Showing 8 open source projects for "parallel computing"

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  • 1
    myopentrader

    myopentrader

    Open-source complex-event based trading engine

    ...We have started MOT in 2012 and we have been using MOT ever since successfully. The best way of describing MOT is a flexible open-source trading framework. It is built from ground up as a parallel computing engine, which allows to do large scale parallel backtesting. MOT is distributed under the GPL v3 License and is free to use for everyone without warranty. MyOpenTrader.org is not responsible for any of your trading losses and can not be held accountable. Use the framework at your OWN risk. MOT is written purely in Java (1.6++) and has dependencies on a DB as well as a MQ Broker (such as ActiveMQ).
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  • 2
    MapPSO
    MapPSO is a tool for Ontology Alignment, which uses Discrete Particle Swarm Optimisation. A particle swarm is used to search for the optimal alignment. The algorithm is massively parallel and adapts naturally on parallel architectures.
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  • 3
    Tuple Spaces

    Tuple Spaces

    Tuple space with time outs and transactions.

    Java implementation of a Tuplespace. Moved to https://github.com/mike-k-houghton/tuplespace A Tuple is an ordered list of items. A Tuple Space is a form of associative memory where entries, tuples, are stored in the space and are retrieved using search criteria that are based on the intrinsic properties of the tuples. The two key operations are put get And that is it! There are refinements on these operations including, for example, timeouts where the tuple will only exist...
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  • 4
    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
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  • 5
    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.
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  • 6
    Designed to allow quick setup of powerful NOW-based clusters to run compute-intensive applications. Applications do not have to be designed specially for these clusters to benefit.
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  • 7
    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
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  • 8
    GAP (Grid Agents Platform) Toolkit for Modeling and Simulation of Mobile Agents in Grid Environments. GAP is an abstraction over GridSim, a Grid Simulation Toolkit for Resource Modelling and Application Scheduling for Parallel and Distributed Computing.
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