelSim simulator. Synthesis results confirmed the resource reduction and speed up advantages of our architectures.

LDMOS Channel Thermometer Based on a Thermal Resistance Sensor for Balancing Temperature in Monolithic Power ICs.

PubMed

Lin, Tingyou; Ho, Yingchieh; Su, Chauchin

2017-06-15

This paper presents a method of thermal balancing for monolithic power integrated circuits (ICs). An on-chip temperature monitoring sensor that consists of a poly resistor strip in each of multiple parallel MOSFET banks is developed. A temperature-to-frequency converter (TFC) is proposed to quantize on-chip temperature. A pulse-width-modulation (PWM) methodology is developed to balance the channel temperature based on the quantization. The modulated PWM pulses control the hottest of metal-oxide-semiconductor field-effect transistor (MOSFET) bank to reduce its power dissipation and heat generation. A test chip with eight parallel MOSFET banks is fabricated in TSMC 0.25 μm HV BCD processes, and total area is 900 × 914 μm². The maximal temperature variation among the eight banks can reduce to 2.8 °C by the proposed thermal balancing system from 9.5 °C with 1.5 W dissipation. As a result, our proposed system improves the lifetime of a power MOSFET by 20%.

LDMOS Channel Thermometer Based on a Thermal Resistance Sensor for Balancing Temperature in Monolithic Power ICs

PubMed Central

Lin, Tingyou; Ho, Yingchieh; Su, Chauchin

2017-01-01

This paper presents a method of thermal balancing for monolithic power integrated circuits (ICs). An on-chip temperature monitoring sensor that consists of a poly resistor strip in each of multiple parallel MOSFET banks is developed. A temperature-to-frequency converter (TFC) is proposed to quantize on-chip temperature. A pulse-width-modulation (PWM) methodology is developed to balance the channel temperature based on the quantization. The modulated PWM pulses control the hottest of metal-oxide-semiconductor field-effect transistor (MOSFET) bank to reduce its power dissipation and heat generation. A test chip with eight parallel MOSFET banks is fabricated in TSMC 0.25 μm HV BCD processes, and total area is 900 × 914 μm2. The maximal temperature variation among the eight banks can reduce to 2.8 °C by the proposed thermal balancing system from 9.5 °C with 1.5 W dissipation. As a result, our proposed system improves the lifetime of a power MOSFET by 20%. PMID:28617346

Modeling and simulation performance of photovoltaic system integration battery and supercapacitor paralellization of MPPT prototipe for solar vehicle

NASA Astrophysics Data System (ADS)

Ajiatmo, Dwi; Robandi, Imam

2017-03-01

This paper proposes a control scheme photovoltaic, battery and super capacitor connected in parallel for use in a solar vehicle. Based on the features of battery charging, the control scheme consists of three modes, namely, mode dynamic irradian, constant load mode and constant voltage charging mode. The shift of the three modes can be realized by controlling the duty cycle of the mosffet Boost converter system. Meanwhile, the high voltage which is more suitable for the application can be obtained. Compared with normal charging method with parallel connected current limiting detention and charging method with dynamic irradian mode, constant load mode and constant voltage charging mode, the control scheme is proposed to shorten the charging time and increase the use of power generated from the PV array. From the simulation results and analysis conducted to determine the performance of the system in state transient and steady-state by using simulation software Matlab / Simulink. Response simulation results demonstrate the suitability of the proposed concept.

Multi-Sensor Data Fusion Identification for Shearer Cutting Conditions Based on Parallel Quasi-Newton Neural Networks and the Dempster-Shafer Theory.

PubMed

Si, Lei; Wang, Zhongbin; Liu, Xinhua; Tan, Chao; Xu, Jing; Zheng, Kehong

2015-11-13

In order to efficiently and accurately identify the cutting condition of a shearer, this paper proposed an intelligent multi-sensor data fusion identification method using the parallel quasi-Newton neural network (PQN-NN) and the Dempster-Shafer (DS) theory. The vibration acceleration signals and current signal of six cutting conditions were collected from a self-designed experimental system and some special state features were extracted from the intrinsic mode functions (IMFs) based on the ensemble empirical mode decomposition (EEMD). In the experiment, three classifiers were trained and tested by the selected features of the measured data, and the DS theory was used to combine the identification results of three single classifiers. Furthermore, some comparisons with other methods were carried out. The experimental results indicate that the proposed method performs with higher detection accuracy and credibility than the competing algorithms. Finally, an industrial application example in the fully mechanized coal mining face was demonstrated to specify the effect of the proposed system.

76 FR 5646 - Self-Regulatory Organizations; NYSE Amex LLC; Order Granting Approval of Proposed Rule Change...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-01

... strike prices and non-parallel strikes in different expiration months of the same issue. The Commission... Listing of Options Series With $1 Strike Prices January 25, 2011. I. Introduction On November 24, 2010... Strike Price Program. The proposed rule change was published for comment in the Federal Register on...

Parallel processing of genomics data

NASA Astrophysics Data System (ADS)

Agapito, Giuseppe; Guzzi, Pietro Hiram; Cannataro, Mario

2016-10-01

The availability of high-throughput experimental platforms for the analysis of biological samples, such as mass spectrometry, microarrays and Next Generation Sequencing, have made possible to analyze a whole genome in a single experiment. Such platforms produce an enormous volume of data per single experiment, thus the analysis of this enormous flow of data poses several challenges in term of data storage, preprocessing, and analysis. To face those issues, efficient, possibly parallel, bioinformatics software needs to be used to preprocess and analyze data, for instance to highlight genetic variation associated with complex diseases. In this paper we present a parallel algorithm for the parallel preprocessing and statistical analysis of genomics data, able to face high dimension of data and resulting in good response time. The proposed system is able to find statistically significant biological markers able to discriminate classes of patients that respond to drugs in different ways. Experiments performed on real and synthetic genomic datasets show good speed-up and scalability.

Design Method of Digital Optimal Control Scheme and Multiple Paralleled Bridge Type Current Amplifier for Generating Gradient Magnetic Fields in MRI Systems

NASA Astrophysics Data System (ADS)

Watanabe, Shuji; Takano, Hiroshi; Fukuda, Hiroya; Hiraki, Eiji; Nakaoka, Mutsuo

This paper deals with a digital control scheme of multiple paralleled high frequency switching current amplifier with four-quadrant chopper for generating gradient magnetic fields in MRI (Magnetic Resonance Imaging) systems. In order to track high precise current pattern in Gradient Coils (GC), the proposal current amplifier cancels the switching current ripples in GC with each other and designed optimum switching gate pulse patterns without influences of the large filter current ripple amplitude. The optimal control implementation and the linear control theory in GC current amplifiers have affinity to each other with excellent characteristics. The digital control system can be realized easily through the digital control implementation, DSPs or microprocessors. Multiple-parallel operational microprocessors realize two or higher paralleled GC current pattern tracking amplifier with optimal control design and excellent results are given for improving the image quality of MRI systems.

A parallel computational model for GATE simulations.

PubMed

Rannou, F R; Vega-Acevedo, N; El Bitar, Z

2013-12-01

GATE/Geant4 Monte Carlo simulations are computationally demanding applications, requiring thousands of processor hours to produce realistic results. The classical strategy of distributing the simulation of individual events does not apply efficiently for Positron Emission Tomography (PET) experiments, because it requires a centralized coincidence processing and large communication overheads. We propose a parallel computational model for GATE that handles event generation and coincidence processing in a simple and efficient way by decentralizing event generation and processing but maintaining a centralized event and time coordinator. The model is implemented with the inclusion of a new set of factory classes that can run the same executable in sequential or parallel mode. A Mann-Whitney test shows that the output produced by this parallel model in terms of number of tallies is equivalent (but not equal) to its sequential counterpart. Computational performance evaluation shows that the software is scalable and well balanced. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Improved CDMA Performance Using Parallel Interference Cancellation

NASA Technical Reports Server (NTRS)

Simon, Marvin; Divsalar, Dariush

1995-01-01

This report considers a general parallel interference cancellation scheme that significantly reduces the degradation effect of user interference but with a lesser implementation complexity than the maximum-likelihood technique. The scheme operates on the fact that parallel processing simultaneously removes from each user the interference produced by the remaining users accessing the channel in an amount proportional to their reliability. The parallel processing can be done in multiple stages. The proposed scheme uses tentative decision devices with different optimum thresholds at the multiple stages to produce the most reliably received data for generation and cancellation of user interference. The 1-stage interference cancellation is analyzed for three types of tentative decision devices, namely, hard, null zone, and soft decision, and two types of user power distribution, namely, equal and unequal powers. Simulation results are given for a multitude of different situations, in particular, those cases for which the analysis is too complex.

Simulating electron wave dynamics in graphene superlattices exploiting parallel processing advantages

NASA Astrophysics Data System (ADS)

Rodrigues, Manuel J.; Fernandes, David E.; Silveirinha, Mário G.; Falcão, Gabriel

2018-01-01

This work introduces a parallel computing framework to characterize the propagation of electron waves in graphene-based nanostructures. The electron wave dynamics is modeled using both "microscopic" and effective medium formalisms and the numerical solution of the two-dimensional massless Dirac equation is determined using a Finite-Difference Time-Domain scheme. The propagation of electron waves in graphene superlattices with localized scattering centers is studied, and the role of the symmetry of the microscopic potential in the electron velocity is discussed. The computational methodologies target the parallel capabilities of heterogeneous multi-core CPU and multi-GPU environments and are built with the OpenCL parallel programming framework which provides a portable, vendor agnostic and high throughput-performance solution. The proposed heterogeneous multi-GPU implementation achieves speedup ratios up to 75x when compared to multi-thread and multi-core CPU execution, reducing simulation times from several hours to a couple of minutes.

Evaluation of a parallel implementation of the learning portion of the backward error propagation neural network: experiments in artifact identification.

PubMed Central

Sittig, D. F.; Orr, J. A.

1991-01-01

Various methods have been proposed in an attempt to solve problems in artifact and/or alarm identification including expert systems, statistical signal processing techniques, and artificial neural networks (ANN). ANNs consist of a large number of simple processing units connected by weighted links. To develop truly robust ANNs, investigators are required to train their networks on huge training data sets, requiring enormous computing power. We implemented a parallel version of the backward error propagation neural network training algorithm in the widely portable parallel programming language C-Linda. A maximum speedup of 4.06 was obtained with six processors. This speedup represents a reduction in total run-time from approximately 6.4 hours to 1.5 hours. We conclude that use of the master-worker model of parallel computation is an excellent method for obtaining speedups in the backward error propagation neural network training algorithm. PMID:1807607

Mantle flow through a tear in the Nazca slab inferred from shear wave splitting

NASA Astrophysics Data System (ADS)

Lynner, Colton; Anderson, Megan L.; Portner, Daniel E.; Beck, Susan L.; Gilbert, Hersh

2017-07-01

A tear in the subducting Nazca slab is located between the end of the Pampean flat slab and normally subducting oceanic lithosphere. Tomographic studies suggest mantle material flows through this opening. The best way to probe this hypothesis is through observations of seismic anisotropy, such as shear wave splitting. We examine patterns of shear wave splitting using data from two seismic deployments in Argentina that lay updip of the slab tear. We observe a simple pattern of plate-motion-parallel fast splitting directions, indicative of plate-motion-parallel mantle flow, beneath the majority of the stations. Our observed splitting contrasts previous observations to the north and south of the flat slab region. Since plate-motion-parallel splitting occurs only coincidentally with the slab tear, we propose mantle material flows through the opening resulting in Nazca plate-motion-parallel flow in both the subslab mantle and mantle wedge.

A sample implementation for parallelizing Divide-and-Conquer algorithms on the GPU.

PubMed

Mei, Gang; Zhang, Jiayin; Xu, Nengxiong; Zhao, Kunyang

2018-01-01

The strategy of Divide-and-Conquer (D&C) is one of the frequently used programming patterns to design efficient algorithms in computer science, which has been parallelized on shared memory systems and distributed memory systems. Tzeng and Owens specifically developed a generic paradigm for parallelizing D&C algorithms on modern Graphics Processing Units (GPUs). In this paper, by following the generic paradigm proposed by Tzeng and Owens, we provide a new and publicly available GPU implementation of the famous D&C algorithm, QuickHull, to give a sample and guide for parallelizing D&C algorithms on the GPU. The experimental results demonstrate the practicality of our sample GPU implementation. Our research objective in this paper is to present a sample GPU implementation of a classical D&C algorithm to help interested readers to develop their own efficient GPU implementations with fewer efforts.

Parallel volume ray-casting for unstructured-grid data on distributed-memory architectures

NASA Technical Reports Server (NTRS)

Ma, Kwan-Liu

1995-01-01

As computing technology continues to advance, computational modeling of scientific and engineering problems produces data of increasing complexity: large in size and unstructured in shape. Volume visualization of such data is a challenging problem. This paper proposes a distributed parallel solution that makes ray-casting volume rendering of unstructured-grid data practical. Both the data and the rendering process are distributed among processors. At each processor, ray-casting of local data is performed independent of the other processors. The global image composing processes, which require inter-processor communication, are overlapped with the local ray-casting processes to achieve maximum parallel efficiency. This algorithm differs from previous ones in four ways: it is completely distributed, less view-dependent, reasonably scalable, and flexible. Without using dynamic load balancing, test results on the Intel Paragon using from two to 128 processors show, on average, about 60% parallel efficiency.

Essential issues in multiprocessor systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gajski, D.D.; Peir, J.K.

1985-06-01

During the past several years, a great number of proposals have been made with the objective to increase supercomputer performance by an order of magnitude on the basis of a utilization of new computer architectures. The present paper is concerned with a suitable classification scheme for comparing these architectures. It is pointed out that there are basically four schools of thought as to the most important factor for an enhancement of computer performance. According to one school, the development of faster circuits will make it possible to retain present architectures, except, possibly, for a mechanism providing synchronization of parallel processes.more » A second school assigns priority to the optimization and vectorization of compilers, which will detect parallelism and help users to write better parallel programs. A third school believes in the predominant importance of new parallel algorithms, while the fourth school supports new models of computation. The merits of the four approaches are critically evaluated. 50 references.« less

Center for Parallel Optimization.

DTIC Science & Technology

1996-03-19

A NEW OPTIMIZATION BASED APPROACH TO IMPROVING GENERALIZATION IN MACHINE LEARNING HAS BEEN PROPOSED AND COMPUTATIONALLY VALIDATED ON SIMPLE LINEAR MODELS AS WELL AS ON HIGHLY NONLINEAR SYSTEMS SUCH AS NEURAL NETWORKS.

Electrically tunable robust edge states in graphene-based topological photonic crystal slabs

NASA Astrophysics Data System (ADS)

Song, Zidong; Liu, HongJun; Huang, Nan; Wang, ZhaoLu

2018-03-01

Topological photonic crystals are optical structures supporting topologically protected unidirectional edge states that exhibit robustness against defects. Here, we propose a graphene-based all-dielectric photonic crystal slab structure that supports two-dimensionally confined topological edge states. These topological edge states can be confined in the out-of-plane direction by two parallel graphene sheets. In the structure, the excitation frequency range of topological edge states can be dynamically and continuously tuned by varying bias voltage across the two parallel graphene sheets. Utilizing this kind of architecture, we construct Z-shaped channels to realize topological edge transmission with diffrerent frequencies. The proposal provides a new degree of freedom to dynamically control topological edge states and potential applications for robust integrated photonic devices and optical communication systems.

Improve load balancing and coding efficiency of tiles in high efficiency video coding by adaptive tile boundary

NASA Astrophysics Data System (ADS)

Chan, Chia-Hsin; Tu, Chun-Chuan; Tsai, Wen-Jiin

2017-01-01

High efficiency video coding (HEVC) not only improves the coding efficiency drastically compared to the well-known H.264/AVC but also introduces coding tools for parallel processing, one of which is tiles. Tile partitioning is allowed to be arbitrary in HEVC, but how to decide tile boundaries remains an open issue. An adaptive tile boundary (ATB) method is proposed to select a better tile partitioning to improve load balancing (ATB-LoadB) and coding efficiency (ATB-Gain) with a unified scheme. Experimental results show that, compared to ordinary uniform-space partitioning, the proposed ATB can save up to 17.65% of encoding times in parallel encoding scenarios and can reduce up to 0.8% of total bit rates for coding efficiency.

FEM analysis of an single stator dual PM rotors axial synchronous machine

NASA Astrophysics Data System (ADS)

Tutelea, L. N.; Deaconu, S. I.; Popa, G. N.

2017-01-01

The actual e - continuously variable transmission (e-CVT) solution for the parallel Hybrid Electric Vehicle (HEV) requires two electric machines, two inverters, and a planetary gear. A distinct electric generator and a propulsion electric motor, both with full power converters, are typical for a series HEV. In an effort to simplify the planetary-geared e-CVT for the parallel HEV or the series HEV we hereby propose to replace the basically two electric machines and their two power converters by a single, axial-air-gap, electric machine central stator, fed from a single PWM converter with dual frequency voltage output and two independent PM rotors. The proposed topologies, the magneto-motive force analysis and quasi 3D-FEM analysis are the core of the paper.

Minimizing makespan in a two-stage flow shop with parallel batch-processing machines and re-entrant jobs

NASA Astrophysics Data System (ADS)

Huang, J. D.; Liu, J. J.; Chen, Q. X.; Mao, N.

2017-06-01

Against a background of heat-treatment operations in mould manufacturing, a two-stage flow-shop scheduling problem is described for minimizing makespan with parallel batch-processing machines and re-entrant jobs. The weights and release dates of jobs are non-identical, but job processing times are equal. A mixed-integer linear programming model is developed and tested with small-scale scenarios. Given that the problem is NP hard, three heuristic construction methods with polynomial complexity are proposed. The worst case of the new constructive heuristic is analysed in detail. A method for computing lower bounds is proposed to test heuristic performance. Heuristic efficiency is tested with sets of scenarios. Compared with the two improved heuristics, the performance of the new constructive heuristic is superior.

Efficient bounding schemes for the two-center hybrid flow shop scheduling problem with removal times.

PubMed

Hidri, Lotfi; Gharbi, Anis; Louly, Mohamed Aly

2014-01-01

We focus on the two-center hybrid flow shop scheduling problem with identical parallel machines and removal times. The job removal time is the required duration to remove it from a machine after its processing. The objective is to minimize the maximum completion time (makespan). A heuristic and a lower bound are proposed for this NP-Hard problem. These procedures are based on the optimal solution of the parallel machine scheduling problem with release dates and delivery times. The heuristic is composed of two phases. The first one is a constructive phase in which an initial feasible solution is provided, while the second phase is an improvement one. Intensive computational experiments have been conducted to confirm the good performance of the proposed procedures.

Efficient Bounding Schemes for the Two-Center Hybrid Flow Shop Scheduling Problem with Removal Times

PubMed Central

2014-01-01

We focus on the two-center hybrid flow shop scheduling problem with identical parallel machines and removal times. The job removal time is the required duration to remove it from a machine after its processing. The objective is to minimize the maximum completion time (makespan). A heuristic and a lower bound are proposed for this NP-Hard problem. These procedures are based on the optimal solution of the parallel machine scheduling problem with release dates and delivery times. The heuristic is composed of two phases. The first one is a constructive phase in which an initial feasible solution is provided, while the second phase is an improvement one. Intensive computational experiments have been conducted to confirm the good performance of the proposed procedures. PMID:25610911

A parallel algorithm for step- and chain-growth polymerization in molecular dynamics.

PubMed

de Buyl, Pierre; Nies, Erik

2015-04-07

Classical Molecular Dynamics (MD) simulations provide insight into the properties of many soft-matter systems. In some situations, it is interesting to model the creation of chemical bonds, a process that is not part of the MD framework. In this context, we propose a parallel algorithm for step- and chain-growth polymerization that is based on a generic reaction scheme, works at a given intrinsic rate and produces continuous trajectories. We present an implementation in the ESPResSo++ simulation software and compare it with the corresponding feature in LAMMPS. For chain growth, our results are compared to the existing simulation literature. For step growth, a rate equation is proposed for the evolution of the crosslinker population that compares well to the simulations for low crosslinker functionality or for short times.

A parallel algorithm for step- and chain-growth polymerization in molecular dynamics

NASA Astrophysics Data System (ADS)

de Buyl, Pierre; Nies, Erik

2015-04-01

Classical Molecular Dynamics (MD) simulations provide insight into the properties of many soft-matter systems. In some situations, it is interesting to model the creation of chemical bonds, a process that is not part of the MD framework. In this context, we propose a parallel algorithm for step- and chain-growth polymerization that is based on a generic reaction scheme, works at a given intrinsic rate and produces continuous trajectories. We present an implementation in the ESPResSo++ simulation software and compare it with the corresponding feature in LAMMPS. For chain growth, our results are compared to the existing simulation literature. For step growth, a rate equation is proposed for the evolution of the crosslinker population that compares well to the simulations for low crosslinker functionality or for short times.

Motion control of planar parallel robot using the fuzzy descriptor system approach.

PubMed

Vermeiren, Laurent; Dequidt, Antoine; Afroun, Mohamed; Guerra, Thierry-Marie

2012-09-01

This work presents the control of a two-degree of freedom parallel robot manipulator. A quasi-LPV approach, through the so-called TS fuzzy model and LMI constraints problems is used. Moreover, in this context a way to derive interesting control laws is to keep the descriptor form of the mechanical system. Therefore, new LMI problems have to be defined that helps to reduce the conservatism of the usual results. Some relaxations are also proposed to leave the pure quadratic stability/stabilization framework. A comparison study between the classical control strategies from robotics and the control design using TS fuzzy descriptor models is carried out to show the interest of the proposed approach. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Mixed methods in gerontological research: Do the qualitative and quantitative data “touch”?

