Showing 3 open source projects for "machine learning"

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    Dragonfly | An In-Memory Data Store without Limits

    Dragonfly Cloud is engineered to handle the heaviest data workloads with the strictest security requirements.

    Dragonfly is a drop-in Redis replacement that is designed for heavy data workloads running on modern cloud hardware. Migrate in less than a day and experience up to 25X the performance on half the infrastructure.
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  • Electronic Lab Notebook (ELN) Software Icon
    Electronic Lab Notebook (ELN) Software

    Ideal for any lab. Whether you’re just starting up, a small or large academic institution, or a globally operating company.

    eLabJournal is an all-in-one Electronic Lab Notebook (ELN) software that includes sample tracking and protocol management modules.
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  • 1
    LoopVectorization.jl

    LoopVectorization.jl

    Macro(s) for vectorizing loops

    ...It analyzes loops and generates highly efficient code that leverages CPU vector instructions, making it ideal for performance-critical computing in fields such as scientific computing, signal processing, and machine learning.
    Downloads: 2 This Week
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  • 2

    Chronological Cohesive Units

    The experimental source code for the paper

    The experimental source code for the paper, "A Novel Recommendation Approach Based on Chronological Cohesive Units in Content Consuming"
    Downloads: 1 This Week
    Last Update:
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  • 3

    Alchemist plugin

    Alchemist GCC/LLVM plugin for code analysis and tuning

    News: since 2015 we continue all related developments within Collective Knowledge Framework: http://github.com/ctuning/ck/wiki Alchemist plugin is a collection of plugins for GCC/LLVM for external and fine-grain code analysis and tuning. It is intended to to extract program properties for machine learning based optimization (see MILEPOST GCC); optimize programs at fine-grain level (such as unrolling, tiling, prefetching, etc); tune default optimization heuristic; gradually decompose program and detect performance or other anomalies; generate benchmarks particularly useful to train ML-based compilers. GCC plugin is licenced under GPLv3 licensed, while future LLVM plugins will be licensed under BSD license. ...
    Downloads: 0 This Week
    Last Update:
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