Showing 95 open source projects for "parallel computing"

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  • 1
    SECTOR
    SECTOR: A Distributed Data Storage and Processing Platform
    Downloads: 0 This Week
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  • 2
    Project provides a set of concurrent building blocks (Java & C/C++) that can be used to develop parallel/multi-threaded applications. Components are grouped into 4 categories: 1.Data Structures 2. Parallel Patterns 3.Parallel functions 4.Atomics and STM
    Downloads: 7 This Week
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  • 3
    Platform for parallel computation in the Amazon cloud, including machine learning ensembles written in R for computational biology and other areas of scientific research. Home to MR-Tandem, a hadoop-enabled fork of X!Tandem peptide search engine.
    Downloads: 0 This Week
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  • 4
    A scripting language and reference implementation to allow command line tools to be chained into complex parallel workflows.
    Downloads: 0 This Week
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  • 5
    Equalizer - Parallel Rendering
    Equalizer is the standard middleware to create parallel OpenGL-based applications. Please visit https://github.com/Eyescale for current development information.
    Downloads: 4 This Week
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  • 6
    Microbase is a Grid infrastructure for deploying massively parallel applications. Our notification-driven task scheduler supports the enactment of complex data processing workflows, such as those commonly used in bioinformatics.
    Downloads: 0 This Week
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  • 7
    This project to be release for parallel computing
    Downloads: 0 This Week
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  • 8
    HadoopDB is a hybrid of parallel database and MapReduce technologies. It approaches parallel databases in performance and efficiency, yet still yields the scalability, fault tolerance, and flexibility of MapReduce systems.
    Downloads: 0 This Week
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  • 9
    Simdist lets you harness the power of cluster computing without any knowledge of parallel libraries such as MPI, and with no restrictions on programming language. Primarily targeted at evolutionary computing and similar master-slave configurations.
    Downloads: 0 This Week
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  • 10
    GridSim allows modeling and simulation of entities in parallel and distributed computing systems such as users, applications, resources, and resource brokers/schedulers for design and evaluation of scheduling algorithms. http://www.gridbus.org/gridsim
    Downloads: 0 This Week
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  • 11
    RT-BOINC
    RT-BOINC stands for a Real-Time BOINC. It was designed for managing highly-interactive, short-term, and massively-parallel real-time applications. We implemented RT-BOINC on top of the recent BOINC server source codes.
    Downloads: 1 This Week
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  • 12
    SimKernel controls parameter scans and iterations for any given C++ code / scientific simulation. Parameters, iteration ranges, settings and dependencies are specified in Mathematica syntax. Parallel processing of parameter scanning via MPI.
    Downloads: 0 This Week
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  • 13
    Distributed Parallel Programming for Python! This package builds on traditional Python by enabling users to write distributed, parallel programs based on MPI message passing primitives. General python objects can be messaged between processors. Ru
    Downloads: 1 This Week
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  • 14
    Roomy is a programming language extension for writing parallel disk-based applications. All details of parallelism and disk I/O are hidden within the Roomy library.
    Downloads: 0 This Week
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  • 15
    PyMW is a Python module for parallel master-worker computing in a variety of environments. With the PyMW module, users can write a single program that scales from multicore machines to global computing platforms.
    Downloads: 0 This Week
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  • 16
    BSPonMPI is an implementation of the BSPlib standard on top of MPI. Both MPI and BSPlib are API's of communication routines meant for parallel computing, but BSPlib is easier to learn and its performance easier to predict.
    Downloads: 0 This Week
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  • 17
    Parallelizable is a tiny framework in complement for java.util.conccurent api. Parallelizable is an abstract class to extend for making asynchronous parallel execution on a synchronous task. Very usefull if task often calls a very long process.
    Downloads: 0 This Week
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  • 18
    Numerical package Parallel EXECution. Using a numerical package like Octave, 'npexec' distribute computation of a math formula among various network elements, collecting result automatically. ->y=npexec('fft(x.^m)', 'm=-8:8','x=ARG');
    Downloads: 1 This Week
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  • 19
    Meerkat is a distributed programming environment. It consists of a virtual machine which is suited to parallel processing. The data model is based on the concept of actors, although it is much more permissive than the traditional description.
    Downloads: 0 This Week
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  • 20
    DKU is an embedded parallel language, or "piggy-back" language that uses function calls to invoke the language's execution model. It tunes task-size to the hardware while hiding hardware details for high performance portability of parallel code.
    Downloads: 0 This Week
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  • 21
    The Application Agent (AA) is a software providing the platform and mechanism for the distributed/parallel applications to interact and negotiate with the underlying grid resource infrastructure such as Condor and SGE on one-to-one and dynamic basis.
    Downloads: 0 This Week
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  • 22
    LIME (Less-is-More) is parallel/concurrent programming environment based on C. Internally, it uses XML technology to describe tasks and their dependencies. Externally, it offers the ANSI C99 programming as well as a set of visually-oriented interfaces.
    Downloads: 0 This Week
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  • 23
    NetWorkSpaces, developed by Scientific Computing Associates Inc., provides a framework to coordinate programs written in R. It allows users to write parallel programs in R easily.
    Downloads: 0 This Week
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  • 24
    Pydusa is a package for parallel programming using Python. It contains a module for doing MPI programming in Python. We have added parallel solver packages such as Parallel SuperLU for solving sparse linear systems.
    Downloads: 0 This Week
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  • 25
    Python Integrated Parallel Programming EnviRonment (PIPPER), Python pre-parser that is designed to manage a pipeline, written in Python. It enables automated parallelization of loops. Think of it like OpenMP for Python, but it works in a computer cluster
    Downloads: 0 This Week
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