PubMed Central

Happ, Mary Beth

2010-01-01

This paper distinguishes between parallel and integrated mixed methods research approaches. Barriers to integrated mixed methods approaches in gerontological research are discussed and critiqued. The author presents examples of mixed methods gerontological research to illustrate approaches to data integration at the levels of data analysis, interpretation, and research reporting. As a summary of the methodological literature, four basic levels of mixed methods data combination are proposed. Opportunities for mixing qualitative and quantitative data are explored using contemporary examples from published studies. Data transformation and visual display, judiciously applied, are proposed as pathways to fuller mixed methods data integration and analysis. Finally, practical strategies for mixing qualitative and quantitative data types are explicated as gerontological research moves beyond parallel mixed methods approaches to achieve data integration. PMID:20077973

Efficient parallel implementation of active appearance model fitting algorithm on GPU.

PubMed

Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou

2014-01-01

The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures.

Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU

PubMed Central

Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou

2014-01-01

The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures. PMID:24723812

Applications of Parallel Computation in Micro-Mechanics and Finite Element Method

NASA Technical Reports Server (NTRS)

Tan, Hui-Qian

1996-01-01

This project discusses the application of parallel computations related with respect to material analyses. Briefly speaking, we analyze some kind of material by elements computations. We call an element a cell here. A cell is divided into a number of subelements called subcells and all subcells in a cell have the identical structure. The detailed structure will be given later in this paper. It is obvious that the problem is "well-structured". SIMD machine would be a better choice. In this paper we try to look into the potentials of SIMD machine in dealing with finite element computation by developing appropriate algorithms on MasPar, a SIMD parallel machine. In section 2, the architecture of MasPar will be discussed. A brief review of the parallel programming language MPL also is given in that section. In section 3, some general parallel algorithms which might be useful to the project will be proposed. And, combining with the algorithms, some features of MPL will be discussed in more detail. In section 4, the computational structure of cell/subcell model will be given. The idea of designing the parallel algorithm for the model will be demonstrated. Finally in section 5, a summary will be given.

Equalizer: a scalable parallel rendering framework.

PubMed

Eilemann, Stefan; Makhinya, Maxim; Pajarola, Renato

2009-01-01

Continuing improvements in CPU and GPU performances as well as increasing multi-core processor and cluster-based parallelism demand for flexible and scalable parallel rendering solutions that can exploit multipipe hardware accelerated graphics. In fact, to achieve interactive visualization, scalable rendering systems are essential to cope with the rapid growth of data sets. However, parallel rendering systems are non-trivial to develop and often only application specific implementations have been proposed. The task of developing a scalable parallel rendering framework is even more difficult if it should be generic to support various types of data and visualization applications, and at the same time work efficiently on a cluster with distributed graphics cards. In this paper we introduce a novel system called Equalizer, a toolkit for scalable parallel rendering based on OpenGL which provides an application programming interface (API) to develop scalable graphics applications for a wide range of systems ranging from large distributed visualization clusters and multi-processor multipipe graphics systems to single-processor single-pipe desktop machines. We describe the system architecture, the basic API, discuss its advantages over previous approaches, present example configurations and usage scenarios as well as scalability results.

Modified Method of Adaptive Artificial Viscosity for Solution of Gas Dynamics Problems on Parallel Computer Systems

NASA Astrophysics Data System (ADS)

Popov, Igor; Sukov, Sergey

2018-02-01

A modification of the adaptive artificial viscosity (AAV) method is considered. This modification is based on one stage time approximation and is adopted to calculation of gasdynamics problems on unstructured grids with an arbitrary type of grid elements. The proposed numerical method has simplified logic, better performance and parallel efficiency compared to the implementation of the original AAV method. Computer experiments evidence the robustness and convergence of the method to difference solution.

Distributed Computing for Signal Processing: Modeling of Asynchronous Parallel Computation.

DTIC Science & Technology

1986-03-01

the proposed approaches 16, 16, 40 . 451. The conclusion most often reached is that the best scheme to use in a particular design depends highly upon...76. 40 . Siegel, H. J., McMillen. R. J., and Mueller. P. T.. Jr. A survey of interconnection methods for reconligurable parallel processing systems...addressing meehaanm distributed in the network area rimonication% tit reach gigabit./second speeds je g.. PoCoS83 .’ i.V--i the lirO! lk i nitronment is

Towards the Teraflop CFD

NASA Technical Reports Server (NTRS)

Schreiber, Robert; Simon, Horst D.

1992-01-01

We are surveying current projects in the area of parallel supercomputers. The machines considered here will become commercially available in the 1990 - 1992 time frame. All are suitable for exploring the critical issues in applying parallel processors to large scale scientific computations, in particular CFD calculations. This chapter presents an overview of the surveyed machines, and a detailed analysis of the various architectural and technology approaches taken. Particular emphasis is placed on the feasibility of a Teraflops capability following the paths proposed by various developers.

Accelerated Electron-Beam Formation with a High Capture Coefficient in a Parallel Coupled Accelerating Structure

NASA Astrophysics Data System (ADS)

Chernousov, Yu. D.; Shebolaev, I. V.; Ikryanov, I. M.

2018-01-01

An electron beam with a high (close to 100%) coefficient of electron capture into the regime of acceleration has been obtained in a linear electron accelerator based on a parallel coupled slow-wave structure, electron gun with microwave-controlled injection current, and permanent-magnet beam-focusing system. The high capture coefficient was due to the properties of the accelerating structure, beam-focusing system, and electron-injection system. Main characteristics of the proposed systems are presented.

A parallel coordinates style interface for exploratory volume visualization.

PubMed

Tory, Melanie; Potts, Simeon; Möller, Torsten

2005-01-01

We present a user interface, based on parallel coordinates, that facilitates exploration of volume data. By explicitly representing the visualization parameter space, the interface provides an overview of rendering options and enables users to easily explore different parameters. Rendered images are stored in an integrated history bar that facilitates backtracking to previous visualization options. Initial usability testing showed clear agreement between users and experts of various backgrounds (usability, graphic design, volume visualization, and medical physics) that the proposed user interface is a valuable data exploration tool.

A portable MPI-based parallel vector template library

NASA Technical Reports Server (NTRS)

Sheffler, Thomas J.

1995-01-01

This paper discusses the design and implementation of a polymorphic collection library for distributed address-space parallel computers. The library provides a data-parallel programming model for C++ by providing three main components: a single generic collection class, generic algorithms over collections, and generic algebraic combining functions. Collection elements are the fourth component of a program written using the library and may be either of the built-in types of C or of user-defined types. Many ideas are borrowed from the Standard Template Library (STL) of C++, although a restricted programming model is proposed because of the distributed address-space memory model assumed. Whereas the STL provides standard collections and implementations of algorithms for uniprocessors, this paper advocates standardizing interfaces that may be customized for different parallel computers. Just as the STL attempts to increase programmer productivity through code reuse, a similar standard for parallel computers could provide programmers with a standard set of algorithms portable across many different architectures. The efficacy of this approach is verified by examining performance data collected from an initial implementation of the library running on an IBM SP-2 and an Intel Paragon.

A Portable MPI-Based Parallel Vector Template Library

NASA Technical Reports Server (NTRS)

Sheffler, Thomas J.

1995-01-01

This paper discusses the design and implementation of a polymorphic collection library for distributed address-space parallel computers. The library provides a data-parallel programming model for C + + by providing three main components: a single generic collection class, generic algorithms over collections, and generic algebraic combining functions. Collection elements are the fourth component of a program written using the library and may be either of the built-in types of c or of user-defined types. Many ideas are borrowed from the Standard Template Library (STL) of C++, although a restricted programming model is proposed because of the distributed address-space memory model assumed. Whereas the STL provides standard collections and implementations of algorithms for uniprocessors, this paper advocates standardizing interfaces that may be customized for different parallel computers. Just as the STL attempts to increase programmer productivity through code reuse, a similar standard for parallel computers could provide programmers with a standard set of algorithms portable across many different architectures. The efficacy of this approach is verified by examining performance data collected from an initial implementation of the library running on an IBM SP-2 and an Intel Paragon.

Potential conflict between TRIPS and GATT concerning parallel importation of drugs and possible solution to prevent undesirable market segmentation.

PubMed

Lo, Chang-Fa

2011-01-01

From international perspective, parallel importation, especially with respect to drugs, has to do with the exhaustion principle in Article 6 of the TRIPS Agreement and the general exception in Article XX of the GATT 1994. Issues concerning the TRIPS Agreement have been constant topics of discussion. However, parallel importation in relation to the general rules of the GATT 1994 as well as to its exceptions provided in Article XX was not seriously discussed. In the view of the paper, there is a conflict between the provisions in these two agreements. The paper explains such conflict and tries to propose a method of interpretation to resolve the conflict between GATT Article XX and TRIPS Article 6 concerning parallel importation for the purpose of reducing the possible undesirable market segmentation in pharmaceutical sector. The method suggested in the paper is a proper application of good faith principle in the Vienna Convention to interpret GATT Article XX, so that there could be some flexibility for those prohibitions of parallel importation which have positive effect on international trade.

A Hybrid Shared-Memory Parallel Max-Tree Algorithm for Extreme Dynamic-Range Images.

PubMed

Moschini, Ugo; Meijster, Arnold; Wilkinson, Michael H F

2018-03-01

Max-trees, or component trees, are graph structures that represent the connected components of an image in a hierarchical way. Nowadays, many application fields rely on images with high-dynamic range or floating point values. Efficient sequential algorithms exist to build trees and compute attributes for images of any bit depth. However, we show that the current parallel algorithms perform poorly already with integers at bit depths higher than 16 bits per pixel. We propose a parallel method combining the two worlds of flooding and merging max-tree algorithms. First, a pilot max-tree of a quantized version of the image is built in parallel using a flooding method. Later, this structure is used in a parallel leaf-to-root approach to compute efficiently the final max-tree and to drive the merging of the sub-trees computed by the threads. We present an analysis of the performance both on simulated and actual 2D images and 3D volumes. Execution times are about better than the fastest sequential algorithm and speed-up goes up to on 64 threads.

Expressing Parallelism with ROOT

NASA Astrophysics Data System (ADS)

Piparo, D.; Tejedor, E.; Guiraud, E.; Ganis, G.; Mato, P.; Moneta, L.; Valls Pla, X.; Canal, P.

2017-10-01

The need for processing the ever-increasing amount of data generated by the LHC experiments in a more efficient way has motivated ROOT to further develop its support for parallelism. Such support is being tackled both for shared-memory and distributed-memory environments. The incarnations of the aforementioned parallelism are multi-threading, multi-processing and cluster-wide executions. In the area of multi-threading, we discuss the new implicit parallelism and related interfaces, as well as the new building blocks to safely operate with ROOT objects in a multi-threaded environment. Regarding multi-processing, we review the new MultiProc framework, comparing it with similar tools (e.g. multiprocessing module in Python). Finally, as an alternative to PROOF for cluster-wide executions, we introduce the efforts on integrating ROOT with state-of-the-art distributed data processing technologies like Spark, both in terms of programming model and runtime design (with EOS as one of the main components). For all the levels of parallelism, we discuss, based on real-life examples and measurements, how our proposals can increase the productivity of scientists.

A Novel Design of 4-Class BCI Using Two Binary Classifiers and Parallel Mental Tasks

PubMed Central

Geng, Tao; Gan, John Q.; Dyson, Matthew; Tsui, Chun SL; Sepulveda, Francisco

2008-01-01

A novel 4-class single-trial brain computer interface (BCI) based on two (rather than four or more) binary linear discriminant analysis (LDA) classifiers is proposed, which is called a “parallel BCI.” Unlike other BCIs where mental tasks are executed and classified in a serial way one after another, the parallel BCI uses properly designed parallel mental tasks that are executed on both sides of the subject body simultaneously, which is the main novelty of the BCI paradigm used in our experiments. Each of the two binary classifiers only classifies the mental tasks executed on one side of the subject body, and the results of the two binary classifiers are combined to give the result of the 4-class BCI. Data was recorded in experiments with both real movement and motor imagery in 3 able-bodied subjects. Artifacts were not detected or removed. Offline analysis has shown that, in some subjects, the parallel BCI can generate a higher accuracy than a conventional 4-class BCI, although both of them have used the same feature selection and classification algorithms. PMID:18584040

Expressing Parallelism with ROOT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Piparo, D.; Tejedor, E.; Guiraud, E.

The need for processing the ever-increasing amount of data generated by the LHC experiments in a more efficient way has motivated ROOT to further develop its support for parallelism. Such support is being tackled both for shared-memory and distributed-memory environments. The incarnations of the aforementioned parallelism are multi-threading, multi-processing and cluster-wide executions. In the area of multi-threading, we discuss the new implicit parallelism and related interfaces, as well as the new building blocks to safely operate with ROOT objects in a multi-threaded environment. Regarding multi-processing, we review the new MultiProc framework, comparing it with similar tools (e.g. multiprocessing module inmore » Python). Finally, as an alternative to PROOF for cluster-wide executions, we introduce the efforts on integrating ROOT with state-of-the-art distributed data processing technologies like Spark, both in terms of programming model and runtime design (with EOS as one of the main components). For all the levels of parallelism, we discuss, based on real-life examples and measurements, how our proposals can increase the productivity of scientists.« less

A transient FETI methodology for large-scale parallel implicit computations in structural mechanics

NASA Technical Reports Server (NTRS)

Farhat, Charbel; Crivelli, Luis; Roux, Francois-Xavier

1992-01-01

Explicit codes are often used to simulate the nonlinear dynamics of large-scale structural systems, even for low frequency response, because the storage and CPU requirements entailed by the repeated factorizations traditionally found in implicit codes rapidly overwhelm the available computing resources. With the advent of parallel processing, this trend is accelerating because explicit schemes are also easier to parallelize than implicit ones. However, the time step restriction imposed by the Courant stability condition on all explicit schemes cannot yet -- and perhaps will never -- be offset by the speed of parallel hardware. Therefore, it is essential to develop efficient and robust alternatives to direct methods that are also amenable to massively parallel processing because implicit codes using unconditionally stable time-integration algorithms are computationally more efficient when simulating low-frequency dynamics. Here we present a domain decomposition method for implicit schemes that requires significantly less storage than factorization algorithms, that is several times faster than other popular direct and iterative methods, that can be easily implemented on both shared and local memory parallel processors, and that is both computationally and communication-wise efficient. The proposed transient domain decomposition method is an extension of the method of Finite Element Tearing and Interconnecting (FETI) developed by Farhat and Roux for the solution of static problems. Serial and parallel performance results on the CRAY Y-MP/8 and the iPSC-860/128 systems are reported and analyzed for realistic structural dynamics problems. These results establish the superiority of the FETI method over both the serial/parallel conjugate gradient algorithm with diagonal scaling and the serial/parallel direct method, and contrast the computational power of the iPSC-860/128 parallel processor with that of the CRAY Y-MP/8 system.

Development of a 3D parallel mechanism robot arm with three vertical-axial pneumatic actuators combined with a stereo vision system.

PubMed

Chiang, Mao-Hsiung; Lin, Hao-Ting

2011-01-01

This study aimed to develop a novel 3D parallel mechanism robot driven by three vertical-axial pneumatic actuators with a stereo vision system for path tracking control. The mechanical system and the control system are the primary novel parts for developing a 3D parallel mechanism robot. In the mechanical system, a 3D parallel mechanism robot contains three serial chains, a fixed base, a movable platform and a pneumatic servo system. The parallel mechanism are designed and analyzed first for realizing a 3D motion in the X-Y-Z coordinate system of the robot's end-effector. The inverse kinematics and the forward kinematics of the parallel mechanism robot are investigated by using the Denavit-Hartenberg notation (D-H notation) coordinate system. The pneumatic actuators in the three vertical motion axes are modeled. In the control system, the Fourier series-based adaptive sliding-mode controller with H(∞) tracking performance is used to design the path tracking controllers of the three vertical servo pneumatic actuators for realizing 3D path tracking control of the end-effector. Three optical linear scales are used to measure the position of the three pneumatic actuators. The 3D position of the end-effector is then calculated from the measuring position of the three pneumatic actuators by means of the kinematics. However, the calculated 3D position of the end-effector cannot consider the manufacturing and assembly tolerance of the joints and the parallel mechanism so that errors between the actual position and the calculated 3D position of the end-effector exist. In order to improve this situation, sensor collaboration is developed in this paper. A stereo vision system is used to collaborate with the three position sensors of the pneumatic actuators. The stereo vision system combining two CCD serves to measure the actual 3D position of the end-effector and calibrate the error between the actual and the calculated 3D position of the end-effector. Furthermore, to verify the feasibility of the proposed parallel mechanism robot driven by three vertical pneumatic servo actuators, a full-scale test rig of the proposed parallel mechanism pneumatic robot is set up. Thus, simulations and experiments for different complex 3D motion profiles of the robot end-effector can be successfully achieved. The desired, the actual and the calculated 3D position of the end-effector can be compared in the complex 3D motion control.

Development of a 3D Parallel Mechanism Robot Arm with Three Vertical-Axial Pneumatic Actuators Combined with a Stereo Vision System

PubMed Central

Chiang, Mao-Hsiung; Lin, Hao-Ting

2011-01-01

This study aimed to develop a novel 3D parallel mechanism robot driven by three vertical-axial pneumatic actuators with a stereo vision system for path tracking control. The mechanical system and the control system are the primary novel parts for developing a 3D parallel mechanism robot. In the mechanical system, a 3D parallel mechanism robot contains three serial chains, a fixed base, a movable platform and a pneumatic servo system. The parallel mechanism are designed and analyzed first for realizing a 3D motion in the X-Y-Z coordinate system of the robot’s end-effector. The inverse kinematics and the forward kinematics of the parallel mechanism robot are investigated by using the Denavit-Hartenberg notation (D-H notation) coordinate system. The pneumatic actuators in the three vertical motion axes are modeled. In the control system, the Fourier series-based adaptive sliding-mode controller with H∞ tracking performance is used to design the path tracking controllers of the three vertical servo pneumatic actuators for realizing 3D path tracking control of the end-effector. Three optical linear scales are used to measure the position of the three pneumatic actuators. The 3D position of the end-effector is then calculated from the measuring position of the three pneumatic actuators by means of the kinematics. However, the calculated 3D position of the end-effector cannot consider the manufacturing and assembly tolerance of the joints and the parallel mechanism so that errors between the actual position and the calculated 3D position of the end-effector exist. In order to improve this situation, sensor collaboration is developed in this paper. A stereo vision system is used to collaborate with the three position sensors of the pneumatic actuators. The stereo vision system combining two CCD serves to measure the actual 3D position of the end-effector and calibrate the error between the actual and the calculated 3D position of the end-effector. Furthermore, to verify the feasibility of the proposed parallel mechanism robot driven by three vertical pneumatic servo actuators, a full-scale test rig of the proposed parallel mechanism pneumatic robot is set up. Thus, simulations and experiments for different complex 3D motion profiles of the robot end-effector can be successfully achieved. The desired, the actual and the calculated 3D position of the end-effector can be compared in the complex 3D motion control. PMID:22247676

Decentralized Interleaving of Paralleled Dc-Dc Buck Converters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Brian B; Rodriguez, Miguel; Sinha, Mohit

We present a decentralized control strategy that yields switch interleaving among parallel-connected dc-dc buck converters. The proposed method is based on the digital implementation of the dynamics of a nonlinear oscillator circuit as the controller. Each controller is fully decentralized, i.e., it only requires the locally measured output current to synthesize the pulse width modulation (PWM) carrier waveform and no communication between different controllers is needed. By virtue of the intrinsic electrical coupling between converters, the nonlinear oscillator-based controllers converge to an interleaved state with uniform phase-spacing across PWM carriers. To the knowledge of the authors, this work presents themore » first fully decentralized strategy for switch interleaving in paralleled dc-dc buck converters.« less

Proxy-equation paradigm: A strategy for massively parallel asynchronous computations

NASA Astrophysics Data System (ADS)

Mittal, Ankita; Girimaji, Sharath

2017-09-01

Massively parallel simulations of transport equation systems call for a paradigm change in algorithm development to achieve efficient scalability. Traditional approaches require time synchronization of processing elements (PEs), which severely restricts scalability. Relaxing synchronization requirement introduces error and slows down convergence. In this paper, we propose and develop a novel "proxy equation" concept for a general transport equation that (i) tolerates asynchrony with minimal added error, (ii) preserves convergence order and thus, (iii) expected to scale efficiently on massively parallel machines. The central idea is to modify a priori the transport equation at the PE boundaries to offset asynchrony errors. Proof-of-concept computations are performed using a one-dimensional advection (convection) diffusion equation. The results demonstrate the promise and advantages of the present strategy.

A parallel strategy for predicting the secondary structure of polycistronic microRNAs.

PubMed

Han, Dianwei; Tang, Guiliang; Zhang, Jun

2013-01-01

The biogenesis of a functional microRNA is largely dependent on the secondary structure of the microRNA precursor (pre-miRNA). Recently, it has been shown that microRNAs are present in the genome as the form of polycistronic transcriptional units in plants and animals. It will be important to design efficient computational methods to predict such structures for microRNA discovery and its applications in gene silencing. In this paper, we propose a parallel algorithm based on the master-slave architecture to predict the secondary structure from an input sequence. We conducted some experiments to verify the effectiveness of our parallel algorithm. The experimental results show that our algorithm is able to produce the optimal secondary structure of polycistronic microRNAs.

