Open Source Python Distributed Computing Software

Browse free open source Python Distributed Computing Software and projects below. Use the toggles on the left to filter open source Python Distributed Computing Software by OS, license, language, programming language, and project status.

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  • 1

    Madara

    Middleware for distributed applications

    The purpose of the project is to develop a portable programming framework that facilitates distributed and multi-threaded programming for C++, Java, and Python. MADARA was originally developed as an agent-based middleware specifically for real-time, distributed artificial intelligence, but is now more general purpose for distributed timing, control, knowledge and reasoning, and quality-of-service. MADARA is composed of several tools and middleware, and the main entry point into the system is the Knowledge and Reasoning Language (KaRL) Engine, which provides a real-time scripting language for nanosecond execution times hooked into a flexible transport layer for distributed reasoning. The KaRL engine also supports object-oriented C++, Java, and Python programming through Containers, classes that provide abstractions and references for variable location within the KaRL Knowledge Base. This project is currently in process of being ported from http://madara.googlecode.com.
    Downloads: 2 This Week
    Last Update:
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  • 2
    An implementation of the Open Group's Application Response Measurement (ARM) Version 4 standard. The ARM standard describes a means of breaking an application down into it's constituent transactions, and measuring response time across multiple tiers.
    Downloads: 0 This Week
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  • 3
    isectd is a middleware daemon that provides many-to-many client-to-server connectivity. Supports multiplexing requests to multiple server processes over IP networks.
    Downloads: 0 This Week
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  • 4
    A metering and charge-back mechanism based on real time pricing (RTP) for the cloud services. This project caters to the need of a dynamic pay-per-use model in the cloud environment.
    Downloads: 0 This Week
    Last Update:
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