Showing 17 open source projects for "parallel programming frameworkc++"

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  • 1
    Sogou C++ Workflow

    Sogou C++ Workflow

    C++ parallel computing and asynchronous networking engine

    As Sogou`s C++ server engine, Sogou C++ Workflow supports almost all back-end C++ online services of Sogou, including all search services, cloud input method, online advertisements, etc., handling more than 10 billion requests every day. This is an enterprise-level programming engine in light and elegant design which can satisfy most C++ back-end development requirements.
    Downloads: 0 This Week
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  • 2
    Bazel

    Bazel

    Fast, scalable, multi-language and extensible build system

    ...Share and re-use language rules written by the growing Bazel community. Bazel is the common build tool throughout Pinterest and has been instrumental in achieving fast, reproducible builds across our programming languages and platforms.
    Downloads: 127 This Week
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  • 3
    FortranBSD

    FortranBSD

    FortranBSD is DragonflyBSD-based OS with built-in GNU Fortran

    I'm excited to introduce the first release of FortranBSD, a new operating system designed specifically for Fortran developers who demand high-performance and seamless multithreading support. FortranBSD is based on DragonflyBSD which is an outstanding OS for HPC application and: 🔹 Superior parallel computing capabilities beat Linux/MS Windows over the performance. 🔹 Optimized for Fortran programming 🔹 Built on a robust, efficient foundation 🔹 Ideal for scientific computing, simulations, and high-performance Computation (HPC) applications FortranBSD is a game-changer for anyone working with Fortran who wants an OS that fully supports and enhances multithreaded execution. ...
    Downloads: 0 This Week
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  • 4
    BMDFM

    BMDFM

    Binary Modular DataFlow Machine (BMDFM)

    Binary Modular DataFlow Machine (BMDFM) is a software package that enables running an application in parallel on shared memory symmetric multiprocessing (SMP) computers using the multiple processors to speed up the execution of single applications. BMDFM automatically identifies and exploits parallelism due to the static and mainly dynamic scheduling of the dataflow instruction sequences derived from the formerly sequential program. The BMDFM dynamic scheduling subsystem performs a...
    Downloads: 0 This Week
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  • 5

    dispy

    Distributed and Parallel Computing with/for Python.

    dispy is a generic and comprehensive, yet easy to use framework for creating and using compute clusters to execute computations in parallel across multiple processors in a single machine (SMP), among many machines in a cluster, grid or cloud. dispy is well suited for data parallel (SIMD) paradigm where a computation (Python function or standalone program) is evaluated with different (large) datasets independently. dispy supports public / private / hybrid cloud computing, fog / edge computing.
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    Downloads: 7 This Week
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  • 6
    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.
    Downloads: 0 This Week
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  • 7
    A modest extension to C, XMTC allows representing parallel (PRAM) algorithms as parallel programs, and run XMTC code using a compiler and cycle accurate simulator of the University of Maryland explicit multi-threaded (XMT) many-core architecture.
    Downloads: 0 This Week
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  • 8
    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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  • 9
    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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  • 10
    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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  • 11
    New programming language for SPS devices like Amtel Controller . The basic element of this language will be small Moduls of Code which work parallel (Multitasking). A Module can work indepent or with addiction to other Moduls.
    Downloads: 0 This Week
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  • 12
    A data parallel scientific programming model. Compiles efficiently to different platforms like distributed memory (MPI), shared memory multi-processor (pthreads), Cell BE processor, Nvidia Cuda, SIMD vectorization (SSE, Altivec), and sequential C++ code.
    Downloads: 0 This Week
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  • 13
    This Project implements the mergesort algorithm in a MPICH2 (parallel programming -) environment.
    Downloads: 0 This Week
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  • 14
    pystim is an open source electrical stimulation device driver and development framework. It features a parallel/sequential block paradigm and supports event-base programming. It also provides a device simulator.
    Downloads: 0 This Week
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  • 15
    This project is setup to maintain a set of Javaparty codes. This includes Javaparty benchmarks and applications. Javaparty (http://www.ipd.uka.de/JavaParty/) is a Java extension for easy and efficient parallel programming. It does so by extending the
    Downloads: 0 This Week
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  • 16
    Utilize Java to create an application capable of massivly parallel operations. Application will be targeted as a Napster Clone, with the additional capability of downloading projects which are seeking computer time.
    Downloads: 0 This Week
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  • 17
    MassiveJava is a Java-based environment for parallel programming. Lithium is able to execute the parallel application using a cluster or a network of workstations. A user is able to program a parallel application without take in account problem like sche
    Downloads: 0 This Week
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