Showing 3 open source projects for "gpu max performance"

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    NVIDIA AI Cluster Runtime (AICR)

    NVIDIA AI Cluster Runtime (AICR)

    Tooling for optimized and reproducible GPU-accelerated AI runtime

    ...Based on its positioning within NVIDIA’s repositories, it is designed to support scalable AI runtime environments, potentially addressing challenges related to orchestration, resource management, or reproducible AI execution. The project likely aligns with NVIDIA’s broader strategy of building modular infrastructure layers that integrate with GPU-accelerated workloads and cloud-native systems. It appears to emphasize automation, consistency, and performance optimization across AI pipelines, potentially targeting enterprise and research use cases. Given NVIDIA’s ecosystem, it may also integrate with containerized environments, Kubernetes, or other orchestration frameworks.
    Downloads: 1 This Week
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  • 2
    Nuclio

    Nuclio

    High-Performance Serverless event and data processing platform

    Nuclio is an open source and managed serverless platform used to minimize development and maintenance overhead and automate the deployment of data-science-based applications. Real-time performance running up to 400,000 function invocations per second. Portable across low laptops, edge, on-prem and multi-cloud deployments. The first serverless platform supporting GPUs for optimized utilization and sharing. Automated deployment to production in a few clicks from Jupyter notebook. Deploy one of...
    Downloads: 3 This Week
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  • 3
    MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
    Downloads: 0 This Week
    Last Update:
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