Showing 9 open source projects for "gnu 8085 programming"

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  • 1
    Genetic Programming Classifier is a distributed evolutionary data classification program. It uses the ensemble method implemented under a parallel co-evolutionary Genetic Programming technique.
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  • 2
    PARUS

    PARUS

    Dataflow parallel programming language for clusters

    PARUS is a data-flow parallel programming language that allows to build parallel programs for clusters and MPP multiprocessors. The data-flow graph is automatically converted to the C++/MPI source and linked with the libparus runtime library. Also there are available tools for benchmarking cluster interconnect and visualize it.
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  • 3
    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.
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  • 4
    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
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  • 5
    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.
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  • 6
    Programming libraries for writing an XMLDC (XML Distributed Computing) applications in C++. XMLDC is a XML-based protocol for remote procedure calls (RPC) between different systems. XMLDC is more powerful than XML-RPC and much simpler than SOAP or CORBA.
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  • 7
    libcsp is C a library makes programming with threads much easier. By providing an easy mechanism to express and reason about programs with multiple threads, it becomes easier to fit software into the real world.
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  • 8
    TOP-C is a library for easily writing parallel applications for both distributed and shared memory architectures. It hides the details of parallel programming, and presents the application programmer with a simple task-oriented interface.
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  • 9
    This library provides an easy way to program the widely used parallel programming library PVM, which works in homogenous and heterogenous network environments.
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