Enhancing instruction scheduling with a block-structured ISA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Melvin, S.; Patt, Y.

It is now generally recognized that not enough parallelism exists within the small basic blocks of most general purpose programs to satisfy high performance processors. Thus, a wide variety of techniques have been developed to exploit instruction level parallelism across basic block boundaries. In this paper we discuss some previous techniques along with their hardware and software requirements. Then we propose a new paradigm for an instruction set architecture (ISA): block-structuring. This new paradigm is presented, its hardware and software requirements are discussed and the results from a simulation study are presented. We show that a block-structured ISA utilizes bothmore » dynamic and compile-time mechanisms for exploiting instruction level parallelism and has significant performance advantages over a conventional ISA.« less

Shared Memory Parallelization of an Implicit ADI-type CFD Code

NASA Technical Reports Server (NTRS)

Hauser, Th.; Huang, P. G.

1999-01-01

A parallelization study designed for ADI-type algorithms is presented using the OpenMP specification for shared-memory multiprocessor programming. Details of optimizations specifically addressed to cache-based computer architectures are described and performance measurements for the single and multiprocessor implementation are summarized. The paper demonstrates that optimization of memory access on a cache-based computer architecture controls the performance of the computational algorithm. A hybrid MPI/OpenMP approach is proposed for clusters of shared memory machines to further enhance the parallel performance. The method is applied to develop a new LES/DNS code, named LESTool. A preliminary DNS calculation of a fully developed channel flow at a Reynolds number of 180, Re(sub tau) = 180, has shown good agreement with existing data.

An Analysis of the Role of ATC in the AILS Concept

NASA Technical Reports Server (NTRS)

Waller, Marvin C.; Doyle, Thomas M.; McGee, Frank G.

2000-01-01

Airborne information for lateral spacing (AILS) is a concept for making approaches to closely spaced parallel runways in instrument meteorological conditions (IMC). Under the concept, each equipped aircraft will assume responsibility for accurately managing its flight path along the approach course and maintaining separation from aircraft on the parallel approach. This document presents the results of an analysis of the AILS concept from an Air Traffic Control (ATC) perspective. The process has been examined in a step by step manner to determine ATC system support necessary to safely conduct closely spaced parallel approaches using the AILS concept. The analysis resulted in recognizing a number of issues related to integrating the process into the airspace system and proposes operating procedures.

Parallel-Connected Photovoltaic Inverters: Zero Frequency Sequence Harmonic Analysis and Solution

NASA Astrophysics Data System (ADS)

Carmeli, Maria Stefania; Mauri, Marco; Frosio, Luisa; Bezzolato, Alberto; Marchegiani, Gabriele

2013-05-01

High-power photovoltaic (PV) plants are usually constituted of the connection of different PV subfields, each of them with its interface transformer. Different solutions have been studied to improve the efficiency of the whole generation system. In particular, transformerless configurations are the more attractive one from efficiency and costs point of view. This paper focuses on transformerless PV configurations characterised by the parallel connection of interface inverters. The problem of zero sequence current due to both the parallel connection and the presence of undesirable parasitic earth capacitances is considered and a solution, which consists of the synchronisation of pulse-width modulation triangular carrier, is proposed and theoretically analysed. The theoretical analysis has been validated through simulation and experimental results.

IQ imbalance tolerable parallel-channel DMT transmission for coherent optical OFDMA access network

NASA Astrophysics Data System (ADS)

Jung, Sang-Min; Mun, Kyoung-Hak; Jung, Sun-Young; Han, Sang-Kook

2016-12-01

Phase diversity of coherent optical communication provides spectrally efficient higher-order modulation for optical communications. However, in-phase/quadrature (IQ) imbalance in coherent optical communication degrades transmission performance by introducing unwanted signal distortions. In a coherent optical orthogonal frequency division multiple access (OFDMA) passive optical network (PON), IQ imbalance-induced signal distortions degrade transmission performance by interferences of mirror subcarriers, inter-symbol interference (ISI), and inter-channel interference (ICI). We propose parallel-channel discrete multitone (DMT) transmission to mitigate transceiver IQ imbalance-induced signal distortions in coherent orthogonal frequency division multiplexing (OFDM) transmissions. We experimentally demonstrate the effectiveness of parallel-channel DMT transmission compared with that of OFDM transmission in the presence of IQ imbalance.

A parallel data management system for large-scale NASA datasets

NASA Technical Reports Server (NTRS)

Srivastava, Jaideep

1993-01-01

The past decade has experienced a phenomenal growth in the amount of data and resultant information generated by NASA's operations and research projects. A key application is the reprocessing problem which has been identified to require data management capabilities beyond those available today (PRAT93). The Intelligent Information Fusion (IIF) system (ROEL91) is an ongoing NASA project which has similar requirements. Deriving our understanding of NASA's future data management needs based on the above, this paper describes an approach to using parallel computer systems (processor and I/O architectures) to develop an efficient parallel database management system to address the needs. Specifically, we propose to investigate issues in low-level record organizations and management, complex query processing, and query compilation and scheduling.

a Spatiotemporal Aggregation Query Method Using Multi-Thread Parallel Technique Based on Regional Division

NASA Astrophysics Data System (ADS)

Liao, S.; Chen, L.; Li, J.; Xiong, W.; Wu, Q.

2015-07-01

Existing spatiotemporal database supports spatiotemporal aggregation query over massive moving objects datasets. Due to the large amounts of data and single-thread processing method, the query speed cannot meet the application requirements. On the other hand, the query efficiency is more sensitive to spatial variation then temporal variation. In this paper, we proposed a spatiotemporal aggregation query method using multi-thread parallel technique based on regional divison and implemented it on the server. Concretely, we divided the spatiotemporal domain into several spatiotemporal cubes, computed spatiotemporal aggregation on all cubes using the technique of multi-thread parallel processing, and then integrated the query results. By testing and analyzing on the real datasets, this method has improved the query speed significantly.

Neural Parallel Engine: A toolbox for massively parallel neural signal processing.

PubMed

Tam, Wing-Kin; Yang, Zhi

2018-05-01

Large-scale neural recordings provide detailed information on neuronal activities and can help elicit the underlying neural mechanisms of the brain. However, the computational burden is also formidable when we try to process the huge data stream generated by such recordings. In this study, we report the development of Neural Parallel Engine (NPE), a toolbox for massively parallel neural signal processing on graphical processing units (GPUs). It offers a selection of the most commonly used routines in neural signal processing such as spike detection and spike sorting, including advanced algorithms such as exponential-component-power-component (EC-PC) spike detection and binary pursuit spike sorting. We also propose a new method for detecting peaks in parallel through a parallel compact operation. Our toolbox is able to offer a 5× to 110× speedup compared with its CPU counterparts depending on the algorithms. A user-friendly MATLAB interface is provided to allow easy integration of the toolbox into existing workflows. Previous efforts on GPU neural signal processing only focus on a few rudimentary algorithms, are not well-optimized and often do not provide a user-friendly programming interface to fit into existing workflows. There is a strong need for a comprehensive toolbox for massively parallel neural signal processing. A new toolbox for massively parallel neural signal processing has been created. It can offer significant speedup in processing signals from large-scale recordings up to thousands of channels. Copyright © 2018 Elsevier B.V. All rights reserved.

Implementation of parallel transmit beamforming using orthogonal frequency division multiplexing--achievable resolution and interbeam interference.

PubMed

Demi, Libertario; Viti, Jacopo; Kusters, Lieneke; Guidi, Francesco; Tortoli, Piero; Mischi, Massimo

2013-11-01

The speed of sound in the human body limits the achievable data acquisition rate of pulsed ultrasound scanners. To overcome this limitation, parallel beamforming techniques are used in ultrasound 2-D and 3-D imaging systems. Different parallel beamforming approaches have been proposed. They may be grouped into two major categories: parallel beamforming in reception and parallel beamforming in transmission. The first category is not optimal for harmonic imaging; the second category may be more easily applied to harmonic imaging. However, inter-beam interference represents an issue. To overcome these shortcomings and exploit the benefit of combining harmonic imaging and high data acquisition rate, a new approach has been recently presented which relies on orthogonal frequency division multiplexing (OFDM) to perform parallel beamforming in transmission. In this paper, parallel transmit beamforming using OFDM is implemented for the first time on an ultrasound scanner. An advanced open platform for ultrasound research is used to investigate the axial resolution and interbeam interference achievable with parallel transmit beamforming using OFDM. Both fundamental and second-harmonic imaging modalities have been considered. Results show that, for fundamental imaging, axial resolution in the order of 2 mm can be achieved in combination with interbeam interference in the order of -30 dB. For second-harmonic imaging, axial resolution in the order of 1 mm can be achieved in combination with interbeam interference in the order of -35 dB.

Serial vs. parallel models of attention in visual search: accounting for benchmark RT-distributions.

PubMed

Moran, Rani; Zehetleitner, Michael; Liesefeld, Heinrich René; Müller, Hermann J; Usher, Marius

2016-10-01

Visual search is central to the investigation of selective visual attention. Classical theories propose that items are identified by serially deploying focal attention to their locations. While this accounts for set-size effects over a continuum of task difficulties, it has been suggested that parallel models can account for such effects equally well. We compared the serial Competitive Guided Search model with a parallel model in their ability to account for RT distributions and error rates from a large visual search data-set featuring three classical search tasks: 1) a spatial configuration search (2 vs. 5); 2) a feature-conjunction search; and 3) a unique feature search (Wolfe, Palmer & Horowitz Vision Research, 50(14), 1304-1311, 2010). In the parallel model, each item is represented by a diffusion to two boundaries (target-present/absent); the search corresponds to a parallel race between these diffusors. The parallel model was highly flexible in that it allowed both for a parametric range of capacity-limitation and for set-size adjustments of identification boundaries. Furthermore, a quit unit allowed for a continuum of search-quitting policies when the target is not found, with "single-item inspection" and exhaustive searches comprising its extremes. The serial model was found to be superior to the parallel model, even before penalizing the parallel model for its increased complexity. We discuss the implications of the results and the need for future studies to resolve the debate.

Accelerating Computation of DCM for ERP in MATLAB by External Function Calls to the GPU.

PubMed

Wang, Wei-Jen; Hsieh, I-Fan; Chen, Chun-Chuan

2013-01-01

This study aims to improve the performance of Dynamic Causal Modelling for Event Related Potentials (DCM for ERP) in MATLAB by using external function calls to a graphics processing unit (GPU). DCM for ERP is an advanced method for studying neuronal effective connectivity. DCM utilizes an iterative procedure, the expectation maximization (EM) algorithm, to find the optimal parameters given a set of observations and the underlying probability model. As the EM algorithm is computationally demanding and the analysis faces possible combinatorial explosion of models to be tested, we propose a parallel computing scheme using the GPU to achieve a fast estimation of DCM for ERP. The computation of DCM for ERP is dynamically partitioned and distributed to threads for parallel processing, according to the DCM model complexity and the hardware constraints. The performance efficiency of this hardware-dependent thread arrangement strategy was evaluated using the synthetic data. The experimental data were used to validate the accuracy of the proposed computing scheme and quantify the time saving in practice. The simulation results show that the proposed scheme can accelerate the computation by a factor of 155 for the parallel part. For experimental data, the speedup factor is about 7 per model on average, depending on the model complexity and the data. This GPU-based implementation of DCM for ERP gives qualitatively the same results as the original MATLAB implementation does at the group level analysis. In conclusion, we believe that the proposed GPU-based implementation is very useful for users as a fast screen tool to select the most likely model and may provide implementation guidance for possible future clinical applications such as online diagnosis.

Specialized Computer Systems for Environment Visualization

NASA Astrophysics Data System (ADS)

Al-Oraiqat, Anas M.; Bashkov, Evgeniy A.; Zori, Sergii A.

2018-06-01

The need for real time image generation of landscapes arises in various fields as part of tasks solved by virtual and augmented reality systems, as well as geographic information systems. Such systems provide opportunities for collecting, storing, analyzing and graphically visualizing geographic data. Algorithmic and hardware software tools for increasing the realism and efficiency of the environment visualization in 3D visualization systems are proposed. This paper discusses a modified path tracing algorithm with a two-level hierarchy of bounding volumes and finding intersections with Axis-Aligned Bounding Box. The proposed algorithm eliminates the branching and hence makes the algorithm more suitable to be implemented on the multi-threaded CPU and GPU. A modified ROAM algorithm is used to solve the qualitative visualization of reliefs' problems and landscapes. The algorithm is implemented on parallel systems—cluster and Compute Unified Device Architecture-networks. Results show that the implementation on MPI clusters is more efficient than Graphics Processing Unit/Graphics Processing Clusters and allows real-time synthesis. The organization and algorithms of the parallel GPU system for the 3D pseudo stereo image/video synthesis are proposed. With realizing possibility analysis on a parallel GPU-architecture of each stage, 3D pseudo stereo synthesis is performed. An experimental prototype of a specialized hardware-software system 3D pseudo stereo imaging and video was developed on the CPU/GPU. The experimental results show that the proposed adaptation of 3D pseudo stereo imaging to the architecture of GPU-systems is efficient. Also it accelerates the computational procedures of 3D pseudo-stereo synthesis for the anaglyph and anamorphic formats of the 3D stereo frame without performing optimization procedures. The acceleration is on average 11 and 54 times for test GPUs.

Accelerating Computation of DCM for ERP in MATLAB by External Function Calls to the GPU

PubMed Central

Wang, Wei-Jen; Hsieh, I-Fan; Chen, Chun-Chuan

2013-01-01

This study aims to improve the performance of Dynamic Causal Modelling for Event Related Potentials (DCM for ERP) in MATLAB by using external function calls to a graphics processing unit (GPU). DCM for ERP is an advanced method for studying neuronal effective connectivity. DCM utilizes an iterative procedure, the expectation maximization (EM) algorithm, to find the optimal parameters given a set of observations and the underlying probability model. As the EM algorithm is computationally demanding and the analysis faces possible combinatorial explosion of models to be tested, we propose a parallel computing scheme using the GPU to achieve a fast estimation of DCM for ERP. The computation of DCM for ERP is dynamically partitioned and distributed to threads for parallel processing, according to the DCM model complexity and the hardware constraints. The performance efficiency of this hardware-dependent thread arrangement strategy was evaluated using the synthetic data. The experimental data were used to validate the accuracy of the proposed computing scheme and quantify the time saving in practice. The simulation results show that the proposed scheme can accelerate the computation by a factor of 155 for the parallel part. For experimental data, the speedup factor is about 7 per model on average, depending on the model complexity and the data. This GPU-based implementation of DCM for ERP gives qualitatively the same results as the original MATLAB implementation does at the group level analysis. In conclusion, we believe that the proposed GPU-based implementation is very useful for users as a fast screen tool to select the most likely model and may provide implementation guidance for possible future clinical applications such as online diagnosis. PMID:23840507

Dubinett - Targeted Sequencing 2012 — EDRN Public Portal

Cancer.gov

we propose to use targeted massively parallel DNA sequencing to identify somatic alterations within mutational hotspots in matched sets of primary lung tumors, premalignant lesions, and adjacent,histologically normal lung tissue.

A novel highly parallel algorithm for linearly unmixing hyperspectral images

NASA Astrophysics Data System (ADS)

Guerra, Raúl; López, Sebastián.; Callico, Gustavo M.; López, Jose F.; Sarmiento, Roberto

2014-10-01

Endmember extraction and abundances calculation represent critical steps within the process of linearly unmixing a given hyperspectral image because of two main reasons. The first one is due to the need of computing a set of accurate endmembers in order to further obtain confident abundance maps. The second one refers to the huge amount of operations involved in these time-consuming processes. This work proposes an algorithm to estimate the endmembers of a hyperspectral image under analysis and its abundances at the same time. The main advantage of this algorithm is its high parallelization degree and the mathematical simplicity of the operations implemented. This algorithm estimates the endmembers as virtual pixels. In particular, the proposed algorithm performs the descent gradient method to iteratively refine the endmembers and the abundances, reducing the mean square error, according with the linear unmixing model. Some mathematical restrictions must be added so the method converges in a unique and realistic solution. According with the algorithm nature, these restrictions can be easily implemented. The results obtained with synthetic images demonstrate the well behavior of the algorithm proposed. Moreover, the results obtained with the well-known Cuprite dataset also corroborate the benefits of our proposal.

Airborne Precision Spacing for Dependent Parallel Operations Interface Study

NASA Technical Reports Server (NTRS)

Volk, Paul M.; Takallu, M. A.; Hoffler, Keith D.; Weiser, Jarold; Turner, Dexter

2012-01-01

This paper describes a usability study of proposed cockpit interfaces to support Airborne Precision Spacing (APS) operations for aircraft performing dependent parallel approaches (DPA). NASA has proposed an airborne system called Pair Dependent Speed (PDS) which uses their Airborne Spacing for Terminal Arrival Routes (ASTAR) algorithm to manage spacing intervals. Interface elements were designed to facilitate the input of APS-DPA spacing parameters to ASTAR, and to convey PDS system information to the crew deemed necessary and/or helpful to conduct the operation, including: target speed, guidance mode, target aircraft depiction, and spacing trend indication. In the study, subject pilots observed recorded simulations using the proposed interface elements in which the ownship managed assigned spacing intervals from two other arriving aircraft. Simulations were recorded using the Aircraft Simulation for Traffic Operations Research (ASTOR) platform, a medium-fidelity simulator based on a modern Boeing commercial glass cockpit. Various combinations of the interface elements were presented to subject pilots, and feedback was collected via structured questionnaires. The results of subject pilot evaluations show that the proposed design elements were acceptable, and that preferable combinations exist within this set of elements. The results also point to potential improvements to be considered for implementation in future experiments.

Medical image denoising via optimal implementation of non-local means on hybrid parallel architecture.

PubMed

Nguyen, Tuan-Anh; Nakib, Amir; Nguyen, Huy-Nam

2016-06-01

The Non-local means denoising filter has been established as gold standard for image denoising problem in general and particularly in medical imaging due to its efficiency. However, its computation time limited its applications in real world application, especially in medical imaging. In this paper, a distributed version on parallel hybrid architecture is proposed to solve the computation time problem and a new method to compute the filters' coefficients is also proposed, where we focused on the implementation and the enhancement of filters' parameters via taking the neighborhood of the current voxel more accurately into account. In terms of implementation, our key contribution consists in reducing the number of shared memory accesses. The different tests of the proposed method were performed on the brain-web database for different levels of noise. Performances and the sensitivity were quantified in terms of speedup, peak signal to noise ratio, execution time, the number of floating point operations. The obtained results demonstrate the efficiency of the proposed method. Moreover, the implementation is compared to that of other techniques, recently published in the literature. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Information criteria for quantifying loss of reversibility in parallelized KMC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gourgoulias, Konstantinos, E-mail: gourgoul@math.umass.edu; Katsoulakis, Markos A., E-mail: markos@math.umass.edu; Rey-Bellet, Luc, E-mail: luc@math.umass.edu

Parallel Kinetic Monte Carlo (KMC) is a potent tool to simulate stochastic particle systems efficiently. However, despite literature on quantifying domain decomposition errors of the particle system for this class of algorithms in the short and in the long time regime, no study yet explores and quantifies the loss of time-reversibility in Parallel KMC. Inspired by concepts from non-equilibrium statistical mechanics, we propose the entropy production per unit time, or entropy production rate, given in terms of an observable and a corresponding estimator, as a metric that quantifies the loss of reversibility. Typically, this is a quantity that cannot bemore » computed explicitly for Parallel KMC, which is why we develop a posteriori estimators that have good scaling properties with respect to the size of the system. Through these estimators, we can connect the different parameters of the scheme, such as the communication time step of the parallelization, the choice of the domain decomposition, and the computational schedule, with its performance in controlling the loss of reversibility. From this point of view, the entropy production rate can be seen both as an information criterion to compare the reversibility of different parallel schemes and as a tool to diagnose reversibility issues with a particular scheme. As a demonstration, we use Sandia Lab's SPPARKS software to compare different parallelization schemes and different domain (lattice) decompositions.« less

Use of parallel computing in mass processing of laser data

NASA Astrophysics Data System (ADS)

Będkowski, J.; Bratuś, R.; Prochaska, M.; Rzonca, A.

2015-12-01

The first part of the paper includes a description of the rules used to generate the algorithm needed for the purpose of parallel computing and also discusses the origins of the idea of research on the use of graphics processors in large scale processing of laser scanning data. The next part of the paper includes the results of an efficiency assessment performed for an array of different processing options, all of which were substantially accelerated with parallel computing. The processing options were divided into the generation of orthophotos using point clouds, coloring of point clouds, transformations, and the generation of a regular grid, as well as advanced processes such as the detection of planes and edges, point cloud classification, and the analysis of data for the purpose of quality control. Most algorithms had to be formulated from scratch in the context of the requirements of parallel computing. A few of the algorithms were based on existing technology developed by the Dephos Software Company and then adapted to parallel computing in the course of this research study. Processing time was determined for each process employed for a typical quantity of data processed, which helped confirm the high efficiency of the solutions proposed and the applicability of parallel computing to the processing of laser scanning data. The high efficiency of parallel computing yields new opportunities in the creation and organization of processing methods for laser scanning data.

Exploiting Symmetry on Parallel Architectures.

