Showing 11 open source projects for "parallel"

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  • 1
    Buildbot

    Buildbot

    Python-based continuous integration testing framework

    Buildbot is an open-source framework for automating software build, test, and release processes. At its core, Buildbot is a job scheduling system: it queues jobs, executes the jobs when the required resources are available, and reports the results. Your Buildbot installation has one or more masters and a collection of workers. The masters monitor source-code repositories for changes, coordinate the activities of the workers, and report results to users and developers. Workers run on a...
    Downloads: 10 This Week
    Last Update:
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  • 2
    Ray

    Ray

    A unified framework for scalable computing

    Modern workloads like deep learning and hyperparameter tuning are compute-intensive and require distributed or parallel execution. Ray makes it effortless to parallelize single machine code — go from a single CPU to multi-core, multi-GPU or multi-node with minimal code changes. Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray. Accelerate your hyperparameter search workloads with Ray Tune. ...
    Downloads: 6 This Week
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  • 3
    Django friendly finite state machine

    Django friendly finite state machine

    Django friendly finite state machine support

    Django-fsm adds simple declarative state management for Django models. If you need parallel task execution, view, and background task code reuse over different flows - check my new project Django-view flow. Instead of adding a state field to a Django model and managing its values by hand, you use FSMField and mark model methods with the transition decorator. These methods could contain side effects of the state change.
    Downloads: 0 This Week
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  • 4
    Intel neon

    Intel neon

    Intel® Nervana™ reference deep learning framework

    ...The Intel Math Kernel Library takes advantages of the parallelization and vectorization capabilities of Intel Xeon and Xeon Phi systems. When hyperthreading is enabled on the system, we recommend the following KMP_AFFINITY setting to make sure parallel threads are 1:1 mapped to the available physical cores.
    Downloads: 0 This Week
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  • 5

    IPS Framework

    A simple Python framework for loosely-coupled multiphysics simulations

    ...In addition to plasma physics, it is also being used in the engineering of batteries. One of the novel features of the IPS framework is its ability to support parallelism at multiple levels: components can launch individual parallel tasks, and also launch multiple tasks concurrently. The framework can execute multiple components concurrently, and even multiple simulations, all within the same pool of compute nodes.
    Downloads: 0 This Week
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  • 6
    SW Test Automation Framework
    The Software Testing Automation Framework (STAF) is a framework designed to improve the level of reuse and automation in test cases and test environments. The goal of STAF is to provide a complete end-to-end automation solution for testers.
    Downloads: 12 This Week
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  • 7

    Drid

    Multi-Purpose Automation Grid

    Console-based tool that will allow for multiple types of automation testing to run in parallel. Written in Python
    Downloads: 0 This Week
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  • 8
    Python bindings for OpenCL, the open standard for parallel programming of heterogeneous systems
    Downloads: 0 This Week
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  • 9
    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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  • 10
    PyGWA is a GPGPU library for Python. It contains Python bindings for AMD CAL and PyGWA.DP - a toy data-parallel programming API.
    Downloads: 0 This Week
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  • 11
    The LisBON Framework is an adaptable framework for developing new parallel Memetic Algorithms (hybrid search algorithms for efficiently solving optimisation problems).
    Downloads: 0 This Week
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