Search Results for "parallel computing" - Page 3

Showing 128 open source projects for "parallel computing"

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  • 1

    CUDA-MEME

    Ultrafast scalable motif discovery algorithm using GPU computing

    mCUDA-MEME is a well-established ultrafast scalable motif discovery algorithm based on MEME (version 4.4.0) algorithm for multiple GPUs using a hybrid combination of CUDA, MPI and OpenMP parallel programming models. This algorithm is a further extension of CUDA-MEME (based on MEME version 3.5.4) with respect to accuracy and speed and has been tested on a GPU cluster with eight compute nodes and two Fermi-based Tesla S2050 (and Tesla-based Tesla S1070) quad-GPU computing systems, running the Linux OS with the MPICH2 library. ...
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  • 2
    Chapel

    Chapel

    a Productive Parallel Programming Language

    Chapel is an emerging parallel programming language whose design and development are being led by HPE in collaboration with academia, computing labs, and industry. Chapel's goal is to improve the productivity of parallel programmers, from laptops to supercomputers. **Please note that Chapel development has moved to GitHub**
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  • 3
    QuickRNASeq

    QuickRNASeq

    A pipeline for large scale RNA-seq data analysis

    We have implemented QuickRNASeq, an open-source based pipeline for large scale RNA-seq data analysis. QuickRNASeq takes advantage of parallel computing resources, a careful selection of previously published algorithms for RNA-seq read mapping, counting and quality control, and a three-stage strategy to build a fully automated workflow. We also implemented built-in functionalities to detect sample swapping or mislabeling in large-scale RNA-seq studies. Our pipeline significantly lifts large-scale RNA-seq data analysis to the next level of automation and visualization. ...
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  • 4
    PyCNN

    PyCNN

    Image Processing with Cellular Neural Networks in Python

    Image Processing with Cellular Neural Networks in Python. Cellular Neural Networks (CNN) are a parallel computing paradigm that was first proposed in 1988. Cellular neural networks are similar to neural networks, with the difference that communication is allowed only between neighboring units. Image Processing is one of its applications. CNN processors were designed to perform image processing; specifically, the original application of CNN processors was to perform real-time ultra-high frame-rate (>10,000 frame/s) processing unachievable by digital processors.
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  • 5

    Advanced Simulation Library

    Free multiphysics simulation software package

    ...Its computational engine is based, among others, on the Lattice Boltzmann Methods (http://en.wikipedia.org/wiki/Lattice_Boltzmann_methods) and is written in OpenCL (http://en.wikipedia.org/wiki/OpenCL) which enable extraordinarily efficient deployment (http://asl.org.il/benchmarks) on a variety of massively parallel architectures, ranging from inexpensive FPGAs, DSPs and GPUs up to heterogeneous clusters and supercomputers. The engine is hidden entirely behind C++ classes, so that no OpenCL knowledge is required from application programmers. ASL can be utilized to model various coupled physical and chemical phenomena and employed in a multitude of fields: computational fluid dynamics, virtual sensing, industrial process data validation and reconciliation, image-guided surgery, computer-aided engineering, high-performance scientific computing, etc..
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  • 6
    4. Bagging Nadaraya Watson Estim. (HPC)

    4. Bagging Nadaraya Watson Estim. (HPC)

    Shell/R program to perform Bagging of the Nadaraya Watson Estimator

    Shell/R program which performs bagging of the Nadaraya Watson Kernel estimator by parallel computing
    Downloads: 1 This Week
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  • 7

    Parallel Quicksort with MPI

    Parallel Quicksort with MPI

    ...It was invented by C.A.R Hoare in 1961and is using the divide-and-conquer strategy for solving problems [3]. Its partitioning aspects make QuickSort amenable to parallelization using task parallelism. MPI is a message passing interface library allowing parallel computing by sending codes to multiple processors, and can therefore be easily used on most multi-core computers available today. The main aim of this study is to implement the QuickSort algorithm using the Open MPI library and therefore compare the sequential with the parallel execution.
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  • 8
    2. Tune kernel Ridge MM (HPC parallel)

    2. Tune kernel Ridge MM (HPC parallel)

    Shell/R program which tunes kernel Ridge by parallel computing

    A shell/R program for HPC Linux clusters which allows users to estimate the optimal rate of decay parameter for kernel Ridge regression, within the mixed model framework, for prediction. The optimal rate of decay is estimated using K-folds cross validation parallelized using cluster nodes.
    Downloads: 1 This Week
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  • 9

    PanCGP

    PanCGP: Pangenome and Comparative Genome Analysis Pipeline tool

    Pan-genome and Comparative Genome analysis Pipeline tool is a high performance parallel computing analysis tool. The aim of developing this high performance and scalable pipeline is to reduce the time cost of calculating the pan-genomes from the given dataset of protein sequences of bacterial strains. The pipeline is able to compute pan-genome analysis from unpublished data-sets as well. Those results are interpreted in the form of pan-genome, core genome/proteins, dispensable genes/proteins, unique/strain-specific genes/proteins, new gene/protein families and total number of genes per strain of the specie. ...
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  • 10

    SAT-Assembler

    Scalable and accurate targeted gene assembly for large-scale NGS data

    ...It recovers genes from gene families of particular interest to biologists with high coverage, low chimera rate, and extremely low memory usage compared with exiting gene assembly tools. Moreover, it is naturally compatible with parallel computing platforms.
    Downloads: 1 This Week
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  • 11

    Polaris CFD

    Aerodynamics simulations based on gas kinetics

    Polaris CFD is a complete CFD software suite for Aerodynamics simulations created by Alta Dynamics. It is validated to provided accurate results for both internal and external flow problems. Its viewer is built on ParaView for pre and post processing.
    Downloads: 1 This Week
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  • 12
    Bat2015