NASA Astrophysics Data System (ADS)

Stiller, Lewis Benjamin

1995-01-01

This thesis describes techniques for the design of parallel programs that solve well-structured problems with inherent symmetry. Part I demonstrates the reduction of such problems to generalized matrix multiplication by a group-equivariant matrix. Fast techniques for this multiplication are described, including factorization, orbit decomposition, and Fourier transforms over finite groups. Our algorithms entail interaction between two symmetry groups: one arising at the software level from the problem's symmetry and the other arising at the hardware level from the processors' communication network. Part II illustrates the applicability of our symmetry -exploitation techniques by presenting a series of case studies of the design and implementation of parallel programs. First, a parallel program that solves chess endgames by factorization of an associated dihedral group-equivariant matrix is described. This code runs faster than previous serial programs, and discovered it a number of results. Second, parallel algorithms for Fourier transforms for finite groups are developed, and preliminary parallel implementations for group transforms of dihedral and of symmetric groups are described. Applications in learning, vision, pattern recognition, and statistics are proposed. Third, parallel implementations solving several computational science problems are described, including the direct n-body problem, convolutions arising from molecular biology, and some communication primitives such as broadcast and reduce. Some of our implementations ran orders of magnitude faster than previous techniques, and were used in the investigation of various physical phenomena.

Information criteria for quantifying loss of reversibility in parallelized KMC

NASA Astrophysics Data System (ADS)

Gourgoulias, Konstantinos; Katsoulakis, Markos A.; Rey-Bellet, Luc

2017-01-01

Parallel Kinetic Monte Carlo (KMC) is a potent tool to simulate stochastic particle systems efficiently. However, despite literature on quantifying domain decomposition errors of the particle system for this class of algorithms in the short and in the long time regime, no study yet explores and quantifies the loss of time-reversibility in Parallel KMC. Inspired by concepts from non-equilibrium statistical mechanics, we propose the entropy production per unit time, or entropy production rate, given in terms of an observable and a corresponding estimator, as a metric that quantifies the loss of reversibility. Typically, this is a quantity that cannot be computed explicitly for Parallel KMC, which is why we develop a posteriori estimators that have good scaling properties with respect to the size of the system. Through these estimators, we can connect the different parameters of the scheme, such as the communication time step of the parallelization, the choice of the domain decomposition, and the computational schedule, with its performance in controlling the loss of reversibility. From this point of view, the entropy production rate can be seen both as an information criterion to compare the reversibility of different parallel schemes and as a tool to diagnose reversibility issues with a particular scheme. As a demonstration, we use Sandia Lab's SPPARKS software to compare different parallelization schemes and different domain (lattice) decompositions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vay, Jean-Luc, E-mail: jlvay@lbl.gov; Haber, Irving; Godfrey, Brendan B.

Pseudo-spectral electromagnetic solvers (i.e. representing the fields in Fourier space) have extraordinary precision. In particular, Haber et al. presented in 1973 a pseudo-spectral solver that integrates analytically the solution over a finite time step, under the usual assumption that the source is constant over that time step. Yet, pseudo-spectral solvers have not been widely used, due in part to the difficulty for efficient parallelization owing to global communications associated with global FFTs on the entire computational domains. A method for the parallelization of electromagnetic pseudo-spectral solvers is proposed and tested on single electromagnetic pulses, and on Particle-In-Cell simulations of themore » wakefield formation in a laser plasma accelerator. The method takes advantage of the properties of the Discrete Fourier Transform, the linearity of Maxwell’s equations and the finite speed of light for limiting the communications of data within guard regions between neighboring computational domains. Although this requires a small approximation, test results show that no significant error is made on the test cases that have been presented. The proposed method opens the way to solvers combining the favorable parallel scaling of standard finite-difference methods with the accuracy advantages of pseudo-spectral methods.« less

GPU-based acceleration of computations in nonlinear finite element deformation analysis.

PubMed

Mafi, Ramin; Sirouspour, Shahin

2014-03-01

The physics of deformation for biological soft-tissue is best described by nonlinear continuum mechanics-based models, which then can be discretized by the FEM for a numerical solution. However, computational complexity of such models have limited their use in applications requiring real-time or fast response. In this work, we propose a graphic processing unit-based implementation of the FEM using implicit time integration for dynamic nonlinear deformation analysis. This is the most general formulation of the deformation analysis. It is valid for large deformations and strains and can account for material nonlinearities. The data-parallel nature and the intense arithmetic computations of nonlinear FEM equations make it particularly suitable for implementation on a parallel computing platform such as graphic processing unit. In this work, we present and compare two different designs based on the matrix-free and conventional preconditioned conjugate gradients algorithms for solving the FEM equations arising in deformation analysis. The speedup achieved with the proposed parallel implementations of the algorithms will be instrumental in the development of advanced surgical simulators and medical image registration methods involving soft-tissue deformation. Copyright © 2013 John Wiley & Sons, Ltd.

Wakefield computations for a corrugated pipe as a beam dechirper for FEL applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ng, C. K.; Bane, K. L.F.

A beam “dechirper” based on a corrugated, metallic vacuum chamber has been proposed recently to cancel residual energy chirp in a beam before it enters the undulator in a linac-based X-ray FEL. Rather than the round geometry that was originally proposed, we consider a pipe composed of two parallel plates with corrugations. The advantage is that the strength of the wake effect can be tuned by adjusting the separation of the plates. The separation of the plates is on the order of millimeters, and the corrugations are fractions of a millimeter in size. The dechirper needs to be meters longmore » in order to provide sufficient longitudinal wakefield to cancel the beam chirp. Considerable computation resources are required to determine accurately the wakefield for such a long structure with small corrugation gaps. Combining the moving window technique and parallel computing using multiple processors, the time domain module in the parallel finite-element electromagnetic suite ACE3P allows efficient determination of the wakefield through convergence studies. In this paper, we will calculate the longitudinal, dipole and quadrupole wakefields for the dechirper and compare the results with those of analytical and field matching approaches.« less

Fast parallel algorithms that compute transitive closure of a fuzzy relation

NASA Technical Reports Server (NTRS)

Kreinovich, Vladik YA.

1993-01-01

The notion of a transitive closure of a fuzzy relation is very useful for clustering in pattern recognition, for fuzzy databases, etc. The original algorithm proposed by L. Zadeh (1971) requires the computation time O(n(sup 4)), where n is the number of elements in the relation. In 1974, J. C. Dunn proposed a O(n(sup 2)) algorithm. Since we must compute n(n-1)/2 different values s(a, b) (a not equal to b) that represent the fuzzy relation, and we need at least one computational step to compute each of these values, we cannot compute all of them in less than O(n(sup 2)) steps. So, Dunn's algorithm is in this sense optimal. For small n, it is ok. However, for big n (e.g., for big databases), it is still a lot, so it would be desirable to decrease the computation time (this problem was formulated by J. Bezdek). Since this decrease cannot be done on a sequential computer, the only way to do it is to use a computer with several processors working in parallel. We show that on a parallel computer, transitive closure can be computed in time O((log(sub 2)(n))2).

Optimization of a Focusable and Rotatable Shear-Wave Periodic Permanent Magnet Electromagnetic Acoustic Transducers for Plates Inspection

PubMed Central

Qiu, Gongzhe

2017-01-01

Due to the symmetry of conventional periodic-permanent-magnet electromagnetic acoustic transducers (PPM EMATs), two shear (SH) waves can be generated and propagated simultaneously in opposite directions, which makes the signal recognition and interpretation complicatedly. Thus, this work presents a new SH wave PPM EMAT design, rotating the parallel line sources to realize the wave beam focusing in a single-direction. The theoretical model of distributed line sources was deduced firstly, and the effects of some parameters, such as the inner coil width, adjacent line sources spacing and the angle between parallel line sources, on SH wave focusing and directivity were studied mainly with the help of 3D FEM. Employing the proposed PPM EMATs, some experiments are carried out to verify the reliability of FEM simulation. The results indicate that rotating the parallel line sources can strength the wave on the closing side of line sources, decreasing the inner coil width and the adjacent line sources spacing can improve the amplitude and directivity of signals excited by transducers. Compared with traditional PPM EMATs, both the capacity of unidirectional excitation and directivity of the proposed PPM EMATs are improved significantly. PMID:29186790

Rigid-flexible coupling dynamic modeling and investigation of a redundantly actuated parallel manipulator with multiple actuation modes

NASA Astrophysics Data System (ADS)

Liang, Dong; Song, Yimin; Sun, Tao; Jin, Xueying

2017-09-01

A systematic dynamic modeling methodology is presented to develop the rigid-flexible coupling dynamic model (RFDM) of an emerging flexible parallel manipulator with multiple actuation modes. By virtue of assumed mode method, the general dynamic model of an arbitrary flexible body with any number of lumped parameters is derived in an explicit closed form, which possesses the modular characteristic. Then the completely dynamic model of system is formulated based on the flexible multi-body dynamics (FMD) theory and the augmented Lagrangian multipliers method. An approach of combining the Udwadia-Kalaba formulation with the hybrid TR-BDF2 numerical algorithm is proposed to address the nonlinear RFDM. Two simulation cases are performed to investigate the dynamic performance of the manipulator with different actuation modes. The results indicate that the redundant actuation modes can effectively attenuate vibration and guarantee higher dynamic performance compared to the traditional non-redundant actuation modes. Finally, a virtual prototype model is developed to demonstrate the validity of the presented RFDM. The systematic methodology proposed in this study can be conveniently extended for the dynamic modeling and controller design of other planar flexible parallel manipulators, especially the emerging ones with multiple actuation modes.

Fine-grained parallel RNAalifold algorithm for RNA secondary structure prediction on FPGA

PubMed Central

Xia, Fei; Dou, Yong; Zhou, Xingming; Yang, Xuejun; Xu, Jiaqing; Zhang, Yang

2009-01-01

Background In the field of RNA secondary structure prediction, the RNAalifold algorithm is one of the most popular methods using free energy minimization. However, general-purpose computers including parallel computers or multi-core computers exhibit parallel efficiency of no more than 50%. Field Programmable Gate-Array (FPGA) chips provide a new approach to accelerate RNAalifold by exploiting fine-grained custom design. Results RNAalifold shows complicated data dependences, in which the dependence distance is variable, and the dependence direction is also across two dimensions. We propose a systolic array structure including one master Processing Element (PE) and multiple slave PEs for fine grain hardware implementation on FPGA. We exploit data reuse schemes to reduce the need to load energy matrices from external memory. We also propose several methods to reduce energy table parameter size by 80%. Conclusion To our knowledge, our implementation with 16 PEs is the only FPGA accelerator implementing the complete RNAalifold algorithm. The experimental results show a factor of 12.2 speedup over the RNAalifold (ViennaPackage – 1.6.5) software for a group of aligned RNA sequences with 2981-residue running on a Personal Computer (PC) platform with Pentium 4 2.6 GHz CPU. PMID:19208138

MapReduce Based Parallel Bayesian Network for Manufacturing Quality Control

NASA Astrophysics Data System (ADS)

Zheng, Mao-Kuan; Ming, Xin-Guo; Zhang, Xian-Yu; Li, Guo-Ming

2017-09-01

Increasing complexity of industrial products and manufacturing processes have challenged conventional statistics based quality management approaches in the circumstances of dynamic production. A Bayesian network and big data analytics integrated approach for manufacturing process quality analysis and control is proposed. Based on Hadoop distributed architecture and MapReduce parallel computing model, big volume and variety quality related data generated during the manufacturing process could be dealt with. Artificial intelligent algorithms, including Bayesian network learning, classification and reasoning, are embedded into the Reduce process. Relying on the ability of the Bayesian network in dealing with dynamic and uncertain problem and the parallel computing power of MapReduce, Bayesian network of impact factors on quality are built based on prior probability distribution and modified with posterior probability distribution. A case study on hull segment manufacturing precision management for ship and offshore platform building shows that computing speed accelerates almost directly proportionally to the increase of computing nodes. It is also proved that the proposed model is feasible for locating and reasoning of root causes, forecasting of manufacturing outcome, and intelligent decision for precision problem solving. The integration of bigdata analytics and BN method offers a whole new perspective in manufacturing quality control.

Optimization of a Focusable and Rotatable Shear-Wave Periodic Permanent Magnet Electromagnetic Acoustic Transducers for Plates Inspection.

PubMed

Song, Xiaochun; Qiu, Gongzhe

2017-11-24

Due to the symmetry of conventional periodic-permanent-magnet electromagnetic acoustic transducers (PPM EMATs), two shear (SH) waves can be generated and propagated simultaneously in opposite directions, which makes the signal recognition and interpretation complicatedly. Thus, this work presents a new SH wave PPM EMAT design, rotating the parallel line sources to realize the wave beam focusing in a single-direction. The theoretical model of distributed line sources was deduced firstly, and the effects of some parameters, such as the inner coil width, adjacent line sources spacing and the angle between parallel line sources, on SH wave focusing and directivity were studied mainly with the help of 3D FEM. Employing the proposed PPM EMATs, some experiments are carried out to verify the reliability of FEM simulation. The results indicate that rotating the parallel line sources can strength the wave on the closing side of line sources, decreasing the inner coil width and the adjacent line sources spacing can improve the amplitude and directivity of signals excited by transducers. Compared with traditional PPM EMATs, both the capacity of unidirectional excitation and directivity of the proposed PPM EMATs are improved significantly.

A Parallel Decoding Algorithm for Short Polar Codes Based on Error Checking and Correcting

PubMed Central

Pan, Xiaofei; Pan, Kegang; Ye, Zhan; Gong, Chao

2014-01-01

We propose a parallel decoding algorithm based on error checking and correcting to improve the performance of the short polar codes. In order to enhance the error-correcting capacity of the decoding algorithm, we first derive the error-checking equations generated on the basis of the frozen nodes, and then we introduce the method to check the errors in the input nodes of the decoder by the solutions of these equations. In order to further correct those checked errors, we adopt the method of modifying the probability messages of the error nodes with constant values according to the maximization principle. Due to the existence of multiple solutions of the error-checking equations, we formulate a CRC-aided optimization problem of finding the optimal solution with three different target functions, so as to improve the accuracy of error checking. Besides, in order to increase the throughput of decoding, we use a parallel method based on the decoding tree to calculate probability messages of all the nodes in the decoder. Numerical results show that the proposed decoding algorithm achieves better performance than that of some existing decoding algorithms with the same code length. PMID:25540813

Comment on Gallistel: behavior theory and information theory: some parallels.

PubMed

Nevin, John A

2012-05-01

In this article, Gallistel proposes information theory as an approach to some enduring problems in the study of operant and classical conditioning. Copyright © 2012 Elsevier B.V. All rights reserved.

A High-Order Direct Solver for Helmholtz Equations with Neumann Boundary Conditions

NASA Technical Reports Server (NTRS)

Sun, Xian-He; Zhuang, Yu

1997-01-01

In this study, a compact finite-difference discretization is first developed for Helmholtz equations on rectangular domains. Special treatments are then introduced for Neumann and Neumann-Dirichlet boundary conditions to achieve accuracy and separability. Finally, a Fast Fourier Transform (FFT) based technique is used to yield a fast direct solver. Analytical and experimental results show this newly proposed solver is comparable to the conventional second-order elliptic solver when accuracy is not a primary concern, and is significantly faster than that of the conventional solver if a highly accurate solution is required. In addition, this newly proposed fourth order Helmholtz solver is parallel in nature. It is readily available for parallel and distributed computers. The compact scheme introduced in this study is likely extendible for sixth-order accurate algorithms and for more general elliptic equations.

A novel sensitivity-based method for damage detection of structures under unknown periodic excitations

NASA Astrophysics Data System (ADS)

Naseralavi, S. S.; Salajegheh, E.; Fadaee, M. J.; Salajegheh, J.

2014-06-01

This paper presents a technique for damage detection in structures under unknown periodic excitations using the transient displacement response. The method is capable of identifying the damage parameters without finding the input excitations. We first define the concept of displacement space as a linear space in which each point represents displacements of structure under an excitation and initial condition. Roughly speaking, the method is based on the fact that structural displacements under free and forced vibrations are associated with two parallel subspaces in the displacement space. Considering this novel geometrical viewpoint, an equation called kernel parallelization equation (KPE) is derived for damage detection under unknown periodic excitations and a sensitivity-based algorithm for solving KPE is proposed accordingly. The method is evaluated via three case studies under periodic excitations, which confirm the efficiency of the proposed method.

A Discretization Algorithm for Meteorological Data and its Parallelization Based on Hadoop

NASA Astrophysics Data System (ADS)

Liu, Chao; Jin, Wen; Yu, Yuting; Qiu, Taorong; Bai, Xiaoming; Zou, Shuilong

2017-10-01

In view of the large amount of meteorological observation data, the property is more and the attribute values are continuous values, the correlation between the elements is the need for the application of meteorological data, this paper is devoted to solving the problem of how to better discretize large meteorological data to more effectively dig out the hidden knowledge in meteorological data and research on the improvement of discretization algorithm for large scale data, in order to achieve data in the large meteorological data discretization for the follow-up to better provide knowledge to provide protection, a discretization algorithm based on information entropy and inconsistency of meteorological attributes is proposed and the algorithm is parallelized under Hadoop platform. Finally, the comparison test validates the effectiveness of the proposed algorithm for discretization in the area of meteorological large data.

Distributed computing methodology for training neural networks in an image-guided diagnostic application.

PubMed

Plagianakos, V P; Magoulas, G D; Vrahatis, M N

2006-03-01

Distributed computing is a process through which a set of computers connected by a network is used collectively to solve a single problem. In this paper, we propose a distributed computing methodology for training neural networks for the detection of lesions in colonoscopy. Our approach is based on partitioning the training set across multiple processors using a parallel virtual machine. In this way, interconnected computers of varied architectures can be used for the distributed evaluation of the error function and gradient values, and, thus, training neural networks utilizing various learning methods. The proposed methodology has large granularity and low synchronization, and has been implemented and tested. Our results indicate that the parallel virtual machine implementation of the training algorithms developed leads to considerable speedup, especially when large network architectures and training sets are used.

Accelerated numerical processing of electronically recorded holograms with reduced speckle noise.

PubMed

Trujillo, Carlos; Garcia-Sucerquia, Jorge

2013-09-01

The numerical reconstruction of digitally recorded holograms suffers from speckle noise. An accelerated method that uses general-purpose computing in graphics processing units to reduce that noise is shown. The proposed methodology utilizes parallelized algorithms to record, reconstruct, and superimpose multiple uncorrelated holograms of a static scene. For the best tradeoff between reduction of the speckle noise and processing time, the method records, reconstructs, and superimposes six holograms of 1024 × 1024 pixels in 68 ms; for this case, the methodology reduces the speckle noise by 58% compared with that exhibited by a single hologram. The fully parallelized method running on a commodity graphics processing unit is one order of magnitude faster than the same technique implemented on a regular CPU using its multithreading capabilities. Experimental results are shown to validate the proposal.

A dynamic system with digital lock-in-photon-counting for pharmacokinetic diffuse fluorescence tomography

NASA Astrophysics Data System (ADS)

Yin, Guoyan; Zhang, Limin; Zhang, Yanqi; Liu, Han; Du, Wenwen; Ma, Wenjuan; Zhao, Huijuan; Gao, Feng

2018-02-01

Pharmacokinetic diffuse fluorescence tomography (DFT) can describe the metabolic processes of fluorescent agents in biomedical tissue and provide helpful information for tumor differentiation. In this paper, a dynamic DFT system was developed by employing digital lock-in-photon-counting with square wave modulation, which predominates in ultra-high sensitivity and measurement parallelism. In this system, 16 frequency-encoded laser diodes (LDs) driven by self-designed light source system were distributed evenly in the imaging plane and irradiated simultaneously. Meanwhile, 16 detection fibers collected emission light in parallel by the digital lock-in-photon-counting module. The fundamental performances of the proposed system were assessed with phantom experiments in terms of stability, linearity, anti-crosstalk as well as images reconstruction. The results validated the availability of the proposed dynamic DFT system.

Contingency learning is reduced for high conflict stimuli.

PubMed

Whitehead, Peter S; Brewer, Gene A; Patwary, Nowed; Blais, Chris

2016-09-16

Recent theories have proposed that contingency learning occurs independent of control processes. These parallel processing accounts propose that behavioral effects originally thought to be products of control processes are in fact products solely of contingency learning. This view runs contrary to conflict-mediated Hebbian-learning models that posit control and contingency learning are parts of an interactive system. In this study we replicate the contingency learning effect and modify it to further test the veracity of the parallel processing accounts in comparison to conflict-mediated Hebbian-learning models. This is accomplished by manipulating conflict to test for an interaction, or lack thereof, between conflict and contingency learning. The results are consistent with conflict-mediated Hebbian-learning in that the addition of conflict reduces the magnitude of the contingency learning effect. Copyright © 2016 Elsevier B.V. All rights reserved.

A parallel adaptive quantum genetic algorithm for the controllability of arbitrary networks.

PubMed

Li, Yuhong; Gong, Guanghong; Li, Ni

2018-01-01

In this paper, we propose a novel algorithm-parallel adaptive quantum genetic algorithm-which can rapidly determine the minimum control nodes of arbitrary networks with both control nodes and state nodes. The corresponding network can be fully controlled with the obtained control scheme. We transformed the network controllability issue into a combinational optimization problem based on the Popov-Belevitch-Hautus rank condition. A set of canonical networks and a list of real-world networks were experimented. Comparison results demonstrated that the algorithm was more ideal to optimize the controllability of networks, especially those larger-size networks. We demonstrated subsequently that there were links between the optimal control nodes and some network statistical characteristics. The proposed algorithm provides an effective approach to improve the controllability optimization of large networks or even extra-large networks with hundreds of thousands nodes.

