Showing 4 open source projects for "parallel computing datamaning"

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    LinDB

    LinDB

    LinDB is a scalable, high performance, high availability database

    LinDB is a scalable, high-performance, high-availability distributed time series database. A single server could easily support more than one million write TPS; With fundamental techniques like efficient compression storage and parallel computing, LinDB delivers highly optimized query performance. The multi-channel replication protocol supports any amount of nodes, and ensures the system's availability. Schema-free multi-dimensional data model with Metric, Tags, and Fields; The LinQL is flexible yet handy for real-time data analytics. Horizontal scalable is made simple by adding more new broker and storage nodes without too much thinking and manual operations. ...
    Downloads: 3 This Week
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  • 2

    PDP-OmniSim

    PDP-OmniSim simulating parallel and distributed processing systems

    PDP-OmniSim 🧬 Scientific Overview PDP-OmniSim is an advanced computational framework for simulating parallel and distributed processing systems, with cutting-edge applications in computational neuroscience, distributed computing, and complex systems modeling. The framework provides researchers with robust tools for large-scale simulations of networked systems and their emergent behaviors. 🎯 Key Scientific Contributions 🔬 Interdisciplinary Research Domains Computational Neuroscience: Large-scale neural population dynamics, brain-inspired computing architectures, and neuro-symbolic AI systems Distributed Systems: Scalable parallel processing simulations, resource allocation optimization, and fault-tolerant computing Complex Systems: Emergent behavior in networked systems, self-organizing criticality, and adaptive network topologies
    Downloads: 0 This Week
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  • 3
    QuickRNASeq

    QuickRNASeq

    A pipeline for large scale RNA-seq data analysis

    We have implemented QuickRNASeq, an open-source based pipeline for large scale RNA-seq data analysis. QuickRNASeq takes advantage of parallel computing resources, a careful selection of previously published algorithms for RNA-seq read mapping, counting and quality control, and a three-stage strategy to build a fully automated workflow. We also implemented built-in functionalities to detect sample swapping or mislabeling in large-scale RNA-seq studies. Our pipeline significantly lifts large-scale RNA-seq data analysis to the next level of automation and visualization. ...
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  • 4
    Parallel Colt is a multithreaded version of Colt - a library for high performance scientific computing in Java. It contains efficient algorithms for data analysis, linear algebra, multi-dimensional arrays, Fourier transforms, statistics and histogramming
    Downloads: 0 This Week
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