Showing 5 open source projects for "vector linux os"

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    XiangShan

    XiangShan

    Open-source high-performance RISC-V processor

    XiangShan is an open-source, high-performance RISC-V processor project that implements out-of-order superscalar cores using Chisel for hardware construction. The design targets modern performance goals—deep pipelines, speculative execution, multi-issue decode/execute, and sophisticated branch prediction—while remaining synthesizable for ASIC flows and portable to FPGAs for research. A modular microarchitecture separates frontend, backend, and memory subsystems with coherent caches and...
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  • 2
    RISC-V BOOM

    RISC-V BOOM

    SonicBOOM: The Berkeley Out-of-Order Machine

    The riscv-boom project (also called BOOM or SonicBOOM) implements a high-performance, synthesizable out-of-order RISC-V core written in the Chisel hardware construction language. It targets the RV64GC (i.e. 64-bit with general + compressed + floating point) instruction set and supports features such as virtual memory, caches, atomics, and IEEE-754 floating point. The design is parameterizable, meaning users can tune pipeline widths, buffer sizes, functional units, and other...
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  • 3
    Marathon

    Marathon

    Deploy and manage containers (including Docker) on top of Apache Mesos

    A container orchestration platform for Mesos and DC/OS. Deploy and manage containers (including Docker) on top of Apache Mesos at scale. Marathon is a production-grade container orchestration platform for Mesosphere’s Datacenter Operating System (DC/OS) and Apache Mesos. Marathon has first-class support for both Mesos containers (using cgroups) and Docker. Marathon runs as an active/passive cluster with leader election for 100% uptime. Marathon can bind persistent storage volumes to your...
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  • 4
    node2vec

    node2vec

    Learn continuous vector embeddings for nodes in a graph using biased R

    The node2vec project provides an implementation of the node2vec algorithm, a scalable feature learning method for networks. The algorithm is designed to learn continuous vector representations of nodes in a graph by simulating biased random walks and applying skip-gram models from natural language processing. These embeddings capture community structure as well as structural equivalence, enabling machine learning on graphs for tasks such as classification, clustering, and link prediction....
    Downloads: 1 This Week
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  • 5
    Math expression parser and evaluator written in Scala. Usable from Java (Sun JRE 1.6) Provides float, integral, boolean and vector data types, some string processing support. Variables may be defined internally or im- and exported through a binding.
    Downloads: 0 This Week
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