Exploration of a Permanent Magnet Synchronous Generator with Compensated Reactance Windings in Parallel Rod Configuration

NASA Astrophysics Data System (ADS)

Lyan, Oleg; Jankunas, Valdas; Guseinoviene, Eleonora; Pašilis, Aleksas; Senulis, Audrius; Knolis, Audrius; Kurt, Erol

2018-02-01

In this study, a permanent magnet synchronous generator (PMSG) topology with compensated reactance windings in parallel rod configuration is proposed to reduce the armature reactance X L and to achieve higher efficiency of PMSG. The PMSG was designed using iron-cored bifilar coil topology to overcome problems of market-dominant rotary type generators. Often the problem is a comparatively high armature reactance X L, which is usually bigger than armature resistance R a. Therefore, the topology is proposed to partially compensate or negligibly reduce the PMSG reactance. The study was performed by using finite element method (FEM) analysis and experimental investigation. FEM analysis was used to investigate magnetic field flux distribution and density in PMSG. The PMSG experimental analyses of no-load losses and electromotive force versus frequency (i.e., speed) was performed. Also terminal voltage, power output and efficiency relation with load current at different frequencies have been evaluated. The reactance of PMSG has low value and a linear relation with operating frequency. The low reactance gives a small variation of efficiency (from 90% to 95%) in a wide range of load (from 3 A to 10 A) and operation frequency (from 44 Hz to 114 Hz). The comparison of PMSG characteristics with parallel and series winding connection showed insignificant power variation. The research results showed that compensated reactance winding in parallel rod configuration in PMSG design provides lower reactance and therefore, higher efficiency under wider load and frequency variation.

Parallel efficient rate control methods for JPEG 2000

NASA Astrophysics Data System (ADS)

Martínez-del-Amor, Miguel Á.; Bruns, Volker; Sparenberg, Heiko

2017-09-01

Since the introduction of JPEG 2000, several rate control methods have been proposed. Among them, post-compression rate-distortion optimization (PCRD-Opt) is the most widely used, and the one recommended by the standard. The approach followed by this method is to first compress the entire image split in code blocks, and subsequently, optimally truncate the set of generated bit streams according to the maximum target bit rate constraint. The literature proposes various strategies on how to estimate ahead of time where a block will get truncated in order to stop the execution prematurely and save time. However, none of them have been defined bearing in mind a parallel implementation. Today, multi-core and many-core architectures are becoming popular for JPEG 2000 codecs implementations. Therefore, in this paper, we analyze how some techniques for efficient rate control can be deployed in GPUs. In order to do that, the design of our GPU-based codec is extended, allowing stopping the process at a given point. This extension also harnesses a higher level of parallelism on the GPU, leading to up to 40% of speedup with 4K test material on a Titan X. In a second step, three selected rate control methods are adapted and implemented in our parallel encoder. A comparison is then carried out, and used to select the best candidate to be deployed in a GPU encoder, which gave an extra 40% of speedup in those situations where it was really employed.

A Smart Cage With Uniform Wireless Power Distribution in 3D for Enabling Long-Term Experiments With Freely Moving Animals.

PubMed

Mirbozorgi, S Abdollah; Bahrami, Hadi; Sawan, Mohamad; Gosselin, Benoit

2016-04-01

This paper presents a novel experimental chamber with uniform wireless power distribution in 3D for enabling long-term biomedical experiments with small freely moving animal subjects. The implemented power transmission chamber prototype is based on arrays of parallel resonators and multicoil inductive links, to form a novel and highly efficient wireless power transmission system. The power transmitter unit includes several identical resonators enclosed in a scalable array of overlapping square coils which are connected in parallel to provide uniform power distribution along x and y. Moreover, the proposed chamber uses two arrays of primary resonators, facing each other, and connected in parallel to achieve uniform power distribution along the z axis. Each surface includes 9 overlapped coils connected in parallel and implemented into two layers of FR4 printed circuit board. The chamber features a natural power localization mechanism, which simplifies its implementation and ease its operation by avoiding the need for active detection and control mechanisms. A single power surface based on the proposed approach can provide a power transfer efficiency (PTE) of 69% and a power delivered to the load (PDL) of 120 mW, for a separation distance of 4 cm, whereas the complete chamber prototype provides a uniform PTE of 59% and a PDL of 100 mW in 3D, everywhere inside the chamber with a size of 27×27×16 cm(3).

CESDIS

NASA Technical Reports Server (NTRS)

1994-01-01

CESDIS, the Center of Excellence in Space Data and Information Sciences was developed jointly by NASA, Universities Space Research Association (USRA), and the University of Maryland in 1988 to focus on the design of advanced computing techniques and data systems to support NASA Earth and space science research programs. CESDIS is operated by USRA under contract to NASA. The Director, Associate Director, Staff Scientists, and administrative staff are located on-site at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The primary CESDIS mission is to increase the connection between computer science and engineering research programs at colleges and universities and NASA groups working with computer applications in Earth and space science. Research areas of primary interest at CESDIS include: 1) High performance computing, especially software design and performance evaluation for massively parallel machines; 2) Parallel input/output and data storage systems for high performance parallel computers; 3) Data base and intelligent data management systems for parallel computers; 4) Image processing; 5) Digital libraries; and 6) Data compression. CESDIS funds multiyear projects at U. S. universities and colleges. Proposals are accepted in response to calls for proposals and are selected on the basis of peer reviews. Funds are provided to support faculty and graduate students working at their home institutions. Project personnel visit Goddard during academic recess periods to attend workshops, present seminars, and collaborate with NASA scientists on research projects. Additionally, CESDIS takes on specific research tasks of shorter duration for computer science research requested by NASA Goddard scientists.

Using Coarrays to Parallelize Legacy Fortran Applications: Strategy and Case Study

DOE PAGES

Radhakrishnan, Hari; Rouson, Damian W. I.; Morris, Karla; ...

2015-01-01

This paper summarizes a strategy for parallelizing a legacy Fortran 77 program using the object-oriented (OO) and coarray features that entered Fortran in the 2003 and 2008 standards, respectively. OO programming (OOP) facilitates the construction of an extensible suite of model-verification and performance tests that drive the development. Coarray parallel programming facilitates a rapid evolution from a serial application to a parallel application capable of running on multicore processors and many-core accelerators in shared and distributed memory. We delineate 17 code modernization steps used to refactor and parallelize the program and study the resulting performance. Our initial studies were donemore » using the Intel Fortran compiler on a 32-core shared memory server. Scaling behavior was very poor, and profile analysis using TAU showed that the bottleneck in the performance was due to our implementation of a collective, sequential summation procedure. We were able to improve the scalability and achieve nearly linear speedup by replacing the sequential summation with a parallel, binary tree algorithm. We also tested the Cray compiler, which provides its own collective summation procedure. Intel provides no collective reductions. With Cray, the program shows linear speedup even in distributed-memory execution. We anticipate similar results with other compilers once they support the new collective procedures proposed for Fortran 2015.« less

Retargeting of existing FORTRAN program and development of parallel compilers

NASA Technical Reports Server (NTRS)

Agrawal, Dharma P.

1988-01-01

The software models used in implementing the parallelizing compiler for the B-HIVE multiprocessor system are described. The various models and strategies used in the compiler development are: flexible granularity model, which allows a compromise between two extreme granularity models; communication model, which is capable of precisely describing the interprocessor communication timings and patterns; loop type detection strategy, which identifies different types of loops; critical path with coloring scheme, which is a versatile scheduling strategy for any multicomputer with some associated communication costs; and loop allocation strategy, which realizes optimum overlapped operations between computation and communication of the system. Using these models, several sample routines of the AIR3D package are examined and tested. It may be noted that automatically generated codes are highly parallelized to provide the maximized degree of parallelism, obtaining the speedup up to a 28 to 32-processor system. A comparison of parallel codes for both the existing and proposed communication model, is performed and the corresponding expected speedup factors are obtained. The experimentation shows that the B-HIVE compiler produces more efficient codes than existing techniques. Work is progressing well in completing the final phase of the compiler. Numerous enhancements are needed to improve the capabilities of the parallelizing compiler.

Framework for Parallel Preprocessing of Microarray Data Using Hadoop

PubMed Central

2018-01-01

Nowadays, microarray technology has become one of the popular ways to study gene expression and diagnosis of disease. National Center for Biology Information (NCBI) hosts public databases containing large volumes of biological data required to be preprocessed, since they carry high levels of noise and bias. Robust Multiarray Average (RMA) is one of the standard and popular methods that is utilized to preprocess the data and remove the noises. Most of the preprocessing algorithms are time-consuming and not able to handle a large number of datasets with thousands of experiments. Parallel processing can be used to address the above-mentioned issues. Hadoop is a well-known and ideal distributed file system framework that provides a parallel environment to run the experiment. In this research, for the first time, the capability of Hadoop and statistical power of R have been leveraged to parallelize the available preprocessing algorithm called RMA to efficiently process microarray data. The experiment has been run on cluster containing 5 nodes, while each node has 16 cores and 16 GB memory. It compares efficiency and the performance of parallelized RMA using Hadoop with parallelized RMA using affyPara package as well as sequential RMA. The result shows the speed-up rate of the proposed approach outperforms the sequential approach and affyPara approach. PMID:29796018

Running Parallel Discrete Event Simulators on Sierra

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barnes, P. D.; Jefferson, D. R.

2015-12-03

In this proposal we consider porting the ROSS/Charm++ simulator and the discrete event models that run under its control so that they run on the Sierra architecture and make efficient use of the Volta GPUs.

Photorefractive optical fuzzy-logic processor based on grating degeneracy

NASA Astrophysics Data System (ADS)

Wu, Weishu; Yang, Changxi; Campbell, Scott; Yeh, Pochi

1995-04-01

A novel optical fuzzy-logic processor using light-induced gratings in photorefractive crystals is proposed and demonstrated. By exploiting grating degeneracy, one can easily implement parallel fuzzy-logic functions in disjunctive normal form.

Validating Proposed Learning Progressions on Force and Motion Using the Force Concept Inventory: Findings from Singapore Secondary Schools

ERIC Educational Resources Information Center

Fulmer, Gavin W.

2015-01-01

This study examines the validity of 2 proposed learning progressions on the force concept when tested using items from the Force Concept Inventory (FCI). This is the first study to compare students' performance with respect to learning progressions both for force and motion and for Newton's third law in parallel. It is also among the first studies…

Reliable Early Classification on Multivariate Time Series with Numerical and Categorical Attributes

DTIC Science & Technology

2015-05-22

design a procedure of feature extraction in REACT named MEG (Mining Equivalence classes with shapelet Generators) based on the concept of...Equivalence Classes Mining [12, 15]. MEG can efficiently and effectively generate the discriminative features. In addition, several strategies are proposed...technique of parallel computing [4] to propose a process of pa- rallel MEG for substantially reducing the computational overhead of discovering shapelet

Rethinking key–value store for parallel I/O optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kougkas, Anthony; Eslami, Hassan; Sun, Xian-He

2015-01-26

Key-value stores are being widely used as the storage system for large-scale internet services and cloud storage systems. However, they are rarely used in HPC systems, where parallel file systems are the dominant storage solution. In this study, we examine the architecture differences and performance characteristics of parallel file systems and key-value stores. We propose using key-value stores to optimize overall Input/Output (I/O) performance, especially for workloads that parallel file systems cannot handle well, such as the cases with intense data synchronization or heavy metadata operations. We conducted experiments with several synthetic benchmarks, an I/O benchmark, and a real application.more » We modeled the performance of these two systems using collected data from our experiments, and we provide a predictive method to identify which system offers better I/O performance given a specific workload. The results show that we can optimize the I/O performance in HPC systems by utilizing key-value stores.« less

Parallel and serial grouping of image elements in visual perception.

PubMed

Houtkamp, Roos; Roelfsema, Pieter R

2010-12-01

The visual system groups image elements that belong to an object and segregates them from other objects and the background. Important cues for this grouping process are the Gestalt criteria, and most theories propose that these are applied in parallel across the visual scene. Here, we find that Gestalt grouping can indeed occur in parallel in some situations, but we demonstrate that there are also situations where Gestalt grouping becomes serial. We observe substantial time delays when image elements have to be grouped indirectly through a chain of local groupings. We call this chaining process incremental grouping and demonstrate that it can occur for only a single object at a time. We suggest that incremental grouping requires the gradual spread of object-based attention so that eventually all the object's parts become grouped explicitly by an attentional labeling process. Our findings inspire a new incremental grouping theory that relates the parallel, local grouping process to feedforward processing and the serial, incremental grouping process to recurrent processing in the visual cortex.

Recognition of the optical packet header for two channels utilizing the parallel reservoir computing based on a semiconductor ring laser

NASA Astrophysics Data System (ADS)

Bao, Xiurong; Zhao, Qingchun; Yin, Hongxi; Qin, Jie

2018-05-01

In this paper, an all-optical parallel reservoir computing (RC) system with two channels for the optical packet header recognition is proposed and simulated, which is based on a semiconductor ring laser (SRL) with the characteristic of bidirectional light paths. The parallel optical loops are built through the cross-feedback of the bidirectional light paths where every optical loop can independently recognize each injected optical packet header. Two input signals are mapped and recognized simultaneously by training all-optical parallel reservoir, which is attributed to the nonlinear states in the laser. The recognition of optical packet headers for two channels from 4 bits to 32 bits is implemented through the simulation optimizing system parameters and therefore, the optimal recognition error ratio is 0. Since this structure can combine with the wavelength division multiplexing (WDM) optical packet switching network, the wavelength of each channel of optical packet headers for recognition can be different, and a better recognition result can be obtained.

New sample cell configuration for wide-frequency dielectric spectroscopy: DC to radio frequencies.

PubMed

Nakanishi, Masahiro; Sasaki, Yasutaka; Nozaki, Ryusuke

2010-12-01

A new configuration for the sample cell to be used in broadband dielectric spectroscopy is presented. A coaxial structure with a parallel plate capacitor (outward parallel plate cell: OPPC) has made it possible to extend the frequency range significantly in comparison with the frequency range of the conventional configuration. In the proposed configuration, stray inductance is significantly decreased; consequently, the upper bound of the frequency range is improved by two orders of magnitude from the upper limit of conventional parallel plate capacitor (1 MHz). Furthermore, the value of capacitance is kept high by using a parallel plate configuration. Therefore, the precision of the capacitance measurement in the lower frequency range remains sufficiently high. Finally, OPPC can cover a wide frequency range (100 Hz-1 GHz) with an appropriate admittance measuring apparatus such as an impedance or network analyzer. The OPPC and the conventional dielectric cell are compared by examining the frequency dependence of the complex permittivity for several polar liquids and polymeric films.

Optimizing a realistic large-scale frequency assignment problem using a new parallel evolutionary approach

NASA Astrophysics Data System (ADS)

Chaves-González, José M.; Vega-Rodríguez, Miguel A.; Gómez-Pulido, Juan A.; Sánchez-Pérez, Juan M.

2011-08-01

This article analyses the use of a novel parallel evolutionary strategy to solve complex optimization problems. The work developed here has been focused on a relevant real-world problem from the telecommunication domain to verify the effectiveness of the approach. The problem, known as frequency assignment problem (FAP), basically consists of assigning a very small number of frequencies to a very large set of transceivers used in a cellular phone network. Real data FAP instances are very difficult to solve due to the NP-hard nature of the problem, therefore using an efficient parallel approach which makes the most of different evolutionary strategies can be considered as a good way to obtain high-quality solutions in short periods of time. Specifically, a parallel hyper-heuristic based on several meta-heuristics has been developed. After a complete experimental evaluation, results prove that the proposed approach obtains very high-quality solutions for the FAP and beats any other result published.

Solving Partial Differential Equations in a data-driven multiprocessor environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gaudiot, J.L.; Lin, C.M.; Hosseiniyar, M.

1988-12-31

Partial differential equations can be found in a host of engineering and scientific problems. The emergence of new parallel architectures has spurred research in the definition of parallel PDE solvers. Concurrently, highly programmable systems such as data-how architectures have been proposed for the exploitation of large scale parallelism. The implementation of some Partial Differential Equation solvers (such as the Jacobi method) on a tagged token data-flow graph is demonstrated here. Asynchronous methods (chaotic relaxation) are studied and new scheduling approaches (the Token No-Labeling scheme) are introduced in order to support the implementation of the asychronous methods in a data-driven environment.more » New high-level data-flow language program constructs are introduced in order to handle chaotic operations. Finally, the performance of the program graphs is demonstrated by a deterministic simulation of a message passing data-flow multiprocessor. An analysis of the overhead in the data-flow graphs is undertaken to demonstrate the limits of parallel operations in dataflow PDE program graphs.« less

PlayStation purpura.

PubMed

Robertson, Susan J; Leonard, Jane; Chamberlain, Alex J

2010-08-01

A 16-year-old boy presented with a number of asymptomatic pigmented macules on the volar aspect of his index fingers. Dermoscopy of each macule revealed a parallel ridge pattern of homogenous reddish-brown pigment. We propose that these lesions were induced by repetitive trauma from a Sony PlayStation 3 (Sony Corporation, Tokyo, Japan) vibration feedback controller. The lesions completely resolved following abstinence from gaming over a number of weeks. Although the parallel ridge pattern is typically the hallmark for early acral lentiginous melanoma, it may be observed in a limited number of benign entities, including subcorneal haematoma.

A parallel algorithm for finding the shortest exit paths in mines

NASA Astrophysics Data System (ADS)

Jastrzab, Tomasz; Buchcik, Agata

2017-11-01

In the paper we study the problem of finding the shortest exit path in an underground mine in case of emergency. Since emergency situations, such as underground fires, can put the miners' lives at risk, the ability to quickly determine the safest exit path is crucial. We propose a parallel algorithm capable of finding the shortest path between the safe exit point and any other point in the mine. The algorithm is also able to take into account the characteristics of individual miners, to make the path determination more reliable.

Content-addressable read/write memories for image analysis

NASA Technical Reports Server (NTRS)

Snyder, W. E.; Savage, C. D.

1982-01-01

The commonly encountered image analysis problems of region labeling and clustering are found to be cases of search-and-rename problem which can be solved in parallel by a system architecture that is inherently suitable for VLSI implementation. This architecture is a novel form of content-addressable memory (CAM) which provides parallel search and update functions, allowing speed reductions down to constant time per operation. It has been proposed in related investigations by Hall (1981) that, with VLSI, CAM-based structures with enhanced instruction sets for general purpose processing will be feasible.

A novel radiation detector for removing scattered radiation in chest radiography: Monte Carlo simulation-based performance evaluation

NASA Astrophysics Data System (ADS)

Roh, Y. H.; Yoon, Y.; Kim, K.; Kim, J.; Kim, J.; Morishita, J.

2016-10-01

Scattered radiation is the main reason for the degradation of image quality and the increased patient exposure dose in diagnostic radiology. In an effort to reduce scattered radiation, a novel structure of an indirect flat panel detector has been proposed. In this study, a performance evaluation of the novel system in terms of image contrast as well as an estimation of the number of photons incident on the detector and the grid exposure factor were conducted using Monte Carlo simulations. The image contrast of the proposed system was superior to that of the no-grid system but slightly inferior to that of the parallel-grid system. The number of photons incident on the detector and the grid exposure factor of the novel system were higher than those of the parallel-grid system but lower than those of the no-grid system. The proposed system exhibited the potential for reduced exposure dose without image quality degradation; additionally, can be further improved by a structural optimization considering the manufacturer's specifications of its lead contents.

Multi-Sensor Data Fusion Identification for Shearer Cutting Conditions Based on Parallel Quasi-Newton Neural Networks and the Dempster-Shafer Theory

PubMed Central

Si, Lei; Wang, Zhongbin; Liu, Xinhua; Tan, Chao; Xu, Jing; Zheng, Kehong

2015-01-01

In order to efficiently and accurately identify the cutting condition of a shearer, this paper proposed an intelligent multi-sensor data fusion identification method using the parallel quasi-Newton neural network (PQN-NN) and the Dempster-Shafer (DS) theory. The vibration acceleration signals and current signal of six cutting conditions were collected from a self-designed experimental system and some special state features were extracted from the intrinsic mode functions (IMFs) based on the ensemble empirical mode decomposition (EEMD). In the experiment, three classifiers were trained and tested by the selected features of the measured data, and the DS theory was used to combine the identification results of three single classifiers. Furthermore, some comparisons with other methods were carried out. The experimental results indicate that the proposed method performs with higher detection accuracy and credibility than the competing algorithms. Finally, an industrial application example in the fully mechanized coal mining face was demonstrated to specify the effect of the proposed system. PMID:26580620

Parallel Computer System for 3D Visualization Stereo on GPU

NASA Astrophysics Data System (ADS)

Al-Oraiqat, Anas M.; Zori, Sergii A.

2018-03-01

This paper proposes the organization of a parallel computer system based on Graphic Processors Unit (GPU) for 3D stereo image synthesis. The development is based on the modified ray tracing method developed by the authors for fast search of tracing rays intersections with scene objects. The system allows significant increase in the productivity for the 3D stereo synthesis of photorealistic quality. The generalized procedure of 3D stereo image synthesis on the Graphics Processing Unit/Graphics Processing Clusters (GPU/GPC) is proposed. The efficiency of the proposed solutions by GPU implementation is compared with single-threaded and multithreaded implementations on the CPU. The achieved average acceleration in multi-thread implementation on the test GPU and CPU is about 7.5 and 1.6 times, respectively. Studying the influence of choosing the size and configuration of the computational Compute Unified Device Archi-tecture (CUDA) network on the computational speed shows the importance of their correct selection. The obtained experimental estimations can be significantly improved by new GPUs with a large number of processing cores and multiprocessors, as well as optimized configuration of the computing CUDA network.

