Showing 2 open source projects for "parallel computing"

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    Parasoft: Automated Testing to Deliver Superior Quality Software

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    Parasoft helps organizations continuously deliver high-quality software with its AI-powered software testing platform and automated test solutions. Supporting the embedded, enterprise, and IoT markets, Parasoft’s proven technologies reduce the time, effort, and cost of delivering secure, reliable, and compliant software by integrating everything from deep code analysis and unit testing to web UI and API testing, plus service virtualization and complete code coverage, into the delivery pipeline. Bringing all this together, Parasoft’s award-winning reporting and analytics dashboard provides a centralized view of quality, enabling organizations to deliver with confidence and succeed in today’s most strategic ecosystems and development initiatives—security, safety-critical, Agile, DevOps, and continuous testing.
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  • The Cloud Sales Acceleration Platform Icon
    The Cloud Sales Acceleration Platform

    For businesses wanting a platform to list, manage, and co-sell on cloud marketplaces with minimal engineering effort

    Streamline and automate your cloud sales cycle, enhance operational efficiency, and capitalize on marketplace opportunities with the Clazar Cloud Sales Acceleration Platform.
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    MarDRe

    MapReduce-based tool to remove duplicate DNA reads

    ...Instead, MarDRe takes advantage of the MapReduce programming model to significantly improve ParDRe performance on distributed systems, especially on cloud-based infrastructures. Written in pure Java to maximize cross-platform compatibility, MarDRe is built upon the open-source Apache Hadoop project, the most popular distributed computing framework for Big Data processing.
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  • 2

    HSRA

    Hadoop spliced read aligner for RNA-seq data

    HSRA is a MapReduce-based parallel tool for mapping reads from RNA sequencing (RNA-seq) experiments. RNA-seq analyses typically begin by mapping reads to a reference genome in order to determine the location from which the reads were originated, which is a very time-consuming step. This tool allows bioinformatics researchers to efficiently distribute their mapping tasks over the nodes of a cluster by combining a fast multithreaded spliced aligner (HISAT2) with Apache Hadoop, which is a distributed computing framework for scalable Big Data processing. ...
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