    Bat2015

    Bachelor of Science (Informatik)

    ...With a focus on the MILP methods we implement a load balancing and speed up the solving process in a multiplicative way. Sometimes we have super-linear speedup with a small set of hardware. With a splitting of problems, parallel computing and distributing the actual best solution to all running processes we solve CBP much faster than a sequential processing can do.
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  • 13
    MPJ Express: Parallel Computing for Java
    MPJ Express is an implementation of an MPI-like API—standardized by the Java Grande forum—used to write parallel Java applications, which can execute on a variety of parallel platforms ranging from multicore processors to compute clusters/clouds.
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    Downloads: 15 This Week
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  • 14

    Distributed Video Transcoding

    Distributed Video Transcoding

    Simple Scalable, Parallel, Multi-bitrate Video Transcoding On Centos / Ubuntu / Suse / RedHat (Bash Scripts) Multi-bitrate Video processing requires lots of computing power and time to process full movie. There are different open source video transcoding and processing tools freely available in Linux, like libav-tools, ffmpeg, mencoder, and handbrake.
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  • 15

    COMRAD-MPI

    Compression of Large Genomic Datasets using Parallel Computing

    COMRAD-MPI is a parallel computing algorithm for reducing the computational time for compressing the large genomic data sets based on COMRAD algorithm. It captures the long range repeat redundancies in large genomes there by providing a way to compress the large DNA data set. Three stages- Substitution, Clean up and Huffman encoding have been parallelized using message passing library.
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  • 16

    HpcTemplateLib

    HPC Template Library to supplement the STL

    This package is intended to provide the user with threadsafe containers and classes for applications in High Performance Computing (HPC) where parallel programming is commonplace. Today’s multi-core computers bring that parallelism into the realm of everyday use. It is important to provide thread safe containers and classes in this environment. The HPC Template Library (HTL) aims to replace certain portions of the STL. It is a merger and rewrite of classes from the STL, QT, Boost, and SigSlots libraries. ...
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  • 17
    mapgraph

    mapgraph

    Massively Parallel Graph processing on GPUs -- now part of Blazegraph

    Mapgraph is SYSTAP’s disruptive new technology to exploit the main memory bandwidth advantages of GPUs. The early work was co-developed with the University of Utah SCI Institute and has its pedigree in the UINTAH software running on over 750M cores on the TITAN Super Computer. Today, SYSTAP has commercialized this technology into it’s Blazegraph Accelerator and Blazegraph HPC products. Checkout our options for GPU acceleration of graphs or contact us to learn more: ...
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  • 18
    Genetic Programming in OpenCL is a parallel implementation of genetic programming targeted at heterogeneous devices, such as CPU and GPU. It is written in OpenCL, an open standard for portable parallel programming across many computing platforms.
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  • 19

    Ezys

    Ezys 3D medical image registration program

    Ezys is a non-linear 3D medical image registration program. Ezys fully exploits the parallel computing power of inexpensive commercial graphics processing units (GPU), resulting in a very fast and accurate program capable of running on desktop PCs and even some laptops. On these systems, non-linear image registrations take less than a minute to complete. Ezys implements a diffeomorphic inverse consistent image registration algorithm with a demons-style regularization based on a non-parametric free form deformation model. ...
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  • 20

    Fast Gauss-Legendre Quadrature Rules

    Computes Gauss-Legendre quadrature nodes and weights

    This software computes Gauss-Legendre quadrature nodes and weights using the formulas developed in "Iteration-Free Computation of Gauss-Legendre Quadrature Nodes and Weights", I. Bogaert, published in the SIAM Journal of Scientific Computing (Permalink: http://dx.doi.org/10.1137/140954969). The key features are: - Speed: due to the simplified formulas and the O(1) complexity computation of individual Gauss-Legendre quadrature nodes and weights. The latter also makes this software perfectly compatible with parallel computing paradigms. - Accuracy: the error on the nodes and weights is smaller than a few ulps (see the paper for details).
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  • 21
    A parallel system simulator kernel that support ultra-large scale computer system simulation.
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  • 22

    Fast Matrix for Java

    General purpose matrix utilities for Java in Parallel Computing

    Fast Matrix for Java (fm4j) is a general-purpose matrix utility library for computing with dense matrices. fm4j encapsulated different underlying implementations and select the optimal one in run-time depending on the size of the input matrix. Moreover, fm4j employs Java (Tm) Concurrency to take advantage of the computation power of multi-cor processors.
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  • 23
    The sequence alignment task in MAGI (magi.ucsd.edu) is based on the miRanda algorithm, but we redesign the miRanda algorithm on GPU by taking its advantages of massively parallel computing and extra high memory bandwidth using using NVIDIA’s Compute Unified Device Architecture (CUDA). The CUDA-miRanda implementation is a fast microRNA target identification algorithm that aligns short nucleotide sequences (i.e., < 32 nucleotides) against longer reference sequences (e.g., 20k nucleotides). It has the ability to report multiple alignments and the corresponding traceback sequences for any given query-reference pair with up to 166x speedup on 4 GPUs compared to regular CPUs.
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  • 24

    GENIE (GEne-geNe IntEraction)

    GPU based Parallel Gene-Gene Interaction Analysis

    Gene-gene interaction in genetic association studies is computationally intensive when a large number of SNPs are involved. Most of the latest Central Processing Units (CPUs) have multiple cores, whereas Graphics Processing Units (GPUs) also have hundreds of cores and have been recently used to implement faster scientific software. However, currently there are no genetic analysis software packages that allow users to fully utilize the computing power of these multi-core devices for genetic...
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  • 25
    FlowVR
    FlowVR is an open source middleware tailored for high performance in situ data processing and analytics running on large parallel machines
    Downloads: 58 This Week
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