An extended algebraic reconstruction technique (E-ART) for dual spectral CT.

PubMed

Zhao, Yunsong; Zhao, Xing; Zhang, Peng

2015-03-01

Compared with standard computed tomography (CT), dual spectral CT (DSCT) has many advantages for object separation, contrast enhancement, artifact reduction, and material composition assessment. But it is generally difficult to reconstruct images from polychromatic projections acquired by DSCT, because of the nonlinear relation between the polychromatic projections and the images to be reconstructed. This paper first models the DSCT reconstruction problem as a nonlinear system problem; and then extend the classic ART method to solve the nonlinear system. One feature of the proposed method is its flexibility. It fits for any scanning configurations commonly used and does not require consistent rays for different X-ray spectra. Another feature of the proposed method is its high degree of parallelism, which means that the method is suitable for acceleration on GPUs (graphic processing units) or other parallel systems. The method is validated with numerical experiments from simulated noise free and noisy data. High quality images are reconstructed with the proposed method from the polychromatic projections of DSCT. The reconstructed images are still satisfactory even if there are certain errors in the estimated X-ray spectra.

Parallel halftoning technique using dot diffusion optimization

NASA Astrophysics Data System (ADS)

Molina-Garcia, Javier; Ponomaryov, Volodymyr I.; Reyes-Reyes, Rogelio; Cruz-Ramos, Clara

2017-05-01

In this paper, a novel approach for halftone images is proposed and implemented for images that are obtained by the Dot Diffusion (DD) method. Designed technique is based on an optimization of the so-called class matrix used in DD algorithm and it consists of generation new versions of class matrix, which has no baron and near-baron in order to minimize inconsistencies during the distribution of the error. Proposed class matrix has different properties and each is designed for two different applications: applications where the inverse-halftoning is necessary, and applications where this method is not required. The proposed method has been implemented in GPU (NVIDIA GeForce GTX 750 Ti), multicore processors (AMD FX(tm)-6300 Six-Core Processor and in Intel core i5-4200U), using CUDA and OpenCV over a PC with linux. Experimental results have shown that novel framework generates a good quality of the halftone images and the inverse halftone images obtained. The simulation results using parallel architectures have demonstrated the efficiency of the novel technique when it is implemented in real-time processing.

Methodology of modeling and measuring computer architectures for plasma simulations

NASA Technical Reports Server (NTRS)

Wang, L. P. T.

1977-01-01

A brief introduction to plasma simulation using computers and the difficulties on currently available computers is given. Through the use of an analyzing and measuring methodology - SARA, the control flow and data flow of a particle simulation model REM2-1/2D are exemplified. After recursive refinements the total execution time may be greatly shortened and a fully parallel data flow can be obtained. From this data flow, a matched computer architecture or organization could be configured to achieve the computation bound of an application problem. A sequential type simulation model, an array/pipeline type simulation model, and a fully parallel simulation model of a code REM2-1/2D are proposed and analyzed. This methodology can be applied to other application problems which have implicitly parallel nature.

Soft-output decoding algorithms in iterative decoding of turbo codes

NASA Technical Reports Server (NTRS)

Benedetto, S.; Montorsi, G.; Divsalar, D.; Pollara, F.

1996-01-01

In this article, we present two versions of a simplified maximum a posteriori decoding algorithm. The algorithms work in a sliding window form, like the Viterbi algorithm, and can thus be used to decode continuously transmitted sequences obtained by parallel concatenated codes, without requiring code trellis termination. A heuristic explanation is also given of how to embed the maximum a posteriori algorithms into the iterative decoding of parallel concatenated codes (turbo codes). The performances of the two algorithms are compared on the basis of a powerful rate 1/3 parallel concatenated code. Basic circuits to implement the simplified a posteriori decoding algorithm using lookup tables, and two further approximations (linear and threshold), with a very small penalty, to eliminate the need for lookup tables are proposed.

Parallel approach for bioinspired algorithms

NASA Astrophysics Data System (ADS)

Zaporozhets, Dmitry; Zaruba, Daria; Kulieva, Nina

2018-05-01

In the paper, a probabilistic parallel approach based on the population heuristic, such as a genetic algorithm, is suggested. The authors proposed using a multithreading approach at the micro level at which new alternative solutions are generated. On each iteration, several threads that independently used the same population to generate new solutions can be started. After the work of all threads, a selection operator combines obtained results in the new population. To confirm the effectiveness of the suggested approach, the authors have developed software on the basis of which experimental computations can be carried out. The authors have considered a classic optimization problem – finding a Hamiltonian cycle in a graph. Experiments show that due to the parallel approach at the micro level, increment of running speed can be obtained on graphs with 250 and more vertices.

A convenient and accurate parallel Input/Output USB device for E-Prime.

PubMed

Canto, Rosario; Bufalari, Ilaria; D'Ausilio, Alessandro

2011-03-01

Psychological and neurophysiological experiments require the accurate control of timing and synchrony for Input/Output signals. For instance, a typical Event-Related Potential (ERP) study requires an extremely accurate synchronization of stimulus delivery with recordings. This is typically done via computer software such as E-Prime, and fast communications are typically assured by the Parallel Port (PP). However, the PP is an old and disappearing technology that, for example, is no longer available on portable computers. Here we propose a convenient USB device enabling parallel I/O capabilities. We tested this device against the PP on both a desktop and a laptop machine in different stress tests. Our data demonstrate the accuracy of our system, which suggests that it may be a good substitute for the PP with E-Prime.

Epitaxial relationship of semipolar s-plane (1101) InN grown on r-plane sapphire

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dimitrakopulos, G. P.

2012-07-02

The heteroepitaxy of semipolar s-plane (1101) InN grown directly on r-plane sapphire by plasma-assisted molecular beam epitaxy is studied using transmission electron microscopy techniques. The epitaxial relationship is determined to be (1101){sub InN} Parallel-To (1102){sub Al{sub 2O{sub 3}}}, [1120]{sub InN} Parallel-To [2021]{sub Al{sub 2O{sub 3}}}, [1102]{sub InN}{approx} Parallel-To [0221]{sub Al{sub 2O{sub 3}}}, which ensures a 0.7% misfit along [1120]{sub InN}. Two orientation variants are identified. Proposed geometrical factors contributing to the high density of basal stacking faults, partial dislocations, and sphalerite cubic pockets include the misfit accommodation and reduction, as well as the accommodation of lattice twist.

Three-dimensional vectorial multifocal arrays created by pseudo-period encoding

NASA Astrophysics Data System (ADS)

Zeng, Tingting; Chang, Chenliang; Chen, Zhaozhong; Wang, Hui-Tian; Ding, Jianping

2018-06-01

Multifocal arrays have been attracting considerable attention recently owing to their potential applications in parallel optical tweezers, parallel single-molecule orientation determination, parallel recording and multifocal multiphoton microscopy. However, the generation of vectorial multifocal arrays with a tailorable structure and polarization state remains a great challenge, and reports on multifocal arrays have hitherto been restricted either to scalar focal spots without polarization versatility or to regular arrays with fixed spacing. In this work, we propose a specific pseudo-period encoding technique to create three-dimensional (3D) vectorial multifocal arrays with the ability to manipulate the position, polarization state and intensity of each focal spot. We experimentally validated the flexibility of our approach in the generation of 3D vectorial multiple spots with polarization multiplicity and position tunability.

2D-RBUC for efficient parallel compression of residuals

NASA Astrophysics Data System (ADS)

Đurđević, Đorđe M.; Tartalja, Igor I.

2018-02-01

In this paper, we present a method for lossless compression of residuals with an efficient SIMD parallel decompression. The residuals originate from lossy or near lossless compression of height fields, which are commonly used to represent models of terrains. The algorithm is founded on the existing RBUC method for compression of non-uniform data sources. We have adapted the method to capture 2D spatial locality of height fields, and developed the data decompression algorithm for modern GPU architectures already present even in home computers. In combination with the point-level SIMD-parallel lossless/lossy high field compression method HFPaC, characterized by fast progressive decompression and seamlessly reconstructed surface, the newly proposed method trades off small efficiency degradation for a non negligible compression ratio (measured up to 91%) benefit.

Fast and Accurate Support Vector Machines on Large Scale Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vishnu, Abhinav; Narasimhan, Jayenthi; Holder, Larry

Support Vector Machines (SVM) is a supervised Machine Learning and Data Mining (MLDM) algorithm, which has become ubiquitous largely due to its high accuracy and obliviousness to dimensionality. The objective of SVM is to find an optimal boundary --- also known as hyperplane --- which separates the samples (examples in a dataset) of different classes by a maximum margin. Usually, very few samples contribute to the definition of the boundary. However, existing parallel algorithms use the entire dataset for finding the boundary, which is sub-optimal for performance reasons. In this paper, we propose a novel distributed memory algorithm to eliminatemore » the samples which do not contribute to the boundary definition in SVM. We propose several heuristics, which range from early (aggressive) to late (conservative) elimination of the samples, such that the overall time for generating the boundary is reduced considerably. In a few cases, a sample may be eliminated (shrunk) pre-emptively --- potentially resulting in an incorrect boundary. We propose a scalable approach to synchronize the necessary data structures such that the proposed algorithm maintains its accuracy. We consider the necessary trade-offs of single/multiple synchronization using in-depth time-space complexity analysis. We implement the proposed algorithm using MPI and compare it with libsvm--- de facto sequential SVM software --- which we enhance with OpenMP for multi-core/many-core parallelism. Our proposed approach shows excellent efficiency using up to 4096 processes on several large datasets such as UCI HIGGS Boson dataset and Offending URL dataset.« less

Projection-based estimation and nonuniformity correction of sensitivity profiles in phased-array surface coils.

PubMed

Yun, Sungdae; Kyriakos, Walid E; Chung, Jun-Young; Han, Yeji; Yoo, Seung-Schik; Park, Hyunwook

2007-03-01

To develop a novel approach for calculating the accurate sensitivity profiles of phased-array coils, resulting in correction of nonuniform intensity in parallel MRI. The proposed intensity-correction method estimates the accurate sensitivity profile of each channel of the phased-array coil. The sensitivity profile is estimated by fitting a nonlinear curve to every projection view through the imaged object. The nonlinear curve-fitting efficiently obtains the low-frequency sensitivity profile by eliminating the high-frequency image contents. Filtered back-projection (FBP) is then used to compute the estimates of the sensitivity profile of each channel. The method was applied to both phantom and brain images acquired from the phased-array coil. Intensity-corrected images from the proposed method had more uniform intensity than those obtained by the commonly used sum-of-squares (SOS) approach. With the use of the proposed correction method, the intensity variation was reduced to 6.1% from 13.1% of the SOS. When the proposed approach was applied to the computation of the sensitivity maps during sensitivity encoding (SENSE) reconstruction, it outperformed the SOS approach in terms of the reconstructed image uniformity. The proposed method is more effective at correcting the intensity nonuniformity of phased-array surface-coil images than the conventional SOS method. In addition, the method was shown to be resilient to noise and was successfully applied for image reconstruction in parallel imaging.

Serial and parallel power equipment with high-temperature superconducting elements

NASA Technical Reports Server (NTRS)

Bencze, Laszlo; Goebl, Nandor; Palotas, Bela; Vajda, Istvan

1995-01-01

One of the prospective, practical applications of high-temperature superconductors is the fault-current limitation in electrical energy networks. The development and testing of experimental HTSC serial current limiters have been reported in the literature. A Hungarian electric power company has proposed the development of a parallel equipment for arc suppressing both in the industrial and customers' networks. On the basis of the company's proposal the authors have outlined the scheme of a compound circuit that can be applied both for current limitation and arc suppressing. In this paper the design principles and methods of the shunt equipment are presented. These principles involve the electrical, mechanical and cryogenic aspects with the special view on the electrical and mechanical connection between the HTSC material and the current lead. Preliminary experiments and tests have been carried out to demonstrate the validity of the design principles developed. The results of the experiments and of the technological investigations are presented.

Comparative evaluation of three shaft seals proposed for high performance turbomachinery

NASA Technical Reports Server (NTRS)

Hendricks, R. C.

1982-01-01

Experimental pressure profiles and leak rate characteristics for three shaft seal prototype model configurations proposed for the space shuttle turbopump were assessed in the concentric and fully eccentric, to point of rub, positions without the effects of rotation. The parallel-cylindrical configuration has moderate to good stiffness with a higher leak rate. It represents a simple concept, but for practical reasons and possible increases in stability, all such seals should be conical-convergent. The three-stepdown-sequential, parallel-cylindrical seal is converging and represents good to possible high stiffness when fluid separation occurs, with a significant decrease in leak rate. Such seals can be very effective. The three-stepdown-sequential labyrinth seal of 33-teeth (i.e., 12-11-10 teeth from inlet to exit) provides excellent leak control but usually has very poor stiffness, depending on cavity design. The seal is complex and not recommended for dynamic control.

Demodulation method for tilted fiber Bragg grating refractometer with high sensitivity

NASA Astrophysics Data System (ADS)

Pham, Xuantung; Si, Jinhai; Chen, Tao; Wang, Ruize; Yan, Lihe; Cao, Houjun; Hou, Xun

2018-05-01

In this paper, we propose a demodulation method for refractive index (RI) sensing with tilted fiber Bragg gratings (TFBGs). It operates by monitoring the TFBG cladding mode resonance "cut-off wavelengths." The idea of a "cut-off wavelength" and its determination method are introduced. The RI sensitivities of TFBGs are significantly enhanced in certain RI ranges by using our demodulation method. The temperature-induced cross sensitivity is eliminated. We also demonstrate a parallel-double-angle TFBG (PDTFBG), in which two individual TFBGs are inscribed in the fiber core in parallel using a femtosecond laser and a phase mask. The RI sensing range of the PDTFBG is significantly broader than that of a conventional single-angle TFBG. In addition, its RI sensitivity can reach 1023.1 nm/refractive index unit in the 1.4401-1.4570 RI range when our proposed demodulation method is used.

An Advanced Framework for Improving Situational Awareness in Electric Power Grid Operation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yousu; Huang, Zhenyu; Zhou, Ning

With the deployment of new smart grid technologies and the penetration of renewable energy in power systems, significant uncertainty and variability is being introduced into power grid operation. Traditionally, the Energy Management System (EMS) operates the power grid in a deterministic mode, and thus will not be sufficient for the future control center in a stochastic environment with faster dynamics. One of the main challenges is to improve situational awareness. This paper reviews the current status of power grid operation and presents a vision of improving wide-area situational awareness for a future control center. An advanced framework, consisting of parallelmore » state estimation, state prediction, parallel contingency selection, parallel contingency analysis, and advanced visual analytics, is proposed to provide capabilities needed for better decision support by utilizing high performance computing (HPC) techniques and advanced visual analytic techniques. Research results are presented to support the proposed vision and framework.« less

The CAnadian NIRISS Unbiased Cluster Survey (CANUCS)

NASA Astrophysics Data System (ADS)

Ravindranath, Swara; NIRISS GTO Team

2017-06-01

CANUCS GTO program is a JWST spectroscopy and imaging survey of five massive galaxy clusters and ten parallel fields using the NIRISS low-resolution grisms, NIRCam imaging and NIRSpec multi-object spectroscopy. The primary goal is to understand the evolution of low mass galaxies across cosmic time. The resolved emission line maps and line ratios for many galaxies, with some at resolution of 100pc via the magnification by gravitational lensing will enable determining the spatial distribution of star formation, dust and metals. Other science goals include the detection and characterization of galaxies within the reionization epoch, using multiply-imaged lensed galaxies to constrain cluster mass distributions and dark matter substructure, and understanding star-formation suppression in the most massive galaxy clusters. In this talk I will describe the science goals of the CANUCS program. The proposed prime and parallel observations will be presented with details of the implementation of the observation strategy using JWST proposal planning tools.

Research on retailer data clustering algorithm based on Spark

NASA Astrophysics Data System (ADS)

Huang, Qiuman; Zhou, Feng

2017-03-01

Big data analysis is a hot topic in the IT field now. Spark is a high-reliability and high-performance distributed parallel computing framework for big data sets. K-means algorithm is one of the classical partition methods in clustering algorithm. In this paper, we study the k-means clustering algorithm on Spark. Firstly, the principle of the algorithm is analyzed, and then the clustering analysis is carried out on the supermarket customers through the experiment to find out the different shopping patterns. At the same time, this paper proposes the parallelization of k-means algorithm and the distributed computing framework of Spark, and gives the concrete design scheme and implementation scheme. This paper uses the two-year sales data of a supermarket to validate the proposed clustering algorithm and achieve the goal of subdividing customers, and then analyze the clustering results to help enterprises to take different marketing strategies for different customer groups to improve sales performance.

Reference datasets for bioequivalence trials in a two-group parallel design.

PubMed

Fuglsang, Anders; Schütz, Helmut; Labes, Detlew

2015-03-01

In order to help companies qualify and validate the software used to evaluate bioequivalence trials with two parallel treatment groups, this work aims to define datasets with known results. This paper puts a total 11 datasets into the public domain along with proposed consensus obtained via evaluations from six different software packages (R, SAS, WinNonlin, OpenOffice Calc, Kinetica, EquivTest). Insofar as possible, datasets were evaluated with and without the assumption of equal variances for the construction of a 90% confidence interval. Not all software packages provide functionality for the assumption of unequal variances (EquivTest, Kinetica), and not all packages can handle datasets with more than 1000 subjects per group (WinNonlin). Where results could be obtained across all packages, one showed questionable results when datasets contained unequal group sizes (Kinetica). A proposal is made for the results that should be used as validation targets.

Encoding Schemes For A Digital Optical Multiplier Using The Modified Signed-Digit Number Representation

NASA Astrophysics Data System (ADS)

Lasher, Mark E.; Henderson, Thomas B.; Drake, Barry L.; Bocker, Richard P.

1986-09-01

The modified signed-digit (MSD) number representation offers full parallel, carry-free addition. A MSD adder has been described by the authors. This paper describes how the adder can be used in a tree structure to implement an optical multiply algorithm. Three different optical schemes, involving position, polarization, and intensity encoding, are proposed for realizing the trinary logic system. When configured in the generic multiplier architecture, these schemes yield the combinatorial logic necessary to carry out the multiplication algorithm. The optical systems are essentially three dimensional arrangements composed of modular units. Of course, this modularity is important for design considerations, while the parallelism and noninterfering communication channels of optical systems are important from the standpoint of reduced complexity. The authors have also designed electronic hardware to demonstrate and model the combinatorial logic required to carry out the algorithm. The electronic and proposed optical systems will be compared in terms of complexity and speed.

Classified one-step high-radix signed-digit arithmetic units

NASA Astrophysics Data System (ADS)

Cherri, Abdallah K.

1998-08-01

High-radix number systems enable higher information storage density, less complexity, fewer system components, and fewer cascaded gates and operations. A simple one-step fully parallel high-radix signed-digit arithmetic is proposed for parallel optical computing based on new joint spatial encodings. This reduces hardware requirements and improves throughput by reducing the space-bandwidth produce needed. The high-radix signed-digit arithmetic operations are based on classifying the neighboring input digit pairs into various groups to reduce the computation rules. A new joint spatial encoding technique is developed to present both the operands and the computation rules. This technique increases the spatial bandwidth product of the spatial light modulators of the system. An optical implementation of the proposed high-radix signed-digit arithmetic operations is also presented. It is shown that our one-step trinary signed-digit and quaternary signed-digit arithmetic units are much simpler and better than all previously reported high-radix signed-digit techniques.

Rapid optimization of tension distribution for cable-driven parallel manipulators with redundant cables

NASA Astrophysics Data System (ADS)

Ouyang, Bo; Shang, Weiwei

2016-03-01

The solution of tension distributions is infinite for cable-driven parallel manipulators(CDPMs) with redundant cables. A rapid optimization method for determining the optimal tension distribution is presented. The new optimization method is primarily based on the geometry properties of a polyhedron and convex analysis. The computational efficiency of the optimization method is improved by the designed projection algorithm, and a fast algorithm is proposed to determine which two of the lines are intersected at the optimal point. Moreover, a method for avoiding the operating point on the lower tension limit is developed. Simulation experiments are implemented on a six degree-of-freedom(6-DOF) CDPM with eight cables, and the results indicate that the new method is one order of magnitude faster than the standard simplex method. The optimal distribution of tension distribution is thus rapidly established on real-time by the proposed method.

A concept of volume rendering guided search process to analyze medical data set.

PubMed

Zhou, Jianlong; Xiao, Chun; Wang, Zhiyan; Takatsuka, Masahiro

2008-03-01

This paper firstly presents an approach of parallel coordinates based parameter control panel (PCP). The PCP is used to control parameters of focal region-based volume rendering (FRVR) during data analysis. It uses a parallel coordinates style interface. Different rendering parameters represented with nodes on each axis, and renditions based on related parameters are connected using polylines to show dependencies between renditions and parameters. Based on the PCP, a concept of volume rendering guided search process is proposed. The search pipeline is divided into four phases. Different parameters of FRVR are recorded and modulated in the PCP during search phases. The concept shows that volume visualization could play the role of guiding a search process in the rendition space to help users to efficiently find local structures of interest. The usability of the proposed approach is evaluated to show its effectiveness.

The parallel globe: a powerful instrument to perform investigations of Earth’s illumination

NASA Astrophysics Data System (ADS)

Rossi, Sabrina; Giordano, Enrica; Lanciano, Nicoletta

2015-01-01

Many researchers have documented the difficulties for learners of different ages and preparations in understanding basic astronomical concepts. Traditional instructional strategies and communication media do not seem to be effective in producing meaningful understanding, or even induce misconceptions and misinterpretations. In line with recent proposals for pedagogical sequences and learning progressions about core concepts and basic procedures in physics and astronomy education, in this paper we suggest an intermediate, essential step in the teaching path from the local geocentric view of the Earth-Sun system to a heliocentric one. With this aim we present data collected over a day and a year from an instrument we call the ‘parallel globe’, a globe positioned locally homothetic to the Earth. Some analyses are suggested, in particular of the phenomenon of illumination of the Earth and its variations, that are consistent with the proposed instructional objectives.

Adaptive proxy map server for efficient vector spatial data rendering

NASA Astrophysics Data System (ADS)

Sayar, Ahmet

2013-01-01

The rapid transmission of vector map data over the Internet is becoming a bottleneck of spatial data delivery and visualization in web-based environment because of increasing data amount and limited network bandwidth. In order to improve both the transmission and rendering performances of vector spatial data over the Internet, we propose a proxy map server enabling parallel vector data fetching as well as caching to improve the performance of web-based map servers in a dynamic environment. Proxy map server is placed seamlessly anywhere between the client and the final services, intercepting users' requests. It employs an efficient parallelization technique based on spatial proximity and data density in case distributed replica exists for the same spatial data. The effectiveness of the proposed technique is proved at the end of the article by the application of creating map images enriched with earthquake seismic data records.

A Model of In vitro Plasticity at the Parallel Fiber—Molecular Layer Interneuron Synapses

PubMed Central

Lennon, William; Yamazaki, Tadashi; Hecht-Nielsen, Robert

2015-01-01

Theoretical and computational models of the cerebellum typically focus on the role of parallel fiber (PF)—Purkinje cell (PKJ) synapses for learned behavior, but few emphasize the role of the molecular layer interneurons (MLIs)—the stellate and basket cells. A number of recent experimental results suggest the role of MLIs is more important than previous models put forth. We investigate learning at PF—MLI synapses and propose a mathematical model to describe plasticity at this synapse. We perform computer simulations with this form of learning using a spiking neuron model of the MLI and show that it reproduces six in vitro experimental results in addition to simulating four novel protocols. Further, we show how this plasticity model can predict the results of other experimental protocols that are not simulated. Finally, we hypothesize what the biological mechanisms are for changes in synaptic efficacy that embody the phenomenological model proposed here. PMID:26733856

Efficient LIDAR Point Cloud Data Managing and Processing in a Hadoop-Based Distributed Framework

NASA Astrophysics Data System (ADS)

Wang, C.; Hu, F.; Sha, D.; Han, X.

2017-10-01

Light Detection and Ranging (LiDAR) is one of the most promising technologies in surveying and mapping city management, forestry, object recognition, computer vision engineer and others. However, it is challenging to efficiently storage, query and analyze the high-resolution 3D LiDAR data due to its volume and complexity. In order to improve the productivity of Lidar data processing, this study proposes a Hadoop-based framework to efficiently manage and process LiDAR data in a distributed and parallel manner, which takes advantage of Hadoop's storage and computing ability. At the same time, the Point Cloud Library (PCL), an open-source project for 2D/3D image and point cloud processing, is integrated with HDFS and MapReduce to conduct the Lidar data analysis algorithms provided by PCL in a parallel fashion. The experiment results show that the proposed framework can efficiently manage and process big LiDAR data.

Research on B Cell Algorithm for Learning to Rank Method Based on Parallel Strategy.

PubMed

Tian, Yuling; Zhang, Hongxian

2016-01-01

For the purposes of information retrieval, users must find highly relevant documents from within a system (and often a quite large one comprised of many individual documents) based on input query. Ranking the documents according to their relevance within the system to meet user needs is a challenging endeavor, and a hot research topic-there already exist several rank-learning methods based on machine learning techniques which can generate ranking functions automatically. This paper proposes a parallel B cell algorithm, RankBCA, for rank learning which utilizes a clonal selection mechanism based on biological immunity. The novel algorithm is compared with traditional rank-learning algorithms through experimentation and shown to outperform the others in respect to accuracy, learning time, and convergence rate; taken together, the experimental results show that the proposed algorithm indeed effectively and rapidly identifies optimal ranking functions.

Research on B Cell Algorithm for Learning to Rank Method Based on Parallel Strategy

PubMed Central

Tian, Yuling; Zhang, Hongxian

2016-01-01

For the purposes of information retrieval, users must find highly relevant documents from within a system (and often a quite large one comprised of many individual documents) based on input query. Ranking the documents according to their relevance within the system to meet user needs is a challenging endeavor, and a hot research topic–there already exist several rank-learning methods based on machine learning techniques which can generate ranking functions automatically. This paper proposes a parallel B cell algorithm, RankBCA, for rank learning which utilizes a clonal selection mechanism based on biological immunity. The novel algorithm is compared with traditional rank-learning algorithms through experimentation and shown to outperform the others in respect to accuracy, learning time, and convergence rate; taken together, the experimental results show that the proposed algorithm indeed effectively and rapidly identifies optimal ranking functions. PMID:27487242

A parallel 3-D discrete wavelet transform architecture using pipelined lifting scheme approach for video coding

NASA Astrophysics Data System (ADS)

Hegde, Ganapathi; Vaya, Pukhraj

2013-10-01

This article presents a parallel architecture for 3-D discrete wavelet transform (3-DDWT). The proposed design is based on the 1-D pipelined lifting scheme. The architecture is fully scalable beyond the present coherent Daubechies filter bank (9, 7). This 3-DDWT architecture has advantages such as no group of pictures restriction and reduced memory referencing. It offers low power consumption, low latency and high throughput. The computing technique is based on the concept that lifting scheme minimises the storage requirement. The application specific integrated circuit implementation of the proposed architecture is done by synthesising it using 65 nm Taiwan Semiconductor Manufacturing Company standard cell library. It offers a speed of 486 MHz with a power consumption of 2.56 mW. This architecture is suitable for real-time video compression even with large frame dimensions.

Parallel Solver for H(div) Problems Using Hybridization and AMG

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Chak S.; Vassilevski, Panayot S.

2016-01-15

In this paper, a scalable parallel solver is proposed for H(div) problems discretized by arbitrary order finite elements on general unstructured meshes. The solver is based on hybridization and algebraic multigrid (AMG). Unlike some previously studied H(div) solvers, the hybridization solver does not require discrete curl and gradient operators as additional input from the user. Instead, only some element information is needed in the construction of the solver. The hybridization results in a H1-equivalent symmetric positive definite system, which is then rescaled and solved by AMG solvers designed for H1 problems. Weak and strong scaling of the method are examinedmore » through several numerical tests. Our numerical results show that the proposed solver provides a promising alternative to ADS, a state-of-the-art solver [12], for H(div) problems. In fact, it outperforms ADS for higher order elements.« less

Parallel processing of real-time dynamic systems simulation on OSCAR (Optimally SCheduled Advanced multiprocessoR)

NASA Technical Reports Server (NTRS)

Kasahara, Hironori; Honda, Hiroki; Narita, Seinosuke

1989-01-01

Parallel processing of real-time dynamic systems simulation on a multiprocessor system named OSCAR is presented. In the simulation of dynamic systems, generally, the same calculation are repeated every time step. However, we cannot apply to Do-all or the Do-across techniques for parallel processing of the simulation since there exist data dependencies from the end of an iteration to the beginning of the next iteration and furthermore data-input and data-output are required every sampling time period. Therefore, parallelism inside the calculation required for a single time step, or a large basic block which consists of arithmetic assignment statements, must be used. In the proposed method, near fine grain tasks, each of which consists of one or more floating point operations, are generated to extract the parallelism from the calculation and assigned to processors by using optimal static scheduling at compile time in order to reduce large run time overhead caused by the use of near fine grain tasks. The practicality of the scheme is demonstrated on OSCAR (Optimally SCheduled Advanced multiprocessoR) which has been developed to extract advantageous features of static scheduling algorithms to the maximum extent.

Parallel heuristics for scalable community detection

DOE PAGES

Lu, Hao; Halappanavar, Mahantesh; Kalyanaraman, Ananth

2015-08-14

Community detection has become a fundamental operation in numerous graph-theoretic applications. Despite its potential for application, there is only limited support for community detection on large-scale parallel computers, largely owing to the irregular and inherently sequential nature of the underlying heuristics. In this paper, we present parallelization heuristics for fast community detection using the Louvain method as the serial template. The Louvain method is an iterative heuristic for modularity optimization. Originally developed in 2008, the method has become increasingly popular owing to its ability to detect high modularity community partitions in a fast and memory-efficient manner. However, the method ismore » also inherently sequential, thereby limiting its scalability. Here, we observe certain key properties of this method that present challenges for its parallelization, and consequently propose heuristics that are designed to break the sequential barrier. For evaluation purposes, we implemented our heuristics using OpenMP multithreading, and tested them over real world graphs derived from multiple application domains. Compared to the serial Louvain implementation, our parallel implementation is able to produce community outputs with a higher modularity for most of the inputs tested, in comparable number or fewer iterations, while providing real speedups of up to 16x using 32 threads.« less

Collisionless Isotropization of the Solar-wind Protons by Compressive Fluctuations and Plasma Instabilities

NASA Astrophysics Data System (ADS)

Verscharen, Daniel; Chandran, Benjamin D. G.; Klein, Kristopher G.; Quataert, Eliot

2016-11-01

Compressive fluctuations are a minor yet significant component of astrophysical plasma turbulence. In the solar wind, long-wavelength compressive slow-mode fluctuations lead to changes in {β }\\parallel {{p}}\\equiv 8π {n}{{p}}{k}{{B}}{T}\\parallel {{p}}/{B}2 and in {R}{{p}}\\equiv {T}\\perp {{p}}/{T}\\parallel {{p}}, where {T}\\perp {{p}} and {T}\\parallel {{p}} are the perpendicular and parallel temperatures of the protons, B is the magnetic field strength, and {n}{{p}} is the proton density. If the amplitude of the compressive fluctuations is large enough, {R}{{p}} crosses one or more instability thresholds for anisotropy-driven microinstabilities. The enhanced field fluctuations from these microinstabilities scatter the protons so as to reduce the anisotropy of the pressure tensor. We propose that this scattering drives the average value of {R}{{p}} away from the marginal stability boundary until the fluctuating value of {R}{{p}} stops crossing the boundary. We model this “fluctuating-anisotropy effect” using linear Vlasov-Maxwell theory to describe the large-scale compressive fluctuations. We argue that this effect can explain why, in the nearly collisionless solar wind, the average value of {R}{{p}} is close to unity.

Visual analysis of inter-process communication for large-scale parallel computing.

PubMed

Muelder, Chris; Gygi, Francois; Ma, Kwan-Liu

2009-01-01

In serial computation, program profiling is often helpful for optimization of key sections of code. When moving to parallel computation, not only does the code execution need to be considered but also communication between the different processes which can induce delays that are detrimental to performance. As the number of processes increases, so does the impact of the communication delays on performance. For large-scale parallel applications, it is critical to understand how the communication impacts performance in order to make the code more efficient. There are several tools available for visualizing program execution and communications on parallel systems. These tools generally provide either views which statistically summarize the entire program execution or process-centric views. However, process-centric visualizations do not scale well as the number of processes gets very large. In particular, the most common representation of parallel processes is a Gantt char t with a row for each process. As the number of processes increases, these charts can become difficult to work with and can even exceed screen resolution. We propose a new visualization approach that affords more scalability and then demonstrate it on systems running with up to 16,384 processes.

Characterization of robotics parallel algorithms and mapping onto a reconfigurable SIMD machine

NASA Technical Reports Server (NTRS)

Lee, C. S. G.; Lin, C. T.

1989-01-01

The kinematics, dynamics, Jacobian, and their corresponding inverse computations are six essential problems in the control of robot manipulators. Efficient parallel algorithms for these computations are discussed and analyzed. Their characteristics are identified and a scheme on the mapping of these algorithms to a reconfigurable parallel architecture is presented. Based on the characteristics including type of parallelism, degree of parallelism, uniformity of the operations, fundamental operations, data dependencies, and communication requirement, it is shown that most of the algorithms for robotic computations possess highly regular properties and some common structures, especially the linear recursive structure. Moreover, they are well-suited to be implemented on a single-instruction-stream multiple-data-stream (SIMD) computer with reconfigurable interconnection network. The model of a reconfigurable dual network SIMD machine with internal direct feedback is introduced. A systematic procedure internal direct feedback is introduced. A systematic procedure to map these computations to the proposed machine is presented. A new scheduling problem for SIMD machines is investigated and a heuristic algorithm, called neighborhood scheduling, that reorders the processing sequence of subtasks to reduce the communication time is described. Mapping results of a benchmark algorithm are illustrated and discussed.

Dynamical Generation of Quasi-Stationary Alfvenic Double Layers and Charge Holes and Unified Theory of Quasi-Static and Alfvenic Auroral Arc Formation

NASA Astrophysics Data System (ADS)

Song, Y.; Lysak, R. L.

2015-12-01

Parallel E-fields play a crucial role for the acceleration of charged particles, creating discrete aurorae. However, once the parallel electric fields are produced, they will disappear right away, unless the electric fields can be continuously generated and sustained for a fairly long time. Thus, the crucial question in auroral physics is how to generate such a powerful and self-sustained parallel electric fields which can effectively accelerate charge particles to high energy during a fairly long time. We propose that nonlinear interaction of incident and reflected Alfven wave packets in inhomogeneous auroral acceleration region can produce quasi-stationary non-propagating electromagnetic plasma structures, such as Alfvenic double layers (DLs) and Charge Holes. Such Alfvenic quasi-static structures often constitute powerful high energy particle accelerators. The Alfvenic DL consists of localized self-sustained powerful electrostatic electric fields nested in a low density cavity and surrounded by enhanced magnetic and mechanical stresses. The enhanced magnetic and velocity fields carrying the free energy serve as a local dynamo, which continuously create the electrostatic parallel electric field for a fairly long time. The generated parallel electric fields will deepen the seed low density cavity, which then further quickly boosts the stronger parallel electric fields creating both Alfvenic and quasi-static discrete aurorae. The parallel electrostatic electric field can also cause ion outflow, perpendicular ion acceleration and heating, and may excite Auroral Kilometric Radiation.

Arithmetic operations in optical computations using a modified trinary number system.

PubMed

Datta, A K; Basuray, A; Mukhopadhyay, S

1989-05-01

A modified trinary number (MTN) system is proposed in which any binary number can be expressed with the help of trinary digits (1, 0, 1 ). Arithmetic operations can be performed in parallel without the need for carry and borrow steps when binary digits are converted to the MTN system. An optical implementation of the proposed scheme that uses spatial light modulators and color-coded light signals is described.

A Fast Multiple Sampling Method for Low-Noise CMOS Image Sensors With Column-Parallel 12-bit SAR ADCs.

PubMed

Kim, Min-Kyu; Hong, Seong-Kwan; Kwon, Oh-Kyong

2015-12-26

This paper presents a fast multiple sampling method for low-noise CMOS image sensor (CIS) applications with column-parallel successive approximation register analog-to-digital converters (SAR ADCs). The 12-bit SAR ADC using the proposed multiple sampling method decreases the A/D conversion time by repeatedly converting a pixel output to 4-bit after the first 12-bit A/D conversion, reducing noise of the CIS by one over the square root of the number of samplings. The area of the 12-bit SAR ADC is reduced by using a 10-bit capacitor digital-to-analog converter (DAC) with four scaled reference voltages. In addition, a simple up/down counter-based digital processing logic is proposed to perform complex calculations for multiple sampling and digital correlated double sampling. To verify the proposed multiple sampling method, a 256 × 128 pixel array CIS with 12-bit SAR ADCs was fabricated using 0.18 μm CMOS process. The measurement results shows that the proposed multiple sampling method reduces each A/D conversion time from 1.2 μs to 0.45 μs and random noise from 848.3 μV to 270.4 μV, achieving a dynamic range of 68.1 dB and an SNR of 39.2 dB.

Design and Analysis of the Measurement Characteristics of a Bidirectional-Decoupling Over-Constrained Six-Dimensional Parallel-Mechanism Force Sensor

PubMed Central

Zhao, Tieshi; Zhao, Yanzhi; Hu, Qiangqiang; Ding, Shixing

2017-01-01

The measurement of large forces and the presence of errors due to dimensional coupling are significant challenges for multi-dimensional force sensors. To address these challenges, this paper proposes an over-constrained six-dimensional force sensor based on a parallel mechanism of steel ball structures as a measurement module. The steel ball structure can be subject to rolling friction instead of sliding friction, thus reducing the influence of friction. However, because the structure can only withstand unidirectional pressure, the application of steel balls in a six-dimensional force sensor is difficult. Accordingly, a new design of the sensor measurement structure was designed in this study. The static equilibrium and displacement compatibility equations of the sensor prototype’s over-constrained structure were established to obtain the transformation function, from which the forces in the measurement branches of the proposed sensor were then analytically derived. The sensor’s measurement characteristics were then analysed through numerical examples. Finally, these measurement characteristics were confirmed through calibration and application experiments. The measurement accuracy of the proposed sensor was determined to be 1.28%, with a maximum coupling error of 1.98%, indicating that the proposed sensor successfully overcomes the issues related to steel ball structures and provides sufficient accuracy. PMID:28867812

MrBayes tgMC3++: A High Performance and Resource-Efficient GPU-Oriented Phylogenetic Analysis Method.

PubMed

Ling, Cheng; Hamada, Tsuyoshi; Gao, Jingyang; Zhao, Guoguang; Sun, Donghong; Shi, Weifeng

2016-01-01

MrBayes is a widespread phylogenetic inference tool harnessing empirical evolutionary models and Bayesian statistics. However, the computational cost on the likelihood estimation is very expensive, resulting in undesirably long execution time. Although a number of multi-threaded optimizations have been proposed to speed up MrBayes, there are bottlenecks that severely limit the GPU thread-level parallelism of likelihood estimations. This study proposes a high performance and resource-efficient method for GPU-oriented parallelization of likelihood estimations. Instead of having to rely on empirical programming, the proposed novel decomposition storage model implements high performance data transfers implicitly. In terms of performance improvement, a speedup factor of up to 178 can be achieved on the analysis of simulated datasets by four Tesla K40 cards. In comparison to the other publicly available GPU-oriented MrBayes, the tgMC 3 ++ method (proposed herein) outperforms the tgMC 3 (v1.0), nMC 3 (v2.1.1) and oMC 3 (v1.00) methods by speedup factors of up to 1.6, 1.9 and 2.9, respectively. Moreover, tgMC 3 ++ supports more evolutionary models and gamma categories, which previous GPU-oriented methods fail to take into analysis.

Lossless data compression for improving the performance of a GPU-based beamformer.

PubMed

Lok, U-Wai; Fan, Gang-Wei; Li, Pai-Chi

2015-04-01

The powerful parallel computation ability of a graphics processing unit (GPU) makes it feasible to perform dynamic receive beamforming However, a real time GPU-based beamformer requires high data rate to transfer radio-frequency (RF) data from hardware to software memory, as well as from central processing unit (CPU) to GPU memory. There are data compression methods (e.g. Joint Photographic Experts Group (JPEG)) available for the hardware front end to reduce data size, alleviating the data transfer requirement of the hardware interface. Nevertheless, the required decoding time may even be larger than the transmission time of its original data, in turn degrading the overall performance of the GPU-based beamformer. This article proposes and implements a lossless compression-decompression algorithm, which enables in parallel compression and decompression of data. By this means, the data transfer requirement of hardware interface and the transmission time of CPU to GPU data transfers are reduced, without sacrificing image quality. In simulation results, the compression ratio reached around 1.7. The encoder design of our lossless compression approach requires low hardware resources and reasonable latency in a field programmable gate array. In addition, the transmission time of transferring data from CPU to GPU with the parallel decoding process improved by threefold, as compared with transferring original uncompressed data. These results show that our proposed lossless compression plus parallel decoder approach not only mitigate the transmission bandwidth requirement to transfer data from hardware front end to software system but also reduce the transmission time for CPU to GPU data transfer. © The Author(s) 2014.

Statistical evaluation of synchronous spike patterns extracted by frequent item set mining

PubMed Central

Torre, Emiliano; Picado-Muiño, David; Denker, Michael; Borgelt, Christian; Grün, Sonja

2013-01-01

We recently proposed frequent itemset mining (FIM) as a method to perform an optimized search for patterns of synchronous spikes (item sets) in massively parallel spike trains. This search outputs the occurrence count (support) of individual patterns that are not trivially explained by the counts of any superset (closed frequent item sets). The number of patterns found by FIM makes direct statistical tests infeasible due to severe multiple testing. To overcome this issue, we proposed to test the significance not of individual patterns, but instead of their signatures, defined as the pairs of pattern size z and support c. Here, we derive in detail a statistical test for the significance of the signatures under the null hypothesis of full independence (pattern spectrum filtering, PSF) by means of surrogate data. As a result, injected spike patterns that mimic assembly activity are well detected, yielding a low false negative rate. However, this approach is prone to additionally classify patterns resulting from chance overlap of real assembly activity and background spiking as significant. These patterns represent false positives with respect to the null hypothesis of having one assembly of given signature embedded in otherwise independent spiking activity. We propose the additional method of pattern set reduction (PSR) to remove these false positives by conditional filtering. By employing stochastic simulations of parallel spike trains with correlated activity in form of injected spike synchrony in subsets of the neurons, we demonstrate for a range of parameter settings that the analysis scheme composed of FIM, PSF and PSR allows to reliably detect active assemblies in massively parallel spike trains. PMID:24167487

A cascadable circular concentrator with parallel compressed structure for increasing the energy density

NASA Astrophysics Data System (ADS)

Ku, Nai-Lun; Chen, Yi-Yung; Hsieh, Wei-Che; Whang, Allen Jong-Woei

2012-02-01

Due to the energy crisis, the principle of green energy gains popularity. This leads the increasing interest in renewable energy such as solar energy. Thus, how to collect the sunlight for indoor illumination becomes our ultimate target. With the environmental awareness increasing, we use the nature light as the light source. Then we start to devote the development of solar collecting system. The Natural Light Guiding System includes three parts, collecting, transmitting and lighting part. The idea of our solar collecting system design is a concept for combining the buildings with a combination of collecting modules. Therefore, we can use it anyplace where the sunlight can directly impinges on buildings with collecting elements. In the meantime, while collecting the sunlight with high efficiency, we can transmit the sunlight into indoor through shorter distance zone by light pipe where we needs the light. We proposed a novel design including disk-type collective lens module. With the design, we can let the incident light and exit light be parallel and compressed. By the parallel and compressed design, we make every output light become compressed in the proposed optical structure. In this way, we can increase the ratio about light compression, get the better efficiency and let the energy distribution more uniform for indoor illumination. By the definition of "KPI" as an performance index about light density as following: lm/(mm)2, the simulation results show that the proposed Concentrator is 40,000,000 KPI much better than the 800,000 KPI measured from the traditional ones.

Method for six-legged robot stepping on obstacles by indirect force estimation

NASA Astrophysics Data System (ADS)

Xu, Yilin; Gao, Feng; Pan, Yang; Chai, Xun

2016-07-01

Adaptive gaits for legged robots often requires force sensors installed on foot-tips, however impact, temperature or humidity can affect or even damage those sensors. Efforts have been made to realize indirect force estimation on the legged robots using leg structures based on planar mechanisms. Robot Octopus III is a six-legged robot using spatial parallel mechanism(UP-2UPS) legs. This paper proposed a novel method to realize indirect force estimation on walking robot based on a spatial parallel mechanism. The direct kinematics model and the inverse kinematics model are established. The force Jacobian matrix is derived based on the kinematics model. Thus, the indirect force estimation model is established. Then, the relation between the output torques of the three motors installed on one leg to the external force exerted on the foot tip is described. Furthermore, an adaptive tripod static gait is designed. The robot alters its leg trajectory to step on obstacles by using the proposed adaptive gait. Both the indirect force estimation model and the adaptive gait are implemented and optimized in a real time control system. An experiment is carried out to validate the indirect force estimation model. The adaptive gait is tested in another experiment. Experiment results show that the robot can successfully step on a 0.2 m-high obstacle. This paper proposes a novel method to overcome obstacles for the six-legged robot using spatial parallel mechanism legs and to avoid installing the electric force sensors in harsh environment of the robot's foot tips.

Rubus: A compiler for seamless and extensible parallelism.

PubMed

Adnan, Muhammad; Aslam, Faisal; Nawaz, Zubair; Sarwar, Syed Mansoor

2017-01-01

Nowadays, a typical processor may have multiple processing cores on a single chip. Furthermore, a special purpose processing unit called Graphic Processing Unit (GPU), originally designed for 2D/3D games, is now available for general purpose use in computers and mobile devices. However, the traditional programming languages which were designed to work with machines having single core CPUs, cannot utilize the parallelism available on multi-core processors efficiently. Therefore, to exploit the extraordinary processing power of multi-core processors, researchers are working on new tools and techniques to facilitate parallel programming. To this end, languages like CUDA and OpenCL have been introduced, which can be used to write code with parallelism. The main shortcoming of these languages is that programmer needs to specify all the complex details manually in order to parallelize the code across multiple cores. Therefore, the code written in these languages is difficult to understand, debug and maintain. Furthermore, to parallelize legacy code can require rewriting a significant portion of code in CUDA or OpenCL, which can consume significant time and resources. Thus, the amount of parallelism achieved is proportional to the skills of the programmer and the time spent in code optimizations. This paper proposes a new open source compiler, Rubus, to achieve seamless parallelism. The Rubus compiler relieves the programmer from manually specifying the low-level details. It analyses and transforms a sequential program into a parallel program automatically, without any user intervention. This achieves massive speedup and better utilization of the underlying hardware without a programmer's expertise in parallel programming. For five different benchmarks, on average a speedup of 34.54 times has been achieved by Rubus as compared to Java on a basic GPU having only 96 cores. Whereas, for a matrix multiplication benchmark the average execution speedup of 84 times has been achieved by Rubus on the same GPU. Moreover, Rubus achieves this performance without drastically increasing the memory footprint of a program.

Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment.

PubMed

Lee, Wei-Po; Hsiao, Yu-Ting; Hwang, Wei-Che

2014-01-16

To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high quality solutions can be obtained within relatively short time. This integrated approach is a promising way for inferring large networks.

Rubus: A compiler for seamless and extensible parallelism

PubMed Central

Adnan, Muhammad; Aslam, Faisal; Sarwar, Syed Mansoor

2017-01-01

Nowadays, a typical processor may have multiple processing cores on a single chip. Furthermore, a special purpose processing unit called Graphic Processing Unit (GPU), originally designed for 2D/3D games, is now available for general purpose use in computers and mobile devices. However, the traditional programming languages which were designed to work with machines having single core CPUs, cannot utilize the parallelism available on multi-core processors efficiently. Therefore, to exploit the extraordinary processing power of multi-core processors, researchers are working on new tools and techniques to facilitate parallel programming. To this end, languages like CUDA and OpenCL have been introduced, which can be used to write code with parallelism. The main shortcoming of these languages is that programmer needs to specify all the complex details manually in order to parallelize the code across multiple cores. Therefore, the code written in these languages is difficult to understand, debug and maintain. Furthermore, to parallelize legacy code can require rewriting a significant portion of code in CUDA or OpenCL, which can consume significant time and resources. Thus, the amount of parallelism achieved is proportional to the skills of the programmer and the time spent in code optimizations. This paper proposes a new open source compiler, Rubus, to achieve seamless parallelism. The Rubus compiler relieves the programmer from manually specifying the low-level details. It analyses and transforms a sequential program into a parallel program automatically, without any user intervention. This achieves massive speedup and better utilization of the underlying hardware without a programmer’s expertise in parallel programming. For five different benchmarks, on average a speedup of 34.54 times has been achieved by Rubus as compared to Java on a basic GPU having only 96 cores. Whereas, for a matrix multiplication benchmark the average execution speedup of 84 times has been achieved by Rubus on the same GPU. Moreover, Rubus achieves this performance without drastically increasing the memory footprint of a program. PMID:29211758

Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment

PubMed Central

2014-01-01

Background To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. Results This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Conclusions Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high quality solutions can be obtained within relatively short time. This integrated approach is a promising way for inferring large networks. PMID:24428926

Electrode pattern design for GaAs betavoltaic batteries

NASA Astrophysics Data System (ADS)

Haiyang, Chen; Jianhua, Yin; Darang, Li

2011-08-01

The sensitivities of betavoltaic batteries and photovoltaic batteries to series and parallel resistance are studied. Based on the study, an electrode pattern design principle of GaAs betavoltaic batteries is proposed. GaAs PIN junctions with and without the proposed electrode pattern are fabricated and measured under the illumination of 63Ni. Results show that the proposed electrode can reduce the backscattering and shadowing for the beta particles from 63Ni to increase the GaAs betavoltaic battery short circuit currents effectively but has little impact on the fill factors and ideal factors.

Implementation of High Time Delay Accuracy of Ultrasonic Phased Array Based on Interpolation CIC Filter

PubMed Central

Liu, Peilu; Li, Xinghua; Li, Haopeng; Su, Zhikun; Zhang, Hongxu

2017-01-01

In order to improve the accuracy of ultrasonic phased array focusing time delay, analyzing the original interpolation Cascade-Integrator-Comb (CIC) filter, an 8× interpolation CIC filter parallel algorithm was proposed, so that interpolation and multichannel decomposition can simultaneously process. Moreover, we summarized the general formula of arbitrary multiple interpolation CIC filter parallel algorithm and established an ultrasonic phased array focusing time delay system based on 8× interpolation CIC filter parallel algorithm. Improving the algorithmic structure, 12.5% of addition and 29.2% of multiplication was reduced, meanwhile the speed of computation is still very fast. Considering the existing problems of the CIC filter, we compensated the CIC filter; the compensated CIC filter’s pass band is flatter, the transition band becomes steep, and the stop band attenuation increases. Finally, we verified the feasibility of this algorithm on Field Programming Gate Array (FPGA). In the case of system clock is 125 MHz, after 8× interpolation filtering and decomposition, time delay accuracy of the defect echo becomes 1 ns. Simulation and experimental results both show that the algorithm we proposed has strong feasibility. Because of the fast calculation, small computational amount and high resolution, this algorithm is especially suitable for applications with high time delay accuracy and fast detection. PMID:29023385

Implementation of High Time Delay Accuracy of Ultrasonic Phased Array Based on Interpolation CIC Filter.

PubMed

Liu, Peilu; Li, Xinghua; Li, Haopeng; Su, Zhikun; Zhang, Hongxu

2017-10-12

In order to improve the accuracy of ultrasonic phased array focusing time delay, analyzing the original interpolation Cascade-Integrator-Comb (CIC) filter, an 8× interpolation CIC filter parallel algorithm was proposed, so that interpolation and multichannel decomposition can simultaneously process. Moreover, we summarized the general formula of arbitrary multiple interpolation CIC filter parallel algorithm and established an ultrasonic phased array focusing time delay system based on 8× interpolation CIC filter parallel algorithm. Improving the algorithmic structure, 12.5% of addition and 29.2% of multiplication was reduced, meanwhile the speed of computation is still very fast. Considering the existing problems of the CIC filter, we compensated the CIC filter; the compensated CIC filter's pass band is flatter, the transition band becomes steep, and the stop band attenuation increases. Finally, we verified the feasibility of this algorithm on Field Programming Gate Array (FPGA). In the case of system clock is 125 MHz, after 8× interpolation filtering and decomposition, time delay accuracy of the defect echo becomes 1 ns. Simulation and experimental results both show that the algorithm we proposed has strong feasibility. Because of the fast calculation, small computational amount and high resolution, this algorithm is especially suitable for applications with high time delay accuracy and fast detection.

Multiscale asymmetric orthogonal wavelet kernel for linear programming support vector learning and nonlinear dynamic systems identification.

PubMed

Lu, Zhao; Sun, Jing; Butts, Kenneth

2014-05-01

Support vector regression for approximating nonlinear dynamic systems is more delicate than the approximation of indicator functions in support vector classification, particularly for systems that involve multitudes of time scales in their sampled data. The kernel used for support vector learning determines the class of functions from which a support vector machine can draw its solution, and the choice of kernel significantly influences the performance of a support vector machine. In this paper, to bridge the gap between wavelet multiresolution analysis and kernel learning, the closed-form orthogonal wavelet is exploited to construct new multiscale asymmetric orthogonal wavelet kernels for linear programming support vector learning. The closed-form multiscale orthogonal wavelet kernel provides a systematic framework to implement multiscale kernel learning via dyadic dilations and also enables us to represent complex nonlinear dynamics effectively. To demonstrate the superiority of the proposed multiscale wavelet kernel in identifying complex nonlinear dynamic systems, two case studies are presented that aim at building parallel models on benchmark datasets. The development of parallel models that address the long-term/mid-term prediction issue is more intricate and challenging than the identification of series-parallel models where only one-step ahead prediction is required. Simulation results illustrate the effectiveness of the proposed multiscale kernel learning.

Increased performance in the short-term water demand forecasting through the use of a parallel adaptive weighting strategy

NASA Astrophysics Data System (ADS)

Sardinha-Lourenço, A.; Andrade-Campos, A.; Antunes, A.; Oliveira, M. S.

2018-03-01

Recent research on water demand short-term forecasting has shown that models using univariate time series based on historical data are useful and can be combined with other prediction methods to reduce errors. The behavior of water demands in drinking water distribution networks focuses on their repetitive nature and, under meteorological conditions and similar consumers, allows the development of a heuristic forecast model that, in turn, combined with other autoregressive models, can provide reliable forecasts. In this study, a parallel adaptive weighting strategy of water consumption forecast for the next 24-48 h, using univariate time series of potable water consumption, is proposed. Two Portuguese potable water distribution networks are used as case studies where the only input data are the consumption of water and the national calendar. For the development of the strategy, the Autoregressive Integrated Moving Average (ARIMA) method and a short-term forecast heuristic algorithm are used. Simulations with the model showed that, when using a parallel adaptive weighting strategy, the prediction error can be reduced by 15.96% and the average error by 9.20%. This reduction is important in the control and management of water supply systems. The proposed methodology can be extended to other forecast methods, especially when it comes to the availability of multiple forecast models.

General design approach and practical realization of decoupling matrices for parallel transmission coils.

PubMed

Mahmood, Zohaib; McDaniel, Patrick; Guérin, Bastien; Keil, Boris; Vester, Markus; Adalsteinsson, Elfar; Wald, Lawrence L; Daniel, Luca

2016-07-01

In a coupled parallel transmit (pTx) array, the power delivered to a channel is partially distributed to other channels because of coupling. This power is dissipated in circulators resulting in a significant reduction in power efficiency. In this study, a technique for designing robust decoupling matrices interfaced between the RF amplifiers and the coils is proposed. The decoupling matrices ensure that most forward power is delivered to the load without loss of encoding capabilities of the pTx array. The decoupling condition requires that the impedance matrix seen by the power amplifiers is a diagonal matrix whose entries match the characteristic impedance of the power amplifiers. In this work, the impedance matrix of the coupled coils is diagonalized by a successive multiplication by its eigenvectors. A general design procedure and software are developed to generate automatically the hardware that implements diagonalization using passive components. The general design method is demonstrated by decoupling two example parallel transmit arrays. Our decoupling matrices achieve better than -20 db decoupling in both cases. A robust framework for designing decoupling matrices for pTx arrays is presented and validated. The proposed decoupling strategy theoretically scales to any arbitrary number of channels. Magn Reson Med 76:329-339, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Study of Contactless Power Supply for Spindle Ultrasonic Vibrator

NASA Astrophysics Data System (ADS)

Chen, T. R.; Lee, Y. L.; Liu, H. T.; Chen, S. M.; Chang, H. Z.

2017-11-01

In this study, a contactless power supply for the ultrasonic motor on the spindle is proposed. The proposed power supply is composed of a series-parallel resonant circuit and a cylindrical contactless transformer. Based on the study and rotation experiments, it can be seen that the proposed power supply can both provide a stable ac power with 25 kHz / 70 V to the ultrasonic motor. When the output power is 250 W, the efficiency of the proposed supply is 89.8 % in respectively rotation tests. When the output power is more than 150 W, the efficiency of the proposed supply is higher than 80 % within the rated output power range.

An asymptotic-preserving Lagrangian algorithm for the time-dependent anisotropic heat transport equation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chacon, Luis; del-Castillo-Negrete, Diego; Hauck, Cory D.

2014-09-01

We propose a Lagrangian numerical algorithm for a time-dependent, anisotropic temperature transport equation in magnetized plasmas in the large guide field regime. The approach is based on an analytical integral formal solution of the parallel (i.e., along the magnetic field) transport equation with sources, and it is able to accommodate both local and non-local parallel heat flux closures. The numerical implementation is based on an operator-split formulation, with two straightforward steps: a perpendicular transport step (including sources), and a Lagrangian (field-line integral) parallel transport step. Algorithmically, the first step is amenable to the use of modern iterative methods, while themore » second step has a fixed cost per degree of freedom (and is therefore scalable). Accuracy-wise, the approach is free from the numerical pollution introduced by the discrete parallel transport term when the perpendicular to parallel transport coefficient ratio X ⊥ /X ∥ becomes arbitrarily small, and is shown to capture the correct limiting solution when ε = X⊥L 2 ∥/X1L 2 ⊥ → 0 (with L∥∙ L⊥ , the parallel and perpendicular diffusion length scales, respectively). Therefore, the approach is asymptotic-preserving. We demonstrate the capabilities of the scheme with several numerical experiments with varying magnetic field complexity in two dimensions, including the case of transport across a magnetic island.« less

Commodity cluster and hardware-based massively parallel implementations of hyperspectral imaging algorithms

NASA Astrophysics Data System (ADS)

Plaza, Antonio; Chang, Chein-I.; Plaza, Javier; Valencia, David

2006-05-01

The incorporation of hyperspectral sensors aboard airborne/satellite platforms is currently producing a nearly continual stream of multidimensional image data, and this high data volume has soon introduced new processing challenges. The price paid for the wealth spatial and spectral information available from hyperspectral sensors is the enormous amounts of data that they generate. Several applications exist, however, where having the desired information calculated quickly enough for practical use is highly desirable. High computing performance of algorithm analysis is particularly important in homeland defense and security applications, in which swift decisions often involve detection of (sub-pixel) military targets (including hostile weaponry, camouflage, concealment, and decoys) or chemical/biological agents. In order to speed-up computational performance of hyperspectral imaging algorithms, this paper develops several fast parallel data processing techniques. Techniques include four classes of algorithms: (1) unsupervised classification, (2) spectral unmixing, and (3) automatic target recognition, and (4) onboard data compression. A massively parallel Beowulf cluster (Thunderhead) at NASA's Goddard Space Flight Center in Maryland is used to measure parallel performance of the proposed algorithms. In order to explore the viability of developing onboard, real-time hyperspectral data compression algorithms, a Xilinx Virtex-II field programmable gate array (FPGA) is also used in experiments. Our quantitative and comparative assessment of parallel techniques and strategies may help image analysts in selection of parallel hyperspectral algorithms for specific applications.

Parallel computation of transverse wakes in linear colliders

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhan, Xiaowei; Ko, Kwok

1996-11-01

SLAC has proposed the detuned structure (DS) as one possible design to control the emittance growth of long bunch trains due to transverse wakefields in the Next Linear Collider (NLC). The DS consists of 206 cells with tapering from cell to cell of the order of few microns to provide Gaussian detuning of the dipole modes. The decoherence of these modes leads to two orders of magnitude reduction in wakefield experienced by the trailing bunch. To model such a large heterogeneous structure realistically is impractical with finite-difference codes using structured grids. The authors have calculated the wakefield in the DSmore » on a parallel computer with a finite-element code using an unstructured grid. The parallel implementation issues are presented along with simulation results that include contributions from higher dipole bands and wall dissipation.« less

An architecture for real-time vision processing

NASA Technical Reports Server (NTRS)

Chien, Chiun-Hong

1994-01-01

To study the feasibility of developing an architecture for real time vision processing, a task queue server and parallel algorithms for two vision operations were designed and implemented on an i860-based Mercury Computing System 860VS array processor. The proposed architecture treats each vision function as a task or set of tasks which may be recursively divided into subtasks and processed by multiple processors coordinated by a task queue server accessible by all processors. Each idle processor subsequently fetches a task and associated data from the task queue server for processing and posts the result to shared memory for later use. Load balancing can be carried out within the processing system without the requirement for a centralized controller. The author concludes that real time vision processing cannot be achieved without both sequential and parallel vision algorithms and a good parallel vision architecture.

Parallel architecture for rapid image generation and analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nerheim, R.J.

1987-01-01

A multiprocessor architecture inspired by the Disney multiplane camera is proposed. For many applications, this approach produces a natural mapping of processors to objects in a scene. Such a mapping promotes parallelism and reduces the hidden-surface work with minimal interprocessor communication and low-overhead cost. Existing graphics architectures store the final picture as a monolithic entity. The architecture here stores each object's image separately. It assembles the final composite picture from component images only when the video display needs to be refreshed. This organization simplifies the work required to animate moving objects that occlude other objects. In addition, the architecture hasmore » multiple processors that generate the component images in parallel. This further shortens the time needed to create a composite picture. In addition to generating images for animation, the architecture has the ability to decompose images.« less

Highly accelerated cardiac cine parallel MRI using low-rank matrix completion and partial separability model

NASA Astrophysics Data System (ADS)

Lyu, Jingyuan; Nakarmi, Ukash; Zhang, Chaoyi; Ying, Leslie

2016-05-01

This paper presents a new approach to highly accelerated dynamic parallel MRI using low rank matrix completion, partial separability (PS) model. In data acquisition, k-space data is moderately randomly undersampled at the center kspace navigator locations, but highly undersampled at the outer k-space for each temporal frame. In reconstruction, the navigator data is reconstructed from undersampled data using structured low-rank matrix completion. After all the unacquired navigator data is estimated, the partial separable model is used to obtain partial k-t data. Then the parallel imaging method is used to acquire the entire dynamic image series from highly undersampled data. The proposed method has shown to achieve high quality reconstructions with reduction factors up to 31, and temporal resolution of 29ms, when the conventional PS method fails.